WorldWideScience

Sample records for big sagebrush communities

  1. Seed bank and big sagebrush plant community composition in a range margin for big sagebrush

    Science.gov (United States)

    Martyn, Trace E.; Bradford, John B.; Schlaepfer, Daniel R.; Burke, Ingrid C.; Laurenroth, William K.

    2016-01-01

    The potential influence of seed bank composition on range shifts of species due to climate change is unclear. Seed banks can provide a means of both species persistence in an area and local range expansion in the case of increasing habitat suitability, as may occur under future climate change. However, a mismatch between the seed bank and the established plant community may represent an obstacle to persistence and expansion. In big sagebrush (Artemisia tridentata) plant communities in Montana, USA, we compared the seed bank to the established plant community. There was less than a 20% similarity in the relative abundance of species between the established plant community and the seed bank. This difference was primarily driven by an overrepresentation of native annual forbs and an underrepresentation of big sagebrush in the seed bank compared to the established plant community. Even though we expect an increase in habitat suitability for big sagebrush under future climate conditions at our sites, the current mismatch between the plant community and the seed bank could impede big sagebrush range expansion into increasingly suitable habitat in the future.

  2. Is fire exclusion in mountain big sagebrush communities prudent? Soil nutrient, plant diversity, and arthropod response to burning

    Science.gov (United States)

    Fire has largely been excluded from many mountain big sagebrush (Artemisia tridentata Nutt. ssp. vaseyana (Rydb.) Beetle) communities. Land and wildlife managers are especially reluctant to reintroduce fire in mountain big sagebrush plant communities, especially those communities without significan...

  3. Effects of using winter grazing as a fuel treatment on Wyoming big sagebrush plant communities

    Science.gov (United States)

    More frequent wildfires and incidences of mega-fires have increased the pressure for fuel treatments in sagebrush (Artemisia) communities. Winter grazing has been one of many fuel treatments proposed for Wyoming big sagebrush (A. tridentata Nutt. subsp. wyomingensis Beetle and A. Young) communitie...

  4. Attempting to restore herbaceous understories in Wyoming big sagebrush communities with mowing and seeding

    Science.gov (United States)

    Shrub steppe communities with depleted perennial herbaceous understories need to be restored to increase resilience, provide quality wildlife habitat, and improve ecosystem function. Mowing has been applied to Wyoming big sagebrush (Artemisia tridentata Nutt. ssp. wyomingensis Beetle &Young) steppe...

  5. Woody fuels reduction in Wyoming big sagebrush communities

    Science.gov (United States)

    Wyoming big sagebrush (Artemisia tridentata Nutt. ssp. wyomingensis Beetle & Young) ecosystems historically have been subject to disturbances that reduce or remove shrubs primarily by fire, although insect outbreaks and disease have also been important. Depending on site productivity, fire return in...

  6. Challenges of establishing big sgebrush (Artemisia tridentata) in rangeland restoration: effects of herbicide, mowing, whole-community seeding, and sagebrush seed sources

    Science.gov (United States)

    Brabec, Martha M.; Germino, Matthew J.; Shinneman, Douglas J.; Pilliod, David S.; McIlroy, Susan K.; Arkle, Robert S.

    2015-01-01

    The loss of big sagebrush (Artemisia tridentata Nutt.) on sites disturbed by fire has motivated restoration seeding and planting efforts. However, the resulting sagebrush establishment is often lower than desired, especially in dry areas. Sagebrush establishment may be increased by addressing factors such as seed source and condition or management of the plant community. We assessed initial establishment of seeded sagebrush and four populations of small outplants (from different geographies, climates, and cytotypes) and small sagebrush outplants in an early seral community where mowing, herbicide, and seeding of other native plants had been experimentally applied. No emergence of seeded sagebrush was detected. Mowing the site before planting seedlings led to greater initial survival probabilities for sagebrush outplants, except where seeding also occurred, and these effects were related to corresponding changes in bare soil exposure. Initial survival probabilities were > 30% greater for the local population of big sagebrush relative to populations imported to the site from typical seed transfer distances of ~320–800 km. Overcoming the high first-year mortality of outplanted or seeded sagebrush is one of the most challenging aspects of postfire restoration and rehabilitation, and further evaluation of the impacts of herb treatments and sagebrush seed sources across different site types and years is needed.

  7. Banking Wyoming big sagebrush seeds

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    Robert P. Karrfalt; Nancy Shaw

    2013-01-01

    Five commercially produced seed lots of Wyoming big sagebrush (Artemisia tridentata Nutt. var. wyomingensis (Beetle & Young) S.L. Welsh [Asteraceae]) were stored under various conditions for 5 y. Purity, moisture content as measured by equilibrium relative humidity, and storage temperature were all important factors to successful seed storage. Our results indicate...

  8. Spatial variability in cost and success of revegetation in a Wyoming big sagebrush community.

    Science.gov (United States)

    Boyd, Chad S; Davies, Kirk W

    2012-09-01

    The ecological integrity of the Wyoming big sagebrush (Artemisia tridentata Nutt. ssp. wyomingensis Beetle and A. Young) alliance is being severely interrupted by post-fire invasion of non-native annual grasses. To curtail this invasion, successful post-fire revegetation of perennial grasses is required. Environmental factors impacting post-fire restoration success vary across space within the Wyoming big sagebrush alliance; however, most restorative management practices are applied uniformly. Our objectives were to define probability of revegetation success over space using relevant soil-related environmental factors, use this information to model cost of successful revegetation and compare the importance of vegetation competition and soil factors to revegetation success. We studied a burned Wyoming big sagebrush landscape in southeast Oregon that was reseeded with perennial grasses. We collected soil and vegetation data at plots spaced at 30 m intervals along a 1.5 km transect in the first two years post-burn. Plots were classified as successful (>5 seedlings/m(2)) or unsuccessful based on density of seeded species. Using logistic regression we found that abundance of competing vegetation correctly predicted revegetation success on 51 % of plots, and soil-related variables correctly predicted revegetation performance on 82.4 % of plots. Revegetation estimates varied from $167.06 to $43,033.94/ha across the 1.5 km transect based on probability of success, but were more homogenous at larger scales. Our experimental protocol provides managers with a technique to identify important environmental drivers of restoration success and this process will be of value for spatially allocating logistical and capital expenditures in a variable restoration environment.

  9. Investigating Seed Longevity of Big Sagebrush (Artemisia tridentata)

    Science.gov (United States)

    Wijayratne, Upekala C.; Pyke, David A.

    2009-01-01

    The Intermountain West is dominated by big sagebrush communities (Artemisia tridentata subspecies) that provide habitat and forage for wildlife, prevent erosion, and are economically important to recreation and livestock industries. The two most prominent subspecies of big sagebrush in this region are Wyoming big sagebrush (A. t. ssp. wyomingensis) and mountain big sagebrush (A. t. ssp. vaseyana). Increased understanding of seed bank dynamics will assist with sustainable management and persistence of sagebrush communities. For example, mountain big sagebrush may be subjected to shorter fire return intervals and prescribed fire is a tool used often to rejuvenate stands and reduce tree (Juniperus sp. or Pinus sp.) encroachment into these communities. A persistent seed bank for mountain big sagebrush would be advantageous under these circumstances. Laboratory germination trials indicate that seed dormancy in big sagebrush may be habitat-specific, with collections from colder sites being more dormant. Our objective was to investigate seed longevity of both subspecies by evaluating viability of seeds in the field with a seed retrieval experiment and sampling for seeds in situ. We chose six study sites for each subspecies. These sites were dispersed across eastern Oregon, southern Idaho, northwestern Utah, and eastern Nevada. Ninety-six polyester mesh bags, each containing 100 seeds of a subspecies, were placed at each site during November 2006. Seed bags were placed in three locations: (1) at the soil surface above litter, (2) on the soil surface beneath litter, and (3) 3 cm below the soil surface to determine whether dormancy is affected by continued darkness or environmental conditions. Subsets of seeds were examined in April and November in both 2007 and 2008 to determine seed viability dynamics. Seed bank samples were taken at each site, separated into litter and soil fractions, and assessed for number of germinable seeds in a greenhouse. Community composition data

  10. Effect of fungicides on Wyoming big sagebrush seed germination

    Science.gov (United States)

    Robert D. Cox; Lance H. Kosberg; Nancy L. Shaw; Stuart P. Hardegree

    2011-01-01

    Germination tests of Wyoming big sagebrush (Artemisia tridentata Nutt. ssp. wyomingensis Beetle & Young [Asteraceae]) seeds often exhibit fungal contamination, but the use of fungicides should be avoided because fungicides may artificially inhibit germination. We tested the effect of seed-applied fungicides on germination of Wyoming big sagebrush at 2 different...

  11. Simulated big sagebrush regeneration supports predicted changes at the trailing and leading edges of distribution shifts

    Science.gov (United States)

    Schlaepfer, Daniel R.; Taylor, Kyle A.; Pennington, Victoria E.; Nelson, Kellen N.; Martin, Trace E.; Rottler, Caitlin M.; Lauenroth, William K.; Bradford, John B.

    2015-01-01

    Many semi-arid plant communities in western North America are dominated by big sagebrush. These ecosystems are being reduced in extent and quality due to economic development, invasive species, and climate change. These pervasive modifications have generated concern about the long-term viability of sagebrush habitat and sagebrush-obligate wildlife species (notably greater sage-grouse), highlighting the need for better understanding of the future big sagebrush distribution, particularly at the species' range margins. These leading and trailing edges of potential climate-driven sagebrush distribution shifts are likely to be areas most sensitive to climate change. We used a process-based regeneration model for big sagebrush, which simulates potential germination and seedling survival in response to climatic and edaphic conditions and tested expectations about current and future regeneration responses at trailing and leading edges that were previously identified using traditional species distribution models. Our results confirmed expectations of increased probability of regeneration at the leading edge and decreased probability of regeneration at the trailing edge below current levels. Our simulations indicated that soil water dynamics at the leading edge became more similar to the typical seasonal ecohydrological conditions observed within the current range of big sagebrush ecosystems. At the trailing edge, an increased winter and spring dryness represented a departure from conditions typically supportive of big sagebrush. Our results highlighted that minimum and maximum daily temperatures as well as soil water recharge and summer dry periods are important constraints for big sagebrush regeneration. Overall, our results confirmed previous predictions, i.e., we see consistent changes in areas identified as trailing and leading edges; however, we also identified potential local refugia within the trailing edge, mostly at sites at higher elevation. Decreasing

  12. Natural regeneration processes in big sagebrush (Artemisia tridentata)

    Science.gov (United States)

    Schlaepfer, Daniel R.; Lauenroth, William K.; Bradford, John B.

    2014-01-01

    Big sagebrush, Artemisia tridentata Nuttall (Asteraceae), is the dominant plant species of large portions of semiarid western North America. However, much of historical big sagebrush vegetation has been removed or modified. Thus, regeneration is recognized as an important component for land management. Limited knowledge about key regeneration processes, however, represents an obstacle to identifying successful management practices and to gaining greater insight into the consequences of increasing disturbance frequency and global change. Therefore, our objective is to synthesize knowledge about natural big sagebrush regeneration. We identified and characterized the controls of big sagebrush seed production, germination, and establishment. The largest knowledge gaps and associated research needs include quiescence and dormancy of embryos and seedlings; variation in seed production and germination percentages; wet-thermal time model of germination; responses to frost events (including freezing/thawing of soils), CO2 concentration, and nutrients in combination with water availability; suitability of microsite vs. site conditions; competitive ability as well as seedling growth responses; and differences among subspecies and ecoregions. Potential impacts of climate change on big sagebrush regeneration could include that temperature increases may not have a large direct influence on regeneration due to the broad temperature optimum for regeneration, whereas indirect effects could include selection for populations with less stringent seed dormancy. Drier conditions will have direct negative effects on germination and seedling survival and could also lead to lighter seeds, which lowers germination success further. The short seed dispersal distance of big sagebrush may limit its tracking of suitable climate; whereas, the low competitive ability of big sagebrush seedlings may limit successful competition with species that track climate. An improved understanding of the

  13. Big and black sagebrush landscapes [Chapter 5

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    Stanley G. Kitchen; E. Durant McArthur

    2007-01-01

    Perhaps no plant evokes a common vision of the semi-arid landscapes of western North America as do the sagebrushes. A collective term, sagebrush is applied to shrubby members of the mostly herbaceous genus, Artemisia L. More precisely, the moniker is usually restricted to members of subgenus Tridentatae, a collection of some 20 woody taxa endemic to North America (...

  14. Reclamation after oil and gas development does not speed up succession or plant community recovery in big sagebrush ecosystems in Wyoming

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    Rottler, Caitlin M.; Burke, Ingrid C.; Palmquist, Kyle A.; Bradford, John B.; Lauenroth, William K.

    2018-01-01

    Article for intended outlet: Restoration Ecology. Abstract: Reclamation is an application of treatment(s) following a disturbance to promote succession and accelerate the return of target conditions. Previous studies have framed reclamation in the context of succession by studying its effectiveness in re-establishing late-successional plant communities. Re-establishment of these plant communities is especially important and potentially challenging in regions such as drylands and shrub steppe ecosystems where succession proceeds slowly. Dryland shrub steppe ecosystems are frequently associated with areas rich in fossil-fuel energy sources, and as such the need for effective reclamation after disturbance from fossil-fuel-related energy development is great. Past research in this field has focused primarily on coal mines; few researchers have studied reclamation after oil and gas development. To address this research gap and to better understand the effect of reclamation on rates of succession in dryland shrub steppe ecosystems, we sampled oil and gas wellpads and adjacent undisturbed big sagebrush plant communities in Wyoming, USA and quantified the extent of recovery for major functional groups on reclaimed and unreclaimed (recovered via natural succession) wellpads relative to the undisturbed plant community. Reclamation increased the rate of recovery for all forb and grass species as a group and for perennial grasses, but did not affect other functional groups. Rather, analyses comparing recovery to environmental variables and time since wellpad abandonment showed that recovery of other groups were affected primarily by soil texture and time since wellpad abandonment. This is consistent with studies in other ecosystems where reclamation has been implemented, suggesting that reclamation may not help re-establish late-successional plant communities more quickly than they would re-establish naturally.

  15. Influence of container size on Wyoming big sagebrush seedling morphology and cold hardiness

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    Kayla R. Herriman; Anthony S. Davis; R. Kasten Dumroese

    2009-01-01

    Wyoming big sagebrush (Artemisia tridentata) is a key component of sagebrush steppe ecosystems and is a dominant shrub throughout the western United States. Our objective was to identify the effect of container size on plant morphology of Wyoming big sagebrush. We used three different stocktypes (45/340 ml [20 in3], 60/250 ml [15 in3], 112/105 ml [6....

  16. Container configuration influences western larch and big sagebrush seedling development

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    Matthew Mehdi. Aghai

    2012-01-01

    Big sagebrush (Artemisia tridentata Nutt.), a woody shrub, and western larch (Larix occidentalis Nutt.), a deciduous conifer, are among many western North American species that have suffered a decline in presence and natural regeneration across their native ranges. These species are economically, ecologically, and intrinsically valuable, therefore many current...

  17. Conversion of sagebrush shrublands to exotic annual grasslands negatively impacts small mammal communities

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    Ostoja, S.M.; Schupp, E.W.

    2009-01-01

    Aim The exotic annual cheatgrass (Bromus tectorum) is fast replacing sagebrush (Artemisia tridentata) communities throughout the Great Basin Desert and nearby regions in the Western United States, impacting native plant communities and altering fire regimes, which contributes to the long-term persistence of this weedy species. The effect of this conversion on native faunal communities remains largely unexamined. We assess the impact of conversion from native perennial to exotic annual plant communities on desert rodent communities. Location Wyoming big sagebrush shrublands and nearby sites previously converted to cheatgrass-dominated annual grasslands in the Great Basin Desert, Utah, USA. Methods At two sites in Tooele County, Utah, USA, we investigated with Sherman live trapping whether intact sagebrush vegetation and nearby converted Bromus tectorum-dominated vegetation differed in rodent abundance, diversity and community composition. Results Rodent abundance and species richness were considerably greater in sagebrush plots than in cheatgrass-dominated plots. Nine species were captured in sagebrush plots; five of these were also trapped in cheatgrass plots, all at lower abundances than in the sagebrush. In contrast, cheatgrass-dominated plots had no species that were not found in sagebrush. In addition, the site that had been converted to cheatgrass longer had lower abundances of rodents than the site more recently converted to cheatgrass-dominated plots. Despite large differences in abundances and species richness, Simpson's D diversity and Shannon-Wiener diversity and Brillouin evenness indices did not differ between sagebrush and cheatgrass-dominated plots. Main conclusions This survey of rodent communities in native sagebrush and in converted cheatgrass-dominated vegetation suggests that the abundances and community composition of rodents may be shifting, potentially at the larger spatial scale of the entire Great Basin, where cheatgrass continues to invade

  18. Restoration of mountain big sagebrush steppe following prescribed burning to control western juniper.

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    Davies, K W; Bates, J D; Madsen, M D; Nafus, A M

    2014-05-01

    Western juniper (Juniperus occidentalis ssp. occidentalis Hook) encroachment into mountain big sagebrush (Artemisia tridentata spp. vaseyana (Rydb.) Beetle) steppe has reduced livestock forage production, increased erosion risk, and degraded sagebrush-associated wildlife habitat. Western juniper has been successfully controlled with partial cutting followed by prescribed burning the next fall, but the herbaceous understory and sagebrush may be slow to recover. We evaluated the effectiveness of seeding perennial herbaceous vegetation and sagebrush at five sites where juniper was controlled by partially cutting and prescribed burning. Treatments tested at each site included an unseeded control, herbaceous seed mix (aerially seeded), and the herbaceous seed mix plus sagebrush seed. In the third year post-treatment, perennial grass cover and density were twice as high in plots receiving the herbaceous seed mix compared to the control plots. Sagebrush cover and density in the sagebrush seeded plots were between 74- and 290-fold and 62- and 155-fold greater than the other treatments. By the third year after treatment, sagebrush cover was as high as 12 % in the sagebrush seeded plots and between 0 % and 0.4 % where it was not seeded. These results indicate that aerial seeding perennial herbaceous vegetation can accelerate the recovery of perennial grasses which likely stabilize the site. Our results also suggest that seeding mountain big sagebrush after prescribed burning encroaching juniper can rapidly recover sagebrush cover and density. In areas where sagebrush habitat is limited, seeding sagebrush after juniper control may increase sagebrush habitat and decrease the risks to sagebrush-associated species.

  19. Big sagebrush (Artemisia tridentata) in a shifting climate context: Assessment of seedling responses to climate

    Science.gov (United States)

    Martha A. Brabec

    2014-01-01

    The loss of big sagebrush (Artemisia tridentata) throughout the Great Basin Desert has motivated efforts to restore it because of fire and other disturbance effects on sagebrush-dependent wildlife and ecosystem function. Initial establishment is the first challenge to restoration, and appropriateness of seeds, climate, and weather variability are factors that may...

  20. Wyoming big sagebrush: Efforts towards development of target plants for restoration

    Science.gov (United States)

    Kayla R. Herriman

    2009-01-01

    Wyoming big sagebrush (Artemisia tridentata Nutt. ssp. wyomingensis) is a dominant shrub throughout much of the interior western United States. It is a key component of sagebrush steppe ecosystems, which have been degraded due to European settlement, improper land use, and changing fire regimes resulting from the invasion of exotic...

  1. Restoring big sagebrush after controlling encroaching western juniper with fire: aspect and subspecies effects

    Science.gov (United States)

    The need for restoration of shrubs is increasingly recognized around the world. In the western USA, restoration of mountain big sagebrush (Artemisia tridentata Nutt. ssp. vaseyana (Rydb.) Beetle) after controlling encroaching conifers is a priority to improve sagebrush-associated wildlife habitat. ...

  2. Outplanting Wyoming big sagebrush following wldfire: stock performance and economics

    Science.gov (United States)

    Dettweiler-Robinson, Eva; Bakker, Jonathan D.; Evans, James R.; Newsome, Heidi; Davies, G. Matt; Wirth, Troy A.; Pyke, David A.; Easterly, Richard T.; Salstrom, Debra; Dunwiddle, Peter W.

    2013-01-01

    Finding ecologically and economically effective ways to establish matrix species is often critical for restoration success. Wyoming big sagebrush (Artemisia tridentata subsp. wyomingensis) historically dominated large areas of western North America, but has been extirpated from many areas by large wildfires; its re-establishment in these areas often requires active management. We evaluated the performance (survival, health) and economic costs of container and bare-root stock based on operational plantings of more than 1.5 million seedlings across 2 200 ha, and compared our plantings with 30 other plantings in which sagebrush survival was tracked for up to 5 yr. Plantings occurred between 2001 and 2007, and included 12 combinations of stock type, planting amendment, and planting year.We monitored 10 500 plants for up to 8 yr after planting. Survival to Year 3 averaged 21% and was higher for container stock (30%) than bare-root stock (17%). Survival did not differ among container stock plantings, whereas survival of bare-root stock was sometimes enhanced by a hydrogel dip before planting, but not by

  3. Mountain big sagebrush age distribution and relationships on the northern Yellowstone Winter Range

    Science.gov (United States)

    Carl L. Wambolt; Trista L. Hoffman

    2001-01-01

    This study was conducted within the Gardiner Basin, an especially critical wintering area for native ungulates utilizing the Northern Yellowstone Winter Range. Mountain big sagebrush plants on 33 sites were classified as large (≥22 cm canopy cover), small (

  4. Short-term regeneration dynamics of Wyoming big sagebrush at two sites in northern Utah

    Science.gov (United States)

    The herbicide tebuthiuron has been used historically to control cover of Wyoming big sagebrush (Artemisia tridentata ssp. wyomingensis - complete taxonomic designation), a widespread shrub across the western United States, with the intent of increasing herbaceous plant cover. Although the tebuthiur...

  5. Modeling regeneration responses of big sagebrush (Artemisia tridentata) to abiotic conditions

    Science.gov (United States)

    Schlaepfer, Daniel R.; Lauenroth, William K.; Bradford, John B.

    2014-01-01

    Ecosystems dominated by big sagebrush, Artemisia tridentata Nuttall (Asteraceae), which are the most widespread ecosystems in semiarid western North America, have been affected by land use practices and invasive species. Loss of big sagebrush and the decline of associated species, such as greater sage-grouse, are a concern to land managers and conservationists. However, big sagebrush regeneration remains difficult to achieve by restoration and reclamation efforts and there is no regeneration simulation model available. We present here the first process-based, daily time-step, simulation model to predict yearly big sagebrush regeneration including relevant germination and seedling responses to abiotic factors. We estimated values, uncertainty, and importance of 27 model parameters using a total of 1435 site-years of observation. Our model explained 74% of variability of number of years with successful regeneration at 46 sites. It also achieved 60% overall accuracy predicting yearly regeneration success/failure. Our results identify specific future research needed to improve our understanding of big sagebrush regeneration, including data at the subspecies level and improved parameter estimates for start of seed dispersal, modified wet thermal-time model of germination, and soil water potential influences. We found that relationships between big sagebrush regeneration and climate conditions were site specific, varying across the distribution of big sagebrush. This indicates that statistical models based on climate are unsuitable for understanding range-wide regeneration patterns or for assessing the potential consequences of changing climate on sagebrush regeneration and underscores the value of this process-based model. We used our model to predict potential regeneration across the range of sagebrush ecosystems in the western United States, which confirmed that seedling survival is a limiting factor, whereas germination is not. Our results also suggested that modeled

  6. The response of big sagebrush (Artemisia tridentata) to interannual climate variation changes across its range.

    Science.gov (United States)

    Kleinhesselink, Andrew R; Adler, Peter B

    2018-05-01

    Understanding how annual climate variation affects population growth rates across a species' range may help us anticipate the effects of climate change on species distribution and abundance. We predict that populations in warmer or wetter parts of a species' range should respond negatively to periods of above average temperature or precipitation, respectively, whereas populations in colder or drier areas should respond positively to periods of above average temperature or precipitation. To test this, we estimated the population sensitivity of a common shrub species, big sagebrush (Artemisia tridentata), to annual climate variation across its range. Our analysis includes 8,175 observations of year-to-year change in sagebrush cover or production from 131 monitoring sites in western North America. We coupled these observations with seasonal weather data for each site and analyzed the effects of spring through fall temperatures and fall through spring accumulated precipitation on annual changes in sagebrush abundance. Sensitivity to annual temperature variation supported our hypothesis: years with above average temperatures were beneficial to sagebrush in colder locations and detrimental to sagebrush in hotter locations. In contrast, sensitivity to precipitation did not change significantly across the distribution of sagebrush. This pattern of responses suggests that regional abundance of this species may be more limited by temperature than by precipitation. We also found important differences in how the ecologically distinct subspecies of sagebrush responded to the effects of precipitation and temperature. Our model predicts that a short-term temperature increase could produce an increase in sagebrush cover at the cold edge of its range and a decrease in cover at the warm edge of its range. This prediction is qualitatively consistent with predictions from species distribution models for sagebrush based on spatial occurrence data, but it provides new mechanistic

  7. Attempting to restore mountain big sagebrush (Artemisia tridentata ssp. vaseyana) four years after fire

    Science.gov (United States)

    Restoration of shrubs is increasingly needed throughout the world because of altered fire regimes, anthropogenic disturbance, and over-utilization. The native shrub mountain big sagebrush (Artemisia tridentata Nutt. ssp. vaseyana (Rydb.) Beetle) is a restoration priority in western North America be...

  8. Do container volume, site preparation, and field fertilization affect restoration potential of Wyoming big sagebrush?

    Science.gov (United States)

    Kayla R. Herriman; Anthony S. Davis; Kent G. Apostol; Olga. A. Kildisheva; Amy L. Ross-Davis; Kas Dumroese

    2016-01-01

    Land management practices, invasive species expansion, and changes in the fire regime greatly impact the distribution of native plants in natural areas. Wyoming big sagebrush (Artemisia tridentata ssp. wyomingensis), a keystone species in the Great Basin, has seen a 50% reduction in its distribution. For many dryland species, reestablishment efforts have...

  9. Seasonal soil CO2 flux under big sagebrush (Artemisia tridentata Nutt.)

    Science.gov (United States)

    Michael C. Amacher; Cheryl L. Mackowiak

    2011-01-01

    Soil respiration is a major contributor to atmospheric CO2, but accurate landscape-scale estimates of soil CO2 flux for many ecosystems including shrublands have yet to be established. We began a project to measure, with high spatial and temporal resolution, soil CO2 flux in a stand (11 x 25 m area) of big sagebrush (Artemisia tridentata Nutt.) at the Logan, Utah,...

  10. Big sagebrush in pinyon-juniper woodlands: Using forest inventory and analysis data as a management tool for quantifying and monitoring mule deer habitat

    Science.gov (United States)

    Chris Witt; Paul L. Patterson

    2011-01-01

    We used Interior West Forest Inventory and Analysis (IW-FIA) data to identify conditions where pinyon-juniper woodlands provide security cover, thermal cover, and suitable amounts of big sagebrush (Artemisia tridentata spp.) forage to mule deer in Utah. Roughly one quarter of Utah's pinyon-juniper woodlands had a big sagebrush component in their understory....

  11. Narrow hybrid zone between two subspecies of big sagebrush (Artemisia tridentata: Asteraceae): XI. Plant-insect interactions in reciprocal transplant gardens

    Science.gov (United States)

    John H. Graham; E. Durant McArthur; D. Carl Freeman

    2001-01-01

    Basin big sagebrush (Artemisia tridentata ssp. tridentata) and mountain big sagebrush (A. t. ssp. vaseyana) hybridize in a narrow zone near Salt Creek, Utah. Reciprocal transplant experiments in this hybrid zone demonstrate that hybrids are more fit than either parental subspecies, but only in the hybrid zone. Do hybrids experience greater, or lesser, use by...

  12. Uptake and kinetics of 226Ra, 210Pb and 210Po in big sagebrush

    International Nuclear Information System (INIS)

    Simon, S.L.

    1985-01-01

    Root uptake of 226 Ra, 210 Pb and 210 Po by mature sagebrush was studied using a soil injection method for spiking the soil with minimal root disturbance. The main objective was to measure vegetation concentrations and determine concentration ratios (CR's) due to root uptake as a function of time in mature big sagebrush. Concentration ratios obtained in mature vegetation and in steady-state situations may be valuable in assessing the impact of uranium mining and milling. The vegetation was sampled approximately every 3 months for a 2 year period. Significant levels of activity were detected in the vegetation beginning at the first sampling (81 days after soil injection for 226 Ra, 28 days for 210 Pb and 210 Po). There was an exponential decrease in concentration to an apparent steady-state value. Mean values (geometric) of the data pooled over the second year period indicated that the steady-state CR's for 226 Ra, 210 Pb and 210 Po, as determined in mature sagebrush, were 0.04, 0.009, and 0.08, respectively. A three compartment mathematical model was formulated to help understand mechanisms of plant uptake and to predict, if possible, the concentration of 226 Ra, 210 Pb and 210 Po in vegetation as a function of time after soil spiking. A numerical solution was determined by 'calibrating' the general model solution with constants determined from regressions of concentrations in vegetation, soil leaching and leaf leaching data. Validation of the model is currently not possible because of an absence of similar time-dependent uptake studies. 168 refs., 19 figs., 18 tabs

  13. Variation in sagebrush communities historically seeded with crested wheatgrass in the eastern great basin

    Science.gov (United States)

    Although crested wheatgrass (CWG; Agropyron cristatum [L.] Gaertn.) has been one of the most commonly seeded exotic species in the western United States, long-term successional trajectories of seeded sites are poorly characterized, especially for big sagebrush (Artemisia tridentana Nutt.) ecosystems...

  14. Investigation of Great Basin big sagebrush and black greasewood as biogeochemical indicators of uranium mineralization. Final report. National Uranium Resource Evaluation

    International Nuclear Information System (INIS)

    Diebold, F.E.; McGrath, S.

    1982-11-01

    The effects of varying phosphate concentrations in natural aqueous systems upon the uptake of uranium by big sagebrush (Artemesia tridentata subsp. tridentata) and black greasewood (Sarcobatus vermiculatus (Hook) Torr.) were investigated. Two separate growth experiments with five drip-flow hyroponic units were used and plant seedlings were grown for 60 days in solutions of varying phosphate and uranium concentrations. Successful growth experiments were obtained only for big sagebrush; black greasewood did not sustain sufficient growth. The phosphate concentration of the water did affect the uptake of uranium by the big sagebrush, and this effect is most pronounced in the region of higher concentrations of uranium in the water. The ratio of the concentration of uranium in the plant to that in the water was observed to decrease with increasing uranium concentration in solution. This is indicative of an absorption barrier in the plants. The field data shows that big sagebrush responds to uranium concentrations in the soil water and not the groundwater. The manifestation of these results is that the use of big sagebrush as a biogeochemical indicator of uranium is not recommended. Since the concentration of phosphate must also be knwon in the water supplying the uranium to the plant, one should analyze this natural aqueous phase as a hydrochemical indicator rather than the big sagebrush

  15. Genetic and environmental effects on seed weight in subspecies of big sagebrush: Applications for restoration

    Science.gov (United States)

    Bryce A. Richardson; Hector G. Ortiz; Stephanie L. Carlson; Deidre M. Jaeger; Nancy L. Shaw

    2015-01-01

    The sagebrush steppe is a patchwork of species and subspecies occupying distinct environmental niches across the intermountain regions of western North America. These ecosystems face degradation from disturbances and exotic weeds. Using sagebrush seed that is matched to its appropriate niche is a critical component to successful restoration, improving habitat for the...

  16. Gold and other metals in big sagebrush (Artemisia tridentata Nutt.) as an exploration tool, Gold Run District, Humboldt County, Nevada

    Science.gov (United States)

    Erdman, J.A.; Cookro, T.M.; O'Leary, R. M.; Harms, T.F.

    1988-01-01

    Big sagebrush - a cold-desert species that dominates the terrain over large parts of western United States - was sampled along several traverses that crossed thermally metamorphosed limestone, phyllitic shale, and schist of the Middle and Upper Cambrian Preble Formation that host skarn-, disseminated gold and silver-, and hot springs gold-type mineral occurrences. Patterns of detectable levels of gold (8 to 28 ppb or ng g-1) in ash of new growth were consistent with areas affected by known or suspected gold mineralization. Soils collected along one of the traverses where a selenium-indicator plant was common contained no gold above background levels of 2ppb, but were consistently high in As, Sb, and Zn, and several samples were unusually high in Se (maximum 11 ppm or ??g g-1). Sagebrush along this traverse contained Li at levels above norms for this species. We also found a puzzling geochemical anomaly at a site basinward from active hot springs along a range-front fault scarp. Sagebrush at this site contained a trace of gold and an unusually high concentration of Cd (13 ppm) and the soil had anomalous concentrations of Cd and Bi (3.2 and 6 ppm, respectively). The source of this anomaly could be either metal-rich waters from an irrigation ditch or leakage along a buried fault. Despite the limited nature of the study, we conclude that gold in sagebrush could be a cost-effective guide to drilling locations in areas where the geology seems favorable for disseminated and vein precious metals. ?? 1988.

  17. Consequences of pre-inoculation with native arbuscular mycorrhizae on root colonization and survival of Artemisia tridentata ssp. wyomingensis (Wyoming big sagebrush) seedlings after transplanting

    Science.gov (United States)

    Bill Eugene Davidson

    2015-01-01

    Inoculation of seedlings with arbuscular mycorrhizal fungi (AMF) is a common practice aimed at improving seedling establishment. The success of this practice largely depends on the ability of the inoculum to multiply and colonize the growing root system after transplanting. These events were investigated in Artemisia tridentata ssp. wyomingensis (Wyoming big sagebrush...

  18. Legacy effects of no-analogue disturbances alter plant community diversity and composition in semi-arid sagebrush steppe

    Science.gov (United States)

    Ripplinger, Julie; Franklin, Janet; Edwards, Thomas C.

    2015-01-01

    Questions(i) What role does the type of managed disturbance play in structuring sagebrush steppe plant communities? (ii) How does the composition of post-disturbance plant communities change with time since disturbance? (iii) Does plant community diversity change over time following managed disturbance?LocationField study within the sagebrush steppe ecosystem. Rich County, Utah, USA.MethodsWe developed a chronosequence spanning up to 50 yrs post-treatment to study sagebrush steppe vegetation dynamics. Direct ordination was used to examine plant community composition by managed disturbance type and time since disturbance, and factorial analysis of covariance was used to examine diversity dynamics following disturbance. Indicator species values were calculated in order to identify characteristic species for each disturbance type.ResultsPlant communities experienced a shift toward distinct community composition for each of the three managed disturbance types, and gave no indication of returning to untreated community composition or diversity. Small post-disturbance increases in the number of non-native grass species were observed in the treatments relative to reference, with native forb species making the largest contribution to altered composition. On fire- and chemically-treated sites the proportional native forb species richness increased over time since disturbance, while the proportional contribution of non-native forbs to total species richness decreased. For all three treatment types, native grasses contributed less on average to total richness than on reference sites, while non-native grasses made up a higher proportion of total richness.ConclusionsCommon shrubland management techniques have legacy effects on the composition and diversity of sagebrush steppe plant communities, and no-analogue disturbances, such as chemical or mechanical treatments, have more pronounced legacy effects than treatments similar to natural disturbance regimes (fire). This study

  19. Bumble bee (Hymenoptera: Apidae) community structure on two sagebrush steppe sites in southern Idaho

    Science.gov (United States)

    Stephen P. Cook; Sara M. Birch; Frank W. Merickel; Carrie Caselton Lowe; Deborah Page-Dumroese

    2011-01-01

    Although sagebrush, Artemisia spp., does not require an insect pollinator, there are several native species of bumble bees, Bombus spp. (Hymenoptera: Apidae), that are present in sagebrush steppe ecosystems where they act as pollinators for various forbs and shrubs. These native pollinators contribute to plant productivity and reproduction. We captured 12 species of...

  20. Insect community responses to climate and weather across elevation gradients in the Sagebrush Steppe, eastern Oregon

    Science.gov (United States)

    Pilliod, David S.; Rohde, Ashley T.

    2016-11-17

    Executive SummaryIn this study, the U.S. Geological Survey investigated the use of insects as bioindicators of climate change in sagebrush steppe shrublands and grasslands in the Upper Columbia Basin. The research was conducted in the Stinkingwater and Pueblo mountain ranges in eastern Oregon on lands administered by the Bureau of Land Management.We used a “space-for-time” sampling design that related insect communities to climate and weather along elevation gradients. We analyzed our insect dataset at three levels of organization: (1) whole-community, (2) feeding guilds (detritivores, herbivores, nectarivores, parasites, and predators), and (3) orders within nectarivores (i.e., pollinators). We captured 59,517 insects from 176 families and 10 orders at the Pueblo Mountains study area and 112,305 insects from 185 families and 11 orders at the Stinkingwater Mountains study area in 2012 and 2013. Of all the individuals captured at the Stinkingwater Mountains study area, 77,688 were from the family Cecidomyiidae (Diptera, gall gnats).We found that the composition of insect communities was associated with variability in long-term (30-yr) temperature and interannual fluctuations in temperature. We found that captures of certain fly, bee, moth, and butterfly pollinators were more strongly associated with some climate and vegetation variables than others. We found that timing of emergence, as measured by first detection of families, was associated with elevation. When analyzed by feeding guilds, we found that all guilds emerged later at high elevations except for detritivores, which emerged earlier at high elevations. The abundance of most taxa varied through time, mostly in response to temperature and precipitation. Of the pollinators, bees (particularly, Halictidae and Megachilidae) peaked in abundance in late June and early July, whereas butterflies and moths peaked in August. Flies peaked in abundance in July.Overall, our interpretation of these patterns is that

  1. Influence of climate and environment on post-fire recovery of mountain big sagebrush

    Science.gov (United States)

    Zachary J. Nelson; Peter J. Weisberg; Stanley G. Kitchen

    2014-01-01

    In arid and semi-arid landscapes around the world, wildfire plays a key role in maintaining species diversity. Dominant plant associations may depend upon particular fire regime characteristics for their persistence. Mountain shrub communities in high-elevation landscapes of the Intermountain West, USA, are strongly influenced by the post-fire recovery dynamics of the...

  2. Sagebrush, greater sage-grouse, and the occurrence and importance of forbs

    Science.gov (United States)

    Pennington, Victoria E.; Schlaepfer, Daniel R.; Beck, Jeffrey L.; Bradford, John B.; Palmquist, Kyle A.; Lauenroth, William K.

    2016-01-01

    Big sagebrush (Artemisia tridentata Nutt.) ecosystems provide habitat for sagebrush-obligate wildlife species such as the Greater Sage-Grouse (Centrocercus urophasianus). The understory of big sagebrush plant communities is composed of grasses and forbs that are important sources of cover and food for wildlife. The grass component is well described in the literature, but the composition, abundance, and habitat role of forbs in these communities is largely unknown. Our objective was to synthesize information about forbs and their importance to Greater Sage-Grouse diets and habitats, how rangeland management practices affect forbs, and how forbs respond to changes in temperature and precipitation. We also sought to identify research gaps and needs concerning forbs in big sagebrush plant communities. We searched for relevant literature including journal articles and state and federal agency reports. Our results indicated that in the spring and summer, Greater Sage-Grouse diets consist of forbs (particularly species in the Asteraceae family), arthropods, and lesser amounts of sagebrush. The diets transition to sagebrush in fall and winter. Forbs provide cover for Greater Sage-Grouse individuals at their lekking, nesting, and brood-rearing sites, and the species has a positive relationship with arthropod presence. The effect of grazing on native forbs may be compounded by invasion of nonnative species and differs depending on grazing intensity. The effect of fire on forbs varies greatly and may depend on time elapsed since burning. In addition, chemical and mechanical treatments affect annual and perennial forbs differently. Temperature and precipitation influence forb phenology, biomass, and abundance differently among species. Our review identified several uncertainties and research needs about forbs in big sagebrush ecosystems. First, in many cases the literature about forbs is reported only at the genus or functional type level. Second, information about forb

  3. Evaluating a seed technology for sagebrush restoration across an elevation gradient: support for bet hedging

    Science.gov (United States)

    Big sagebrush (Artemisia tridentata Nutt.) restoration is needed across vast areas, especially after large wildfires, to restore important ecosystem services. Sagebrush restoration success is inconsistent with a high rate of seeding failures, particularly at lower elevations. Seed enhancement tech...

  4. The economics of fuel management: Wildfire, invasive plants, and the dynamics of sagebrush rangelands in the western United States

    Science.gov (United States)

    Michael H. Taylor; Kimberly Rollins; Mimako Kobayashi; Robin J. Tausch

    2013-01-01

    In this article we develop a simulation model to evaluate the economic efficiency of fuel treatments and apply it to two sagebrush ecosystems in the Great Basin of the western United States: the Wyoming Sagebrush Steppe and Mountain Big Sagebrush ecosystems. These ecosystems face the two most prominent concerns in sagebrush ecosystems relative to wildfire: annual grass...

  5. Sagebrush ecosystems: current status and trends.

    Science.gov (United States)

    Beever, E.A.; Connelly, J.W.; Knick, S.T.; Schroeder, M.A.; Stiver, S. J.

    2004-01-01

    The sagebrush (Artemisia spp.) biome has changed since settlement by Europeans. The current distribution, composition and dynamics, and disturbance regimes of sagebrush ecosystems have been altered by interactions among disturbance, land use, and invasion of exotic plants. In this chapter, we present the dominant factors that have influenced habitats across the sagebrush biome. Using a large-scale analysis, we identified regional changes and patterns in “natural disturbance”, invasive exotic species, and influences of land use in sagebrush systems. Number of fires and total area burned has increased since 1980 across much of the sagebrush biome. Juniper (Juniperus spp.) and pinyon (Pinus spp.) woodlands have expanded into sagebrush habitats at higher elevations. Cheatgrass (Bromus tectorum), an exotic annual grass, has invaded much of lower elevation, more xeric sagebrush landscapes across the western portion of the biome. Consequently, synergistic feedbacks between habitats and disturbance (natural and human-caused) have altered disturbance regimes, plant community dynamics and contributed to loss of sagebrush habitats and change in plant communities. Habitat conversion to agriculture has occurred in the highly productive regions of the sagebrush biome and influenced up to 56% of the Conservation Assessment area. Similarly, urban areas, and road, railroad, and powerline networks fragment habitats, facilitate predator movements, and provide corridors for spread of exotic species across the entire sagebrush biome. Livestock grazing has altered sagebrush habitats; the effects of overgrazing combined with drought on plant communities in the late 1880s and early 1900s still influences current habitats. Management of livestock grazing has influenced sagebrush ecosystems by habitat treatments to increase forage and reduce sagebrush and other plant species unpalatable to livestock. Fences, roads, and water developments to manage livestock movements have further

  6. Selecting sagebrush seed sources for restoration in a variable climate: ecophysiological variation among genotypes

    Science.gov (United States)

    Germino, Matthew J.

    2012-01-01

    Big sagebrush (Artemisia tridentata) communities dominate a large fraction of the United States and provide critical habitat for a number of wildlife species of concern. Loss of big sagebrush due to fire followed by poor restoration success continues to reduce ecological potential of this ecosystem type, particularly in the Great Basin. Choice of appropriate seed sources for restoration efforts is currently unguided due to knowledge gaps on genetic variation and local adaptation as they relate to a changing landscape. We are assessing ecophysiological responses of big sagebrush to climate variation, comparing plants that germinated from ~20 geographically distinct populations of each of the three subspecies of big sagebrush. Seedlings were previously planted into common gardens by US Forest Service collaborators Drs. B. Richardson and N. Shaw, (USFS Rocky Mountain Research Station, Provo, Utah and Boise, Idaho) as part of the Great Basin Native Plant Selection and Increase Project. Seed sources spanned all states in the conterminous Western United States. Germination, establishment, growth and ecophysiological responses are being linked to genomics and foliar palatability. New information is being produced to aid choice of appropriate seed sources by Bureau of Land Management and USFS field offices when they are planning seed acquisitions for emergency post-fire rehabilitation projects while considering climate variability and wildlife needs.

  7. Response of bird community structure to habitat management in piñon-juniper woodland-sagebrush ecotones

    Science.gov (United States)

    Knick, Steven T.; Hanser, Steven E.; Grace, James B.; Hollenbeck, Jeff P.; Leu, Matthias

    2017-01-01

    Piñon (Pinus spp.) and juniper (Juniperus spp.) woodlands have been expanding their range across the intermountain western United States into landscapes dominated by sagebrush (Artemisia spp.) shrublands. Management actions using prescribed fire and mechanical cutting to reduce woodland cover and control expansion provided opportunities to understand how environmental structure and changes due to these treatments influence bird communities in piñon-juniper systems. We surveyed 43 species of birds and measured vegetation for 1–3 years prior to treatment and 6–7 years post-treatment at 13 locations across Oregon, California, Idaho, Nevada, and Utah. We used structural equation modeling to develop and statistically test our conceptual model that the current bird assembly at a site is structured primarily by the previous bird community with additional drivers from current and surrounding habitat conditions as well as external regional bird dynamics. Treatment reduced woodland cover by >5% at 80 of 378 survey sites. However, habitat change achieved by treatment was highly variable because actual disturbance differed widely in extent and intensity. Biological inertia in the bird community was the strongest single driver; 72% of the variation in the bird assemblage was explained by the community that existed seven years earlier. Greater net reduction in woodlands resulted in slight shifts in the bird community to one having ecotone or shrubland affinities. However, the overall influence of woodland changes from treatment were relatively small and were buffered by other extrinsic factors. Regional bird dynamics did not significantly influence the structure of local bird communities at our sites. Our results suggest that bird communities in piñon-juniper woodlands can be highly stable when management treatments are conducted in areas with more advanced woodland development and at the level of disturbance measured in our study.

  8. Data Report: Meteorological and Evapotranspiration Data from Sagebrush and Pinyon Pine/Juniper Communities at Pahute Mesa, Nevada National Security Site, 2011-2012

    Energy Technology Data Exchange (ETDEWEB)

    Jasoni, Richard L [DRI; Larsen, Jessica D [DRI; Lyles, Brad F. [DRI; Healey, John M [DRI; Cooper, Clay A [DRI; Hershey, Ronald L [DRI; Lefebre, Karen J [DRI

    2013-04-01

    Pahute Mesa is a groundwater recharge area at the Nevada National Security Site. Because underground nuclear testing was conducted at Pahute Mesa, groundwater recharge may transport radionuclides from underground test sites downward to the water table; the amount of groundwater recharge is also an important component of contaminant transport models. To estimate the amount of groundwater recharge at Pahute Mesa, an INFIL3.0 recharge-runoff model is being developed. Two eddy covariance (EC) stations were installed on Pahute Mesa to estimate evapotranspiration (ET) to support the groundwater recharge modeling project. This data report describes the methods that were used to estimate ET and collect meteorological data. Evapotranspiration was estimated for two predominant plant communities on Pahute Mesa; one site was located in a sagebrush plant community, the other site in a pinyon pine/juniper community. Annual ET was estimated to be 310±13.9 mm for the sagebrush site and 347±15.9 mm for the pinyon pine/juniper site (March 26, 2011 to March 26, 2012). Annual precipitation measured with unheated tipping bucket rain gauges was 179 mm at the sagebrush site and 159 mm at the pinyon pine/juniper site. Annual precipitation measured with bulk precipitation gauges was 222 mm at the sagebrush site and 227 mm at the pinyon pine/juniper site (March 21, 2011 to March 28, 2012). A comparison of tipping bucket versus bulk precipitation data showed that total precipitation measured by the tipping bucket rain gauges was 17 to 20 percent lower than the bulk precipitation gauges. These differences were most likely the result of the unheated tipping bucket precipitation gauges not measuring frozen precipitation as accurately as the bulk precipitation gauges. In this one-year study, ET exceeded precipitation at both study sites because estimates of ET included precipitation that fell during the winter of 2010-2011 prior to EC instrumentation and the precipitation gauges started

  9. Historical fire regimes, reconstructed from land-survey data, led to complexity and fluctuation in sagebrush landscapes.

    Science.gov (United States)

    Bukowski, Beth E; Baker, William L

    2013-04-01

    Sagebrush landscapes provide habitat for Sage-Grouse and other sagebrush obligates, yet historical fire regimes and the structure of historical sagebrush landscapes are poorly known, hampering ecological restoration and management. To remedy this, General Land Office Survey (GLO) survey notes were used to reconstruct over two million hectares of historical vegetation for four sagebrush-dominated (Artemisia spp.) study areas in the western United States. Reconstructed vegetation was analyzed for fire indicators used to identify historical fires and reconstruct historical fire regimes. Historical fire-size distributions were inverse-J shaped, and one fire > 100 000 ha was identified. Historical fire rotations were estimated at 171-342 years for Wyoming big sagebrush (A. tridentata ssp. wyomingensis) and 137-217 years for mountain big sagebrush (A. tridentata ssp. vaseyana). Historical fire and patch sizes were significantly larger in Wyoming big sagebrush than mountain big sagebrush, and historical fire rotations were significantly longer in Wyoming big sagebrush than mountain big sagebrush. Historical fire rotations in Wyoming were longer than those in other study areas. Fine-scale mosaics of burned and unburned area and larger unburned inclusions within fire perimeters were less common than in modern fires. Historical sagebrush landscapes were dominated by large, contiguous areas of sagebrush, though large grass-dominated areas and finer-scale mosaics of grass and sagebrush were also present in smaller amounts. Variation in sagebrush density was a common source of patchiness, and areas classified as "dense" made up 24.5% of total sagebrush area, compared to 16.3% for "scattered" sagebrush. Results suggest significant differences in historical and modern fire regimes. Modern fire rotations in Wyoming big sagebrush are shorter than historical fire rotations. Results also suggest that historical sagebrush landscapes would have fluctuated, because of infrequent

  10. Curating Big Data Made Simple: Perspectives from Scientific Communities.

    Science.gov (United States)

    Sowe, Sulayman K; Zettsu, Koji

    2014-03-01

    The digital universe is exponentially producing an unprecedented volume of data that has brought benefits as well as fundamental challenges for enterprises and scientific communities alike. This trend is inherently exciting for the development and deployment of cloud platforms to support scientific communities curating big data. The excitement stems from the fact that scientists can now access and extract value from the big data corpus, establish relationships between bits and pieces of information from many types of data, and collaborate with a diverse community of researchers from various domains. However, despite these perceived benefits, to date, little attention is focused on the people or communities who are both beneficiaries and, at the same time, producers of big data. The technical challenges posed by big data are as big as understanding the dynamics of communities working with big data, whether scientific or otherwise. Furthermore, the big data era also means that big data platforms for data-intensive research must be designed in such a way that research scientists can easily search and find data for their research, upload and download datasets for onsite/offsite use, perform computations and analysis, share their findings and research experience, and seamlessly collaborate with their colleagues. In this article, we present the architecture and design of a cloud platform that meets some of these requirements, and a big data curation model that describes how a community of earth and environmental scientists is using the platform to curate data. Motivation for developing the platform, lessons learnt in overcoming some challenges associated with supporting scientists to curate big data, and future research directions are also presented.

  11. Multiscale sagebrush rangeland habitat modeling in southwest Wyoming

    Science.gov (United States)

    Homer, Collin G.; Aldridge, Cameron L.; Meyer, Debra K.; Coan, Michael J.; Bowen, Zachary H.

    2009-01-01

    four secondary targets included percent sagebrush (Artemisia spp.), percent big sagebrush (Artemisia tridentata), percent Wyoming sagebrush (Artemisia tridentata wyomingensis), and sagebrush height (centimeters). Results were validated by an independent accuracy assessment with root mean square error (RMSE) values ranging from 6.38 percent for bare ground to 2.99 percent for sagebrush at the QuickBird scale and RMSE values ranging from 12.07 percent for bare ground to 6.34 percent for sagebrush at the full Landsat scale. Subsequent project phases are now in progress, with plans to deliver products that improve accuracies of existing components, model new components, complete models over larger areas, track changes over time (from 1988 to 2007), and ultimately model wildlife population trends against these changes. We believe these results offer significant improvement in sagebrush rangeland quantification at multiple scales and offer users products that have been rigorously validated.

  12. Success of seeding native compared with introduced perennial vegetation for revegetating medusahead-invaded sagebrush rangeland

    Science.gov (United States)

    Millions of hectares of Wyoming big sagebrush (Artemisia tridentata Nutt. ssp. wyomingensis Beetle &Young) rangeland have been invaded by medusahead (Taeniatherum caput-medusae [L.] Nevski), an exotic annual grass that degrades wildlife habitat, reduces forage production, and decreases biodiversity....

  13. Protocols for sagebrush seed processing and seedling production at the Lucky Peak Nursery

    Science.gov (United States)

    Clark D. Fleege

    2010-01-01

    This paper presents the production protocols currently practiced at the USDA Forest Service Lucky Peak Nursery (Boise, ID) for seed processing and bareroot and container seedling production for three subspecies of big sagebrush (Artemisia tridentata).

  14. Big data and virtual communities: methodological issues

    OpenAIRE

    Martínez Torres, María del Rocío; Toral, S. L.; Fornara, Nicoletta

    2014-01-01

    Virtual communities represent today en emergent phenomenon through which users get together to create ideas, to obtain help from one another, or just to casually engage in discussions. Their increasing popularity as well as their utility as a source of business value and marketing strategies justify the necessity of defi ning some specifi c methodologies for analyzing them. The aim of this paper is providing new insights into virtual communities from a methodological viewpoint, hi...

  15. Models for predicting fuel consumption in sagebrush-dominated ecosystems

    Science.gov (United States)

    Clinton S. Wright

    2013-01-01

    Fuel consumption predictions are necessary to accurately estimate or model fire effects, including pollutant emissions during wildland fires. Fuel and environmental measurements on a series of operational prescribed fires were used to develop empirical models for predicting fuel consumption in big sagebrush (Artemisia tridentate Nutt.) ecosystems....

  16. Conserving and restoring habitat for Greater Sage-Grouse and other sagebrush-obligate wildlife: The crucial link of forbs and sagebrush diversity

    Science.gov (United States)

    Kas Dumroese; Tara Luna; Bryce A. Richardson; Francis F. Kilkenny; Justin B. Runyon

    2015-01-01

    In the western US, Greater Sage-Grouse (Centrocercus urophasianus Bonaparte [Phasianidae]) have become an indicator species of the overall health of the sagebrush (Artemisia L. [Asteraceae]) dominated communities that support a rich diversity of flora and fauna. This species has an integral association with sagebrush, its understory forbs and grasses, and the...

  17. W-519 Sagebrush Mitigation Project FY-2004 Final Review and Status

    Energy Technology Data Exchange (ETDEWEB)

    Durham, Robin E.; Sackschewsky, Michael R.

    2004-09-30

    This report summarizes activities conducted as mitigation for loss of sagebrush-steppe habitats due to Project W-519, the construction of the infrastructure for the Tank Waste Remediation System Vitrification Plant. The focus of this report is to provide a review and final status of mitigation actions performed through FY2004. Data collected since FY1999 have been included where appropriate. The Mitigation Action Plan (MAP) for Project W-519 prescribed three general actions to be performed as mitigation for the disturbance of approximately 40 ha (100 acres) of mature sagebrush-steppe habitat. These actions included: (1) transplanting approximately 130,000 sagebrush seedlings on the Fitzner-Eberhardt Arid Lands Ecology Reserve (ALE); (2) rectification of the new transmission line corridor via seeding with native grasses and sagebrush; and (3) research on native plant species with a goal of increasing species diversity in future mitigation or restoration actions. Nearly 130,000 Wyoming big sagebrush seedlings where planted on ALE during FY2000 and FY2001. About 39,000 of those seedlings were burned during the 24-Command Fire of June 2000. The surviving and subsequent replanting has resulted in about 91,000 seedlings that were planted across four general areas on ALE. A 50% survival rate at any monitoring period was defined as the performance standard in the MAP for this project. Data collected in 2004 indicate that of the over 5000 monitored plants, 51.1% are still alive, and of those the majority are thriving and blooming. These results support the potential for natural recruitment and the ultimate goal of wildlife habitat replacement. Thus, the basic performance standard for sagebrush survival within the habitat compensation planting has been met. Monitoring activities conducted in 2004 indicate considerable variation in seedling survival depending on the type of plant material, site conditions, and to a lesser extent, treatments performed at the time of planting

  18. W-519 Sagebrush Mitigation Project FY-2004 Final Review and Status

    International Nuclear Information System (INIS)

    Durham, Robin E.; Sackschewsky, Michael R.

    2004-01-01

    This report/SUMmarizes activities conducted as mitigation for loss of sagebrush-steppe habitats due to Project W-519, the construction of the infrastructure for the Tank Waste Remediation System Vitrification Plant. The focus of this report is to provide a review and final status of mitigation actions performed through FY2004. Data collected since FY1999 have been included where appropriate. The Mitigation Action Plan (MAP) for Project W-519 prescribed three general actions to be performed as mitigation for the disturbance of approximately 40 ha (100 acres) of mature sagebrush-steppe habitat. These actions included: (1) transplanting approximately 130,000 sagebrush seedlings on the Fitzner-Eberhardt Arid Lands Ecology Reserve (ALE); (2) rectification of the new transmission line corridor via seeding with native grasses and sagebrush; and (3) research on native plant species with a goal of increasing species diversity in future mitigation or restoration actions. Nearly 130,000 Wyoming big sagebrush seedlings where planted on ALE during FY2000 and FY2001. About 39,000 of those seedlings were burned during the 24-Command Fire of June 2000. The surviving and subsequent replanting has resulted in about 91,000 seedlings that were planted across four general areas on ALE. A 50% survival rate at any monitoring period was defined as the performance standard in the MAP for this project. Data collected in 2004 indicate that of the over 5000 monitored plants, 51.1% are still alive, and of those the majority are thriving and blooming. These results support the potential for natural recruitment and the ultimate goal of wildlife habitat replacement. Thus, the basic performance standard for sagebrush survival within the habitat compensation planting has been met. Monitoring activities conducted in 2004 indicate considerable variation in seedling survival depending on the type of plant material, site conditions, and to a lesser extent, treatments performed at the time of planting

  19. Genotype, soil type, and locale effects on reciprocal transplant vigor, endophyte growth, and microbial functional diversity of a narrow sagebrush hybrid zone in Salt Creek Canyon, Utah

    Science.gov (United States)

    Miglia, K.J.; McArthur, E.D.; Redman, R.S.; Rodriguez, R.J.; Zak, J.C.; Freeman, D.C.

    2007-01-01

    When addressing the nature of ecological adaptation and environmental factors limiting population ranges and contributing to speciation, it is important to consider not only the plant's genotype and its response to the environment, but also any close interactions that it has with other organisms, specifically, symbiotic microorganisms. To investigate this, soils and seedlings were reciprocally transplanted into common gardens of the big sagebrush hybrid zone in Salt Creek Canyon, Utah, to determine location and edaphic effects on the fitness of parental and hybrid plants. Endophytic symbionts and functional microbial diversity of indigenous and transplanted soils and sagebrush plants were also examined. Strong selection occurred against the parental genotypes in the middle hybrid zone garden in middle hybrid zone soil; F1 hybrids had the highest fitness under these conditions. Neither of the parental genotypes had superior fitness in their indigenous soils and habitats; rather F1 hybrids with the nonindigenous maternal parent were superiorly fit. Significant garden-by-soil type interactions indicate adaptation of both plant and soil microorganisms to their indigenous soils and habitats, most notably in the middle hybrid zone garden in middle hybrid zone soil. Contrasting performances of F1 hybrids suggest asymmetrical gene flow with mountain, rather than basin, big sagebrush acting as the maternal parent. We showed that the microbial community impacted the performance of parental and hybrid plants in different soils, likely limiting the ranges of the different genotypes.

  20. Using Big (and Critical) Data to Unmask Inequities in Community Colleges

    Science.gov (United States)

    Rios-Aguilar, Cecilia

    2014-01-01

    This chapter presents various definitions of big data and examines some of the assumptions regarding the value and power of big data, especially as it relates to issues of equity in community colleges. Finally, this chapter ends with a discussion of the opportunities and challenges of using big data, critically, for institutional researchers.

  1. Multiscale sagebrush rangeland habitat modeling in the Gunnison Basin of Colorado

    Science.gov (United States)

    Homer, Collin G.; Aldridge, Cameron L.; Meyer, Debra K.; Schell, Spencer J.

    2013-01-01

    North American sagebrush-steppe ecosystems have decreased by about 50 percent since European settlement. As a result, sagebrush-steppe dependent species, such as the Gunnison sage-grouse, have experienced drastic range contractions and population declines. Coordinated ecosystem-wide research, integrated with monitoring and management activities, is needed to help maintain existing sagebrush habitats; however, products that accurately model and map sagebrush habitats in detail over the Gunnison Basin in Colorado are still unavailable. The goal of this project is to provide a rigorous large-area sagebrush habitat classification and inventory with statistically validated products and estimates of precision across the Gunnison Basin. This research employs a combination of methods, including (1) modeling sagebrush rangeland as a series of independent objective components that can be combined and customized by any user at multiple spatial scales; (2) collecting ground measured plot data on 2.4-meter QuickBird satellite imagery in the same season the imagery is acquired; (3) modeling of ground measured data on 2.4-meter imagery to maximize subsequent extrapolation; (4) acquiring multiple seasons (spring, summer, and fall) of Landsat Thematic Mapper imagery (30-meter) for optimal modeling; (5) using regression tree classification technology that optimizes data mining of multiple image dates, ratios, and bands with ancillary data to extrapolate ground training data to coarser resolution Landsat Thematic Mapper; and 6) employing accuracy assessment of model predictions to enable users to understand their dependencies. Results include the prediction of four primary components including percent bare ground, percent herbaceous, percent shrub, and percent litter, and four secondary components including percent sagebrush (Artemisia spp.), percent big sagebrush (Artemisia tridentata), percent Wyoming sagebrush (Artemisia tridentata wyomingensis), and shrub height (centimeters

  2. Big data analytics to aid developing livable communities.

    Science.gov (United States)

    2015-12-31

    In transportation, ubiquitous deployment of low-cost sensors combined with powerful : computer hardware and high-speed network makes big data available. USDOT defines big : data research in transportation as a number of advanced techniques applied to...

  3. Selection of anthropogenic features and vegetation characteristics by nesting Common Ravens in the sagebrush ecosystem

    Science.gov (United States)

    Howe, Kristy B.; Coates, Peter S.; Delehanty, David J.

    2014-01-01

    Common Raven (Corvus corax) numbers and distribution are increasing throughout the sagebrush steppe, influencing avian communities in complex ways. Anthropogenic structures are thought to increase raven populations by providing food and nesting subsidies, which is cause for concern because ravens are important nest predators of sensitive species, including Greater Sage-Grouse (Centrocercus urophasianus). During 2007–2009, we located raven nests in southeastern Idaho and conducted a resource selection analysis. We measured variables at multiple spatial scales for 72 unique nest locations, including landscape-level vegetation characteristics and anthropogenic structures. Using generalized linear mixed models and an information-theoretic approach, we found a 31% decrease in the odds of nesting by ravens for every 1 km increase in distance away from a transmission line. Furthermore, a 100-m increase in distance away from the edge of two different land cover types decreased the odds of nesting by 20%, and an increase in the amount of edge by 1 km within an area of 102.1 ha centered on the nest increased the odds of nesting by 49%. A post hoc analysis revealed that ravens were most likely to nest near edges of adjoining big sagebrush (Artemisia tridentata) and land cover types that were associated with direct human disturbance or fire. These findings contribute to our understanding of raven expansion into rural environments and could be used to make better-informed conservation decisions, especially in the face of increasing renewable energy development.

  4. Scales of snow depth variability in high elevation rangeland sagebrush

    Science.gov (United States)

    Tedesche, Molly E.; Fassnacht, Steven R.; Meiman, Paul J.

    2017-09-01

    In high elevation semi-arid rangelands, sagebrush and other shrubs can affect transport and deposition of wind-blown snow, enabling the formation of snowdrifts. Datasets from three field experiments were used to investigate the scales of spatial variability of snow depth around big mountain sagebrush ( Artemisia tridentata Nutt.) at a high elevation plateau rangeland in North Park, Colorado, during the winters of 2002, 2003, and 2008. Data were collected at multiple resolutions (0.05 to 25 m) and extents (2 to 1000 m). Finer scale data were collected specifically for this study to examine the correlation between snow depth, sagebrush microtopography, the ground surface, and the snow surface, as well as the temporal consistency of snow depth patterns. Variograms were used to identify the spatial structure and the Moran's I statistic was used to determine the spatial correlation. Results show some temporal consistency in snow depth at several scales. Plot scale snow depth variability is partly a function of the nature of individual shrubs, as there is some correlation between the spatial structure of snow depth and sagebrush, as well as between the ground and snow depth. The optimal sampling resolution appears to be 25-cm, but over a large area, this would require a multitude of samples, and thus a random stratified approach is recommended with a fine measurement resolution of 5-cm.

  5. The Sagebrush Steppe Treatment Evaluation Project (SageSTEP): a test of state-and-transition theory

    Science.gov (United States)

    James D. McIver; Mark Brunson; Steve C. Bunting; Jeanne Chambers; Nora Devoe; Paul Doescher; James Grace; Dale Johnson; Steve Knick; Richard Miller; Mike Pellant; Fred Pierson; David Pyke; Kim Rollins; Bruce Roundy; Eugene Schupp; Robin Tausch; David Turner

    2010-01-01

    The Sagebrush Steppe Treatment Evaluation Project (SageSTEP) is a comprehensive, integrated, long-term study that evaluates the ecological effects of fire and fire surrogate treatments designed to reduce fuel and to restore sagebrush (Artemisia spp.) communities of the Great Basin and surrounding areas. SageSTEP has several features that make it ideal for testing...

  6. Vegetation responses to sagebrush-reduction treatments measured by satellites

    Science.gov (United States)

    Johnston, Aaron; Beever, Erik; Merkle, Jerod A.; Chong, Geneva W.

    2018-01-01

    Time series of vegetative indices derived from satellite imagery constitute tools to measure ecological effects of natural and management-induced disturbances to ecosystems. Over the past century, sagebrush-reduction treatments have been applied widely throughout western North America to increase herbaceous vegetation for livestock and wildlife. We used indices from satellite imagery to 1) quantify effects of prescribed-fire, herbicide, and mechanical treatments on vegetative cover, productivity, and phenology, and 2) describe how vegetation changed over time following these treatments. We hypothesized that treatments would increase herbaceous cover and accordingly shift phenologies towards those typical of grass-dominated systems. We expected prescribed burns would lead to the greatest and most-prolonged effects on vegetative cover and phenology, followed by herbicide and mechanical treatments. Treatments appeared to increase herbaceous cover and productivity, which coincided with signs of earlier senescence − signals expected of grass-dominated systems, relative to sagebrush-dominated systems. Spatial heterogeneity for most phenometrics was lower in treated areas relative to controls, which suggested treatment-induced homogenization of vegetative communities. Phenometrics that explain spring migrations of ungulates mostly were unaffected by sagebrush treatments. Fire had the strongest effect on vegetative cover, and yielded the least evidence for sagebrush recovery. Overall, treatment effects were small relative to those reported from field-based studies for reasons most likely related to sagebrush recovery, treatment specification, and untreated patches within mosaicked treatment applications. Treatment effects were also small relative to inter-annual variation in phenology and productivity that was explained by temperature, snowpack, and growing-season precipitation. Our results indicated that cumulative NDVI, late-season phenometrics, and spatial

  7. Characterization of a sagebrush (Artemisia tridentata ssp. wyomingensis) die-off on the Handford Site

    International Nuclear Information System (INIS)

    Cardenas, A.; Lewinsohn, J.; Auger, C.; Downs, J.L.; Cadwell, L.L.; Burrows, R.

    1997-09-01

    The Hanford Site contains one of the few remaining contiguous areas of shrub-steppe habitat left in Washington State. This habitat is home to many native plant and wildlife species, some of which are threatened with extinction or are unique to the Site. The importance of the Hanford Site increases as other lands surrounding the Site are developed, and these native species and habitats are lost. Stands of Wyoming big sagebrush (Artemisia tridentata ssp. wyomingensis) on the Site are a particularly important component of shrub-steppe habitat, because a number of wildlife require big sagebrush for food and cover. Since 1993, researchers and field biologists have made anecdotal observations of dying and declining sagebrush in stands of shrubs near the 100 Areas. This study was initiated to delineate and document the general boundary where sagebrush stands appear to be declining. We mapped the areal extent of the die-off using a global positioning system and found that the central portion of the die-off encompasses 280 hectares. Shrub stand defoliation was estimated to be near or greater than 80% in this area. The remainder of the die-off area exhibits varying mixtures of completely defoliated, partially defoliated, and healthy-looking stands. Declining sagebrush stands comprise a total of 1776 hectares

  8. Characterization of a sagebrush (Artemisia tridentata ssp. wyomingensis) die-off on the Handford Site

    Energy Technology Data Exchange (ETDEWEB)

    Cardenas, A.; Lewinsohn, J.; Auger, C.; Downs, J.L.; Cadwell, L.L.; Burrows, R.

    1997-09-01

    The Hanford Site contains one of the few remaining contiguous areas of shrub-steppe habitat left in Washington State. This habitat is home to many native plant and wildlife species, some of which are threatened with extinction or are unique to the Site. The importance of the Hanford Site increases as other lands surrounding the Site are developed, and these native species and habitats are lost. Stands of Wyoming big sagebrush (Artemisia tridentata ssp. wyomingensis) on the Site are a particularly important component of shrub-steppe habitat, because a number of wildlife require big sagebrush for food and cover. Since 1993, researchers and field biologists have made anecdotal observations of dying and declining sagebrush in stands of shrubs near the 100 Areas. This study was initiated to delineate and document the general boundary where sagebrush stands appear to be declining. We mapped the areal extent of the die-off using a global positioning system and found that the central portion of the die-off encompasses 280 hectares. Shrub stand defoliation was estimated to be near or greater than 80% in this area. The remainder of the die-off area exhibits varying mixtures of completely defoliated, partially defoliated, and healthy-looking stands. Declining sagebrush stands comprise a total of 1776 hectares.

  9. Resilience and resistance of sagebrush ecosystems: implications for state and transition models and management treatments

    Science.gov (United States)

    Chambers, Jeanne C.; Miller, Richard F.; Board, David I.; Pyke, David A.; Roundy, Bruce A.; Grace, James B.; Schupp, Eugene W.; Tausch, Robin J.

    2014-01-01

    In sagebrush ecosystems invasion of annual exotics and expansion of piñon (Pinus monophylla Torr. and Frem.) and juniper (Juniperus occidentalis Hook., J. osteosperma [Torr.] Little) are altering fire regimes and resulting in large-scale ecosystem transformations. Management treatments aim to increase resilience to disturbance and enhance resistance to invasive species by reducing woody fuels and increasing native perennial herbaceous species. We used Sagebrush Steppe Treatment Evaluation Project data to test predictions on effects of fire vs. mechanical treatments on resilience and resistance for three site types exhibiting cheatgrass (Bromus tectorum L.) invasion and/or piñon and juniper expansion: 1) warm and dry Wyoming big sagebrush (WY shrub); 2) warm and moist Wyoming big sagebrush (WY PJ); and 3) cool and moist mountain big sagebrush (Mtn PJ). Warm and dry (mesic/aridic) WY shrub sites had lower resilience to fire (less shrub recruitment and native perennial herbaceous response) than cooler and moister (frigid/xeric) WY PJ and Mtn PJ sites. Warm (mesic) WY Shrub and WY PJ sites had lower resistance to annual exotics than cool (frigid to cool frigid) Mtn PJ sites. In WY shrub, fire and sagebrush mowing had similar effects on shrub cover and, thus, on perennial native herbaceous and exotic cover. In WY PJ and Mtn PJ, effects were greater for fire than cut-and-leave treatments and with high tree cover in general because most woody vegetation was removed increasing resources for other functional groups. In WY shrub, about 20% pretreatment perennial native herb cover was necessary to prevent increases in exotics after treatment. Cooler and moister WY PJ and especially Mtn PJ were more resistant to annual exotics, but perennial native herb cover was still required for site recovery. We use our results to develop state and transition models that illustrate how resilience and resistance influence vegetation dynamics and management options.

  10. Common raven occurrence in relation to energy transmission line corridors transiting human-altered sagebrush steppe

    Science.gov (United States)

    Coates, Peter S.; Howe, Kristy B.; Casazza, Michael L.; Delehanty, David J.

    2014-01-01

    Energy-related infrastructure and other human enterprises within sagebrush steppe of the American West often results in changes that promote common raven (Corvus corax; hereafter, raven) populations. Ravens, a generalist predator capable of behavioral innovation, present a threat to many species of conservation concern. We evaluate the effects of detailed features of an altered landscape on the probability of raven occurrence using extensive raven survey (n= 1045) and mapping data from southern Idaho, USA. We found nonlinear relationships between raven occurrence and distances to transmission lines, roads, and facilities. Most importantly, raven occurrence was greater with presence of transmission lines up to 2.2 km from the corridor.We further explain variation in raven occurrence along anthropogenic features based on the amount of non-native vegetation and cover type edge, such that ravens select fragmented sagebrush stands with patchy, exotic vegetative introgression. Raven occurrence also increased with greater length of edge formed by the contact of big sagebrush (Artemisia tridentate spp.) with non-native vegetation cover types. In consideration of increasing alteration of sagebrush steppe, these findings will be useful for planning energy transmission corridor placement and other management activities where conservation of sagebrush obligate species is a priority.

  11. Mid-latitude shrub steppe plant communities: climate change consequences for soil water resources.

    Science.gov (United States)

    Palmquist, Kyle A; Schlaepfer, Daniel R; Bradford, John B; Lauenroth, William K

    2016-09-01

    In the coming century, climate change is projected to impact precipitation and temperature regimes worldwide, with especially large effects in drylands. We use big sagebrush ecosystems as a model dryland ecosystem to explore the impacts of altered climate on ecohydrology and the implications of those changes for big sagebrush plant communities using output from 10 Global Circulation Models (GCMs) for two representative concentration pathways (RCPs). We ask: (1) What is the magnitude of variability in future temperature and precipitation regimes among GCMs and RCPs for big sagebrush ecosystems, and (2) How will altered climate and uncertainty in climate forecasts influence key aspects of big sagebrush water balance? We explored these questions across 1980-2010, 2030-2060, and 2070-2100 to determine how changes in water balance might develop through the 21st century. We assessed ecohydrological variables at 898 sagebrush sites across the western US using a process-based soil water model, SOILWAT, to model all components of daily water balance using site-specific vegetation parameters and site-specific soil properties for multiple soil layers. Our modeling approach allowed for changes in vegetation based on climate. Temperature increased across all GCMs and RCPs, whereas changes in precipitation were more variable across GCMs. Winter and spring precipitation was predicted to increase in the future (7% by 2030-2060, 12% by 2070-2100), resulting in slight increases in soil water potential (SWP) in winter. Despite wetter winter soil conditions, SWP decreased in late spring and summer due to increased evapotranspiration (6% by 2030-2060, 10% by 2070-2100) and groundwater recharge (26% and 30% increase by 2030-2060 and 2070-2100). Thus, despite increased precipitation in the cold season, soils may dry out earlier in the year, resulting in potentially longer, drier summer conditions. If winter precipitation cannot offset drier summer conditions in the future, we expect big

  12. Mid-latitude shrub steppe plant communities: Climate change consequences for soil water resources

    Science.gov (United States)

    Palmquist, Kyle A.; Schlaepfer, Daniel R.; Bradford, John B.; Lauenroth, Willliam K.

    2016-01-01

    In the coming century, climate change is projected to impact precipitation and temperature regimes worldwide, with especially large effects in drylands. We use big sagebrush ecosystems as a model dryland ecosystem to explore the impacts of altered climate on ecohydrology and the implications of those changes for big sagebrush plant communities using output from 10 Global Circulation Models (GCMs) for two representative concentration pathways (RCPs). We ask: 1) What is the magnitude of variability in future temperature and precipitation regimes among GCMs and RCPs for big sagebrush ecosystems and 2) How will altered climate and uncertainty in climate forecasts influence key aspects of big sagebrush water balance? We explored these questions across 1980-2010, 2030-2060, and 2070-2100 to determine how changes in water balance might develop through the 21st century. We assessed ecohydrological variables at 898 sagebrush sites across the western US using a process-based soil water model, SOILWAT to model all components of daily water balance using site-specific vegetation parameters and site-specific soil properties for multiple soil layers. Our modeling approach allowed for changes in vegetation based on climate. Temperature increased across all GCMs and RCPs, while changes in precipitation were more variable across GCMs. Winter and spring precipitation was predicted to increase in the future (7% by 2030-2060, 12% by 2070-2100), resulting in slight increases in soil water potential (SWP) in winter. Despite wetter winter soil conditions, SWP decreased in late spring and summer due to increased evapotranspiration (6% by 2030-2060, 10% by 2070-2100) and groundwater recharge (26% and 30% increase by 2030-2060 and 2070-2100). Thus, despite increased precipitation in the cold season, soils may dry out earlier in the year, resulting in potentially longer drier summer conditions. If winter precipitation cannot offset drier summer conditions in the future, we expect big

  13. Simulating the Dependence of Sagebrush Steppe Vegetation on Redistributed Snow in a Semi-Arid Watershed.

    Science.gov (United States)

    Soderquist, B.; Kavanagh, K.; Link, T. E.; Strand, E. K.; Seyfried, M. S.

    2014-12-01

    In mountainous regions across the western USA, the composition of aspen (Populus tremuloides) and sagebrush steppe plant communities is often closely related to heterogeneous soil moisture subsidies resulting from redistributed snow. With decades of climate and precipitation data across elevational and precipitation gradients, the Reynolds Creek Experimental Watershed (RCEW) and critical zone observatory (CZO) in southwest Idaho provides a unique opportunity to study the relationship between vegetation types and redistributed snow. Within the RCEW, the total amount of precipitation has remained unchanged over the past 50 years, however the percentage of the precipitation falling as snow has declined by approximately 4% per decade at mid-elevation sites. As shifts in precipitation phase continue, future trends in vegetation composition and net primary productivity (NPP) of different plant functional types remains a critical question. We hypothesize that redistribution of snow may supplement drought sensitive species like aspen more so than drought tolerant species like mountain big sagebrush (Artemisia tridentata spp. vaseyana). To assess the importance of snowdrift subsidies on sagebrush steppe vegetation, NPP of aspen, shrub, and grass species was simulated at three sites using the biogeochemical process model BIOME-BGC. Each site is located directly downslope from snowdrifts providing soil moisture inputs to aspen stands and neighboring vegetation. Drifts vary in size with the largest containing up to four times the snow water equivalent (SWE) of a uniform precipitation layer. Precipitation inputs used by BIOME-BGC were modified to represent the redistribution of snow and simulations were run using daily climate data from 1985-2013. Simulated NPP of annual grasses at each site was not responsive to subsidies from drifting snow. However, at the driest site, aspen and shrub annual NPP was increased by as much as 44 and 30%, respectively, with the redistribution of

  14. Prescribed Fire Effects on Runoff, Erosion, and Soil Water Repellency on Steeply-Sloped Sagebrush Rangeland over a Five Year Period

    Science.gov (United States)

    Williams, C. J.; Pierson, F. B.; Al-Hamdan, O. Z.

    2014-12-01

    Fire is an inherent component of sagebrush steppe rangelands in western North America and can dramatically affect runoff and erosion processes. Post-fire flooding and erosion events pose substantial threats to proximal resources, property, and human life. Yet, prescribed fire can serve as a tool to manage vegetation and fuels on sagebrush rangelands and to reduce the potential for large catastrophic fires and mass erosion events. The impact of burning on event hydrologic and erosion responses is strongly related to the degree to which burning alters vegetation, ground cover, and surface soils and the intensity and duration of precipitation. Fire impacts on hydrologic and erosion response may be intensified or reduced by inherent site characteristics such as topography and soil properties. Parameterization of these diverse conditions in predictive tools is often limited by a lack of data and/or understanding for the domain of interest. Furthermore, hydrologic and erosion functioning change as vegetation and ground cover recover in the years following burning and few studies track these changes over time. In this study, we evaluated the impacts of prescribed fire on vegetation, ground cover, soil water repellency, and hydrologic and erosion responses 1, 2, and 5 yr following burning of a mountain big sagebrush community on steep hillslopes with fine-textured soils. The study site is within the Reynolds Creek Experimental Watershed, southwestern Idaho, USA. Vegetation, ground cover, and soil properties were measured over plot scales of 0.5 m2 to 9 m2. Rainfall simulations (0.5 m2) were used to assess the impacts of fire on soil water repellency, infiltration, runoff generation, and splash-sheet erosion. Overland flow experiments (9 m2) were used to assess the effects of fire-reduced ground cover on concentrated-flow runoff and erosion processes. The study results provide insight regarding fire impacts on runoff, erosion, and soil water repellency in the immediate and

  15. Development of Competency-Based Articulated Automotive Program. Big Bend Community College and Area High Schools. Final Report.

    Science.gov (United States)

    Buche, Fred; Cox, Charles

    A competency-based automotive mechanics curriculum was developed at Big Bend Community College (Washington) in order to provide the basis for an advanced placement procedure for high school graduates and experienced adults through a competency assessment. In order to create the curriculum, Big Bend Community College automotive mechanics…

  16. History of fire and Douglas-fir establishment in a savanna and sagebrush-grassland mosaic, southwestern Montana, USA

    Science.gov (United States)

    Emily K. Heyerdahl; Richard F. Miller; Russell A. Parsons

    2006-01-01

    Over the past century, trees have encroached into grass- and shrublands across western North America. These include Douglas-fir trees (Pseudotsuga menziesii (Mirb.) Franco var. glauca (Beissn.) Franco) encroaching into mountain big sagebrush Nutt. ssp. vaseyana (Rydb.) Beetle) from stable islands of savanna in...

  17. Community Engagement for Big Epidemiology: Deliberative Democracy as a Tool

    Directory of Open Access Journals (Sweden)

    Rebekah E. McWhirter

    2014-11-01

    Full Text Available Public trust is critical in any project requiring significant public support, both in monetary terms and to encourage participation. The research community has widely recognized the centrality of public trust, garnered through community consultation, to the success of large-scale epidemiology. This paper examines the potential utility of the deliberative democracy methodology within the public health research setting. A deliberative democracy event was undertaken in Tasmania, Australia, as part of a wider program of community consultation regarding the potential development of a Tasmanian Biobank. Twenty-five Tasmanians of diverse backgrounds participated in two weekends of deliberation; involving elements of information gathering; discussion; identification of issues and formation of group resolutions. Participants demonstrated strong support for a Tasmanian Biobank and their deliberations resulted in specific proposals in relation to consent; privacy; return of results; governance; funding; and, commercialization and benefit sharing. They exhibited a high degree of satisfaction with the event, and confidence in the outcomes. Deliberative democracy methodology is a useful tool for community engagement that addresses some of the limitations of traditional consultation methods.

  18. Community Engagement for Big Epidemiology: Deliberative Democracy as a Tool

    Science.gov (United States)

    McWhirter, Rebekah E.; Critchley, Christine R.; Nicol, Dianne; Chalmers, Don; Whitton, Tess; Otlowski, Margaret; Burgess, Michael M.; Dickinson, Joanne L.

    2014-01-01

    Public trust is critical in any project requiring significant public support, both in monetary terms and to encourage participation. The research community has widely recognized the centrality of public trust, garnered through community consultation, to the success of large-scale epidemiology. This paper examines the potential utility of the deliberative democracy methodology within the public health research setting. A deliberative democracy event was undertaken in Tasmania, Australia, as part of a wider program of community consultation regarding the potential development of a Tasmanian Biobank. Twenty-five Tasmanians of diverse backgrounds participated in two weekends of deliberation; involving elements of information gathering; discussion; identification of issues and formation of group resolutions. Participants demonstrated strong support for a Tasmanian Biobank and their deliberations resulted in specific proposals in relation to consent; privacy; return of results; governance; funding; and, commercialization and benefit sharing. They exhibited a high degree of satisfaction with the event, and confidence in the outcomes. Deliberative democracy methodology is a useful tool for community engagement that addresses some of the limitations of traditional consultation methods. PMID:25563457

  19. Discussing the Life of the Others: Doing Ethnography in the Brazilian Big Brother Fan Community

    Directory of Open Access Journals (Sweden)

    Bruno Campanella

    2009-05-01

    Full Text Available The aim of this paper is to present some of the initial results of ethnographic research conducted in early 2008 with the online fan community of the Brazilian Big Brother (BBB. After a brief introduction to some of the challenges faced by ethnographic work on television audiences in the last couple of decades, the current piece will explore some of the main characteristics constituting this new social space. Beyond the gossiping, and the more immediate talks about behaviors and game strategies of the Big Brother housemates, these forums sometimes trigger exchanges about Brazilian society at large, and the role of television broadcasting in general. Nonetheless, a closer inspection reveals how the debates found in the community are themselves permeated by the participants' struggle for status.

  20. Evaluating winter/spring seeding of a native perennial bunchgrass in the sagebrush steppe

    Science.gov (United States)

    Sagebrush (Artemisia tridentata Nutt.) plant communities in the US Great Basin region are being severely impacted by increasingly frequent wildfires in association with the expansion of exotic annual grasses. Maintenance of native perennial bunchgrasses is key to controlling annual grass expansion,...

  1. Creation a Geo Big Data Outreach and Training Collaboratory for Wildfire Community

    Science.gov (United States)

    Altintas, I.; Sale, J.; Block, J.; Cowart, C.; Crawl, D.

    2015-12-01

    A major challenge for the geoscience community is the training and education of current and next generation big data geoscientists. In wildfire research, there are an increasing number of tools, middleware and techniques to use for data science related to wildfires. The necessary computing infrastructures are often within reach and most of the software tools for big data are freely available. But what has been lacking is a transparent platform and training program to produce data science experts who can use these integrated tools effectively. Scientists well versed to take advantage of big data technologies in geoscience applications is of critical importance to the future of research and knowledge advancement. To address this critical need, we are developing learning modules to teach process-based thinking to capture the value of end-to-end systems of reusable blocks of knowledge and integrate the tools and technologies used in big data analysis in an intuitive manner. WIFIRE is an end-to-end cyberinfrastructure for dynamic data-driven simulation, prediction and visualization of wildfire behavior.To this end, we are openly extending an environment we have built for "big data training" (biobigdata.ucsd.edu) to similar MOOC-based approaches to the wildfire community. We are building an environment that includes training modules for distributed platforms and systems, Big Data concepts, and scalable workflow tools, along with other basics of data science including data management, reproducibility and sharing of results. We also plan to provide teaching modules with analytical and dynamic data-driven wildfire behavior modeling case studies which address the needs not only of standards-based K-12 science education but also the needs of a well-educated and informed citizenry.Another part our outreach mission is to educate our community on all aspects of wildfire research. One of the most successful ways of accomplishing this is through high school and undergraduate

  2. Effectiveness of prescribed fire to re-establish sagebrush vegetation and ecohydrologic function on woodland-encroached sagebrush steppe, Great Basin, USA

    Science.gov (United States)

    Williams, C. J.; Pierson, F. B.; Kormos, P.; Al-Hamdan, O. Z.; Nouwakpo, S.; Weltz, M.; Vega, S.; Lindsay, K.

    2017-12-01

    Range expansion of pinyon (Pinus spp.) and juniper (Juniperus spp.) conifers into sagebrush steppe (Artemisia spp.) communities has imperiled a vast domain in the western US. Encroachment of sagebrush ecosystems by pinyon and juniper conifers has negative ramifications to ecosystem structure and function and delivery of goods and services. Scientists, land management agencies, and private land owners throughout the western US are challenged with selecting from a suite of options to reduce pinyon and juniper woody fuels and re-establish sagebrush steppe structure and function. This study evaluated the effectiveness of prescribed fire to re-establish sagebrush vegetation and ecohydrologic function over a 9 yr period. Nine years post-fire hydrologic and erosion responses reflect the combination of pre-fire site conditions, perennial grass recruitment, delayed litter cover, and inherent site characteristics. Burning initially increased bare ground, runoff, and erosion for well-vegetated areas underneath tree and shrub canopies, but had minimal impact on hydrology and erosion for degraded interspaces between plants. The degraded interspaces were primarily bare ground and exhibited high runoff and erosion rates prior to burning. Initial fire effects persisted for two years, but increased productivity of grasses improved hydrologic function of interspaces over the full 9 yr period. At the hillslope scale, grass recruitment in the intercanopy between trees reduced runoff from rainsplash, sheetflow, and concentrated overland flow at one site, but did not reduce the high levels of runoff and erosion from a more degraded site. In areas formerly occupied by trees (tree zones), burning increased invasive annual grass cover due to fire removal of limited native perennial plants and competition for resources. The invasive annual grass cover had no net effect on runoff and erosion from tree zones however. Runoff and erosion increased in tree zones at the more degraded site due to

  3. Multi-scale remote sensing sagebrush characterization with regression trees over Wyoming, USA: laying a foundation for monitoring

    Science.gov (United States)

    Homer, Collin G.; Aldridge, Cameron L.; Meyer, Debra K.; Schell, Spencer J.

    2012-01-01

    agebrush ecosystems in North America have experienced extensive degradation since European settlement. Further degradation continues from exotic invasive plants, altered fire frequency, intensive grazing practices, oil and gas development, and climate change – adding urgency to the need for ecosystem-wide understanding. Remote sensing is often identified as a key information source to facilitate ecosystem-wide characterization, monitoring, and analysis; however, approaches that characterize sagebrush with sufficient and accurate local detail across large enough areas to support this paradigm are unavailable. We describe the development of a new remote sensing sagebrush characterization approach for the state of Wyoming, U.S.A. This approach integrates 2.4 m QuickBird, 30 m Landsat TM, and 56 m AWiFS imagery into the characterization of four primary continuous field components including percent bare ground, percent herbaceous cover, percent litter, and percent shrub, and four secondary components including percent sagebrush (Artemisia spp.), percent big sagebrush (Artemisia tridentata), percent Wyoming sagebrush (Artemisia tridentata Wyomingensis), and shrub height using a regression tree. According to an independent accuracy assessment, primary component root mean square error (RMSE) values ranged from 4.90 to 10.16 for 2.4 m QuickBird, 6.01 to 15.54 for 30 m Landsat, and 6.97 to 16.14 for 56 m AWiFS. Shrub and herbaceous components outperformed the current data standard called LANDFIRE, with a shrub RMSE value of 6.04 versus 12.64 and a herbaceous component RMSE value of 12.89 versus 14.63. This approach offers new advancements in sagebrush characterization from remote sensing and provides a foundation to quantitatively monitor these components into the future.

  4. Evapotranspiration over spatially extensive plant communities in the Big Cypress National Preserve, southern Florida, 2007-2010

    Science.gov (United States)

    Shoemaker, W. Barclay; Lopez, Christian D.; Duever, Michael J.

    2011-01-01

    Evapotranspiration (ET) was quantified over plant communities within the Big Cypress National Preserve (BCNP) using the eddy covariance method for a period of 3 years from October 2007 to September 2010. Plant communities selected for study included Pine Upland, Wet Prairie, Marsh, Cypress Swamp, and Dwarf Cypress. These plant communities are spatially extensive in southern Florida, and thus, the ET measurements described herein can be applied to other humid subtropical locations such as the Everglades.

  5. Crop type influences edge effects on the reproduction of songbirds in sagebrush habitat near agriculture

    Directory of Open Access Journals (Sweden)

    Elly C. Knight

    2014-06-01

    Full Text Available Extensive fragmentation of the sagebrush shrubsteppe of western North America could be contributing to observed population declines of songbirds in sagebrush habitat. We examined whether habitat fragmentation impacts the reproduction of songbirds in sagebrush edge habitat near agriculture, and if potential impacts vary depending on the adjacent crop type. Specifically, we evaluated whether nest abundance and nest survival varied between orchard edge habitat, vineyard edge habitat, and interior habitat. We then examined whether the local nest predator community and vegetation could explain the differences detected. We detected fewer nests in edge than interior habitat. Nest abundance per songbird was also lower in edge than interior habitat, although only adjacent to vineyards. Nest predation was more frequent in orchard edge habitat than vineyard edge or interior habitat. Predators identified with nest cameras were primarily snakes, however, reduced nest survival in orchard edge habitat was not explained by differences in the abundance of snakes or any other predator species identified. Information theoretic analysis of daily survival rates showed that greater study plot shrub cover and lower grass height at nests were partially responsible for the lower rate of predation-specific daily nest survival rate (PDSR observed in orchard edge habitat, but additional factors are likely important. Results of this study suggest that different crop types have different edge effects on songbirds nesting in sagebrush shrubsteppe, and that these reproductive edge effects may contribute to observed declines of these species. Habitat managers should avoid the creation of new orchard-sagebrush habitat edges to avoid further impacts on already declining songbird populations.

  6. Utilizing Big Data and Twitter to Discover Emergent Online Communities of Cannabis Users

    Directory of Open Access Journals (Sweden)

    Peter Baumgartner

    2017-05-01

    Full Text Available Large shifts in medical, recreational, and illicit cannabis consumption in the United States have implications for personalizing treatment and prevention programs to a wide variety of populations. As such, considerable research has investigated clinical presentations of cannabis users in clinical and population-based samples. Studies leveraging big data, social media, and social network analysis have emerged as a promising mechanism to generate timely insights that can inform treatment and prevention research. This study extends a novel method called stochastic block modeling to derive communities of cannabis consumers as part of a complex social network on Twitter. A set of examples illustrate how this method can ascertain candidate samples of medical, recreational, and illicit cannabis users. Implications for research planning, intervention design, and public health surveillance are discussed.

  7. Putting Big Data to Work: Community Colleges Use Detailed Reports to Design Smarter Workforce Training and Education Programs

    Science.gov (United States)

    Woods, Bob

    2013-01-01

    In this article, Bob Woods reports that "Big data" is all the rage on college campuses, and it makes sense that administrators would use what they know to boost student outcomes. Woods points out that community colleges around the country are using the data: (1) to guide the systematic expansion of its curriculum, providing targeted…

  8. Big Data Clustering via Community Detection and Hyperbolic Network Embedding in IoT Applications.

    Science.gov (United States)

    Karyotis, Vasileios; Tsitseklis, Konstantinos; Sotiropoulos, Konstantinos; Papavassiliou, Symeon

    2018-04-15

    In this paper, we present a novel data clustering framework for big sensory data produced by IoT applications. Based on a network representation of the relations among multi-dimensional data, data clustering is mapped to node clustering over the produced data graphs. To address the potential very large scale of such datasets/graphs that test the limits of state-of-the-art approaches, we map the problem of data clustering to a community detection one over the corresponding data graphs. Specifically, we propose a novel computational approach for enhancing the traditional Girvan-Newman (GN) community detection algorithm via hyperbolic network embedding. The data dependency graph is embedded in the hyperbolic space via Rigel embedding, allowing more efficient computation of edge-betweenness centrality needed in the GN algorithm. This allows for more efficient clustering of the nodes of the data graph in terms of modularity, without sacrificing considerable accuracy. In order to study the operation of our approach with respect to enhancing GN community detection, we employ various representative types of artificial complex networks, such as scale-free, small-world and random geometric topologies, and frequently-employed benchmark datasets for demonstrating its efficacy in terms of data clustering via community detection. Furthermore, we provide a proof-of-concept evaluation by applying the proposed framework over multi-dimensional datasets obtained from an operational smart-city/building IoT infrastructure provided by the Federated Interoperable Semantic IoT/cloud Testbeds and Applications (FIESTA-IoT) testbed federation. It is shown that the proposed framework can be indeed used for community detection/data clustering and exploited in various other IoT applications, such as performing more energy-efficient smart-city/building sensing.

  9. Big Data Clustering via Community Detection and Hyperbolic Network Embedding in IoT Applications

    Directory of Open Access Journals (Sweden)

    Vasileios Karyotis

    2018-04-01

    Full Text Available In this paper, we present a novel data clustering framework for big sensory data produced by IoT applications. Based on a network representation of the relations among multi-dimensional data, data clustering is mapped to node clustering over the produced data graphs. To address the potential very large scale of such datasets/graphs that test the limits of state-of-the-art approaches, we map the problem of data clustering to a community detection one over the corresponding data graphs. Specifically, we propose a novel computational approach for enhancing the traditional Girvan–Newman (GN community detection algorithm via hyperbolic network embedding. The data dependency graph is embedded in the hyperbolic space via Rigel embedding, allowing more efficient computation of edge-betweenness centrality needed in the GN algorithm. This allows for more efficient clustering of the nodes of the data graph in terms of modularity, without sacrificing considerable accuracy. In order to study the operation of our approach with respect to enhancing GN community detection, we employ various representative types of artificial complex networks, such as scale-free, small-world and random geometric topologies, and frequently-employed benchmark datasets for demonstrating its efficacy in terms of data clustering via community detection. Furthermore, we provide a proof-of-concept evaluation by applying the proposed framework over multi-dimensional datasets obtained from an operational smart-city/building IoT infrastructure provided by the Federated Interoperable Semantic IoT/cloud Testbeds and Applications (FIESTA-IoT testbed federation. It is shown that the proposed framework can be indeed used for community detection/data clustering and exploited in various other IoT applications, such as performing more energy-efficient smart-city/building sensing.

  10. The effect of herbaceous species removal, fire and cheatgrass (Bromus tectorum) on soil water availability in sagebrush steppe

    Science.gov (United States)

    Alison Whittaker; Bruce Roundy; Jeanne Chambers; Susan Meyer; Robert Blank; Stanley Kitchen; John Korfmacher

    2008-01-01

    Over the past several decades, cheatgrass (Bromus tectorum) has been continually expanding in the sagebrush steppe ecosystem. There has been very little research that examines why cheatgrass is able to invade these communities. To determine the effects of herbaceous vegetation removal and fire on available water for cheatgrass invasion, as well as...

  11. Sagebrush-ungulate relationships on the Northern Yellowstone Winter Range

    Science.gov (United States)

    Carl L. Wambolt

    2005-01-01

    Sagebrush (Artemisia) taxa have historically been the landscape dominants over much of the Northern Yellowstone Winter Range (NYWR). Their importance to the unnaturally large ungulate populations on the NYWR throughout the twentieth century has been recognized since the 1920s. Sagebrush-herbivore ecology has been the focus of research on the NYWR for...

  12. Remote sensing of sagebrush canopy nitrogen

    Science.gov (United States)

    Mitchell, Jessica J.; Glenn, Nancy F.; Sankey, Temuulen T.; Derryberry, DeWayne R.; Germino, Matthew J.

    2012-01-01

    This paper presents a combination of techniques suitable for remotely sensing foliar Nitrogen (N) in semiarid shrublands – a capability that would significantly improve our limited understanding of vegetation functionality in dryland ecosystems. The ability to estimate foliar N distributions across arid and semi-arid environments could help answer process-driven questions related to topics such as controls on canopy photosynthesis, the influence of N on carbon cycling behavior, nutrient pulse dynamics, and post-fire recovery. Our study determined that further exploration into estimating sagebrush canopy N concentrations from an airborne platform is warranted, despite remote sensing challenges inherent to open canopy systems. Hyperspectral data transformed using standard derivative analysis were capable of quantifying sagebrush canopy N concentrations using partial least squares (PLS) regression with an R2 value of 0.72 and an R2 predicted value of 0.42 (n = 35). Subsetting the dataset to minimize the influence of bare ground (n = 19) increased R2 to 0.95 (R2 predicted = 0.56). Ground-based estimates of canopy N using leaf mass per unit area measurements (LMA) yielded consistently better model fits than ground-based estimates of canopy N using cover and height measurements. The LMA approach is likely a method that could be extended to other semiarid shrublands. Overall, the results of this study are encouraging for future landscape scale N estimates and represent an important step in addressing the confounding influence of bare ground, which we found to be a major influence on predictions of sagebrush canopy N from an airborne platform.

  13. Comparison of radionuclide levels in soil, sagebrush, plant litter, cryptogams, and small mammals

    International Nuclear Information System (INIS)

    Landeen, D.S.

    1994-09-01

    Soil, sagebrush, plant litter, cryptogam, and small mammal samples were collected and analyzed for cesium-137, strontium-90, plutonium-238, plutonium 239/240, technetium-99, and iodine-129 from 1981 to 1986 at the US Department of Energy Hanford Site in southeastern Washington State as part of site characterization and environmental monitoring activities. Samples were collected on the 200 Areas Plateau, downwind from ongoing waste management activities. Plant litter, cryptogams, and small mammals are media that are not routinely utilized in monitoring or characterization efforts for determination of radionuclide concentrations. Studies at Hanford, other US Department of Energy sites, and in eastern Europe have indicated that plant litter and cryptogams may serve as effective ''natural'' monitors of air quality. Plant litter in this study consists of fallen leaves from sagebrush and ''cryptogams'' describes that portion of the soil crust composed of mosses, lichens, algae, and fungi. Comparisons of cesium-137 and strontium-90 concentrations in the soil, sagebrush, litter, and cryptogams revealed significantly higher (p<0.05) levels in plant litter and cryptogams. Technetium-99 values were the highest in sagebrush and litter. Plutonium-238 and 239/40 and iodine-129 concentrations never exceeded 0.8 pCi/gm in all media. No evidence of any significant amounts of any radionuclides being incorporated into the small mammal community was discovered. The data indicate that plant litter and cryptogams may be better, indicators of environmental quality than soil or vegetation samples. Augmenting a monitoring program with samples of litter and cryptogams may provide a more accurate representation of radionuclide environmental uptake and/or contamination levels in surrounding ecosystems. The results of this study may be applied directly to other radioecological monitoring conducted at other nuclear sites and to the monitoring of other pollutants

  14. Ecological influence and pathways of land use in sagebrush

    Science.gov (United States)

    Knick, Steven T.; Hanser, Steven E.; Miller, Richard F.; Pyke, David A.; Wisdom, Michael J.; Finn, Sean P.; Rinkes, E. Thomas; Henny, Charles J.; Knick, Steven T.; Connelly, John W.

    2011-01-01

    Land use in sagebrush (Artemisia spp.) landscapes influences all sage-grouse (Centrocer-cus spp.) populations in western North America. Croplands and the network of irrigation canals cover 230,000 km2 and indirectly influence up to 77% of the Sage-Grouse Conservation Area and 73% of sagebrush land cover by subsidizing synanthropic predators on sage-grouse. Urbanization and the demands of human population growth have created an extensive network of con-necting infrastructure that is expanding its influence on sagebrush landscapes. Over 2,500 km2 are now covered by interstate highways and paved roads; when secondary roads are included, 15% of the Sage-Grouse Conservation Area and 5% of existing sagebrush habitats are 2.5 km from roads. Density of secondary roads often exceeds 5 km/km2, resulting in widespread motorized access for recreation, creating extensive travel corridors for management actions and resource development, subsidizing predators adapted to human presence, and facilitating spread of exotic or invasive plants. Sagebrush lands also are being used for their wilderness and recreation values, including off highway vehicle use. Approximately 12,000,000 animal use months (AUM amount of forage to support one livestock unit per month) are permitted for grazing livestock on public lands in the western states. Direct effects of grazing on sage-grouse populations or sagebrush landscapes are not possible to assess from current data. However, management of lands grazed by livestock has influenced sagebrush ecosystems by vegetation treatments to increase forage and reduce sagebrush and other plant species unpalatable to livestock. Fences (2 km/km2 in some regions), roads, and water developments to manage livestock movements further modify the landscape. Oil and gas development influences 8% of the sagebrush habitats with the highest intensities occurring in the eastern range of sage-grouse; 20% of the sagebrush distribution is indirectly influenced in the Great

  15. Big Data and Big Science

    OpenAIRE

    Di Meglio, Alberto

    2014-01-01

    Brief introduction to the challenges of big data in scientific research based on the work done by the HEP community at CERN and how the CERN openlab promotes collaboration among research institutes and industrial IT companies. Presented at the FutureGov 2014 conference in Singapore.

  16. A conservation paradox in the Great Basin—Altering sagebrush landscapes with fuel breaks to reduce habitat loss from wildfire

    Science.gov (United States)

    Shinneman, Douglas J.; Aldridge, Cameron L.; Coates, Peter S.; Germino, Matthew J.; Pilliod, David S.; Vaillant, Nicole M.

    2018-03-15

    to ultimately reduce a greater threat of their destruction from wildfire. However, there is relatively little published science that directly addresses the ability of fuel breaks to influence fire behavior in dryland landscapes or that addresses the potential ecological effects of the construction and maintenance of fuel breaks on sagebrush ecosystems and associated wildlife species.This report is intended to provide an initial assessment of both the potential effectiveness of fuel breaks and their ecological costs and benefits. To provide this assessment, we examined prior studies on fuel breaks and other scientific evidence to address three crucial questions: (1) How effective are fuel breaks in reducing or slowing the spread of wildfire in arid and semi-arid shrubland ecosystems? (2) How do fuel breaks affect sagebrush plant communities? (3) What are the effects of fuel breaks on the greater sage-grouse, other sagebrush obligates, and sagebrush-associated wildlife species? We also provide an overview of recent federal policies and management directives aimed at protecting remaining sagebrush and greater sage-grouse habitat; describe the fuel conditions, fire behavior, and fire trends in the Great Basin; and suggest how scientific inquiry and management actions can improve our understanding of fuel breaks and their effects in sagebrush landscapes.

  17. Are Big Food's corporate social responsibility strategies valuable to communities? A qualitative study with parents and children.

    Science.gov (United States)

    Richards, Zoe; Phillipson, Lyn

    2017-12-01

    Recent studies have identified parents and children as two target groups whom Big Food hopes to positively influence through its corporate social responsibility (CSR) strategies. The current preliminary study aimed to gain an in-depth understanding of parents and children's awareness and interpretation of Big Food's CSR strategies to understand how CSR shapes their beliefs about companies. Community-based qualitative semi-structured interviews. New South Wales, Australia. Parents (n 15) and children aged 8-12 years (n 15). Parents and children showed unprompted recognition of CSR activities when shown McDonald's and Coca-Cola brand logos, indicating a strong level of association between the brands and activities that target the settings of children. When discussing CSR strategies some parents and most children saw value in the activities, viewing them as acts of merit or worth. For some parents and children, the companies' CSR activities were seen as a reflection of the company's moral attributes, which resonated with their own values of charity and health. For others, CSR strategies were in conflict with companies' core business. Finally, some also viewed the activities as harmful, representing a deceit of the public and a smokescreen for the companies' ultimately unethical behaviour. A large proportion of participants valued the CSR activities, signalling that denormalising CSR to sever the strong ties between the community and Big Food will be a difficult process for the public health community. Efforts to gain public acceptance for action on CSR may need greater levels of persuasion to gain public support of a comprehensive and restrictive approach.

  18. Big Surveys, Big Data Centres

    Science.gov (United States)

    Schade, D.

    2016-06-01

    Well-designed astronomical surveys are powerful and have consistently been keystones of scientific progress. The Byurakan Surveys using a Schmidt telescope with an objective prism produced a list of about 3000 UV-excess Markarian galaxies but these objects have stimulated an enormous amount of further study and appear in over 16,000 publications. The CFHT Legacy Surveys used a wide-field imager to cover thousands of square degrees and those surveys are mentioned in over 1100 publications since 2002. Both ground and space-based astronomy have been increasing their investments in survey work. Survey instrumentation strives toward fair samples and large sky coverage and therefore strives to produce massive datasets. Thus we are faced with the "big data" problem in astronomy. Survey datasets require specialized approaches to data management. Big data places additional challenging requirements for data management. If the term "big data" is defined as data collections that are too large to move then there are profound implications for the infrastructure that supports big data science. The current model of data centres is obsolete. In the era of big data the central problem is how to create architectures that effectively manage the relationship between data collections, networks, processing capabilities, and software, given the science requirements of the projects that need to be executed. A stand alone data silo cannot support big data science. I'll describe the current efforts of the Canadian community to deal with this situation and our successes and failures. I'll talk about how we are planning in the next decade to try to create a workable and adaptable solution to support big data science.

  19. A synopsis of short-term response to alternative restoration treatments in sagebrush-steppe: the SageSTEP project

    Science.gov (United States)

    McIver, James; Brunson, Mark; Bunting, Steve; Chambers, Jeanne; Doescher, Paul; Grace, James; Hulet, April; Johnson, Dale; Knick, Steven T.; Miller, Richard; Pellant, Mike; Pierson, Fred; Pyke, David; Rau, Benjamin; Rollins, Kim; Roundy, Bruce; Schupp, Eugene; Tausch, Robin; Williams, Jason

    2014-01-01

    The Sagebrush Steppe Treatment Evaluation Project (SageSTEP) is an integrated long-term study that evaluates ecological effects of alternative treatments designed to reduce woody fuels and to stimulate the herbaceous understory of sagebrush steppe communities of the Intermountain West. This synopsis summarizes results through 3 yr posttreatment. Woody vegetation reduction by prescribed fire, mechanical treatments, or herbicides initiated a cascade of effects, beginning with increased availability of nitrogen and soil water, followed by increased growth of herbaceous vegetation. Response of butterflies and magnitudes of runoff and erosion closely followed herbaceous vegetation recovery. Effects on shrubs, biological soil crust, tree cover, surface woody fuel loads, and sagebrush-obligate bird communities will take longer to be fully expressed. In the short term, cool wet sites were more resilient than warm dry sites, and resistance was mostly dependent on pretreatment herbaceous cover. At least 10 yr of posttreatment time will likely be necessary to determine outcomes for most sites. Mechanical treatments did not serve as surrogates for prescribed fire in how each influenced the fuel bed, the soil, erosion, and sage-obligate bird communities. Woody vegetation reduction by any means resulted in increased availability of soil water, higher herbaceous cover, and greater butterfly numbers. We identified several trade-offs (desirable outcomes for some variables, undesirable for others), involving most components of the study system. Trade-offs are inevitable when managing complex natural systems, and they underline the importance of asking questions about the whole system when developing management objectives. Substantial spatial and temporal heterogeneity in sagebrush steppe ecosystems emphasizes the point that there will rarely be a “recipe” for choosing management actions on any specific area. Use of a consistent evaluation process linked to monitoring may be the

  20. 76 FR 62087 - Draft Conservation Plan and Draft Environmental Assessment; Dunes Sagebrush Lizard, Texas

    Science.gov (United States)

    2011-10-06

    ...] Draft Conservation Plan and Draft Environmental Assessment; Dunes Sagebrush Lizard, Texas AGENCY: Fish... draft Texas Conservation Plan for the Dunes Sagebrush Lizard (TCP). The draft TCP will function as a... the Applicant for the dunes sagebrush lizard (Sceloporus arenicolus) throughout its range in Texas...

  1. 76 FR 19304 - Endangered and Threatened Wildlife and Plants; Endangered Status for Dunes Sagebrush Lizard

    Science.gov (United States)

    2011-04-07

    ... for Dunes Sagebrush Lizard AGENCY: Fish and Wildlife Service, Interior. ACTION: Proposed rule... list the dunes sagebrush lizard (Sceloporus arenicolus) under the Endangered Species Act of 1973, as... dunes sagebrush lizard (Sceloporus arenicolus) that was published in the Federal Register on December 14...

  2. The community-driven BiG CZ software system for integration and analysis of bio- and geoscience data in the critical zone

    Science.gov (United States)

    Aufdenkampe, A. K.; Mayorga, E.; Horsburgh, J. S.; Lehnert, K. A.; Zaslavsky, I.; Valentine, D. W., Jr.; Richard, S. M.; Cheetham, R.; Meyer, F.; Henry, C.; Berg-Cross, G.; Packman, A. I.; Aronson, E. L.

    2014-12-01

    Here we present the prototypes of a new scientific software system designed around the new Observations Data Model version 2.0 (ODM2, https://github.com/UCHIC/ODM2) to substantially enhance integration of biological and Geological (BiG) data for Critical Zone (CZ) science. The CZ science community takes as its charge the effort to integrate theory, models and data from the multitude of disciplines collectively studying processes on the Earth's surface. The central scientific challenge of the CZ science community is to develop a "grand unifying theory" of the critical zone through a theory-model-data fusion approach, for which the key missing need is a cyberinfrastructure for seamless 4D visual exploration of the integrated knowledge (data, model outputs and interpolations) from all the bio and geoscience disciplines relevant to critical zone structure and function, similar to today's ability to easily explore historical satellite imagery and photographs of the earth's surface using Google Earth. This project takes the first "BiG" steps toward answering that need. The overall goal of this project is to co-develop with the CZ science and broader community, including natural resource managers and stakeholders, a web-based integration and visualization environment for joint analysis of cross-scale bio and geoscience processes in the critical zone (BiG CZ), spanning experimental and observational designs. We will: (1) Engage the CZ and broader community to co-develop and deploy the BiG CZ software stack; (2) Develop the BiG CZ Portal web application for intuitive, high-performance map-based discovery, visualization, access and publication of data by scientists, resource managers, educators and the general public; (3) Develop the BiG CZ Toolbox to enable cyber-savvy CZ scientists to access BiG CZ Application Programming Interfaces (APIs); and (4) Develop the BiG CZ Central software stack to bridge data systems developed for multiple critical zone domains into a single

  3. A Proposed Collaboration Against Big Tobacco: Common Ground Between the Vaping and Public Health Community in the United States.

    Science.gov (United States)

    Wagener, Theodore L; Meier, Ellen; Tackett, Alayna P; Matheny, James D; Pechacek, Terry F

    2016-05-01

    An unfortunate conflict is underway between the public health community and the vaping community over e-cigarettes' harmfulness or lack thereof. This conflict is made worse by an information vacuum that is being filled by vocal members on both sides of the debate; a perceived lack of credibility of public health officials by those in the vaping community; the tobacco industry's recent involvement in e-cigarettes; and the constant evolution of different styles and types of e-cigarettes. This conflict is avoidable; common ground exists. If both groups rally around what is in their own and the public's best interest-the end of combustible tobacco--all will benefit significantly. If not, the result may be missed opportunities, misguided alliances, and--ultimately-poorer public health. This study brings light to the contentious debate between the vaping and public health communities. It addresses how both sides are responsible for bringing misleading information to the public and vocal leaders on both sides are unknowingly intensifying and polarizing the debate-likely at the expense of public health. It also describes how this conflict is avoidable, and provides a starting point for potential positions of common ground against Big Tobacco. © The Author 2015. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  4. Ecosystem functional response across precipitation extremes in a sagebrush steppe.

    Science.gov (United States)

    Tredennick, Andrew T; Kleinhesselink, Andrew R; Taylor, J Bret; Adler, Peter B

    2018-01-01

    Precipitation is predicted to become more variable in the western United States, meaning years of above and below average precipitation will become more common. Periods of extreme precipitation are major drivers of interannual variability in ecosystem functioning in water limited communities, but how ecosystems respond to these extremes over the long-term may shift with precipitation means and variances. Long-term changes in ecosystem functional response could reflect compensatory changes in species composition or species reaching physiological thresholds at extreme precipitation levels. We conducted a five year precipitation manipulation experiment in a sagebrush steppe ecosystem in Idaho, United States. We used drought and irrigation treatments (approximately 50% decrease/increase) to investigate whether ecosystem functional response remains consistent under sustained high or low precipitation. We recorded data on aboveground net primary productivity (ANPP), species abundance, and soil moisture. We fit a generalized linear mixed effects model to determine if the relationship between ANPP and soil moisture differed among treatments. We used nonmetric multidimensional scaling to quantify community composition over the five years. Ecosystem functional response, defined as the relationship between soil moisture and ANPP, was similar among irrigation and control treatments, but the drought treatment had a greater slope than the control treatment. However, all estimates for the effect of soil moisture on ANPP overlapped zero, indicating the relationship is weak and uncertain regardless of treatment. There was also large spatial variation in ANPP within-years, which contributes to the uncertainty of the soil moisture effect. Plant community composition was remarkably stable over the course of the experiment and did not differ among treatments. Despite some evidence that ecosystem functional response became more sensitive under sustained drought conditions, the response

  5. Biological zonation of the last unbound big river in the West Carpathians: reference scheme based on caddisfly communities

    Directory of Open Access Journals (Sweden)

    Čiliak M.

    2014-01-01

    Full Text Available A thorough understanding of biotic communities distribution in predisturbance state is essential for predictions of their future changes related to human activities. In this regard, pre-damming data on spatial distribution of benthic communities are highly valuable. Caddisflies were sampled at 14 sites of the Hron River and analysed in order to establish longitudinal zonation of the river and to determine environmental factors affecting assemblages’ distribution in the longitudinal profile. A total of 2600 individuals of caddisflies belonging to 40 taxa of 12 families were recorded. Diversity of caddisflies was found to be higher in the upper (rhithral part of the river. Major change, with shift to much more uniform caddisfly assemblages, occurred in the middle part of the river. Four zones (subzones were distinguished using caddisfly communities: epirhithral, metarhithral, hyporhithral and epipotamal. Canonical correspondence analysis demonstrated the determining influence of altitude and conductivity on the caddisflies. Pre-damming zonation patterns presented here could serve as basic information for management of the Hron River as well as a reference scheme for other, previously dammed big rivers in the West Carpathian region.

  6. Making big communities small: using network science to understand the ecological and behavioral requirements for community social capital.

    Science.gov (United States)

    Neal, Zachary

    2015-06-01

    The concept of social capital is becoming increasingly common in community psychology and elsewhere. However, the multiple conceptual and operational definitions of social capital challenge its utility as a theoretical tool. The goals of this paper are to clarify two forms of social capital (bridging and bonding), explicitly link them to the structural characteristics of small world networks, and explore the behavioral and ecological prerequisites of its formation. First, I use the tools of network science and specifically the concept of small-world networks to clarify what patterns of social relationships are likely to facilitate social capital formation. Second, I use an agent-based model to explore how different ecological characteristics (diversity and segregation) and behavioral tendencies (homophily and proximity) impact communities' potential for developing social capital. The results suggest diverse communities have the greatest potential to develop community social capital, and that segregation moderates the effects that the behavioral tendencies of homophily and proximity have on community social capital. The discussion highlights how these findings provide community-based researchers with both a deeper understanding of the contextual constraints with which they must contend, and a useful tool for targeting their efforts in communities with the greatest need or greatest potential.

  7. Little behaviors with big impacts: Exploring the sense of community surrounding socially conscious consumption

    Science.gov (United States)

    Devincenzo, Marie E. Hafey

    The thesis is a study of socially conscious consumption practices and the meanings those behaviors have for consumers who participate in them. Psychological sense of community was used as the theoretical grounding for the study because it provided a way to examine socially conscious behaviors not solely as the behaviors of individuals but as behaviors within a social context with social meaning. Data were collected in two phases. First, a written, projective instrument compared cultural perceptions of various types of socially conscious consumption practices. Then, in-depth interviews were conducted to collect consumption narratives from participants and nonparticipants in a wind energy program called Blue Sky. The interviews were analyzed using a hermeneutical approach. The findings identified a new type of consumption community not recognized in prior literature: the principle based consumption community.

  8. Local Community Advocacy for the Thirty Meter Telescope on the Big Island of Hawai’i

    Science.gov (United States)

    Currie, Thayne; Ha, Richard; Imai-Hong, Amber; Silva, Jasmin; Stark, Chris; Naea Stevens, Dashiel

    2018-01-01

    The Thirty Meter Telescope project is a next-generation ground-based optical/infrared telescope planned for construction on Mauna Kea. It is also a prominent social issue in Hawai’i, touching upon a wide range of island-specific issues, including economic/educational opportunities and justice, Hawaii’s long and proud history of astronomy/navigation, the cultural significance of Mauna Kea to some Hawaiians, and Hawaiian sovereignty. In this talk, we describe local community outreach carried out by Hawai’i island resident members of our group, Yes2TMT, and also by the pro-TMT Hawaiian group P.U.E.O based in Hilo. We have cultivated a substantial social media community and persistent on-the-ground advocacy that addresses the many misconceptions about TMT while providing an outlet for concerns from our neighbors. Since early 2016 and thanks to the efforts of many on Hawai’i, support for TMT has increased, especially from the Hawaiian community: the project is now favored by at least 70% of Hawaii’s residents. Our goal is to help bring TMT to Hawai’i under conditions deemed acceptable by the vast majority of the local community.

  9. Rolling Deck to Repository (R2R): Big Data and Standard Services for the Fleet Community

    Science.gov (United States)

    Arko, R. A.; Carbotte, S. M.; Chandler, C. L.; Smith, S. R.; Stocks, K. I.

    2014-12-01

    The Rolling Deck to Repository (R2R; http://rvdata.us/) program curates underway environmental sensor data from the U.S. academic oceanographic research fleet, ensuring data sets are routinely and consistently documented, preserved in long-term archives, and disseminated to the science community. Currently 25 in-service vessels contribute 7 terabytes of data to R2R each year, acquired from a full suite of geophysical, oceanographic, meteorological, and navigational sensors on over 400 cruises worldwide. To accommodate this large volume and variety of data, R2R has developed highly efficient stewardship procedures. These include scripted "break out" of cruise data packages from each vessel based on standard filename and directory patterns; automated harvest of cruise metadata from the UNOLS Office via Web Services and from OpenXML-based forms submitted by vessel operators; scripted quality assessment routines that calculate statistical summaries and standard ratings for selected data types; adoption of community-standard controlled vocabularies for vessel codes, instrument types, etc, provided by the NERC Vocabulary Server, in lieu of maintaining custom local term lists; and a standard package structure based on the IETF BagIt format for delivering data to long-term archives. Documentation and standard post-field products, including quality-controlled shiptrack navigation data for every cruise, are published in multiple services and formats to satisfy a diverse range of clients. These include Catalog Service for Web (CSW), GeoRSS, and OAI-PMH discovery services via a GeoNetwork portal; OGC Web Map and Feature Services for GIS clients; a citable Digital Object Identifier (DOI) for each dataset; ISO 19115-2 standard geospatial metadata records suitable for submission to long-term archives as well as the POGO global catalog; and Linked Open Data resources with a SPARQL query endpoint for Semantic Web clients. R2R participates in initiatives such as the Ocean Data

  10. Big universe, big data

    DEFF Research Database (Denmark)

    Kremer, Jan; Stensbo-Smidt, Kristoffer; Gieseke, Fabian Cristian

    2017-01-01

    , modern astronomy requires big data know-how, in particular it demands highly efficient machine learning and image analysis algorithms. But scalability is not the only challenge: Astronomy applications touch several current machine learning research questions, such as learning from biased data and dealing......, and highlight some recent methodological advancements in machine learning and image analysis triggered by astronomical applications....

  11. Big city consultants shut down our pool : a shocking community pool gets checked for stray voltage

    Energy Technology Data Exchange (ETDEWEB)

    Lynch, P. [Power Line Systems Engineering Inc., Markham, ON (Canada)

    2009-12-15

    This article discussed an investigation conducted at a community pool where swimmers complained of receiving electrical shocks both in the pool and on the pool's deck area. Electrical measurements taken at the pool revealed current flows from the pool water to various points around the deck area. Measured current flow in the pool area was 30 amps even when the main pool service breaker was opened to shut off power to the entire facility. Thirty amps of primary neutral current was then measured on the primary side aerial neutral in front of the pool. A 10 amp primary feeder from the pool joined up with the complex's primary neutral wire to increase the neutral current to 40 amps. The combined 40 amps current then returned to the secondary side of a nearby utility transformer substation. The study showed that the underground wet low-resistance grounded surface area of the pool was attracting the 30 amps of utility current from the surrounding ground area. The local utility disconnected the primary and secondary neutral interconnection at the pool's main 600-volt step-down transformer. The pool deck was removed in order to install additional copper bonding grounds. In order to avert serious injuries, many experts propose that all electric utilities should be required by law to reconfigure their power systems to prevent primary power neutral currents from entering private buildings. 1 tab., 2 figs.

  12. Carbon dioxide effluxes and their environmental controls in sagebrush steppe ecosystems along an elevation gradient in the Reynolds Creek Critical Zone Observatory

    Science.gov (United States)

    Lohse, K. A.; Fellows, A.; Flerchinger, G. N.; Seyfried, M. S.

    2017-12-01

    The spatial and temporal variation of carbon dioxide effluxes and their environmental controls are poorly constrained in cold shrub steppe ecosystems. The objectives of this study were to 1) analyze environmental parameters in determining soil CO2 efflux, 2) assess the level of agreement between manual chambers and force diffusion (FD) soil CO2 efflux chambers, when both measurements are extrapolated across the growing season, and lastly to compare respiration fluxes to modeled ecosystem respiration fluxes. We installed FD chambers at four sites co-located with eddy covariance (EC) towers and soil moisture and temperature sensors along an elevation gradient in the Reynolds Creek Critical Zone Observatory in SW Idaho. FD chamber fluxes were collected continuously at 15-minute intervals. We sampled soil CO2 efflux with manual chambers at plant and interplant spaces in five plots at each site biweekly to monthly during the growing season. The sites included a Wyoming big sagebrush site, a low sagebrush site, a post-fire mountain big sagebrush site, and a mountain big sagebrush site located at elevations of 1425, 1680, 1808 and 2111 m. Climate variation followed the montane elevation gradient; mean annual precipitation (MAP) at the sites is 290, 337, 425, and 795 mm, respectively, and mean annual temperature is 8.9, 8.4, 6.1, 5.4°C. Automated force diffusion chambers detected large differences in carbon dioxide pulse dynamics along the elevation gradient. Growing season carbon dioxide fluxes were 3 times higher at the 425 mm MAP site compared than the lowest elevation sites at 290 and 337 MAP sites and >1.5 higher than the 795 mm MAP site over the same period. Manual fluxes showed similar seasonal patterns as FD chamber fluxes but often higher and greater spatial variability in fluxes than FD chamber fluxes. Plant and interplant flux differences were surprisingly similar, especially at higher elevations. Soil respiration ranged from 0.2-0.48 of ecosystem respiration

  13. Big data, big responsibilities

    Directory of Open Access Journals (Sweden)

    Primavera De Filippi

    2014-01-01

    Full Text Available Big data refers to the collection and aggregation of large quantities of data produced by and about people, things or the interactions between them. With the advent of cloud computing, specialised data centres with powerful computational hardware and software resources can be used for processing and analysing a humongous amount of aggregated data coming from a variety of different sources. The analysis of such data is all the more valuable to the extent that it allows for specific patterns to be found and new correlations to be made between different datasets, so as to eventually deduce or infer new information, as well as to potentially predict behaviours or assess the likelihood for a certain event to occur. This article will focus specifically on the legal and moral obligations of online operators collecting and processing large amounts of data, to investigate the potential implications of big data analysis on the privacy of individual users and on society as a whole.

  14. Restoration handbook for sagebrush steppe ecosystems with emphasis on greater sage-grouse habitat - Part 1

    Science.gov (United States)

    David A. Pyke; Jeanne C. Chambers; Mike Pellant; Steven T. Knick; Richard F. Miller; Jeffrey L. Beck; Paul S. Doescher; Eugene W. Schupp; Bruce A. Roundy; Mark Brunson; James D. McIver

    2015-01-01

    Sagebrush steppe ecosystems in the United States currently occur on only about one-half of their historical land area because of changes in land use, urban growth, and degradation of land, including invasions of non-native plants. The existence of many animal species depends on the existence of sagebrush steppe habitat. The greater sage-grouse (Centrocercus...

  15. Greater sage-grouse as an umbrella species for sagebrush-associated vertebrates.

    Science.gov (United States)

    Mary M. Rowland; Michael J. Wisdom; Lowell Suring; Cara W. Meinke

    2006-01-01

    Widespread degradation of the sagebrush ecosystem in the western United States, including the invasion of cheatgrass, has prompted resource managers to consider a variety of approaches to restore and conserve habitats for sagebrush-associated species. One such approach involves the use of greater sage-grouse, a species of prominent conservation interest, as an umbrella...

  16. Big science

    CERN Multimedia

    Nadis, S

    2003-01-01

    " "Big science" is moving into astronomy, bringing large experimental teams, multi-year research projects, and big budgets. If this is the wave of the future, why are some astronomers bucking the trend?" (2 pages).

  17. Effects of land cover and regional climate variations on long-term spatiotemporal changes in sagebrush ecosystems

    Science.gov (United States)

    Xian, George Z.; Homer, Collin G.; Aldridge, Cameron L.

    2012-01-01

    This research investigated the effects of climate and land cover change on variation in sagebrush ecosystems. We combined information of multi-year sagebrush distribution derived from multitemporal remote sensing imagery and climate data to study the variation patterns of sagebrush ecosystems under different potential disturbances. We found that less than 40% of sagebrush ecosystem changes involved abrupt changes directly caused by landscape transformations and over 60% of the variations involved gradual changes directly related to climatic perturbations. The primary increases in bare ground and declines in sagebrush vegetation abundance were significantly correlated with the 1996-2006 decreasing trend in annual precipitation.

  18. Sagebrush-associated species of conservation concern

    Science.gov (United States)

    Mary M. Rowland; Lowell H. Suring; Matthias Leu; Steven T. Knick; Michael J. Wisdom

    2011-01-01

    Selection of species of concern is a critical early step in conducting broad-scale ecological assessments for conservation planning and management. Many criteria can be used to guide this selection, such as conservation status, existing knowledge base, and association with plant communities of interest. In conducting the Wyoming Basins Ecoregional Assessment (WBEA), we...

  19. U.S. Geological Survey sage-grouse and sagebrush ecosystem research annual report for 2017

    Science.gov (United States)

    Hanser, Steven E.

    2017-09-08

    The sagebrush (Artemisia spp.) ecosystem extends across a large portion of the Western United States, and the greater sage-grouse (Centrocercus urophasianus) is one of the iconic species of this ecosystem. Greater sage-grouse populations occur in 11 States and are dependent on relatively large expanses of sagebrush-dominated habitat. Sage-grouse populations have been experiencing long-term declines owing to multiple stressors, including interactions among fire, exotic plant invasions, and human land uses, which have resulted in significant loss, fragmentation, and degradation of landscapes once dominated by sagebrush. In addition to the sage-grouse, over 350 species of plants and animals are dependent on the sagebrush ecosystem.Increasing knowledge about how these species and the sagebrush ecosystem respond to these stressors and to management actions can inform and improve strategies to maintain existing areas of intact sagebrush and restore degraded landscapes. The U.S. Geological Survey (USGS) has a broad research program focused on providing the science needed to inform these strate-gies and to help land and resource managers at the Federal, State, Tribal, and local levels as they work towards sustainable sage-grouse populations and restored landscapes for the broad range of uses critical to stakeholders in the Western United States.USGS science has provided a foundation for major land and resource management decisions including those that precluded the need to list the greater sage-grouse under the Endangered Species Act. The USGS is continuing to build on that foundation to inform science-based decisions to help support local economies and the continued conservation, management, and restoration of the sagebrush ecosystem.This report contains descriptions of USGS sage-grouse and sagebrush ecosystem research projects that are ongoing or were active during 2017 and is organized into five thematic areas: Fire, Invasive Species, Restoration, Sagebrush and Sage

  20. 2004 annual progress report: Stratton Sagebrush Hydrology Study Area: Establishment of a long-term research site in a high-elevation sagebrush steppe

    Science.gov (United States)

    Schoenecker, Kate; Lange, Bob; Calton, Mike

    2005-01-01

    In 2004 the U.S. Geological Survey, Fort Collins Science Center (FORT) and the Bureau of Land Management (BLM), Rawlins Field Office (RFO), began a cooperative effort to reestablish the Stratton Sagebrush Hydrology Study Area (Stratton) as a research location, with the goal of making it a site for long-term research on sagebrush (Artemisia spp.) ecology. No other long-term research sites in high-elevation sagebrush habitat currently exist, and the Stratton area, with its 30+ year history of research and baseline data, was a logical location to restart investigations aimed at answering pertinent and timely questions about sagebrush ecology and sagebrush-obligate species. During the first year of the study, USGS scientists conducted an in-depth literature search to locate publications from research conducted at Stratton. We contacted previous researchers to acquire literature and unpublished reports of work conducted at Stratton. Collated papers and published manuscripts were presented in an annotated bibliography (Burgess and Schoenecker, 2004).

  1. Urbanising Big

    DEFF Research Database (Denmark)

    Ljungwall, Christer

    2013-01-01

    Development in China raises the question of how big a city can become, and at the same time be sustainable, writes Christer Ljungwall of the Swedish Agency for Growth Policy Analysis.......Development in China raises the question of how big a city can become, and at the same time be sustainable, writes Christer Ljungwall of the Swedish Agency for Growth Policy Analysis....

  2. The Big Sky inside

    Science.gov (United States)

    Adams, Earle; Ward, Tony J.; Vanek, Diana; Marra, Nancy; Hester, Carolyn; Knuth, Randy; Spangler, Todd; Jones, David; Henthorn, Melissa; Hammill, Brock; Smith, Paul; Salisbury, Rob; Reckin, Gene; Boulafentis, Johna

    2009-01-01

    The University of Montana (UM)-Missoula has implemented a problem-based program in which students perform scientific research focused on indoor air pollution. The Air Toxics Under the Big Sky program (Jones et al. 2007; Adams et al. 2008; Ward et al. 2008) provides a community-based framework for understanding the complex relationship between poor…

  3. Mechanical mastication of Utah juniper encroaching sagebrush steppe increases inorganic soil N

    Science.gov (United States)

    Juniper (Juniperus spp.) has encroached millions of hectares of sagebrush (Artemisia spp.) steppe. Juniper mechanical mastication increases cover of understory species, but could increase resource availability and subsequently invasive plant species. We quantified the effects of juniper mastication ...

  4. Big Argumentation?

    Directory of Open Access Journals (Sweden)

    Daniel Faltesek

    2013-08-01

    Full Text Available Big Data is nothing new. Public concern regarding the mass diffusion of data has appeared repeatedly with computing innovations, in the formation before Big Data it was most recently referred to as the information explosion. In this essay, I argue that the appeal of Big Data is not a function of computational power, but of a synergistic relationship between aesthetic order and a politics evacuated of a meaningful public deliberation. Understanding, and challenging, Big Data requires an attention to the aesthetics of data visualization and the ways in which those aesthetics would seem to depoliticize information. The conclusion proposes an alternative argumentative aesthetic as the appropriate response to the depoliticization posed by the popular imaginary of Big Data.

  5. Big data

    DEFF Research Database (Denmark)

    Madsen, Anders Koed; Flyverbom, Mikkel; Hilbert, Martin

    2016-01-01

    is to outline a research agenda that can be used to raise a broader set of sociological and practice-oriented questions about the increasing datafication of international relations and politics. First, it proposes a way of conceptualizing big data that is broad enough to open fruitful investigations......The claim that big data can revolutionize strategy and governance in the context of international relations is increasingly hard to ignore. Scholars of international political sociology have mainly discussed this development through the themes of security and surveillance. The aim of this paper...... into the emerging use of big data in these contexts. This conceptualization includes the identification of three moments contained in any big data practice. Second, it suggests a research agenda built around a set of subthemes that each deserve dedicated scrutiny when studying the interplay between big data...

  6. How Big Is Too Big?

    Science.gov (United States)

    Cibes, Margaret; Greenwood, James

    2016-01-01

    Media Clips appears in every issue of Mathematics Teacher, offering readers contemporary, authentic applications of quantitative reasoning based on print or electronic media. This issue features "How Big is Too Big?" (Margaret Cibes and James Greenwood) in which students are asked to analyze the data and tables provided and answer a…

  7. Restoration handbook for sagebrush steppe ecosystems with emphasis on greater sage-grouse habitat - Part 3: Site level restoration decisions

    Science.gov (United States)

    David A. Pyke; Jeanne C. Chambers; Mike Pellant; Richard F. Miller; Jeffrey L. Beck; Paul S. Doescher; Bruce A. Roundy; Eugene W. Schupp; Steven T. Knick; Mark Brunson; James D. McIver

    2017-01-01

    Sagebrush steppe ecosystems in the United States currently (2016) occur on only about one-half of their historical land area because of changes in land use, urban growth, and degradation of land, including invasions of non-native plants. The existence of many animal species depends on the existence of sagebrush steppe habitat. The greater sage-grouse (Centrocercus...

  8. The role of symbiotic nitrogen fixation in nitrogen availability, competition and plant invasion into the sagebrush steppe

    Science.gov (United States)

    Erin M. Goergen

    2009-01-01

    In the semi-arid sagebrush steppe of the Northeastern Sierra Nevada, resources are both spatially and temporally variable, arguably making resource availability a primary factor determining invasion success. N fixing plant species, primarily native legumes, are often relatively abundant in sagebrush steppe and can contribute to ecosystem nitrogen budgets. ...

  9. Ecohydrology of adjacent sagebrush and lodgepole pine ecosystems: the consequences of climate change and disturbance

    Science.gov (United States)

    Bradford, John B.; Schlaepfer, Daniel R.; Lauenroth, William K.

    2014-01-01

    Sagebrush steppe and lodgepole pine forests are two of the most widespread vegetation types in the western United States and they play crucial roles in the hydrologic cycle of these water-limited regions. We used a process-based ecosystem water model to characterize the potential impact of climate change and disturbance (wildfire and beetle mortality) on water cycling in adjacent sagebrush and lodgepole pine ecosystems. Despite similar climatic and topographic conditions between these ecosystems at the sites examined, lodgepole pine, and sagebrush exhibited consistent differences in water balance, notably more evaporation and drier summer soils in the sagebrush and greater transpiration and less water yield in lodgepole pine. Canopy disturbances (either fire or beetle) have dramatic impacts on water balance and availability: reducing transpiration while increasing evaporation and water yield. Results suggest that climate change may reduce snowpack, increase evaporation and transpiration, and lengthen the duration of dry soil conditions in the summer, but may have uncertain effects on drainage. Changes in the distribution of sagebrush and lodgepole pine ecosystems as a consequence of climate change and/or altered disturbance regimes will likely alter ecosystem water balance.

  10. BigDataBench: a Big Data Benchmark Suite from Internet Services

    OpenAIRE

    Wang, Lei; Zhan, Jianfeng; Luo, Chunjie; Zhu, Yuqing; Yang, Qiang; He, Yongqiang; Gao, Wanling; Jia, Zhen; Shi, Yingjie; Zhang, Shujie; Zheng, Chen; Lu, Gang; Zhan, Kent; Li, Xiaona; Qiu, Bizhu

    2014-01-01

    As architecture, systems, and data management communities pay greater attention to innovative big data systems and architectures, the pressure of benchmarking and evaluating these systems rises. Considering the broad use of big data systems, big data benchmarks must include diversity of data and workloads. Most of the state-of-the-art big data benchmarking efforts target evaluating specific types of applications or system software stacks, and hence they are not qualified for serving the purpo...

  11. Land use and habitat conditions across the southwestern Wyoming sagebrush steppe: development impacts, management effectiveness and the distribution of invasive plants

    Science.gov (United States)

    Manier, Daniel J.; Aldridge, Cameron L.; Anderson, Patrick; Chong, Geneva; Homer, Collin G.; O'Donnell, Michael S.; Schell, Spencer

    2011-01-01

    For the past several years, USGS has taken a multi-faceted approach to investigating the condition and trends in sagebrush steppe ecosystems. This recent effort builds upon decades of work in semi-arid ecosystems providing a specific, applied focus on the cumulative impacts of expanding human activities across these landscapes. Here, we discuss several on-going projects contributing to these efforts: (1) mapping and monitoring the distribution and condition of shrub steppe communities with local detail at a regional scale, (2) assessing the relationships between specific, land-use features (for example, roads, transmission lines, industrial pads) and invasive plants, including their potential (environmentally defined) distribution across the region, and (3) monitoring the effects of habitat treatments on the ecosystem, including wildlife use and invasive plant abundance. This research is focused on the northern sagebrush steppe, primarily in Wyoming, but also extending into Montana, Colorado, Utah and Idaho. The study area includes a range of sagebrush types (including, Artemisia tridentata ssp. tridentata, Artemisia tridentata ssp. wyomingensis, Artemisia tridentata ssp. vaseyana, Artemisia nova) and other semi-arid shrubland types (for example, Sarcobatus vermiculatus, Atriplex confertifolia, Atriplex gardneri), impacted by extensive interface between steppe ecosystems and industrial energy activities resulting in a revealing multiple-variable analysis. We use a combination of remote sensing (AWiFS (1 Any reference to platforms, data sources, equipment, software, patented or trade-marked methods is for information purposes only. It does not represent endorsement of the U.S.D.I., U.S.G.S. or the authors), Landsat and Quickbird platforms), Geographic Information System (GIS) design and data management, and field-based, replicated sampling to generate multiple scales of data representing the distribution of shrub communities for the habitat inventory. Invasive plant

  12. Big Opportunities and Big Concerns of Big Data in Education

    Science.gov (United States)

    Wang, Yinying

    2016-01-01

    Against the backdrop of the ever-increasing influx of big data, this article examines the opportunities and concerns over big data in education. Specifically, this article first introduces big data, followed by delineating the potential opportunities of using big data in education in two areas: learning analytics and educational policy. Then, the…

  13. Nest mortality of sagebrush songbirds due to a severe hailstorm

    Science.gov (United States)

    Hightower, Jessica N.; Carlisle, Jason D.; Chalfoun, Anna D.

    2018-01-01

    Demographic assessments of nesting birds typically focus on failures due to nest predation or brood parasitism. Extreme weather events such as hailstorms, however, can also destroy eggs and injure or kill juvenile and adult birds at the nest. We documented the effects of a severe hailstorm on 3 species of sagebrush-associated songbirds: Sage Thrasher (Oreoscoptes montanus), Brewer's Sparrow (Spizella breweri), and Vesper Sparrow (Pooecetes gramineus), nesting at eight 24 ha study plots in central Wyoming, USA. Across all plots, 17% of 128 nests failed due to the hailstorm; however, all failed nests were located at a subset of study plots (n = 3) where the hailstorm was most intense, and 45% of all nests failures on those plots were due to hail. Mortality rates varied by species, nest architecture, and nest placement. Nests with more robust architecture and those sited more deeply under the shrub canopy were more likely to survive the hailstorm, suggesting that natural history traits may modulate mortality risk due to hailstorms. While sporadic in nature, hailstorms may represent a significant source of nest failure to songbirds in certain locations, especially with increasing storm frequency and severity forecasted in some regions with ongoing climate change.

  14. Big Dreams

    Science.gov (United States)

    Benson, Michael T.

    2015-01-01

    The Keen Johnson Building is symbolic of Eastern Kentucky University's historic role as a School of Opportunity. It is a place that has inspired generations of students, many from disadvantaged backgrounds, to dream big dreams. The construction of the Keen Johnson Building was inspired by a desire to create a student union facility that would not…

  15. Big Science

    Energy Technology Data Exchange (ETDEWEB)

    Anon.

    1986-05-15

    Astronomy, like particle physics, has become Big Science where the demands of front line research can outstrip the science budgets of whole nations. Thus came into being the European Southern Observatory (ESO), founded in 1962 to provide European scientists with a major modern observatory to study the southern sky under optimal conditions.

  16. Big Egos in Big Science

    DEFF Research Database (Denmark)

    Andersen, Kristina Vaarst; Jeppesen, Jacob

    In this paper we investigate the micro-mechanisms governing structural evolution and performance of scientific collaboration. Scientific discovery tends not to be lead by so called lone ?stars?, or big egos, but instead by collaboration among groups of researchers, from a multitude of institutions...

  17. Big inquiry

    Energy Technology Data Exchange (ETDEWEB)

    Wynne, B [Lancaster Univ. (UK)

    1979-06-28

    The recently published report entitled 'The Big Public Inquiry' from the Council for Science and Society and the Outer Circle Policy Unit is considered, with especial reference to any future enquiry which may take place into the first commercial fast breeder reactor. Proposals embodied in the report include stronger rights for objectors and an attempt is made to tackle the problem that participation in a public inquiry is far too late to be objective. It is felt by the author that the CSS/OCPU report is a constructive contribution to the debate about big technology inquiries but that it fails to understand the deeper currents in the economic and political structure of technology which so influence the consequences of whatever formal procedures are evolved.

  18. Big Data

    OpenAIRE

    Bútora, Matúš

    2017-01-01

    Cieľom bakalárskej práca je popísať problematiku Big Data a agregačné operácie OLAP pre podporu rozhodovania, ktoré sú na ne aplikované pomocou technológie Apache Hadoop. Prevažná časť práce je venovaná popisu práve tejto technológie. Posledná kapitola sa zaoberá spôsobom aplikovania agregačných operácií a problematikou ich realizácie. Nasleduje celkové zhodnotenie práce a možnosti využitia výsledného systému do budúcna. The aim of the bachelor thesis is to describe the Big Data issue and ...

  19. BIG DATA

    OpenAIRE

    Abhishek Dubey

    2018-01-01

    The term 'Big Data' portrays inventive methods and advances to catch, store, disseminate, oversee and break down petabyte-or bigger estimated sets of data with high-speed & diverted structures. Enormous information can be organized, non-structured or half-organized, bringing about inadequacy of routine information administration techniques. Information is produced from different distinctive sources and can touch base in the framework at different rates. With a specific end goal to handle this...

  20. Fungal and bacterial contributions to nitrogen cycling in cheatgrass-invaded and uninvaded native sagebrush soils of the western USA

    Science.gov (United States)

    DeCrappeo, Nicole; DeLorenze, Elizabeth J.; Giguere, Andrew T; Pyke, David A.; Bottomley, Peter J.

    2017-01-01

    AimThere is interest in determining how cheatgrass (Bromus tectorum L.) modifies N cycling in sagebrush (Artemisia tridentata Nutt.) soils of the western USA.MethodsTo gain insight into the roles of fungi and bacteria in N cycling of cheatgrass-invaded and uninvaded sagebrush soils, the fungal protein synthesis inhibitor, cycloheximide (CHX), and the bacteriocidal compound, bronopol (BRO) were combined with a 15NH4+ isotope pool dilution approach.ResultsCHX reduced gross N mineralization to the same rate in both sagebrush and cheatgrass soils indicating a role for fungi in N mineralization in both soil types. In cheatgrass soils BRO completely inhibited gross N mineralization, whereas, in sagebrush soils a BRO-resistant gross N mineralization rate was detected that was slower than CHX sensitive gross N mineralization, suggesting that the microbial drivers of gross N mineralization were different in sagebrush and cheatgrass soils. Net N mineralization was stimulated to a higher rate in sagebrush than in cheatgrass soils by CHX, implying that a CHX inhibited N sink was larger in the former than the latter soils. Initial gross NH4+ consumption rates were reduced significantly by both CHX and BRO in both soil types, yet, consumption rates recovered significantly between 24 and 48 h in CHX-treated sagebrush soils. The recovery of NH4+ consumption in sagebrush soils corresponded with an increase in the rate of net nitrification.ConclusionsThese results suggest that cheatgrass invasion of sagebrush soils of the northern Great Basin reduces the capacity of the fungal N consumption sink, enhances the capacity of a CHX resistant N sink and alters the contributions of bacteria and fungi to gross N mineralization.

  1. Keynote: Big Data, Big Opportunities

    OpenAIRE

    Borgman, Christine L.

    2014-01-01

    The enthusiasm for big data is obscuring the complexity and diversity of data in scholarship and the challenges for stewardship. Inside the black box of data are a plethora of research, technology, and policy issues. Data are not shiny objects that are easily exchanged. Rather, data are representations of observations, objects, or other entities used as evidence of phenomena for the purposes of research or scholarship. Data practices are local, varying from field to field, individual to indiv...

  2. 75 FR 77801 - Endangered and Threatened Wildlife and Plants; Endangered Status for Dunes Sagebrush Lizard

    Science.gov (United States)

    2010-12-14

    ... public lands in Texas. It is evident that the dunes sagebrush lizard is still present at the park, but... expected to contribute to habitat loss, modification, or fragmentation in the future include wind and solar... and Solar Energy Development Eastern New Mexico and western Texas are highly suitable areas for wind...

  3. Tapping soil survey information for rapid assessment of sagebrush ecosystem resilience and resistance

    Science.gov (United States)

    Jeremy D. Maestas; Steven B. Campbell; Jeanne C. Chambers; Mike Pellant; Richard F. Miller

    2016-01-01

    A new ecologically-based approach to risk abatement has emerged that can aid land managers in grappling with escalating impacts of large-scale wildfire and invasive annual grasses in sagebrush ecosystems, particularly in the Great Basin. Specifically, ecosystem resilience and resistance (R&R) concepts have been more fully operationalized from regional...

  4. Birds of a Great Basin Sagebrush Habitat in East-Central Nevada

    OpenAIRE

    United States Department of Agriculture, Forest Service

    1992-01-01

    Breeding bird populations ranged from 3.35 to 3.48 individuals/ha over a 3-year study conducted from 1981 to 1983. Brewer's sparrows, sage sparrows, sage thrashers, and black-throated sparrows were numerically dominant. Horned larks and western meadowlarks were less common. Results are compared with bird populations in Great Basin sagebrush habitats elsewhere in the United States.

  5. Networking for big data

    CERN Document Server

    Yu, Shui; Misic, Jelena; Shen, Xuemin (Sherman)

    2015-01-01

    Networking for Big Data supplies an unprecedented look at cutting-edge research on the networking and communication aspects of Big Data. Starting with a comprehensive introduction to Big Data and its networking issues, it offers deep technical coverage of both theory and applications.The book is divided into four sections: introduction to Big Data, networking theory and design for Big Data, networking security for Big Data, and platforms and systems for Big Data applications. Focusing on key networking issues in Big Data, the book explains network design and implementation for Big Data. It exa

  6. Big Data

    DEFF Research Database (Denmark)

    Aaen, Jon; Nielsen, Jeppe Agger

    2016-01-01

    Big Data byder sig til som en af tidens mest hypede teknologiske innovationer, udråbt til at rumme kimen til nye, værdifulde operationelle indsigter for private virksomheder og offentlige organisationer. Mens de optimistiske udmeldinger er mange, er forskningen i Big Data i den offentlige sektor...... indtil videre begrænset. Denne artikel belyser, hvordan den offentlige sundhedssektor kan genanvende og udnytte en stadig større mængde data under hensyntagen til offentlige værdier. Artiklen bygger på et casestudie af anvendelsen af store mængder sundhedsdata i Dansk AlmenMedicinsk Database (DAMD......). Analysen viser, at (gen)brug af data i nye sammenhænge er en flerspektret afvejning mellem ikke alene økonomiske rationaler og kvalitetshensyn, men også kontrol over personfølsomme data og etiske implikationer for borgeren. I DAMD-casen benyttes data på den ene side ”i den gode sags tjeneste” til...

  7. Big data analytics turning big data into big money

    CERN Document Server

    Ohlhorst, Frank J

    2012-01-01

    Unique insights to implement big data analytics and reap big returns to your bottom line Focusing on the business and financial value of big data analytics, respected technology journalist Frank J. Ohlhorst shares his insights on the newly emerging field of big data analytics in Big Data Analytics. This breakthrough book demonstrates the importance of analytics, defines the processes, highlights the tangible and intangible values and discusses how you can turn a business liability into actionable material that can be used to redefine markets, improve profits and identify new business opportuni

  8. Indicators of ecosystem function identify alternate states in the sagebrush steppe.

    Science.gov (United States)

    Kachergis, Emily; Rocca, Monique E; Fernandez-Gimenez, Maria E

    2011-10-01

    Models of ecosystem change that incorporate nonlinear dynamics and thresholds, such as state-and-transition models (STMs), are increasingly popular tools for land management decision-making. However, few models are based on systematic collection and documentation of ecological data, and of these, most rely solely on structural indicators (species composition) to identify states and transitions. As STMs are adopted as an assessment framework throughout the United States, finding effective and efficient ways to create data-driven models that integrate ecosystem function and structure is vital. This study aims to (1) evaluate the utility of functional indicators (indicators of rangeland health, IRH) as proxies for more difficult ecosystem function measurements and (2) create a data-driven STM for the sagebrush steppe of Colorado, USA, that incorporates both ecosystem structure and function. We sampled soils, plant communities, and IRH at 41 plots with similar clayey soils but different site histories to identify potential states and infer the effects of management practices and disturbances on transitions. We found that many IRH were correlated with quantitative measures of functional indicators, suggesting that the IRH can be used to approximate ecosystem function. In addition to a reference state that functions as expected for this soil type, we identified four biotically and functionally distinct potential states, consistent with the theoretical concept of alternate states. Three potential states were related to management practices (chemical and mechanical shrub treatments and seeding history) while one was related only to ecosystem processes (erosion). IRH and potential states were also related to environmental variation (slope, soil texture), suggesting that there are environmental factors within areas with similar soils that affect ecosystem dynamics and should be noted within STMs. Our approach generated an objective, data-driven model of ecosystem dynamics

  9. Using a Novel Evolutionary Algorithm to More Effectively Apply Community-Driven EcoHealth Interventions in Big Data with Application to Chagas Disease

    Science.gov (United States)

    Rizzo, D. M.; Hanley, J.; Monroy, C.; Rodas, A.; Stevens, L.; Dorn, P.

    2016-12-01

    Chagas disease is a deadly, neglected tropical disease that is endemic to every country in Central and South America. The principal insect vector of Chagas disease in Central America is Triatoma dimidiata. EcoHealth interventions are an environmentally friendly alternative that use local materials to lower household infestation, reduce the risk of infestation, and improve the quality of life. Our collaborators from La Universidad de San Carlos de Guatemala along with Ministry of Health Officials reach out to communities with high infestation and teach the community EcoHealth interventions. The process of identifying which interventions have the potential to be most effective as well as the houses that are most at risk is both expensive and time consuming. In order to better identify the risk factors associated with household infestation of T. dimidiata, a number of studies have conducted socioeconomic and entomologic surveys that contain numerous potential risk factors consisting of both nominal and ordinal data. Univariate logistic regression is one of the more popular methods for determining which risk factors are most closely associated with infestation. However, this tool has limitations, especially with the large amount and type of "Big Data" associated with our study sites (e.g., 5 villages comprise of socioeconomic, demographic, and entomologic data). The infestation of a household with T. dimidiata is a complex problem that is most likely not univariate in nature and is likely to contain higher order epistatic relationships that cannot be discovered using univariate logistic regression. Add to this, the problems raised with using p-values in traditional statistics. Also, our T. dimidiata infestation dataset is too large to exhaustively search. Therefore, we use a novel evolutionary algorithm to efficiently search for higher order interactions in surveys associated with households infested with T. dimidiata. In this study, we use our novel evolutionary

  10. Semantic Web Technologies and Big Data Infrastructures: SPARQL Federated Querying of Heterogeneous Big Data Stores

    OpenAIRE

    Konstantopoulos, Stasinos; Charalambidis, Angelos; Mouchakis, Giannis; Troumpoukis, Antonis; Jakobitsch, Jürgen; Karkaletsis, Vangelis

    2016-01-01

    The ability to cross-link large scale data with each other and with structured Semantic Web data, and the ability to uniformly process Semantic Web and other data adds value to both the Semantic Web and to the Big Data community. This paper presents work in progress towards integrating Big Data infrastructures with Semantic Web technologies, allowing for the cross-linking and uniform retrieval of data stored in both Big Data infrastructures and Semantic Web data. The technical challenges invo...

  11. The challenges of big data.

    Science.gov (United States)

    Mardis, Elaine R

    2016-05-01

    The largely untapped potential of big data analytics is a feeding frenzy that has been fueled by the production of many next-generation-sequencing-based data sets that are seeking to answer long-held questions about the biology of human diseases. Although these approaches are likely to be a powerful means of revealing new biological insights, there are a number of substantial challenges that currently hamper efforts to harness the power of big data. This Editorial outlines several such challenges as a means of illustrating that the path to big data revelations is paved with perils that the scientific community must overcome to pursue this important quest. © 2016. Published by The Company of Biologists Ltd.

  12. Restoration handbook for sagebrush steppe ecosystems with emphasis on greater sage-grouse habitat—Part 1. Concepts for understanding and applying restoration

    Science.gov (United States)

    Pyke, David A.; Chambers, Jeanne C.; Pellant, Mike; Knick, Steven T.; Miller, Richard F.; Beck, Jeffrey L.; Doescher, Paul S.; Schupp, Eugene W.; Roundy, Bruce A.; Brunson, Mark; McIver, James D.

    2015-10-26

    Sagebrush steppe ecosystems in the United States currently occur on only about one-half of their historical land area because of changes in land use, urban growth, and degradation of land, including invasions of non-native plants. The existence of many animal species depends on the existence of sagebrush steppe habitat. The greater sage-grouse (Centrocercus urophasianus) is a landscape-dependent bird that requires intact habitat and combinations of sagebrush and perennial grasses to exist. In addition, other sagebrush-obligate animals also have similar requirements and restoration of landscapes for greater sage-grouse also will benefit these animals. Once sagebrush lands are degraded, they may require restoration actions to make those lands viable habitat for supporting sagebrushobligate animals. This restoration handbook is the first in a three-part series on restoration of sagebrush ecosystems. In Part 1, we discuss concepts surrounding landscape and restoration ecology of sagebrush ecosystems and greater sage-grouse that habitat managers and restoration practitioners need to know to make informed decisions regarding where and how to restore specific areas. We will describe the plant dynamics of sagebrush steppe ecosystems and their responses to major disturbances, fire, and defoliation. We will introduce the concepts of ecosystem resilience to disturbances and resistance to invasions of annual grasses within sagebrush steppe. An introduction to soils and ecological site information will provide insights into the specific plants that can be restored in a location. Soil temperature and moisture regimes are described as a tool for determining resilience and resistance and the potential for various restoration actions. Greater sage-grouse are considered landscape birds that require large areas of intact sagebrush steppe; therefore, we describe concepts of landscape ecology that aid our decisions regarding habitat restoration. We provide a brief overview of

  13. Thinking big

    Science.gov (United States)

    Collins, Harry

    2008-02-01

    Physicists are often quick to discount social research based on qualitative techniques such as ethnography and "deep case studies" - where a researcher draws conclusions about a community based on immersion in the field - thinking that only quantitative research backed up by statistical analysis is sound. The balance is not so clear, however.

  14. Benchmarking Big Data Systems and the BigData Top100 List.

    Science.gov (United States)

    Baru, Chaitanya; Bhandarkar, Milind; Nambiar, Raghunath; Poess, Meikel; Rabl, Tilmann

    2013-03-01

    "Big data" has become a major force of innovation across enterprises of all sizes. New platforms with increasingly more features for managing big datasets are being announced almost on a weekly basis. Yet, there is currently a lack of any means of comparability among such platforms. While the performance of traditional database systems is well understood and measured by long-established institutions such as the Transaction Processing Performance Council (TCP), there is neither a clear definition of the performance of big data systems nor a generally agreed upon metric for comparing these systems. In this article, we describe a community-based effort for defining a big data benchmark. Over the past year, a Big Data Benchmarking Community has become established in order to fill this void. The effort focuses on defining an end-to-end application-layer benchmark for measuring the performance of big data applications, with the ability to easily adapt the benchmark specification to evolving challenges in the big data space. This article describes the efforts that have been undertaken thus far toward the definition of a BigData Top100 List. While highlighting the major technical as well as organizational challenges, through this article, we also solicit community input into this process.

  15. Big Data - What is it and why it matters.

    Science.gov (United States)

    Tattersall, Andy; Grant, Maria J

    2016-06-01

    Big data, like MOOCs, altmetrics and open access, is a term that has been commonplace in the library community for some time yet, despite its prevalence, many in the library and information sector remain unsure of the relationship between big data and their roles. This editorial explores what big data could mean for the day-to-day practice of health library and information workers, presenting examples of big data in action, considering the ethics of accessing big data sets and the potential for new roles for library and information workers. © 2016 Health Libraries Group.

  16. Big Data, Big Problems: A Healthcare Perspective.

    Science.gov (United States)

    Househ, Mowafa S; Aldosari, Bakheet; Alanazi, Abdullah; Kushniruk, Andre W; Borycki, Elizabeth M

    2017-01-01

    Much has been written on the benefits of big data for healthcare such as improving patient outcomes, public health surveillance, and healthcare policy decisions. Over the past five years, Big Data, and the data sciences field in general, has been hyped as the "Holy Grail" for the healthcare industry promising a more efficient healthcare system with the promise of improved healthcare outcomes. However, more recently, healthcare researchers are exposing the potential and harmful effects Big Data can have on patient care associating it with increased medical costs, patient mortality, and misguided decision making by clinicians and healthcare policy makers. In this paper, we review the current Big Data trends with a specific focus on the inadvertent negative impacts that Big Data could have on healthcare, in general, and specifically, as it relates to patient and clinical care. Our study results show that although Big Data is built up to be as a the "Holy Grail" for healthcare, small data techniques using traditional statistical methods are, in many cases, more accurate and can lead to more improved healthcare outcomes than Big Data methods. In sum, Big Data for healthcare may cause more problems for the healthcare industry than solutions, and in short, when it comes to the use of data in healthcare, "size isn't everything."

  17. Big Game Reporting Stations

    Data.gov (United States)

    Vermont Center for Geographic Information — Point locations of big game reporting stations. Big game reporting stations are places where hunters can legally report harvested deer, bear, or turkey. These are...

  18. Stalin's Big Fleet Program

    National Research Council Canada - National Science Library

    Mauner, Milan

    2002-01-01

    Although Dr. Milan Hauner's study 'Stalin's Big Fleet program' has focused primarily on the formation of Big Fleets during the Tsarist and Soviet periods of Russia's naval history, there are important lessons...

  19. Big Data Semantics

    NARCIS (Netherlands)

    Ceravolo, Paolo; Azzini, Antonia; Angelini, Marco; Catarci, Tiziana; Cudré-Mauroux, Philippe; Damiani, Ernesto; Mazak, Alexandra; van Keulen, Maurice; Jarrar, Mustafa; Santucci, Giuseppe; Sattler, Kai-Uwe; Scannapieco, Monica; Wimmer, Manuel; Wrembel, Robert; Zaraket, Fadi

    2018-01-01

    Big Data technology has discarded traditional data modeling approaches as no longer applicable to distributed data processing. It is, however, largely recognized that Big Data impose novel challenges in data and infrastructure management. Indeed, multiple components and procedures must be

  20. Characterizing Big Data Management

    OpenAIRE

    Rogério Rossi; Kechi Hirama

    2015-01-01

    Big data management is a reality for an increasing number of organizations in many areas and represents a set of challenges involving big data modeling, storage and retrieval, analysis and visualization. However, technological resources, people and processes are crucial to facilitate the management of big data in any kind of organization, allowing information and knowledge from a large volume of data to support decision-making. Big data management can be supported by these three dimensions: t...

  1. Social big data mining

    CERN Document Server

    Ishikawa, Hiroshi

    2015-01-01

    Social Media. Big Data and Social Data. Hypotheses in the Era of Big Data. Social Big Data Applications. Basic Concepts in Data Mining. Association Rule Mining. Clustering. Classification. Prediction. Web Structure Mining. Web Content Mining. Web Access Log Mining, Information Extraction and Deep Web Mining. Media Mining. Scalability and Outlier Detection.

  2. Deep sequencing of amplicons reveals widespread intraspecific hybridization and multiple origins of polyploidy in big sagebrush (Artemisia tridentata, Asteraceae)

    Science.gov (United States)

    Bryce A. Richardson; Justin T. Page; Prabin Bajgain; Stewart C. Sanderson; Joshua A. Udall

    2012-01-01

    Premise of the study: Hybridization has played an important role in the evolution and ecological adaptation of diploid and polyploid plants. Artemisia tridentata (Asteraceae) tetraploids are extremely widespread and of great ecological importance. These tetraploids are often taxonomically identified as A. tridentata subsp. wyomingensis or as autotetraploids of diploid...

  3. Seasonal relationships between foliar moisture content, heat content and biochemistry of lodge pole pine and big sagebrush foliage

    Science.gov (United States)

    Yi Qi; Matt Jolly; Philip E. Dennison; Rachael C. Kropp

    2016-01-01

    Wildland fires propagate by liberating energy contained within living and senescent plant biomass. The maximum amount of energy that can be generated by burning a given plant part can be quantified and is generally referred to as its heat content (HC). Many studies have examined heat content of wildland fuels but studies examining the seasonal variation in foliar HC...

  4. Composition of the essential oils from Rocky Mountain juniper (Juniperus scopulorum), Big sagebrush (Artemisia tridentata), and White Sage (Salvia apiana).

    Energy Technology Data Exchange (ETDEWEB)

    Hochrein, James Michael; Irwin, Adriane Nadine; Borek, Theodore Thaddeus III

    2003-09-01

    The essential oils of Juniperus scopulorum, Artemisia tridentata, and Salvia apiana obtained by steam extraction were analyzed by GC-MS and GC-FID. For J. scopulorum, twenty-five compounds were identified which accounts for 92.43% of the oil. The primary constituents were sabinene (49.91%), {alpha}-terpinene (9.95%), and 4-terpineol (6.79%). For A. tridentata, twenty compounds were identified which accounts for 84.32% of the oil. The primary constituents were camphor (28.63%), camphene (16.88%), and 1,8-cineole (13.23%). For S. apiana, fourteen compounds were identified which accounts for 96.76% of the oil. The primary component was 1,8-cineole (60.65%).

  5. A cross-scale approach to understand drought-induced variability of sagebrush ecosystem productivity

    Science.gov (United States)

    Assal, T.; Anderson, P. J.

    2016-12-01

    Sagebrush (Artemisia spp.) mortality has recently been reported in the Upper Green River Basin (Wyoming, USA) of the sagebrush steppe of western North America. Numerous causes have been suggested, but recent drought (2012-13) is the likely mechanism of mortality in this water-limited ecosystem which provides critical habitat for many species of wildlife. An understanding of the variability in patterns of productivity with respect to climate is essential to exploit landscape scale remote sensing for detection of subtle changes associated with mortality in this sparse, uniformly vegetated ecosystem. We used the standardized precipitation index to characterize drought conditions and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery (250-m resolution) to characterize broad characteristics of growing season productivity. We calculated per-pixel growing season anomalies over a 16-year period (2000-2015) to identify the spatial and temporal variability in productivity. Metrics derived from Landsat satellite imagery (30-m resolution) were used to further investigate trends within anomalous areas at local scales. We found evidence to support an initial hypothesis that antecedent winter drought was most important in explaining reduced productivity. The results indicate drought effects were inconsistent over space and time. MODIS derived productivity deviated by more than four standard deviations in heavily impacted areas, but was well within the interannual variability in other areas. Growing season anomalies highlighted dramatic declines in productivity during the 2012 and 2013 growing seasons. However, large negative anomalies persisted in other areas during the 2014 growing season, indicating lag effects of drought. We are further investigating if the reduction in productivity is mediated by local biophysical properties. Our analysis identified spatially explicit patterns of ecosystem properties altered by severe drought which are consistent with

  6. Big data computing

    CERN Document Server

    Akerkar, Rajendra

    2013-01-01

    Due to market forces and technological evolution, Big Data computing is developing at an increasing rate. A wide variety of novel approaches and tools have emerged to tackle the challenges of Big Data, creating both more opportunities and more challenges for students and professionals in the field of data computation and analysis. Presenting a mix of industry cases and theory, Big Data Computing discusses the technical and practical issues related to Big Data in intelligent information management. Emphasizing the adoption and diffusion of Big Data tools and technologies in industry, the book i

  7. Microsoft big data solutions

    CERN Document Server

    Jorgensen, Adam; Welch, John; Clark, Dan; Price, Christopher; Mitchell, Brian

    2014-01-01

    Tap the power of Big Data with Microsoft technologies Big Data is here, and Microsoft's new Big Data platform is a valuable tool to help your company get the very most out of it. This timely book shows you how to use HDInsight along with HortonWorks Data Platform for Windows to store, manage, analyze, and share Big Data throughout the enterprise. Focusing primarily on Microsoft and HortonWorks technologies but also covering open source tools, Microsoft Big Data Solutions explains best practices, covers on-premises and cloud-based solutions, and features valuable case studies. Best of all,

  8. Integrated disposal Facility Sagebrush Habitat Mitigation Project: FY2007 Compensation Area Monitoring Report

    Energy Technology Data Exchange (ETDEWEB)

    Durham, Robin E.; Sackschewsky, Michael R.

    2007-09-01

    This report summarizes the first year survival of sagebrush seedlings planted as compensatory mitigation for the Integrated Disposal Facility Project. Approximately 42,600 bare root seedlings and 26,000 pluglings were planted at a mitigation site along Army Loop Road in February 2007. Initial baseline monitoring occurred in March 2007, and first summer survival was assessed in September 2007. Overall survival was 19%, with bare root survival being marginally better than pluglings (21% versus 14%). Likely major factors contributing to low survival were late season planting and insufficient soil moisture during seedling establishment.

  9. Characterizing Big Data Management

    Directory of Open Access Journals (Sweden)

    Rogério Rossi

    2015-06-01

    Full Text Available Big data management is a reality for an increasing number of organizations in many areas and represents a set of challenges involving big data modeling, storage and retrieval, analysis and visualization. However, technological resources, people and processes are crucial to facilitate the management of big data in any kind of organization, allowing information and knowledge from a large volume of data to support decision-making. Big data management can be supported by these three dimensions: technology, people and processes. Hence, this article discusses these dimensions: the technological dimension that is related to storage, analytics and visualization of big data; the human aspects of big data; and, in addition, the process management dimension that involves in a technological and business approach the aspects of big data management.

  10. Big data integration: scalability and sustainability

    KAUST Repository

    Zhang, Zhang

    2016-01-26

    Integration of various types of omics data is critically indispensable for addressing most important and complex biological questions. In the era of big data, however, data integration becomes increasingly tedious, time-consuming and expensive, posing a significant obstacle to fully exploit the wealth of big biological data. Here we propose a scalable and sustainable architecture that integrates big omics data through community-contributed modules. Community modules are contributed and maintained by different committed groups and each module corresponds to a specific data type, deals with data collection, processing and visualization, and delivers data on-demand via web services. Based on this community-based architecture, we build Information Commons for Rice (IC4R; http://ic4r.org), a rice knowledgebase that integrates a variety of rice omics data from multiple community modules, including genome-wide expression profiles derived entirely from RNA-Seq data, resequencing-based genomic variations obtained from re-sequencing data of thousands of rice varieties, plant homologous genes covering multiple diverse plant species, post-translational modifications, rice-related literatures, and community annotations. Taken together, such architecture achieves integration of different types of data from multiple community-contributed modules and accordingly features scalable, sustainable and collaborative integration of big data as well as low costs for database update and maintenance, thus helpful for building IC4R into a comprehensive knowledgebase covering all aspects of rice data and beneficial for both basic and translational researches.

  11. Main Issues in Big Data Security

    Directory of Open Access Journals (Sweden)

    Julio Moreno

    2016-09-01

    Full Text Available Data is currently one of the most important assets for companies in every field. The continuous growth in the importance and volume of data has created a new problem: it cannot be handled by traditional analysis techniques. This problem was, therefore, solved through the creation of a new paradigm: Big Data. However, Big Data originated new issues related not only to the volume or the variety of the data, but also to data security and privacy. In order to obtain a full perspective of the problem, we decided to carry out an investigation with the objective of highlighting the main issues regarding Big Data security, and also the solutions proposed by the scientific community to solve them. In this paper, we explain the results obtained after applying a systematic mapping study to security in the Big Data ecosystem. It is almost impossible to carry out detailed research into the entire topic of security, and the outcome of this research is, therefore, a big picture of the main problems related to security in a Big Data system, along with the principal solutions to them proposed by the research community.

  12. Big Data in Drug Discovery.

    Science.gov (United States)

    Brown, Nathan; Cambruzzi, Jean; Cox, Peter J; Davies, Mark; Dunbar, James; Plumbley, Dean; Sellwood, Matthew A; Sim, Aaron; Williams-Jones, Bryn I; Zwierzyna, Magdalena; Sheppard, David W

    2018-01-01

    Interpretation of Big Data in the drug discovery community should enhance project timelines and reduce clinical attrition through improved early decision making. The issues we encounter start with the sheer volume of data and how we first ingest it before building an infrastructure to house it to make use of the data in an efficient and productive way. There are many problems associated with the data itself including general reproducibility, but often, it is the context surrounding an experiment that is critical to success. Help, in the form of artificial intelligence (AI), is required to understand and translate the context. On the back of natural language processing pipelines, AI is also used to prospectively generate new hypotheses by linking data together. We explain Big Data from the context of biology, chemistry and clinical trials, showcasing some of the impressive public domain sources and initiatives now available for interrogation. © 2018 Elsevier B.V. All rights reserved.

  13. Conservation and restoration of sagebrush ecosystems and sage-grouse: An assessment of USDA Forest Service Science

    Science.gov (United States)

    Deborah M. Finch; Douglas A. Boyce; Jeanne C. Chambers; Chris J. Colt; Kas Dumroese; Stanley G. Kitchen; Clinton McCarthy; Susan E. Meyer; Bryce A. Richardson; Mary M. Rowland; Mark A. Rumble; Michael K. Schwartz; Monica S. Tomosy; Michael J. Wisdom

    2016-01-01

    Sagebrush ecosystems are among the largest and most threatened ecosystems in North America. Greater sage-grouse has served as the bellwether for species conservation in these ecosystems and has been considered for listing under the Endangered Species Act eight times. In September 2015, the decision was made not to list greater sage-grouse, but to reevaluate its status...

  14. Evolutionary and ecological implications of genome size in the North American endemic sagebrushes and allies (Artemisia, Asteraceae)

    Science.gov (United States)

    Sonia Garcia; Miguel A. Canela; Teresa Garnatje; E. Durant McArthur; Jaume Pellicer; Stewart C. Sanderson; Joan Valles

    2008-01-01

    The genome size of 51 populations of 20 species of the North American endemic sagebrushes (subgenus Tridentatae), related species, and some hybrid taxa were assessed by flow cytometry, and were analysed in a phylogenetic framework. Results were similar for most Tridentatae species, with the exception of three taxonomically conflictive species: Artemisia bigelovii Gray...

  15. Plant age, communication, and resistance to herbivores: young sagebrush plants are better emitters and receivers.

    Science.gov (United States)

    Shiojiri, Kaori; Karban, Richard

    2006-08-01

    Plants progress through a series of distinct stages during development, although the role of plant ontogeny in their defenses against herbivores is poorly understood. Recent work indicates that many plants activate systemic induced resistance after herbivore attack, although the relationship between resistance and ontogeny has not been a focus of this work. In addition, for sagebrush and a few other species, individuals near neighbors that experience simulated herbivory become more resistant to subsequent attack. Volatile, airborne cues are required for both systemic induced resistance among branches and for communication among individuals. We conducted experiments in stands of sagebrush of mixed ages to determine effects of plant age on volatile signaling between branches and individuals. Young and old control plants did not differ in levels of chewing damage that they experienced. Systemic induced resistance among branches was only observed for young plants. Young plants showed strong evidence of systemic resistance only if airflow was permitted among branches; plants with only vascular connections showed no systemic resistance. We also found evidence for volatile communication between individuals. For airborne communication, young plants were more effective emitters of cues as well as more responsive receivers of volatile cues.

  16. HARNESSING BIG DATA VOLUMES

    Directory of Open Access Journals (Sweden)

    Bogdan DINU

    2014-04-01

    Full Text Available Big Data can revolutionize humanity. Hidden within the huge amounts and variety of the data we are creating we may find information, facts, social insights and benchmarks that were once virtually impossible to find or were simply inexistent. Large volumes of data allow organizations to tap in real time the full potential of all the internal or external information they possess. Big data calls for quick decisions and innovative ways to assist customers and the society as a whole. Big data platforms and product portfolio will help customers harness to the full the value of big data volumes. This paper deals with technical and technological issues related to handling big data volumes in the Big Data environment.

  17. The big bang

    International Nuclear Information System (INIS)

    Chown, Marcus.

    1987-01-01

    The paper concerns the 'Big Bang' theory of the creation of the Universe 15 thousand million years ago, and traces events which physicists predict occurred soon after the creation. Unified theory of the moment of creation, evidence of an expanding Universe, the X-boson -the particle produced very soon after the big bang and which vanished from the Universe one-hundredth of a second after the big bang, and the fate of the Universe, are all discussed. (U.K.)

  18. Big Earth Data Initiative: Metadata Improvement: Case Studies

    Science.gov (United States)

    Kozimor, John; Habermann, Ted; Farley, John

    2016-01-01

    Big Earth Data Initiative (BEDI) The Big Earth Data Initiative (BEDI) invests in standardizing and optimizing the collection, management and delivery of U.S. Government's civil Earth observation data to improve discovery, access use, and understanding of Earth observations by the broader user community. Complete and consistent standard metadata helps address all three goals.

  19. Summary big data

    CERN Document Server

    2014-01-01

    This work offers a summary of Cukier the book: "Big Data: A Revolution That Will Transform How we Live, Work, and Think" by Viktor Mayer-Schonberg and Kenneth. Summary of the ideas in Viktor Mayer-Schonberg's and Kenneth Cukier's book: " Big Data " explains that big data is where we use huge quantities of data to make better predictions based on the fact we identify patters in the data rather than trying to understand the underlying causes in more detail. This summary highlights that big data will be a source of new economic value and innovation in the future. Moreover, it shows that it will

  20. Data: Big and Small.

    Science.gov (United States)

    Jones-Schenk, Jan

    2017-02-01

    Big data is a big topic in all leadership circles. Leaders in professional development must develop an understanding of what data are available across the organization that can inform effective planning for forecasting. Collaborating with others to integrate data sets can increase the power of prediction. Big data alone is insufficient to make big decisions. Leaders must find ways to access small data and triangulate multiple types of data to ensure the best decision making. J Contin Educ Nurs. 2017;48(2):60-61. Copyright 2017, SLACK Incorporated.

  1. A Big Video Manifesto

    DEFF Research Database (Denmark)

    Mcilvenny, Paul Bruce; Davidsen, Jacob

    2017-01-01

    and beautiful visualisations. However, we also need to ask what the tools of big data can do both for the Humanities and for more interpretative approaches and methods. Thus, we prefer to explore how the power of computation, new sensor technologies and massive storage can also help with video-based qualitative......For the last few years, we have witnessed a hype about the potential results and insights that quantitative big data can bring to the social sciences. The wonder of big data has moved into education, traffic planning, and disease control with a promise of making things better with big numbers...

  2. Plant litter effects on soil nutrient availability and vegetation dynamics: changes that occur when annual grasses invade shrub-steppe communities

    Science.gov (United States)

    Sheel Bansal; Roger L. Sheley; Bob Blank; Edward A. Vasquez

    2014-01-01

    Changes in the quantity and quality of plant litter occur in many ecosystems as they are invaded by exotic species, which impact soil nutrient cycling and plant community composition. Such changes in sagebrush-steppe communities are occurring with invasion of annual grasses (AG) into a perennial grass (PG) dominated system. We conducted a 5-year litter manipulation...

  3. Bliver big data til big business?

    DEFF Research Database (Denmark)

    Ritter, Thomas

    2015-01-01

    Danmark har en digital infrastruktur, en registreringskultur og it-kompetente medarbejdere og kunder, som muliggør en førerposition, men kun hvis virksomhederne gør sig klar til næste big data-bølge.......Danmark har en digital infrastruktur, en registreringskultur og it-kompetente medarbejdere og kunder, som muliggør en førerposition, men kun hvis virksomhederne gør sig klar til næste big data-bølge....

  4. Dual of big bang and big crunch

    International Nuclear Information System (INIS)

    Bak, Dongsu

    2007-01-01

    Starting from the Janus solution and its gauge theory dual, we obtain the dual gauge theory description of the cosmological solution by the procedure of double analytic continuation. The coupling is driven either to zero or to infinity at the big-bang and big-crunch singularities, which are shown to be related by the S-duality symmetry. In the dual Yang-Mills theory description, these are nonsingular as the coupling goes to zero in the N=4 super Yang-Mills theory. The cosmological singularities simply signal the failure of the supergravity description of the full type IIB superstring theory

  5. Status and use of important native grasses adapted to sagebrush communities

    Science.gov (United States)

    Thomas A. Jones; Steven R. Larson

    2005-01-01

    Due to the emphasis on restoration, native cool-season grass species are increasing in importance in the commercial seed trade in the Western U.S. Cultivated seed production of these native grasses has often been hampered by seed dormancy, seed shattering, and pernicious awns that are advantageous outside of cultivation. Relatively low seed yields and poor seedling...

  6. Estudiarán el Big Bang por Internet

    CERN Multimedia

    2007-01-01

    The most powerful Internet, star of the present, goes for another challenge that mixes past and future: to join the scientific world community to clarify the orígines of the universe, the Big Bang. (1/2 page)

  7. Big Data and Neuroimaging.

    Science.gov (United States)

    Webb-Vargas, Yenny; Chen, Shaojie; Fisher, Aaron; Mejia, Amanda; Xu, Yuting; Crainiceanu, Ciprian; Caffo, Brian; Lindquist, Martin A

    2017-12-01

    Big Data are of increasing importance in a variety of areas, especially in the biosciences. There is an emerging critical need for Big Data tools and methods, because of the potential impact of advancements in these areas. Importantly, statisticians and statistical thinking have a major role to play in creating meaningful progress in this arena. We would like to emphasize this point in this special issue, as it highlights both the dramatic need for statistical input for Big Data analysis and for a greater number of statisticians working on Big Data problems. We use the field of statistical neuroimaging to demonstrate these points. As such, this paper covers several applications and novel methodological developments of Big Data tools applied to neuroimaging data.

  8. Big data for health.

    Science.gov (United States)

    Andreu-Perez, Javier; Poon, Carmen C Y; Merrifield, Robert D; Wong, Stephen T C; Yang, Guang-Zhong

    2015-07-01

    This paper provides an overview of recent developments in big data in the context of biomedical and health informatics. It outlines the key characteristics of big data and how medical and health informatics, translational bioinformatics, sensor informatics, and imaging informatics will benefit from an integrated approach of piecing together different aspects of personalized information from a diverse range of data sources, both structured and unstructured, covering genomics, proteomics, metabolomics, as well as imaging, clinical diagnosis, and long-term continuous physiological sensing of an individual. It is expected that recent advances in big data will expand our knowledge for testing new hypotheses about disease management from diagnosis to prevention to personalized treatment. The rise of big data, however, also raises challenges in terms of privacy, security, data ownership, data stewardship, and governance. This paper discusses some of the existing activities and future opportunities related to big data for health, outlining some of the key underlying issues that need to be tackled.

  9. Assessing long-term variations in sagebrush habitat: characterization of spatial extents and distribution patterns using multi-temporal satellite remote-sensing data

    Science.gov (United States)

    Xian, George; Homer, Collin G.; Aldridge, Cameron L.

    2012-01-01

    An approach that can generate sagebrush habitat change estimates for monitoring large-area sagebrush ecosystems has been developed and tested in southwestern Wyoming, USA. This prototype method uses a satellite-based image change detection algorithm and regression models to estimate sub-pixel percentage cover for five sagebrush habitat components: bare ground, herbaceous, litter, sagebrush and shrub. Landsat images from three different months in 1988, 1996 and 2006 were selected to identify potential landscape change during these time periods using change vector (CV) analysis incorporated with an image normalization algorithm. Regression tree (RT) models were used to estimate percentage cover for five components on all change areas identified in 1988 and 1996, using unchanged 2006 baseline data as training for both estimates. Over the entire study area (24 950 km2), a net increase of 98.83 km2, or 0.7%, for bare ground was measured between 1988 and 2006. Over the same period, the other four components had net losses of 20.17 km2, or 0.6%, for herbaceous vegetation; 30.16 km2, or 0.7%, for litter; 32.81 km2, or 1.5%, for sagebrush; and 33.34 km2, or 1.2%, for shrubs. The overall accuracy for shrub vegetation change between 1988 and 2006 was 89.56%. Change patterns within sagebrush habitat components differ spatially and quantitatively from each other, potentially indicating unique responses by these components to disturbances imposed upon them.

  10. From Big Data to Big Business

    DEFF Research Database (Denmark)

    Lund Pedersen, Carsten

    2017-01-01

    Idea in Brief: Problem: There is an enormous profit potential for manufacturing firms in big data, but one of the key barriers to obtaining data-driven growth is the lack of knowledge about which capabilities are needed to extract value and profit from data. Solution: We (BDBB research group at C...

  11. Big data, big knowledge: big data for personalized healthcare.

    Science.gov (United States)

    Viceconti, Marco; Hunter, Peter; Hose, Rod

    2015-07-01

    The idea that the purely phenomenological knowledge that we can extract by analyzing large amounts of data can be useful in healthcare seems to contradict the desire of VPH researchers to build detailed mechanistic models for individual patients. But in practice no model is ever entirely phenomenological or entirely mechanistic. We propose in this position paper that big data analytics can be successfully combined with VPH technologies to produce robust and effective in silico medicine solutions. In order to do this, big data technologies must be further developed to cope with some specific requirements that emerge from this application. Such requirements are: working with sensitive data; analytics of complex and heterogeneous data spaces, including nontextual information; distributed data management under security and performance constraints; specialized analytics to integrate bioinformatics and systems biology information with clinical observations at tissue, organ and organisms scales; and specialized analytics to define the "physiological envelope" during the daily life of each patient. These domain-specific requirements suggest a need for targeted funding, in which big data technologies for in silico medicine becomes the research priority.

  12. Community Cup, We Are a Big Family”: Examining Social Inclusion and Acculturation of Newcomers to Canada through a Participatory Sport Event

    Directory of Open Access Journals (Sweden)

    Kyle A. Rich

    2015-06-01

    Full Text Available While sport is widely understood to produce positive social outcomes for communities, such as the inclusion of diverse and marginalized groups, little researched has focused on the specific processes through which these outcomes may or may not be occurring. In this paper, we discuss the Community Cup program, and specifically a participatory sport event which seeks to connect newcomers to Canada (recent immigrants and refugees in order to build capacity, connect communities, and facilitate further avenues to participation in community life. For this research, we worked collaboratively with the program to conduct an intrinsic case study, utilizing participant observation, document analysis, focus group, and semi-structured interviews. We discuss how the structure and organization of the event influences participants’ experiences and consequently how this impacts the adaptation and acculturation processes. Using Donnelly and Coakley's (2002 cornerstones of social inclusion and Berry’s (1992 framework for understanding acculturation, we critically discuss the ways that the participatory sport event may provide an avenue for inclusion of newcomers, as well as the aspects of inclusion that the event does not address. While exploratory in nature, this paper begins to unpack the complex process of how inclusion may or may not be facilitated through sport, as well discussing the role of the management of these sporting practices. Furthermore, based on our discussion, we offer suggestions for sport event managers to improve the design and implementation of programming offered for diverse/newcomer populations.

  13. Using Unmanned Aerial Vehicles to Assess Vegetative Cover in Sagebrush Steppe Ecosytstems

    Energy Technology Data Exchange (ETDEWEB)

    Robert P. Breckenridge

    2005-09-01

    The Idaho National Laboratory (INL), in conjunction with the University of Idaho, is evaluating novel approaches for using unmanned aerial vehicles (UAVs) as a quicker and safer method for monitoring biotic resources. Evaluating vegetative cover is an important factor in understanding the sustainability of many ecosystems. In assessing vegetative cover, methods that improve accuracy and cost efficiency could revolutionize how biotic resources are monitored on western federal lands. Sagebrush steppe ecosystems provide important habitat for a variety of species, some of which are important indicator species (e.g., sage grouse). Improved methods are needed to support monitoring these habitats because there are not enough resource specialists or funds available for comprehensive ground evaluation of these ecosystems. In this project, two types of UAV platforms (fixed wing and helicopter) were used to collect still-frame imagery to assess cover in sagebrush steppe ecosystems. This paper discusses the process for collecting and analyzing imagery from the UAVs to (1) estimate total percent cover, (2) estimate percent cover for six different types of vegetation, and (3) locate sage grouse based on representative decoys. The field plots were located on the INL site west of Idaho Falls, Idaho, in areas with varying amounts and types of vegetative cover. A software program called SamplePoint developed by the U.S. Department of Agriculture, Agricultural Research Service (USDA-ARS) was used to evaluate the imagery for percent cover for the six vegetation types (bare ground, litter, shrubs, dead shrubs, grasses, and forbs). Results were compared against standard field measurements to assess accuracy.

  14. Big Five personality traits may inform public health policy and preventive medicine: Evidence from a cross-sectional and a prospective longitudinal epidemiologic study in a Swiss community.

    Science.gov (United States)

    Hengartner, Michael P; Kawohl, Wolfram; Haker, Helene; Rössler, Wulf; Ajdacic-Gross, Vladeta

    2016-05-01

    Some evidence documents the importance of personality assessments for health research and practise. However, no study has opted to test whether a short self-report personality inventory may comprehensively inform health policy. Data were taken from a population-based epidemiologic survey in Zurich, Switzerland, conducted from 2010-2012. A short form of the Big Five Inventory was completed by n=1155 participants (54.4% women; mean age=29.6 years), while health-related outcomes were taken from a comprehensive semi-structured clinical interview. A convenience subsample averaging n=171 participants additionally provided laboratory measures and n=133 were subsequently followed-up at least once over a maximal period of 6 months. Personality traits, in particular high neuroticism and low conscientiousness, related significantly to poor environmental resources such as low social support (R(2)=0.071), health-impairing behaviours such as cannabis use (R(2)=0.071), and psychopathology, including negative affect (R(2)=0.269) and various mental disorders (R(2)=0.060-0.195). The proportion of total variance explained was R(2)=0.339 in persons with three or more mental disorders. Personality significantly related to some laboratory measures including total cholesterol (R(2)=0.095) and C-Reactive Protein (R(2)=0.062). Finally, personality prospectively predicted global psychopathological distress and vegetative symptoms over a 6-month observation period. Personality relates consistently to poor socio-environmental resources, health-impairing behaviours and psychopathology. We also found some evidence for an association with metabolic and immune functions that are assumed to influence health. A short personality inventory could provide valuable information for preventive medicine when used as a means to screen entire populations for distinct risk exposure, in particular with respect to psychopathology. Copyright © 2016 Elsevier Inc. All rights reserved.

  15. Big Data in industry

    Science.gov (United States)

    Latinović, T. S.; Preradović, D. M.; Barz, C. R.; Latinović, M. T.; Petrica, P. P.; Pop-Vadean, A.

    2016-08-01

    The amount of data at the global level has grown exponentially. Along with this phenomena, we have a need for a new unit of measure like exabyte, zettabyte, and yottabyte as the last unit measures the amount of data. The growth of data gives a situation where the classic systems for the collection, storage, processing, and visualization of data losing the battle with a large amount, speed, and variety of data that is generated continuously. Many of data that is created by the Internet of Things, IoT (cameras, satellites, cars, GPS navigation, etc.). It is our challenge to come up with new technologies and tools for the management and exploitation of these large amounts of data. Big Data is a hot topic in recent years in IT circles. However, Big Data is recognized in the business world, and increasingly in the public administration. This paper proposes an ontology of big data analytics and examines how to enhance business intelligence through big data analytics as a service by presenting a big data analytics services-oriented architecture. This paper also discusses the interrelationship between business intelligence and big data analytics. The proposed approach in this paper might facilitate the research and development of business analytics, big data analytics, and business intelligence as well as intelligent agents.

  16. Big data a primer

    CERN Document Server

    Bhuyan, Prachet; Chenthati, Deepak

    2015-01-01

    This book is a collection of chapters written by experts on various aspects of big data. The book aims to explain what big data is and how it is stored and used. The book starts from  the fundamentals and builds up from there. It is intended to serve as a review of the state-of-the-practice in the field of big data handling. The traditional framework of relational databases can no longer provide appropriate solutions for handling big data and making it available and useful to users scattered around the globe. The study of big data covers a wide range of issues including management of heterogeneous data, big data frameworks, change management, finding patterns in data usage and evolution, data as a service, service-generated data, service management, privacy and security. All of these aspects are touched upon in this book. It also discusses big data applications in different domains. The book will prove useful to students, researchers, and practicing database and networking engineers.

  17. Recht voor big data, big data voor recht

    NARCIS (Netherlands)

    Lafarre, Anne

    Big data is een niet meer weg te denken fenomeen in onze maatschappij. Het is de hype cycle voorbij en de eerste implementaties van big data-technieken worden uitgevoerd. Maar wat is nu precies big data? Wat houden de vijf V's in die vaak genoemd worden in relatie tot big data? Ter inleiding van

  18. Big Data Analytics in Chemical Engineering.

    Science.gov (United States)

    Chiang, Leo; Lu, Bo; Castillo, Ivan

    2017-06-07

    Big data analytics is the journey to turn data into insights for more informed business and operational decisions. As the chemical engineering community is collecting more data (volume) from different sources (variety), this journey becomes more challenging in terms of using the right data and the right tools (analytics) to make the right decisions in real time (velocity). This article highlights recent big data advancements in five industries, including chemicals, energy, semiconductors, pharmaceuticals, and food, and then discusses technical, platform, and culture challenges. To reach the next milestone in multiplying successes to the enterprise level, government, academia, and industry need to collaboratively focus on workforce development and innovation.

  19. Assessing Big Data

    DEFF Research Database (Denmark)

    Leimbach, Timo; Bachlechner, Daniel

    2015-01-01

    In recent years, big data has been one of the most controversially discussed technologies in terms of its possible positive and negative impact. Therefore, the need for technology assessments is obvious. This paper first provides, based on the results of a technology assessment study, an overview...... of the potential and challenges associated with big data and then describes the problems experienced during the study as well as methods found helpful to address them. The paper concludes with reflections on how the insights from the technology assessment study may have an impact on the future governance of big...... data....

  20. Big bang nucleosynthesis

    International Nuclear Information System (INIS)

    Boyd, Richard N.

    2001-01-01

    The precision of measurements in modern cosmology has made huge strides in recent years, with measurements of the cosmic microwave background and the determination of the Hubble constant now rivaling the level of precision of the predictions of big bang nucleosynthesis. However, these results are not necessarily consistent with the predictions of the Standard Model of big bang nucleosynthesis. Reconciling these discrepancies may require extensions of the basic tenets of the model, and possibly of the reaction rates that determine the big bang abundances

  1. Big data for dummies

    CERN Document Server

    Hurwitz, Judith; Halper, Fern; Kaufman, Marcia

    2013-01-01

    Find the right big data solution for your business or organization Big data management is one of the major challenges facing business, industry, and not-for-profit organizations. Data sets such as customer transactions for a mega-retailer, weather patterns monitored by meteorologists, or social network activity can quickly outpace the capacity of traditional data management tools. If you need to develop or manage big data solutions, you'll appreciate how these four experts define, explain, and guide you through this new and often confusing concept. You'll learn what it is, why it m

  2. Big Data, indispensable today

    Directory of Open Access Journals (Sweden)

    Radu-Ioan ENACHE

    2015-10-01

    Full Text Available Big data is and will be used more in the future as a tool for everything that happens both online and offline. Of course , online is a real hobbit, Big Data is found in this medium , offering many advantages , being a real help for all consumers. In this paper we talked about Big Data as being a plus in developing new applications, by gathering useful information about the users and their behaviour.We've also presented the key aspects of real-time monitoring and the architecture principles of this technology. The most important benefit brought to this paper is presented in the cloud section.

  3. Forecasting sagebrush ecosystem components and greater sage-grouse habitat for 2050: learning from past climate patterns and Landsat imagery to predict the future

    Science.gov (United States)

    Homer, Collin G.; Xian, George Z.; Aldridge, Cameron L.; Meyer, Debra K.; Loveland, Thomas R.; O'Donnell, Michael S.

    2015-01-01

    Sagebrush (Artemisia spp.) ecosystems constitute the largest single North American shrub ecosystem and provide vital ecological, hydrological, biological, agricultural, and recreational ecosystem services. Disturbances have altered and reduced this ecosystem historically, but climate change may ultimately represent the greatest future risk. Improved ways to quantify, monitor, and predict climate-driven gradual change in this ecosystem is vital to its future management. We examined the annual change of Daymet precipitation (daily gridded climate data) and five remote sensing ecosystem sagebrush vegetation and soil components (bare ground, herbaceous, litter, sagebrush, and shrub) from 1984 to 2011 in southwestern Wyoming. Bare ground displayed an increasing trend in abundance over time, and herbaceous, litter, shrub, and sagebrush showed a decreasing trend. Total precipitation amounts show a downward trend during the same period. We established statistically significant correlations between each sagebrush component and historical precipitation records using a simple least squares linear regression. Using the historical relationship between sagebrush component abundance and precipitation in a linear model, we forecasted the abundance of the sagebrush components in 2050 using Intergovernmental Panel on Climate Change (IPCC) precipitation scenarios A1B and A2. Bare ground was the only component that increased under both future scenarios, with a net increase of 48.98 km2 (1.1%) across the study area under the A1B scenario and 41.15 km2 (0.9%) under the A2 scenario. The remaining components decreased under both future scenarios: litter had the highest net reductions with 49.82 km2 (4.1%) under A1B and 50.8 km2 (4.2%) under A2, and herbaceous had the smallest net reductions with 39.95 km2 (3.8%) under A1B and 40.59 km2 (3.3%) under A2. We applied the 2050 forecast sagebrush component values to contemporary (circa 2006) greater sage-grouse (Centrocercus

  4. Big Data in der Cloud

    DEFF Research Database (Denmark)

    Leimbach, Timo; Bachlechner, Daniel

    2014-01-01

    Technology assessment of big data, in particular cloud based big data services, for the Office for Technology Assessment at the German federal parliament (Bundestag)......Technology assessment of big data, in particular cloud based big data services, for the Office for Technology Assessment at the German federal parliament (Bundestag)...

  5. Small Big Data Congress 2017

    NARCIS (Netherlands)

    Doorn, J.

    2017-01-01

    TNO, in collaboration with the Big Data Value Center, presents the fourth Small Big Data Congress! Our congress aims at providing an overview of practical and innovative applications based on big data. Do you want to know what is happening in applied research with big data? And what can already be

  6. Cryptography for Big Data Security

    Science.gov (United States)

    2015-07-13

    Cryptography for Big Data Security Book Chapter for Big Data: Storage, Sharing, and Security (3S) Distribution A: Public Release Ariel Hamlin1 Nabil...Email: arkady@ll.mit.edu ii Contents 1 Cryptography for Big Data Security 1 1.1 Introduction...48 Chapter 1 Cryptography for Big Data Security 1.1 Introduction With the amount

  7. Big data opportunities and challenges

    CERN Document Server

    2014-01-01

    This ebook aims to give practical guidance for all those who want to understand big data better and learn how to make the most of it. Topics range from big data analysis, mobile big data and managing unstructured data to technologies, governance and intellectual property and security issues surrounding big data.

  8. Mercury distribution in two Sierran forest and one desert sagebrush steppe ecosystems and the effects of fire

    International Nuclear Information System (INIS)

    Engle, Mark A.; Sexauer Gustin, Mae; Johnson, Dale W.; Murphy, James F.; Miller, Wally W.; Walker, Roger F.; Wright, Joan; Markee, Melissa

    2006-01-01

    Mercury (Hg) concentration, reservoir mass, and Hg reservoir size were determined for vegetation components, litter, and mineral soil for two Sierran forest sites and one desert sagebrush steppe site. Mercury was found to be held primarily in the mineral soil (maximum depth of 60 to 100 cm), which contained more than 90% of the total ecosystem reservoir. However, Hg in foliage, bark, and litter plays a more dominant role in Hg cycling than the mineral soil. Mercury partitioning into ecosystem components at the Sierran forest sites was similar to that observed for other US forest sites. Vegetation and litter Hg reservoirs were significantly smaller in the sagebrush steppe system because of lower biomass. Data collected from these ecosystems after wildfire and prescribed burns showed a significant decrease in the Hg pool from certain reservoirs. No loss from mineral soil was observed for the study areas but data from fire severity points suggested that Hg in the upper few millimeters of surface soil may be volatilized due to exposure to elevated temperatures. Comparison of data from burned and unburned plots suggested that the only significant source of atmospheric Hg from the prescribed burn was combustion of litter. Differences in unburned versus burned Hg reservoirs at the forest wildfire site demonstrated that drastic reduction in the litter and above ground live biomass Hg reservoirs after burning had occurred. Sagebrush and litter were absent in the burned plots after a wildfire suggesting that both reservoirs were released during the fire. Mercury emissions due to fire from the forest prescribed burn, forest wildfire, and sagebrush steppe wildfire sites were roughly estimated at 2.0 to 5.1, 2.2 to 4.9, and 0.36 ± 0.13 g ha -1 , respectively, with litter and vegetation being the most important sources

  9. Big Data as Governmentality

    DEFF Research Database (Denmark)

    Flyverbom, Mikkel; Madsen, Anders Koed; Rasche, Andreas

    This paper conceptualizes how large-scale data and algorithms condition and reshape knowledge production when addressing international development challenges. The concept of governmentality and four dimensions of an analytics of government are proposed as a theoretical framework to examine how big...... data is constituted as an aspiration to improve the data and knowledge underpinning development efforts. Based on this framework, we argue that big data’s impact on how relevant problems are governed is enabled by (1) new techniques of visualizing development issues, (2) linking aspects...... shows that big data problematizes selected aspects of traditional ways to collect and analyze data for development (e.g. via household surveys). We also demonstrate that using big data analyses to address development challenges raises a number of questions that can deteriorate its impact....

  10. Big Data Revisited

    DEFF Research Database (Denmark)

    Kallinikos, Jannis; Constantiou, Ioanna

    2015-01-01

    We elaborate on key issues of our paper New games, new rules: big data and the changing context of strategy as a means of addressing some of the concerns raised by the paper’s commentators. We initially deal with the issue of social data and the role it plays in the current data revolution...... and the technological recording of facts. We further discuss the significance of the very mechanisms by which big data is produced as distinct from the very attributes of big data, often discussed in the literature. In the final section of the paper, we qualify the alleged importance of algorithms and claim...... that the structures of data capture and the architectures in which data generation is embedded are fundamental to the phenomenon of big data....

  11. The Big Bang Singularity

    Science.gov (United States)

    Ling, Eric

    The big bang theory is a model of the universe which makes the striking prediction that the universe began a finite amount of time in the past at the so called "Big Bang singularity." We explore the physical and mathematical justification of this surprising result. After laying down the framework of the universe as a spacetime manifold, we combine physical observations with global symmetrical assumptions to deduce the FRW cosmological models which predict a big bang singularity. Next we prove a couple theorems due to Stephen Hawking which show that the big bang singularity exists even if one removes the global symmetrical assumptions. Lastly, we investigate the conditions one needs to impose on a spacetime if one wishes to avoid a singularity. The ideas and concepts used here to study spacetimes are similar to those used to study Riemannian manifolds, therefore we compare and contrast the two geometries throughout.

  12. BigDansing

    KAUST Repository

    Khayyat, Zuhair; Ilyas, Ihab F.; Jindal, Alekh; Madden, Samuel; Ouzzani, Mourad; Papotti, Paolo; Quiané -Ruiz, Jorge-Arnulfo; Tang, Nan; Yin, Si

    2015-01-01

    of the underlying distributed platform. BigDansing takes these rules into a series of transformations that enable distributed computations and several optimizations, such as shared scans and specialized joins operators. Experimental results on both synthetic

  13. Boarding to Big data

    Directory of Open Access Journals (Sweden)

    Oana Claudia BRATOSIN

    2016-05-01

    Full Text Available Today Big data is an emerging topic, as the quantity of the information grows exponentially, laying the foundation for its main challenge, the value of the information. The information value is not only defined by the value extraction from huge data sets, as fast and optimal as possible, but also by the value extraction from uncertain and inaccurate data, in an innovative manner using Big data analytics. At this point, the main challenge of the businesses that use Big data tools is to clearly define the scope and the necessary output of the business so that the real value can be gained. This article aims to explain the Big data concept, its various classifications criteria, architecture, as well as the impact in the world wide processes.

  14. Big Creek Pit Tags

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The BCPITTAGS database is used to store data from an Oncorhynchus mykiss (steelhead/rainbow trout) population dynamics study in Big Creek, a coastal stream along the...

  15. Scaling Big Data Cleansing

    KAUST Repository

    Khayyat, Zuhair

    2017-01-01

    on top of general-purpose distributed platforms. Its programming inter- face allows users to express data quality rules independently from the requirements of parallel and distributed environments. Without sacrificing their quality, BigDans- ing also

  16. Reframing Open Big Data

    DEFF Research Database (Denmark)

    Marton, Attila; Avital, Michel; Jensen, Tina Blegind

    2013-01-01

    Recent developments in the techniques and technologies of collecting, sharing and analysing data are challenging the field of information systems (IS) research let alone the boundaries of organizations and the established practices of decision-making. Coined ‘open data’ and ‘big data......’, these developments introduce an unprecedented level of societal and organizational engagement with the potential of computational data to generate new insights and information. Based on the commonalities shared by open data and big data, we develop a research framework that we refer to as open big data (OBD......) by employing the dimensions of ‘order’ and ‘relationality’. We argue that these dimensions offer a viable approach for IS research on open and big data because they address one of the core value propositions of IS; i.e. how to support organizing with computational data. We contrast these dimensions with two...

  17. Range-wide assessment of livestock grazing across the sagebrush biome

    Science.gov (United States)

    Veblen, Kari E.; Pyke, David A.; Jones, Christopher A.; Casazza, Michael L.; Assal, Timothy J.; Farinha, Melissa A.

    2011-01-01

    Domestic livestock grazing occurs in virtually all sagebrush habitats and is a prominent disturbance factor. By affecting habitat condition and trend, grazing influences the resources required by, and thus, the distribution and abundance of sagebrush-obligate wildlife species (for example, sage-grouse Centrocercus spp.). Yet, the risks that livestock grazing may pose to these species and their habitats are not always clear. Although livestock grazing intensity and associated habitat condition may be known in many places at the local level, we have not yet been able to answer questions about use, condition, and trend at the landscape scale or at the range-wide scale for wildlife species. A great deal of information about grazing use, management regimes, and ecological condition exists at the local level (for individual livestock management units) under the oversight of organizations such as the Bureau of Land Management (BLM). However, the extent, quality, and types of existing data are unknown, which hinders the compilation, mapping, or analysis of these data. Once compiled, these data may be helpful for drawing conclusions about rangeland status, and we may be able to identify relationships between those data and wildlife habitat at the landscape scale. The overall objective of our study was to perform a range-wide assessment of livestock grazing effects (and the relevant supporting data) in sagebrush ecosystems managed by the BLM. Our assessments and analyses focused primarily on local-level management and data collected at the scale of BLM grazing allotments (that is, individual livestock management units). Specific objectives included the following: 1. Identify and refine existing range-wide datasets to be used for analyses of livestock grazing effects on sagebrush ecosystems. 2. Assess the extent, quality, and types of livestock grazing-related natural resource data collected by BLM range-wide (i.e., across allotments, districts and regions). 3. Compile and

  18. Conociendo Big Data

    Directory of Open Access Journals (Sweden)

    Juan José Camargo-Vega

    2014-12-01

    Full Text Available Teniendo en cuenta la importancia que ha adquirido el término Big Data, la presente investigación buscó estudiar y analizar de manera exhaustiva el estado del arte del Big Data; además, y como segundo objetivo, analizó las características, las herramientas, las tecnologías, los modelos y los estándares relacionados con Big Data, y por último buscó identificar las características más relevantes en la gestión de Big Data, para que con ello se pueda conocer todo lo concerniente al tema central de la investigación.La metodología utilizada incluyó revisar el estado del arte de Big Data y enseñar su situación actual; conocer las tecnologías de Big Data; presentar algunas de las bases de datos NoSQL, que son las que permiten procesar datos con formatos no estructurados, y mostrar los modelos de datos y las tecnologías de análisis de ellos, para terminar con algunos beneficios de Big Data.El diseño metodológico usado para la investigación fue no experimental, pues no se manipulan variables, y de tipo exploratorio, debido a que con esta investigación se empieza a conocer el ambiente del Big Data.

  19. Big Bang baryosynthesis

    International Nuclear Information System (INIS)

    Turner, M.S.; Chicago Univ., IL

    1983-01-01

    In these lectures I briefly review Big Bang baryosynthesis. In the first lecture I discuss the evidence which exists for the BAU, the failure of non-GUT symmetrical cosmologies, the qualitative picture of baryosynthesis, and numerical results of detailed baryosynthesis calculations. In the second lecture I discuss the requisite CP violation in some detail, further the statistical mechanics of baryosynthesis, possible complications to the simplest scenario, and one cosmological implication of Big Bang baryosynthesis. (orig./HSI)

  20. Minsky on "Big Government"

    Directory of Open Access Journals (Sweden)

    Daniel de Santana Vasconcelos

    2014-03-01

    Full Text Available This paper objective is to assess, in light of the main works of Minsky, his view and analysis of what he called the "Big Government" as that huge institution which, in parallels with the "Big Bank" was capable of ensuring stability in the capitalist system and regulate its inherently unstable financial system in mid-20th century. In this work, we analyze how Minsky proposes an active role for the government in a complex economic system flawed by financial instability.

  1. Big data need big theory too.

    Science.gov (United States)

    Coveney, Peter V; Dougherty, Edward R; Highfield, Roger R

    2016-11-13

    The current interest in big data, machine learning and data analytics has generated the widespread impression that such methods are capable of solving most problems without the need for conventional scientific methods of inquiry. Interest in these methods is intensifying, accelerated by the ease with which digitized data can be acquired in virtually all fields of endeavour, from science, healthcare and cybersecurity to economics, social sciences and the humanities. In multiscale modelling, machine learning appears to provide a shortcut to reveal correlations of arbitrary complexity between processes at the atomic, molecular, meso- and macroscales. Here, we point out the weaknesses of pure big data approaches with particular focus on biology and medicine, which fail to provide conceptual accounts for the processes to which they are applied. No matter their 'depth' and the sophistication of data-driven methods, such as artificial neural nets, in the end they merely fit curves to existing data. Not only do these methods invariably require far larger quantities of data than anticipated by big data aficionados in order to produce statistically reliable results, but they can also fail in circumstances beyond the range of the data used to train them because they are not designed to model the structural characteristics of the underlying system. We argue that it is vital to use theory as a guide to experimental design for maximal efficiency of data collection and to produce reliable predictive models and conceptual knowledge. Rather than continuing to fund, pursue and promote 'blind' big data projects with massive budgets, we call for more funding to be allocated to the elucidation of the multiscale and stochastic processes controlling the behaviour of complex systems, including those of life, medicine and healthcare.This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'. © 2015 The Authors.

  2. Big Data and medicine: a big deal?

    Science.gov (United States)

    Mayer-Schönberger, V; Ingelsson, E

    2018-05-01

    Big Data promises huge benefits for medical research. Looking beyond superficial increases in the amount of data collected, we identify three key areas where Big Data differs from conventional analyses of data samples: (i) data are captured more comprehensively relative to the phenomenon under study; this reduces some bias but surfaces important trade-offs, such as between data quantity and data quality; (ii) data are often analysed using machine learning tools, such as neural networks rather than conventional statistical methods resulting in systems that over time capture insights implicit in data, but remain black boxes, rarely revealing causal connections; and (iii) the purpose of the analyses of data is no longer simply answering existing questions, but hinting at novel ones and generating promising new hypotheses. As a consequence, when performed right, Big Data analyses can accelerate research. Because Big Data approaches differ so fundamentally from small data ones, research structures, processes and mindsets need to adjust. The latent value of data is being reaped through repeated reuse of data, which runs counter to existing practices not only regarding data privacy, but data management more generally. Consequently, we suggest a number of adjustments such as boards reviewing responsible data use, and incentives to facilitate comprehensive data sharing. As data's role changes to a resource of insight, we also need to acknowledge the importance of collecting and making data available as a crucial part of our research endeavours, and reassess our formal processes from career advancement to treatment approval. © 2017 The Association for the Publication of the Journal of Internal Medicine.

  3. Big data uncertainties.

    Science.gov (United States)

    Maugis, Pierre-André G

    2018-07-01

    Big data-the idea that an always-larger volume of information is being constantly recorded-suggests that new problems can now be subjected to scientific scrutiny. However, can classical statistical methods be used directly on big data? We analyze the problem by looking at two known pitfalls of big datasets. First, that they are biased, in the sense that they do not offer a complete view of the populations under consideration. Second, that they present a weak but pervasive level of dependence between all their components. In both cases we observe that the uncertainty of the conclusion obtained by statistical methods is increased when used on big data, either because of a systematic error (bias), or because of a larger degree of randomness (increased variance). We argue that the key challenge raised by big data is not only how to use big data to tackle new problems, but to develop tools and methods able to rigorously articulate the new risks therein. Copyright © 2016. Published by Elsevier Ltd.

  4. Community

    Science.gov (United States)

    stability Science & Innovation Collaboration Careers Community Environment Science & Innovation Recruitment Events Community Commitment Giving Campaigns, Drives Economic Development Employee Funded neighbor pledge: contribute to quality of life in Northern New Mexico through economic development

  5. Restructuring Big Data to Improve Data Access and Performance in Analytic Services Making Research More Efficient for the Study of Extreme Weather Events and Application User Communities

    Science.gov (United States)

    Ostrenga, D.; Shen, S.; Vollmer, B.; Meyer, D. L.

    2017-12-01

    NASA climate reanalysis dataset from MERRA-2 contains numerous data for atmosphere, land, and ocean, that are grouped into 95 products of archived volume over 300 TB. The data files are saved as hourly-file, day-file (hourly time interval) and month-file containing up to 125 parameters. Due to the large number of data files and the sheer data volumes, it is a challenging for users, especially those in the application research community, to handle dealing with the original data files. Most of these researchers prefer to focus on a small region or single location using the hourly data for long time periods to analyze extreme weather events or say winds for renewable energy applications. At the GES DISC, we have been working closely with the science teams and the application user community to create several new value added data products and high quality services to facilitate the use of the model data for various types of research. We have tested converting hourly data from one-day per file into different data cubes, such as one-month, one-year, or whole-mission and then continued to analyze the efficiency of the accessibility of this newly structured data through various services. Initial results have shown that compared to the original file structure, the new data has significantly improved the performance for accessing long time series. It is noticed that the performance is associated to the cube size and structure, the compression method, and how the data are accessed. The optimized data cube structure will not only improve the data access, but also enable better online analytic services for doing statistical analysis and extreme events mining. Two case studies will be presented using the newly structured data and value added services, the California drought and the extreme drought of the Northeastern states of Brazil. Furthermore, data access and analysis through cloud storage capabilities will be investigated.

  6. Big data has big potential for applications to climate change adaptation

    NARCIS (Netherlands)

    Ford, James D.; Tilleard, Simon E.; Berrang-Ford, Lea; Araos, Malcolm; Biesbroek, Robbert; Lesnikowski, Alexandra C.; MacDonald, Graham K.; Hsu, Angel; Chen, Chen; Bizikova, Livia

    2016-01-01

    The capacity to collect and analyze massive amounts
    of data is transforming research in the natural and social
    sciences (1). And yet, the climate change adaptation
    community has largely overlooked these developments.
    Here, we examine how “big data” can inform adaptation
    research

  7. Using resistance and resilience concepts to reduce impacts of invasive annual grasses and altered fire regimes on the sagebrush ecosystem and greater sage-grouse: A strategic multi-scale approach

    Science.gov (United States)

    Jeanne C. Chambers; David A. Pyke; Jeremy D. Maestas; Mike Pellant; Chad S. Boyd; Steven B. Campbell; Shawn Espinosa; Douglas W. Havlina; Kenneth E. Mayer; Amarina Wuenschel

    2014-01-01

    This Report provides a strategic approach for conservation of sagebrush ecosystems and Greater Sage- Grouse (sage-grouse) that focuses specifically on habitat threats caused by invasive annual grasses and altered fire regimes. It uses information on factors that influence (1) sagebrush ecosystem resilience to disturbance and resistance to invasive annual grasses and (2...

  8. Science framework for conservation and restoration of the sagebrush biome: Linking the Department of the Interior’s Integrated Rangeland Fire Management Strategy to long-term strategic conservation actions

    Science.gov (United States)

    J.C. Chambers; J.L. Beck; J.B. Bradford; J. Bybee; S. Campbell; J. Carlson; T.J. Christiansen; K.J. Clause; G. Collins; M.R. Crist; J.B. Dinkins; K.E. Doherty; F. Edwards; S. Espinosa; K.A. Griffin; P. Griffin; J.R. Haas; S.E. Hanser; D.W. Havlina; K.F. Henke; J.D. Hennig; L.A. Joyce; F.M. Kilkenny; S.M. Kulpa; L.L. Kurth; J.D. Maestas; M. Manning; K.E. Mayer; B.A. Mealor; C. McCarthy; M. Pellant; M.A. Perea; K.L. Prentice; D.A. Pyke; L.A. Wiechman; A. Wuenschel

    2017-01-01

    The Science Framework is intended to link the Department of the Interior’s Integrated Rangeland Fire Management Strategy with long-term strategic conservation actions in the sagebrush biome. The Science Framework provides a multiscale approach for prioritizing areas for management and determining effective management strategies within the sagebrush biome. The emphasis...

  9. Using resilience and resistance concepts to manage threats to sagebrush ecosystems, Gunnison sage-grouse, and Greater sage-grouse in their eastern range: A strategic multi-scale approach

    Science.gov (United States)

    Jeanne C. Chambers; Jeffrey L. Beck; Steve Campbell; John Carlson; Thomas J. Christiansen; Karen J. Clause; Jonathan B. Dinkins; Kevin E. Doherty; Kathleen A. Griffin; Douglas W. Havlina; Kenneth F. Henke; Jacob D. Hennig; Laurie L. Kurth; Jeremy D. Maestas; Mary Manning; Kenneth E. Mayer; Brian A. Mealor; Clinton McCarthy; Marco A. Perea; David A. Pyke

    2016-01-01

    This report provides a strategic approach developed by a Western Association of Fish and Wildlife Agencies interagency working group for conservation of sagebrush ecosystems, Greater sage-grouse, and Gunnison sage-grouse. It uses information on (1) factors that influence sagebrush ecosystem resilience to disturbance and resistance to nonnative invasive annual grasses...

  10. The big data-big model (BDBM) challenges in ecological research

    Science.gov (United States)

    Luo, Y.

    2015-12-01

    The field of ecology has become a big-data science in the past decades due to development of new sensors used in numerous studies in the ecological community. Many sensor networks have been established to collect data. For example, satellites, such as Terra and OCO-2 among others, have collected data relevant on global carbon cycle. Thousands of field manipulative experiments have been conducted to examine feedback of terrestrial carbon cycle to global changes. Networks of observations, such as FLUXNET, have measured land processes. In particular, the implementation of the National Ecological Observatory Network (NEON), which is designed to network different kinds of sensors at many locations over the nation, will generate large volumes of ecological data every day. The raw data from sensors from those networks offer an unprecedented opportunity for accelerating advances in our knowledge of ecological processes, educating teachers and students, supporting decision-making, testing ecological theory, and forecasting changes in ecosystem services. Currently, ecologists do not have the infrastructure in place to synthesize massive yet heterogeneous data into resources for decision support. It is urgent to develop an ecological forecasting system that can make the best use of multiple sources of data to assess long-term biosphere change and anticipate future states of ecosystem services at regional and continental scales. Forecasting relies on big models that describe major processes that underlie complex system dynamics. Ecological system models, despite great simplification of the real systems, are still complex in order to address real-world problems. For example, Community Land Model (CLM) incorporates thousands of processes related to energy balance, hydrology, and biogeochemistry. Integration of massive data from multiple big data sources with complex models has to tackle Big Data-Big Model (BDBM) challenges. Those challenges include interoperability of multiple

  11. BigDansing

    KAUST Repository

    Khayyat, Zuhair

    2015-06-02

    Data cleansing approaches have usually focused on detecting and fixing errors with little attention to scaling to big datasets. This presents a serious impediment since data cleansing often involves costly computations such as enumerating pairs of tuples, handling inequality joins, and dealing with user-defined functions. In this paper, we present BigDansing, a Big Data Cleansing system to tackle efficiency, scalability, and ease-of-use issues in data cleansing. The system can run on top of most common general purpose data processing platforms, ranging from DBMSs to MapReduce-like frameworks. A user-friendly programming interface allows users to express data quality rules both declaratively and procedurally, with no requirement of being aware of the underlying distributed platform. BigDansing takes these rules into a series of transformations that enable distributed computations and several optimizations, such as shared scans and specialized joins operators. Experimental results on both synthetic and real datasets show that BigDansing outperforms existing baseline systems up to more than two orders of magnitude without sacrificing the quality provided by the repair algorithms.

  12. Big data challenges

    DEFF Research Database (Denmark)

    Bachlechner, Daniel; Leimbach, Timo

    2016-01-01

    Although reports on big data success stories have been accumulating in the media, most organizations dealing with high-volume, high-velocity and high-variety information assets still face challenges. Only a thorough understanding of these challenges puts organizations into a position in which...... they can make an informed decision for or against big data, and, if the decision is positive, overcome the challenges smoothly. The combination of a series of interviews with leading experts from enterprises, associations and research institutions, and focused literature reviews allowed not only...... framework are also relevant. For large enterprises and startups specialized in big data, it is typically easier to overcome the challenges than it is for other enterprises and public administration bodies....

  13. Thick-Big Descriptions

    DEFF Research Database (Denmark)

    Lai, Signe Sophus

    The paper discusses the rewards and challenges of employing commercial audience measurements data – gathered by media industries for profitmaking purposes – in ethnographic research on the Internet in everyday life. It questions claims to the objectivity of big data (Anderson 2008), the assumption...... communication systems, language and behavior appear as texts, outputs, and discourses (data to be ‘found’) – big data then documents things that in earlier research required interviews and observations (data to be ‘made’) (Jensen 2014). However, web-measurement enterprises build audiences according...... to a commercial logic (boyd & Crawford 2011) and is as such directed by motives that call for specific types of sellable user data and specific segmentation strategies. In combining big data and ‘thick descriptions’ (Geertz 1973) scholars need to question how ethnographic fieldwork might map the ‘data not seen...

  14. Big data in biomedicine.

    Science.gov (United States)

    Costa, Fabricio F

    2014-04-01

    The increasing availability and growth rate of biomedical information, also known as 'big data', provides an opportunity for future personalized medicine programs that will significantly improve patient care. Recent advances in information technology (IT) applied to biomedicine are changing the landscape of privacy and personal information, with patients getting more control of their health information. Conceivably, big data analytics is already impacting health decisions and patient care; however, specific challenges need to be addressed to integrate current discoveries into medical practice. In this article, I will discuss the major breakthroughs achieved in combining omics and clinical health data in terms of their application to personalized medicine. I will also review the challenges associated with using big data in biomedicine and translational science. Copyright © 2013 Elsevier Ltd. All rights reserved.

  15. Big data bioinformatics.

    Science.gov (United States)

    Greene, Casey S; Tan, Jie; Ung, Matthew; Moore, Jason H; Cheng, Chao

    2014-12-01

    Recent technological advances allow for high throughput profiling of biological systems in a cost-efficient manner. The low cost of data generation is leading us to the "big data" era. The availability of big data provides unprecedented opportunities but also raises new challenges for data mining and analysis. In this review, we introduce key concepts in the analysis of big data, including both "machine learning" algorithms as well as "unsupervised" and "supervised" examples of each. We note packages for the R programming language that are available to perform machine learning analyses. In addition to programming based solutions, we review webservers that allow users with limited or no programming background to perform these analyses on large data compendia. © 2014 Wiley Periodicals, Inc.

  16. Community.

    Science.gov (United States)

    Grauer, Kit, Ed.

    1995-01-01

    Art in context of community is the theme of this newsletter. The theme is introduced in an editorial "Community-Enlarging the Definition" (Kit Grauer). Related articles include: (1) "The Children's Bridge is not Destroyed: Heart in the Middle of the World" (Emil Robert Tanay); (2) "Making Bridges: The Sock Doll…

  17. The BIG Data Center: from deposition to integration to translation.

    Science.gov (United States)

    2017-01-04

    Biological data are generated at unprecedentedly exponential rates, posing considerable challenges in big data deposition, integration and translation. The BIG Data Center, established at Beijing Institute of Genomics (BIG), Chinese Academy of Sciences, provides a suite of database resources, including (i) Genome Sequence Archive, a data repository specialized for archiving raw sequence reads, (ii) Gene Expression Nebulas, a data portal of gene expression profiles based entirely on RNA-Seq data, (iii) Genome Variation Map, a comprehensive collection of genome variations for featured species, (iv) Genome Warehouse, a centralized resource housing genome-scale data with particular focus on economically important animals and plants, (v) Methylation Bank, an integrated database of whole-genome single-base resolution methylomes and (vi) Science Wikis, a central access point for biological wikis developed for community annotations. The BIG Data Center is dedicated to constructing and maintaining biological databases through big data integration and value-added curation, conducting basic research to translate big data into big knowledge and providing freely open access to a variety of data resources in support of worldwide research activities in both academia and industry. All of these resources are publicly available and can be found at http://bigd.big.ac.cn. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  18. Big Java late objects

    CERN Document Server

    Horstmann, Cay S

    2012-01-01

    Big Java: Late Objects is a comprehensive introduction to Java and computer programming, which focuses on the principles of programming, software engineering, and effective learning. It is designed for a two-semester first course in programming for computer science students.

  19. Big ideas: innovation policy

    OpenAIRE

    John Van Reenen

    2011-01-01

    In the last CentrePiece, John Van Reenen stressed the importance of competition and labour market flexibility for productivity growth. His latest in CEP's 'big ideas' series describes the impact of research on how policy-makers can influence innovation more directly - through tax credits for business spending on research and development.

  20. Big Data ethics

    NARCIS (Netherlands)

    Zwitter, Andrej

    2014-01-01

    The speed of development in Big Data and associated phenomena, such as social media, has surpassed the capacity of the average consumer to understand his or her actions and their knock-on effects. We are moving towards changes in how ethics has to be perceived: away from individual decisions with

  1. Big data in history

    CERN Document Server

    Manning, Patrick

    2013-01-01

    Big Data in History introduces the project to create a world-historical archive, tracing the last four centuries of historical dynamics and change. Chapters address the archive's overall plan, how to interpret the past through a global archive, the missions of gathering records, linking local data into global patterns, and exploring the results.

  2. Moving Another Big Desk.

    Science.gov (United States)

    Fawcett, Gay

    1996-01-01

    New ways of thinking about leadership require that leaders move their big desks and establish environments that encourage trust and open communication. Educational leaders must trust their colleagues to make wise choices. When teachers are treated democratically as leaders, classrooms will also become democratic learning organizations. (SM)

  3. A Big Bang Lab

    Science.gov (United States)

    Scheider, Walter

    2005-01-01

    The February 2005 issue of The Science Teacher (TST) reminded everyone that by learning how scientists study stars, students gain an understanding of how science measures things that can not be set up in lab, either because they are too big, too far away, or happened in a very distant past. The authors of "How Far are the Stars?" show how the…

  4. New 'bigs' in cosmology

    International Nuclear Information System (INIS)

    Yurov, Artyom V.; Martin-Moruno, Prado; Gonzalez-Diaz, Pedro F.

    2006-01-01

    This paper contains a detailed discussion on new cosmic solutions describing the early and late evolution of a universe that is filled with a kind of dark energy that may or may not satisfy the energy conditions. The main distinctive property of the resulting space-times is that they make to appear twice the single singular events predicted by the corresponding quintessential (phantom) models in a manner which can be made symmetric with respect to the origin of cosmic time. Thus, big bang and big rip singularity are shown to take place twice, one on the positive branch of time and the other on the negative one. We have also considered dark energy and phantom energy accretion onto black holes and wormholes in the context of these new cosmic solutions. It is seen that the space-times of these holes would then undergo swelling processes leading to big trip and big hole events taking place on distinct epochs along the evolution of the universe. In this way, the possibility is considered that the past and future be connected in a non-paradoxical manner in the universes described by means of the new symmetric solutions

  5. The Big Bang

    CERN Multimedia

    Moods, Patrick

    2006-01-01

    How did the Universe begin? The favoured theory is that everything - space, time, matter - came into existence at the same moment, around 13.7 thousand million years ago. This event was scornfully referred to as the "Big Bang" by Sir Fred Hoyle, who did not believe in it and maintained that the Universe had always existed.

  6. Big Data Analytics

    Indian Academy of Sciences (India)

    The volume and variety of data being generated using computersis doubling every two years. It is estimated that in 2015,8 Zettabytes (Zetta=1021) were generated which consistedmostly of unstructured data such as emails, blogs, Twitter,Facebook posts, images, and videos. This is called big data. Itis possible to analyse ...

  7. Identifying Dwarfs Workloads in Big Data Analytics

    OpenAIRE

    Gao, Wanling; Luo, Chunjie; Zhan, Jianfeng; Ye, Hainan; He, Xiwen; Wang, Lei; Zhu, Yuqing; Tian, Xinhui

    2015-01-01

    Big data benchmarking is particularly important and provides applicable yardsticks for evaluating booming big data systems. However, wide coverage and great complexity of big data computing impose big challenges on big data benchmarking. How can we construct a benchmark suite using a minimum set of units of computation to represent diversity of big data analytics workloads? Big data dwarfs are abstractions of extracting frequently appearing operations in big data computing. One dwarf represen...

  8. Big Data and Chemical Education

    Science.gov (United States)

    Pence, Harry E.; Williams, Antony J.

    2016-01-01

    The amount of computerized information that organizations collect and process is growing so large that the term Big Data is commonly being used to describe the situation. Accordingly, Big Data is defined by a combination of the Volume, Variety, Velocity, and Veracity of the data being processed. Big Data tools are already having an impact in…

  9. Scaling Big Data Cleansing

    KAUST Repository

    Khayyat, Zuhair

    2017-07-31

    Data cleansing approaches have usually focused on detecting and fixing errors with little attention to big data scaling. This presents a serious impediment since identify- ing and repairing dirty data often involves processing huge input datasets, handling sophisticated error discovery approaches and managing huge arbitrary errors. With large datasets, error detection becomes overly expensive and complicated especially when considering user-defined functions. Furthermore, a distinctive algorithm is de- sired to optimize inequality joins in sophisticated error discovery rather than na ̈ıvely parallelizing them. Also, when repairing large errors, their skewed distribution may obstruct effective error repairs. In this dissertation, I present solutions to overcome the above three problems in scaling data cleansing. First, I present BigDansing as a general system to tackle efficiency, scalability, and ease-of-use issues in data cleansing for Big Data. It automatically parallelizes the user’s code on top of general-purpose distributed platforms. Its programming inter- face allows users to express data quality rules independently from the requirements of parallel and distributed environments. Without sacrificing their quality, BigDans- ing also enables parallel execution of serial repair algorithms by exploiting the graph representation of discovered errors. The experimental results show that BigDansing outperforms existing baselines up to more than two orders of magnitude. Although BigDansing scales cleansing jobs, it still lacks the ability to handle sophisticated error discovery requiring inequality joins. Therefore, I developed IEJoin as an algorithm for fast inequality joins. It is based on sorted arrays and space efficient bit-arrays to reduce the problem’s search space. By comparing IEJoin against well- known optimizations, I show that it is more scalable, and several orders of magnitude faster. BigDansing depends on vertex-centric graph systems, i.e., Pregel

  10. Big Data and Biomedical Informatics: A Challenging Opportunity

    Science.gov (United States)

    2014-01-01

    Summary Big data are receiving an increasing attention in biomedicine and healthcare. It is therefore important to understand the reason why big data are assuming a crucial role for the biomedical informatics community. The capability of handling big data is becoming an enabler to carry out unprecedented research studies and to implement new models of healthcare delivery. Therefore, it is first necessary to deeply understand the four elements that constitute big data, namely Volume, Variety, Velocity, and Veracity, and their meaning in practice. Then, it is mandatory to understand where big data are present, and where they can be beneficially collected. There are research fields, such as translational bioinformatics, which need to rely on big data technologies to withstand the shock wave of data that is generated every day. Other areas, ranging from epidemiology to clinical care, can benefit from the exploitation of the large amounts of data that are nowadays available, from personal monitoring to primary care. However, building big data-enabled systems carries on relevant implications in terms of reproducibility of research studies and management of privacy and data access; proper actions should be taken to deal with these issues. An interesting consequence of the big data scenario is the availability of new software, methods, and tools, such as map-reduce, cloud computing, and concept drift machine learning algorithms, which will not only contribute to big data research, but may be beneficial in many biomedical informatics applications. The way forward with the big data opportunity will require properly applied engineering principles to design studies and applications, to avoid preconceptions or over-enthusiasms, to fully exploit the available technologies, and to improve data processing and data management regulations. PMID:24853034

  11. Big data and biomedical informatics: a challenging opportunity.

    Science.gov (United States)

    Bellazzi, R

    2014-05-22

    Big data are receiving an increasing attention in biomedicine and healthcare. It is therefore important to understand the reason why big data are assuming a crucial role for the biomedical informatics community. The capability of handling big data is becoming an enabler to carry out unprecedented research studies and to implement new models of healthcare delivery. Therefore, it is first necessary to deeply understand the four elements that constitute big data, namely Volume, Variety, Velocity, and Veracity, and their meaning in practice. Then, it is mandatory to understand where big data are present, and where they can be beneficially collected. There are research fields, such as translational bioinformatics, which need to rely on big data technologies to withstand the shock wave of data that is generated every day. Other areas, ranging from epidemiology to clinical care, can benefit from the exploitation of the large amounts of data that are nowadays available, from personal monitoring to primary care. However, building big data-enabled systems carries on relevant implications in terms of reproducibility of research studies and management of privacy and data access; proper actions should be taken to deal with these issues. An interesting consequence of the big data scenario is the availability of new software, methods, and tools, such as map-reduce, cloud computing, and concept drift machine learning algorithms, which will not only contribute to big data research, but may be beneficial in many biomedical informatics applications. The way forward with the big data opportunity will require properly applied engineering principles to design studies and applications, to avoid preconceptions or over-enthusiasms, to fully exploit the available technologies, and to improve data processing and data management regulations.

  12. How Big Are "Martin's Big Words"? Thinking Big about the Future.

    Science.gov (United States)

    Gardner, Traci

    "Martin's Big Words: The Life of Dr. Martin Luther King, Jr." tells of King's childhood determination to use "big words" through biographical information and quotations. In this lesson, students in grades 3 to 5 explore information on Dr. King to think about his "big" words, then they write about their own…

  13. Aeolian nutrient fluxes following wildfire in sagebrush steppe: implications for soil carbon storage

    Directory of Open Access Journals (Sweden)

    N. J. Hasselquist

    2011-12-01

    Full Text Available Pulses of aeolian transport following fire can profoundly affect the biogeochemical cycling of nutrients in semi-arid and arid ecosystems. Our objective was to determine horizontal nutrient fluxes occurring in the saltation zone during an episodic pulse of aeolian transport that occurred following a wildfire in a semi-arid sagebrush steppe ecosystem in southern Idaho, USA. We also examined how temporal trends in nutrient fluxes were affected by changes in particle sizes of eroded mass as well as nutrient concentrations associated with different particle size classes. In the burned area, total carbon (C and nitrogen (N fluxes were as high as 235 g C m−1 d−1 and 19 g N m−1 d−1 during the first few months following fire, whereas C and N fluxes were negligible in an adjacent unburned area throughout the study. Temporal variation in C and N fluxes following fire was largely attributable to the redistribution of saltation-sized particles. Total N and organic C concentrations in the soil surface were significantly lower in the burned relative to the unburned area one year after fire. Our results show how an episodic pulse of aeolian transport following fire can affect the spatial distribution of soil C and N, which, in turn, can have important implications for soil C storage. These findings demonstrate how an ecological disturbance can exacerbate a geomorphic process and highlight the need for further research to better understand the role aeolian transport plays in the biogeochemical cycling of C and N in recently burned landscapes.

  14. Weak interspecific interactions in a sagebrush steppe? Conflicting evidence from observations and experiments.

    Science.gov (United States)

    Adler, Peter B; Kleinhesselink, Andrew; Giles, Hooker; Taylor, J Bret; Teller, Brittany; Ellner, Stephen P

    2018-04-28

    Stable coexistence requires intraspecific limitations to be stronger than interspecific limitations. The greater the difference between intra- and interspecific limitations, the more stable the coexistence, and the weaker the competitive release any species should experience following removal of competitors. We conducted a removal experiment to test whether a previously estimated model, showing surprisingly weak interspecific competition for four dominant species in a sagebrush steppe, accurately predicts competitive release. Our treatments were 1) removal of all perennial grasses and 2) removal of the dominant shrub, Artemisia tripartita. We regressed survival, growth and recruitment on the locations, sizes, and species identities of neighboring plants, along with an indicator variable for removal treatment. If our "baseline" regression model, which accounts for local plant-plant interactions, accurately explains the observed responses to removals, then the removal coefficient should be non-significant. For survival, the removal coefficients were never significantly different from zero, and only A. tripartita showed a (negative) response to removals at the recruitment stage. For growth, the removal treatment effect was significant and positive for two species, Poa secunda and Pseudoroegneria spicata, indicating that the baseline model underestimated interspecific competition. For all three grass species, population models based on the vital rate regressions that included removal effects projected 1.4 to 3-fold increases in equilibrium population size relative to the baseline model (no removal effects). However, we found no evidence of higher response to removal in quadrats with higher pretreatment cover of A. tripartita, or by plants experiencing higher pre-treatment crowding by A. tripartita, raising questions about the mechanisms driving the positive response to removal. While our results show the value of combining observations with a simple removal experiment

  15. Big Data-Survey

    Directory of Open Access Journals (Sweden)

    P.S.G. Aruna Sri

    2016-03-01

    Full Text Available Big data is the term for any gathering of information sets, so expensive and complex, that it gets to be hard to process for utilizing customary information handling applications. The difficulties incorporate investigation, catch, duration, inquiry, sharing, stockpiling, Exchange, perception, and protection infringement. To reduce spot business patterns, anticipate diseases, conflict etc., we require bigger data sets when compared with the smaller data sets. Enormous information is hard to work with utilizing most social database administration frameworks and desktop measurements and perception bundles, needing rather enormously parallel programming running on tens, hundreds, or even a large number of servers. In this paper there was an observation on Hadoop architecture, different tools used for big data and its security issues.

  16. Finding the big bang

    CERN Document Server

    Page, Lyman A; Partridge, R Bruce

    2009-01-01

    Cosmology, the study of the universe as a whole, has become a precise physical science, the foundation of which is our understanding of the cosmic microwave background radiation (CMBR) left from the big bang. The story of the discovery and exploration of the CMBR in the 1960s is recalled for the first time in this collection of 44 essays by eminent scientists who pioneered the work. Two introductory chapters put the essays in context, explaining the general ideas behind the expanding universe and fossil remnants from the early stages of the expanding universe. The last chapter describes how the confusion of ideas and measurements in the 1960s grew into the present tight network of tests that demonstrate the accuracy of the big bang theory. This book is valuable to anyone interested in how science is done, and what it has taught us about the large-scale nature of the physical universe.

  17. Big Data as Governmentality

    DEFF Research Database (Denmark)

    Flyverbom, Mikkel; Klinkby Madsen, Anders; Rasche, Andreas

    data is constituted as an aspiration to improve the data and knowledge underpinning development efforts. Based on this framework, we argue that big data’s impact on how relevant problems are governed is enabled by (1) new techniques of visualizing development issues, (2) linking aspects......This paper conceptualizes how large-scale data and algorithms condition and reshape knowledge production when addressing international development challenges. The concept of governmentality and four dimensions of an analytics of government are proposed as a theoretical framework to examine how big...... of international development agendas to algorithms that synthesize large-scale data, (3) novel ways of rationalizing knowledge claims that underlie development efforts, and (4) shifts in professional and organizational identities of those concerned with producing and processing data for development. Our discussion...

  18. Big nuclear accidents

    International Nuclear Information System (INIS)

    Marshall, W.; Billingon, D.E.; Cameron, R.F.; Curl, S.J.

    1983-09-01

    Much of the debate on the safety of nuclear power focuses on the large number of fatalities that could, in theory, be caused by extremely unlikely but just imaginable reactor accidents. This, along with the nuclear industry's inappropriate use of vocabulary during public debate, has given the general public a distorted impression of the risks of nuclear power. The paper reviews the way in which the probability and consequences of big nuclear accidents have been presented in the past and makes recommendations for the future, including the presentation of the long-term consequences of such accidents in terms of 'loss of life expectancy', 'increased chance of fatal cancer' and 'equivalent pattern of compulsory cigarette smoking'. The paper presents mathematical arguments, which show the derivation and validity of the proposed methods of presenting the consequences of imaginable big nuclear accidents. (author)

  19. Big Bounce and inhomogeneities

    International Nuclear Information System (INIS)

    Brizuela, David; Mena Marugan, Guillermo A; Pawlowski, Tomasz

    2010-01-01

    The dynamics of an inhomogeneous universe is studied with the methods of loop quantum cosmology, via a so-called hybrid quantization, as an example of the quantization of vacuum cosmological spacetimes containing gravitational waves (Gowdy spacetimes). The analysis of this model with an infinite number of degrees of freedom, performed at the effective level, shows that (i) the initial Big Bang singularity is replaced (as in the case of homogeneous cosmological models) by a Big Bounce, joining deterministically two large universes, (ii) the universe size at the bounce is at least of the same order of magnitude as that of the background homogeneous universe and (iii) for each gravitational wave mode, the difference in amplitude at very early and very late times has a vanishing statistical average when the bounce dynamics is strongly dominated by the inhomogeneities, whereas this average is positive when the dynamics is in a near-vacuum regime, so that statistically the inhomogeneities are amplified. (fast track communication)

  20. Big Data and reality

    Directory of Open Access Journals (Sweden)

    Ryan Shaw

    2015-11-01

    Full Text Available DNA sequencers, Twitter, MRIs, Facebook, particle accelerators, Google Books, radio telescopes, Tumblr: what do these things have in common? According to the evangelists of “data science,” all of these are instruments for observing reality at unprecedentedly large scales and fine granularities. This perspective ignores the social reality of these very different technological systems, ignoring how they are made, how they work, and what they mean in favor of an exclusive focus on what they generate: Big Data. But no data, big or small, can be interpreted without an understanding of the process that generated them. Statistical data science is applicable to systems that have been designed as scientific instruments, but is likely to lead to confusion when applied to systems that have not. In those cases, a historical inquiry is preferable.

  1. Really big numbers

    CERN Document Server

    Schwartz, Richard Evan

    2014-01-01

    In the American Mathematical Society's first-ever book for kids (and kids at heart), mathematician and author Richard Evan Schwartz leads math lovers of all ages on an innovative and strikingly illustrated journey through the infinite number system. By means of engaging, imaginative visuals and endearing narration, Schwartz manages the monumental task of presenting the complex concept of Big Numbers in fresh and relatable ways. The book begins with small, easily observable numbers before building up to truly gigantic ones, like a nonillion, a tredecillion, a googol, and even ones too huge for names! Any person, regardless of age, can benefit from reading this book. Readers will find themselves returning to its pages for a very long time, perpetually learning from and growing with the narrative as their knowledge deepens. Really Big Numbers is a wonderful enrichment for any math education program and is enthusiastically recommended to every teacher, parent and grandparent, student, child, or other individual i...

  2. Big Bang Circus

    Science.gov (United States)

    Ambrosini, C.

    2011-06-01

    Big Bang Circus is an opera I composed in 2001 and which was premiered at the Venice Biennale Contemporary Music Festival in 2002. A chamber group, four singers and a ringmaster stage the story of the Universe confronting and interweaving two threads: how early man imagined it and how scientists described it. Surprisingly enough fancy, myths and scientific explanations often end up using the same images, metaphors and sometimes even words: a strong tension, a drumskin starting to vibrate, a shout…

  3. Big Bang 5

    CERN Document Server

    Apolin, Martin

    2007-01-01

    Physik soll verständlich sein und Spaß machen! Deshalb beginnt jedes Kapitel in Big Bang mit einem motivierenden Überblick und Fragestellungen und geht dann von den Grundlagen zu den Anwendungen, vom Einfachen zum Komplizierten. Dabei bleibt die Sprache einfach, alltagsorientiert und belletristisch. Der Band 5 RG behandelt die Grundlagen (Maßsystem, Größenordnungen) und die Mechanik (Translation, Rotation, Kraft, Erhaltungssätze).

  4. Big Bang 8

    CERN Document Server

    Apolin, Martin

    2008-01-01

    Physik soll verständlich sein und Spaß machen! Deshalb beginnt jedes Kapitel in Big Bang mit einem motivierenden Überblick und Fragestellungen und geht dann von den Grundlagen zu den Anwendungen, vom Einfachen zum Komplizierten. Dabei bleibt die Sprache einfach, alltagsorientiert und belletristisch. Band 8 vermittelt auf verständliche Weise Relativitätstheorie, Kern- und Teilchenphysik (und deren Anwendungen in der Kosmologie und Astrophysik), Nanotechnologie sowie Bionik.

  5. Big Bang 6

    CERN Document Server

    Apolin, Martin

    2008-01-01

    Physik soll verständlich sein und Spaß machen! Deshalb beginnt jedes Kapitel in Big Bang mit einem motivierenden Überblick und Fragestellungen und geht dann von den Grundlagen zu den Anwendungen, vom Einfachen zum Komplizierten. Dabei bleibt die Sprache einfach, alltagsorientiert und belletristisch. Der Band 6 RG behandelt die Gravitation, Schwingungen und Wellen, Thermodynamik und eine Einführung in die Elektrizität anhand von Alltagsbeispielen und Querverbindungen zu anderen Disziplinen.

  6. Big Bang 7

    CERN Document Server

    Apolin, Martin

    2008-01-01

    Physik soll verständlich sein und Spaß machen! Deshalb beginnt jedes Kapitel in Big Bang mit einem motivierenden Überblick und Fragestellungen und geht dann von den Grundlagen zu den Anwendungen, vom Einfachen zum Komplizierten. Dabei bleibt die Sprache einfach, alltagsorientiert und belletristisch. In Band 7 werden neben einer Einführung auch viele aktuelle Aspekte von Quantenmechanik (z. Beamen) und Elektrodynamik (zB Elektrosmog), sowie die Klimaproblematik und die Chaostheorie behandelt.

  7. Big Bang Darkleosynthesis

    OpenAIRE

    Krnjaic, Gordan; Sigurdson, Kris

    2014-01-01

    In a popular class of models, dark matter comprises an asymmetric population of composite particles with short range interactions arising from a confined nonabelian gauge group. We show that coupling this sector to a well-motivated light mediator particle yields efficient darkleosynthesis , a dark-sector version of big-bang nucleosynthesis (BBN), in generic regions of parameter space. Dark matter self-interaction bounds typically require the confinement scale to be above ΛQCD , which generica...

  8. Big³. Editorial.

    Science.gov (United States)

    Lehmann, C U; Séroussi, B; Jaulent, M-C

    2014-05-22

    To provide an editorial introduction into the 2014 IMIA Yearbook of Medical Informatics with an overview of the content, the new publishing scheme, and upcoming 25th anniversary. A brief overview of the 2014 special topic, Big Data - Smart Health Strategies, and an outline of the novel publishing model is provided in conjunction with a call for proposals to celebrate the 25th anniversary of the Yearbook. 'Big Data' has become the latest buzzword in informatics and promise new approaches and interventions that can improve health, well-being, and quality of life. This edition of the Yearbook acknowledges the fact that we just started to explore the opportunities that 'Big Data' will bring. However, it will become apparent to the reader that its pervasive nature has invaded all aspects of biomedical informatics - some to a higher degree than others. It was our goal to provide a comprehensive view at the state of 'Big Data' today, explore its strengths and weaknesses, as well as its risks, discuss emerging trends, tools, and applications, and stimulate the development of the field through the aggregation of excellent survey papers and working group contributions to the topic. For the first time in history will the IMIA Yearbook be published in an open access online format allowing a broader readership especially in resource poor countries. For the first time, thanks to the online format, will the IMIA Yearbook be published twice in the year, with two different tracks of papers. We anticipate that the important role of the IMIA yearbook will further increase with these changes just in time for its 25th anniversary in 2016.

  9. Recent big flare

    International Nuclear Information System (INIS)

    Moriyama, Fumio; Miyazawa, Masahide; Yamaguchi, Yoshisuke

    1978-01-01

    The features of three big solar flares observed at Tokyo Observatory are described in this paper. The active region, McMath 14943, caused a big flare on September 16, 1977. The flare appeared on both sides of a long dark line which runs along the boundary of the magnetic field. Two-ribbon structure was seen. The electron density of the flare observed at Norikura Corona Observatory was 3 x 10 12 /cc. Several arc lines which connect both bright regions of different magnetic polarity were seen in H-α monochrome image. The active region, McMath 15056, caused a big flare on December 10, 1977. At the beginning, several bright spots were observed in the region between two main solar spots. Then, the area and the brightness increased, and the bright spots became two ribbon-shaped bands. A solar flare was observed on April 8, 1978. At first, several bright spots were seen around the solar spot in the active region, McMath 15221. Then, these bright spots developed to a large bright region. On both sides of a dark line along the magnetic neutral line, bright regions were generated. These developed to a two-ribbon flare. The time required for growth was more than one hour. A bright arc which connects two ribbons was seen, and this arc may be a loop prominence system. (Kato, T.)

  10. Big Data Technologies

    Science.gov (United States)

    Bellazzi, Riccardo; Dagliati, Arianna; Sacchi, Lucia; Segagni, Daniele

    2015-01-01

    The so-called big data revolution provides substantial opportunities to diabetes management. At least 3 important directions are currently of great interest. First, the integration of different sources of information, from primary and secondary care to administrative information, may allow depicting a novel view of patient’s care processes and of single patient’s behaviors, taking into account the multifaceted nature of chronic care. Second, the availability of novel diabetes technologies, able to gather large amounts of real-time data, requires the implementation of distributed platforms for data analysis and decision support. Finally, the inclusion of geographical and environmental information into such complex IT systems may further increase the capability of interpreting the data gathered and extract new knowledge from them. This article reviews the main concepts and definitions related to big data, it presents some efforts in health care, and discusses the potential role of big data in diabetes care. Finally, as an example, it describes the research efforts carried on in the MOSAIC project, funded by the European Commission. PMID:25910540

  11. [Structural Change, Contextuality, and Transfer in Health Promotion--Sustainable Implementation of the BIG Project].

    Science.gov (United States)

    Rütten, A; Frahsa, A; Rosenhäger, N; Wolff, A

    2015-09-01

    The BIG approach aims at promoting physical activity and health among socially disadvantaged women. BIG has been developed and sustainably implemented in Erlangen/Bavaria. Subsequently, it has been transferred to other communities and states in Germany. Crucial factors for sustainability and transfer in BIG are (1) lifestyle and policy analysis, (2) assets approach, (3) empowerment of target group, (4) enabling of policy-makers and professionals. © Georg Thieme Verlag KG Stuttgart · New York.

  12. EKALAVYA MODEL OF HIGHER EDUCATION – AN INNOVATION OF IBM’S BIG DATA UNIVERSITY

    OpenAIRE

    Dr. P. S. Aithal; Shubhrajyotsna Aithal

    2016-01-01

    Big Data Science is a new multi-disciplinary subject in the society, comprising of business intelligence, data analytics, and the related fields have become increasingly important in both the academic and the business communities during the 21st century. Many organizations and business intelligence experts have foreseen the significant development in the big data field as next big wave in future research arena in many industry sectors and the society. To become an expert and skilled in this n...

  13. Big Data in the Earth Observing System Data and Information System

    Science.gov (United States)

    Lynnes, Chris; Baynes, Katie; McInerney, Mark

    2016-01-01

    Approaches that are being pursued for the Earth Observing System Data and Information System (EOSDIS) data system to address the challenges of Big Data were presented to the NASA Big Data Task Force. Cloud prototypes are underway to tackle the volume challenge of Big Data. However, advances in computer hardware or cloud won't help (much) with variety. Rather, interoperability standards, conventions, and community engagement are the key to addressing variety.

  14. Machine learning for Big Data analytics in plants.

    Science.gov (United States)

    Ma, Chuang; Zhang, Hao Helen; Wang, Xiangfeng

    2014-12-01

    Rapid advances in high-throughput genomic technology have enabled biology to enter the era of 'Big Data' (large datasets). The plant science community not only needs to build its own Big-Data-compatible parallel computing and data management infrastructures, but also to seek novel analytical paradigms to extract information from the overwhelming amounts of data. Machine learning offers promising computational and analytical solutions for the integrative analysis of large, heterogeneous and unstructured datasets on the Big-Data scale, and is gradually gaining popularity in biology. This review introduces the basic concepts and procedures of machine-learning applications and envisages how machine learning could interface with Big Data technology to facilitate basic research and biotechnology in the plant sciences. Copyright © 2014 Elsevier Ltd. All rights reserved.

  15. Some experiences and opportunities for big data in translational research.

    Science.gov (United States)

    Chute, Christopher G; Ullman-Cullere, Mollie; Wood, Grant M; Lin, Simon M; He, Min; Pathak, Jyotishman

    2013-10-01

    Health care has become increasingly information intensive. The advent of genomic data, integrated into patient care, significantly accelerates the complexity and amount of clinical data. Translational research in the present day increasingly embraces new biomedical discovery in this data-intensive world, thus entering the domain of "big data." The Electronic Medical Records and Genomics consortium has taught us many lessons, while simultaneously advances in commodity computing methods enable the academic community to affordably manage and process big data. Although great promise can emerge from the adoption of big data methods and philosophy, the heterogeneity and complexity of clinical data, in particular, pose additional challenges for big data inferencing and clinical application. However, the ultimate comparability and consistency of heterogeneous clinical information sources can be enhanced by existing and emerging data standards, which promise to bring order to clinical data chaos. Meaningful Use data standards in particular have already simplified the task of identifying clinical phenotyping patterns in electronic health records.

  16. Big bang and big crunch in matrix string theory

    OpenAIRE

    Bedford, J; Papageorgakis, C; Rodríguez-Gómez, D; Ward, J

    2007-01-01

    Following the holographic description of linear dilaton null Cosmologies with a Big Bang in terms of Matrix String Theory put forward by Craps, Sethi and Verlinde, we propose an extended background describing a Universe including both Big Bang and Big Crunch singularities. This belongs to a class of exact string backgrounds and is perturbative in the string coupling far away from the singularities, both of which can be resolved using Matrix String Theory. We provide a simple theory capable of...

  17. Disaggregating asthma: Big investigation versus big data.

    Science.gov (United States)

    Belgrave, Danielle; Henderson, John; Simpson, Angela; Buchan, Iain; Bishop, Christopher; Custovic, Adnan

    2017-02-01

    We are facing a major challenge in bridging the gap between identifying subtypes of asthma to understand causal mechanisms and translating this knowledge into personalized prevention and management strategies. In recent years, "big data" has been sold as a panacea for generating hypotheses and driving new frontiers of health care; the idea that the data must and will speak for themselves is fast becoming a new dogma. One of the dangers of ready accessibility of health care data and computational tools for data analysis is that the process of data mining can become uncoupled from the scientific process of clinical interpretation, understanding the provenance of the data, and external validation. Although advances in computational methods can be valuable for using unexpected structure in data to generate hypotheses, there remains a need for testing hypotheses and interpreting results with scientific rigor. We argue for combining data- and hypothesis-driven methods in a careful synergy, and the importance of carefully characterized birth and patient cohorts with genetic, phenotypic, biological, and molecular data in this process cannot be overemphasized. The main challenge on the road ahead is to harness bigger health care data in ways that produce meaningful clinical interpretation and to translate this into better diagnoses and properly personalized prevention and treatment plans. There is a pressing need for cross-disciplinary research with an integrative approach to data science, whereby basic scientists, clinicians, data analysts, and epidemiologists work together to understand the heterogeneity of asthma. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  18. Big data and educational research

    OpenAIRE

    Beneito-Montagut, Roser

    2017-01-01

    Big data and data analytics offer the promise to enhance teaching and learning, improve educational research and progress education governance. This chapter aims to contribute to the conceptual and methodological understanding of big data and analytics within educational research. It describes the opportunities and challenges that big data and analytics bring to education as well as critically explore the perils of applying a data driven approach to education. Despite the claimed value of the...

  19. The trashing of Big Green

    International Nuclear Information System (INIS)

    Felten, E.

    1990-01-01

    The Big Green initiative on California's ballot lost by a margin of 2-to-1. Green measures lost in five other states, shocking ecology-minded groups. According to the postmortem by environmentalists, Big Green was a victim of poor timing and big spending by the opposition. Now its supporters plan to break up the bill and try to pass some provisions in the Legislature

  20. Big data in fashion industry

    Science.gov (United States)

    Jain, S.; Bruniaux, J.; Zeng, X.; Bruniaux, P.

    2017-10-01

    Significant work has been done in the field of big data in last decade. The concept of big data includes analysing voluminous data to extract valuable information. In the fashion world, big data is increasingly playing a part in trend forecasting, analysing consumer behaviour, preference and emotions. The purpose of this paper is to introduce the term fashion data and why it can be considered as big data. It also gives a broad classification of the types of fashion data and briefly defines them. Also, the methodology and working of a system that will use this data is briefly described.

  1. Big Data Analytics An Overview

    Directory of Open Access Journals (Sweden)

    Jayshree Dwivedi

    2015-08-01

    Full Text Available Big data is a data beyond the storage capacity and beyond the processing power is called big data. Big data term is used for data sets its so large or complex that traditional data it involves data sets with sizes. Big data size is a constantly moving target year by year ranging from a few dozen terabytes to many petabytes of data means like social networking sites the amount of data produced by people is growing rapidly every year. Big data is not only a data rather it become a complete subject which includes various tools techniques and framework. It defines the epidemic possibility and evolvement of data both structured and unstructured. Big data is a set of techniques and technologies that require new forms of assimilate to uncover large hidden values from large datasets that are diverse complex and of a massive scale. It is difficult to work with using most relational database management systems and desktop statistics and visualization packages exacting preferably massively parallel software running on tens hundreds or even thousands of servers. Big data environment is used to grab organize and resolve the various types of data. In this paper we describe applications problems and tools of big data and gives overview of big data.

  2. Was there a big bang

    International Nuclear Information System (INIS)

    Narlikar, J.

    1981-01-01

    In discussing the viability of the big-bang model of the Universe relative evidence is examined including the discrepancies in the age of the big-bang Universe, the red shifts of quasars, the microwave background radiation, general theory of relativity aspects such as the change of the gravitational constant with time, and quantum theory considerations. It is felt that the arguments considered show that the big-bang picture is not as soundly established, either theoretically or observationally, as it is usually claimed to be, that the cosmological problem is still wide open and alternatives to the standard big-bang picture should be seriously investigated. (U.K.)

  3. Big questions, big science: meeting the challenges of global ecology.

    Science.gov (United States)

    Schimel, David; Keller, Michael

    2015-04-01

    Ecologists are increasingly tackling questions that require significant infrastucture, large experiments, networks of observations, and complex data and computation. Key hypotheses in ecology increasingly require more investment, and larger data sets to be tested than can be collected by a single investigator's or s group of investigator's labs, sustained for longer than a typical grant. Large-scale projects are expensive, so their scientific return on the investment has to justify the opportunity cost-the science foregone because resources were expended on a large project rather than supporting a number of individual projects. In addition, their management must be accountable and efficient in the use of significant resources, requiring the use of formal systems engineering and project management to mitigate risk of failure. Mapping the scientific method into formal project management requires both scientists able to work in the context, and a project implementation team sensitive to the unique requirements of ecology. Sponsoring agencies, under pressure from external and internal forces, experience many pressures that push them towards counterproductive project management but a scientific community aware and experienced in large project science can mitigate these tendencies. For big ecology to result in great science, ecologists must become informed, aware and engaged in the advocacy and governance of large ecological projects.

  4. How Big is Earth?

    Science.gov (United States)

    Thurber, Bonnie B.

    2015-08-01

    How Big is Earth celebrates the Year of Light. Using only the sunlight striking the Earth and a wooden dowel, students meet each other and then measure the circumference of the earth. Eratosthenes did it over 2,000 years ago. In Cosmos, Carl Sagan shared the process by which Eratosthenes measured the angle of the shadow cast at local noon when sunlight strikes a stick positioned perpendicular to the ground. By comparing his measurement to another made a distance away, Eratosthenes was able to calculate the circumference of the earth. How Big is Earth provides an online learning environment where students do science the same way Eratosthenes did. A notable project in which this was done was The Eratosthenes Project, conducted in 2005 as part of the World Year of Physics; in fact, we will be drawing on the teacher's guide developed by that project.How Big Is Earth? expands on the Eratosthenes project by providing an online learning environment provided by the iCollaboratory, www.icollaboratory.org, where teachers and students from Sweden, China, Nepal, Russia, Morocco, and the United States collaborate, share data, and reflect on their learning of science and astronomy. They are sharing their information and discussing their ideas/brainstorming the solutions in a discussion forum. There is an ongoing database of student measurements and another database to collect data on both teacher and student learning from surveys, discussions, and self-reflection done online.We will share our research about the kinds of learning that takes place only in global collaborations.The entrance address for the iCollaboratory is http://www.icollaboratory.org.

  5. Privacy and Big Data

    CERN Document Server

    Craig, Terence

    2011-01-01

    Much of what constitutes Big Data is information about us. Through our online activities, we leave an easy-to-follow trail of digital footprints that reveal who we are, what we buy, where we go, and much more. This eye-opening book explores the raging privacy debate over the use of personal data, with one undeniable conclusion: once data's been collected, we have absolutely no control over who uses it or how it is used. Personal data is the hottest commodity on the market today-truly more valuable than gold. We are the asset that every company, industry, non-profit, and government wants. Pri

  6. Visualizing big energy data

    DEFF Research Database (Denmark)

    Hyndman, Rob J.; Liu, Xueqin Amy; Pinson, Pierre

    2018-01-01

    Visualization is a crucial component of data analysis. It is always a good idea to plot the data before fitting models, making predictions, or drawing conclusions. As sensors of the electric grid are collecting large volumes of data from various sources, power industry professionals are facing th...... the challenge of visualizing such data in a timely fashion. In this article, we demonstrate several data-visualization solutions for big energy data through three case studies involving smart-meter data, phasor measurement unit (PMU) data, and probabilistic forecasts, respectively....

  7. Big Data Challenges

    Directory of Open Access Journals (Sweden)

    Alexandru Adrian TOLE

    2013-10-01

    Full Text Available The amount of data that is traveling across the internet today, not only that is large, but is complex as well. Companies, institutions, healthcare system etc., all of them use piles of data which are further used for creating reports in order to ensure continuity regarding the services that they have to offer. The process behind the results that these entities requests represents a challenge for software developers and companies that provide IT infrastructure. The challenge is how to manipulate an impressive volume of data that has to be securely delivered through the internet and reach its destination intact. This paper treats the challenges that Big Data creates.

  8. Big data naturally rescaled

    International Nuclear Information System (INIS)

    Stoop, Ruedi; Kanders, Karlis; Lorimer, Tom; Held, Jenny; Albert, Carlo

    2016-01-01

    We propose that a handle could be put on big data by looking at the systems that actually generate the data, rather than the data itself, realizing that there may be only few generic processes involved in this, each one imprinting its very specific structures in the space of systems, the traces of which translate into feature space. From this, we propose a practical computational clustering approach, optimized for coping with such data, inspired by how the human cortex is known to approach the problem.

  9. A Matrix Big Bang

    OpenAIRE

    Craps, Ben; Sethi, Savdeep; Verlinde, Erik

    2005-01-01

    The light-like linear dilaton background represents a particularly simple time-dependent 1/2 BPS solution of critical type IIA superstring theory in ten dimensions. Its lift to M-theory, as well as its Einstein frame metric, are singular in the sense that the geometry is geodesically incomplete and the Riemann tensor diverges along a light-like subspace of codimension one. We study this background as a model for a big bang type singularity in string theory/M-theory. We construct the dual Matr...

  10. Using resistance and resilience concepts to reduce impacts of annual grasses and altered fire regimes on the sagebrush ecosystem and sage-grouse- A strategic multi-scale approach

    Science.gov (United States)

    Chambers, Jeanne C.; Pyke, David A.; Maestas, Jeremy D.; Boyd, Chad S.; Campbell, Steve; Espinosa, Shawn; Havlina, Doug; Mayer, Kenneth F.; Wuenschel, Amarina

    2014-01-01

    This Report provides a strategic approach for conservation of sagebrush ecosystems and Greater Sage- Grouse (sage-grouse) that focuses specifically on habitat threats caused by invasive annual grasses and altered fire regimes. It uses information on factors that influence (1) sagebrush ecosystem resilience to disturbance and resistance to invasive annual grasses and (2) distribution, relative abundance, and persistence of sage-grouse populations to develop management strategies at both landscape and site scales. A sage-grouse habitat matrix links relative resilience and resistance of sagebrush ecosystems with sage-grouse habitat requirements for landscape cover of sagebrush to help decision makers assess risks and determine appropriate management strategies at landscape scales. Focal areas for management are assessed by overlaying matrix components with sage-grouse Priority Areas for Conservation (PACs), breeding bird densities, and specific habitat threats. Decision tools are discussed for determining the suitability of focal areas for treatment and the most appropriate management treatments.

  11. BIG Data - BIG Gains? Understanding the Link Between Big Data Analytics and Innovation

    OpenAIRE

    Niebel, Thomas; Rasel, Fabienne; Viete, Steffen

    2017-01-01

    This paper analyzes the relationship between firms’ use of big data analytics and their innovative performance for product innovations. Since big data technologies provide new data information practices, they create new decision-making possibilities, which firms can use to realize innovations. Applying German firm-level data we find suggestive evidence that big data analytics matters for the likelihood of becoming a product innovator as well as the market success of the firms’ product innovat...

  12. BIG data - BIG gains? Empirical evidence on the link between big data analytics and innovation

    OpenAIRE

    Niebel, Thomas; Rasel, Fabienne; Viete, Steffen

    2017-01-01

    This paper analyzes the relationship between firms’ use of big data analytics and their innovative performance in terms of product innovations. Since big data technologies provide new data information practices, they create novel decision-making possibilities, which are widely believed to support firms’ innovation process. Applying German firm-level data within a knowledge production function framework we find suggestive evidence that big data analytics is a relevant determinant for the likel...

  13. Science framework for conservation and restoration of the sagebrush biome: Linking the Department of the Interior’s Integrated Rangeland Fire Management Strategy to long-term strategic conservation actions, Part 1. Science basis and applications

    Science.gov (United States)

    Chambers, Jeanne C.; Beck, Jeffrey L.; Bradford, John B.; Bybee, Jared; Campbell, Steve; Carlson, John; Christiansen, Thomas J; Clause, Karen J.; Collins, Gail; Crist, Michele R.; Dinkins, Jonathan B.; Doherty, Kevin E.; Edwards, Fred; Espinosa, Shawn; Griffin, Kathleen A.; Griffin, Paul; Haas, Jessica R.; Hanser, Steven E.; Havlina, Douglas W.; Henke, Kenneth F.; Hennig, Jacob D.; Joyce, Linda A; Kilkenny, Francis F.; Kulpa, Sarah M; Kurth, Laurie L; Maestas, Jeremy D; Manning, Mary E.; Mayer, Kenneth E.; Mealor, Brian A.; McCarthy, Clinton; Pellant, Mike; Perea, Marco A.; Prentice, Karen L.; Pyke, David A.; Wiechman , Lief A.; Wuenschel, Amarina

    2017-01-01

    The Science Framework is intended to link the Department of the Interior’s Integrated Rangeland Fire Management Strategy with long-term strategic conservation actions in the sagebrush biome. The Science Framework provides a multiscale approach for prioritizing areas for management and determining effective management strategies within the sagebrush biome. The emphasis is on sagebrush (Artemisia spp.) ecosystems and Greater sage-grouse (Centrocercus urophasianus). The approach provided in the Science Framework links sagebrush ecosystem resilience to disturbance and resistance to nonnative, invasive plant species to species habitat information based on the distribution and abundance of focal species. A geospatial process is presented that overlays information on ecosystem resilience and resistance, species habitats, and predominant threats and that can be used at the mid-scale to prioritize areas for management. A resilience and resistance habitat matrix is provided that can help decisionmakers evaluate risks and determine appropriate management strategies. Prioritized areas and management strategies can be refined by managers and stakeholders at the local scale based on higher resolution data and local knowledge. Decision tools are discussed for determining appropriate management actions for areas that are prioritized for management. Geospatial data, maps, and models are provided through the U.S. Geological Survey (USGS) ScienceBase and Bureau of Land Management (BLM) Landscape Approach Data Portal. The Science Framework is intended to be adaptive and will be updated as additional data become available on other values and species at risk. It is anticipated that the Science Framework will be widely used to: (1) inform emerging strategies to conserve sagebrush ecosystems, sagebrush dependent species, and human uses of the sagebrush system, and (2) assist managers in prioritizing and planning on-the-ground restoration and mitigation actions across the sagebrush biome.

  14. [Big data in imaging].

    Science.gov (United States)

    Sewerin, Philipp; Ostendorf, Benedikt; Hueber, Axel J; Kleyer, Arnd

    2018-04-01

    Until now, most major medical advancements have been achieved through hypothesis-driven research within the scope of clinical trials. However, due to a multitude of variables, only a certain number of research questions could be addressed during a single study, thus rendering these studies expensive and time consuming. Big data acquisition enables a new data-based approach in which large volumes of data can be used to investigate all variables, thus opening new horizons. Due to universal digitalization of the data as well as ever-improving hard- and software solutions, imaging would appear to be predestined for such analyses. Several small studies have already demonstrated that automated analysis algorithms and artificial intelligence can identify pathologies with high precision. Such automated systems would also seem well suited for rheumatology imaging, since a method for individualized risk stratification has long been sought for these patients. However, despite all the promising options, the heterogeneity of the data and highly complex regulations covering data protection in Germany would still render a big data solution for imaging difficult today. Overcoming these boundaries is challenging, but the enormous potential advances in clinical management and science render pursuit of this goal worthwhile.

  15. Big bang nucleosynthesis

    International Nuclear Information System (INIS)

    Fields, Brian D.; Olive, Keith A.

    2006-01-01

    We present an overview of the standard model of big bang nucleosynthesis (BBN), which describes the production of the light elements in the early universe. The theoretical prediction for the abundances of D, 3 He, 4 He, and 7 Li is discussed. We emphasize the role of key nuclear reactions and the methods by which experimental cross section uncertainties are propagated into uncertainties in the predicted abundances. The observational determination of the light nuclides is also discussed. Particular attention is given to the comparison between the predicted and observed abundances, which yields a measurement of the cosmic baryon content. The spectrum of anisotropies in the cosmic microwave background (CMB) now independently measures the baryon density to high precision; we show how the CMB data test BBN, and find that the CMB and the D and 4 He observations paint a consistent picture. This concordance stands as a major success of the hot big bang. On the other hand, 7 Li remains discrepant with the CMB-preferred baryon density; possible explanations are reviewed. Finally, moving beyond the standard model, primordial nucleosynthesis constraints on early universe and particle physics are also briefly discussed

  16. Nursing Needs Big Data and Big Data Needs Nursing.

    Science.gov (United States)

    Brennan, Patricia Flatley; Bakken, Suzanne

    2015-09-01

    Contemporary big data initiatives in health care will benefit from greater integration with nursing science and nursing practice; in turn, nursing science and nursing practice has much to gain from the data science initiatives. Big data arises secondary to scholarly inquiry (e.g., -omics) and everyday observations like cardiac flow sensors or Twitter feeds. Data science methods that are emerging ensure that these data be leveraged to improve patient care. Big data encompasses data that exceed human comprehension, that exist at a volume unmanageable by standard computer systems, that arrive at a velocity not under the control of the investigator and possess a level of imprecision not found in traditional inquiry. Data science methods are emerging to manage and gain insights from big data. The primary methods included investigation of emerging federal big data initiatives, and exploration of exemplars from nursing informatics research to benchmark where nursing is already poised to participate in the big data revolution. We provide observations and reflections on experiences in the emerging big data initiatives. Existing approaches to large data set analysis provide a necessary but not sufficient foundation for nursing to participate in the big data revolution. Nursing's Social Policy Statement guides a principled, ethical perspective on big data and data science. There are implications for basic and advanced practice clinical nurses in practice, for the nurse scientist who collaborates with data scientists, and for the nurse data scientist. Big data and data science has the potential to provide greater richness in understanding patient phenomena and in tailoring interventional strategies that are personalized to the patient. © 2015 Sigma Theta Tau International.

  17. Some big ideas for some big problems.

    Science.gov (United States)

    Winter, D D

    2000-05-01

    Although most psychologists do not see sustainability as a psychological problem, our environmental predicament is caused largely by human behaviors, accompanied by relevant thoughts, feelings, attitudes, and values. The huge task of building sustainable cultures will require a great many psychologists from a variety of backgrounds. In an effort to stimulate the imaginations of a wide spectrum of psychologists to take on the crucial problem of sustainability, this article discusses 4 psychological approaches (neo-analytic, behavioral, social, and cognitive) and outlines some of their insights into environmentally relevant behavior. These models are useful for illuminating ways to increase environmentally responsible behaviors of clients, communities, and professional associations.

  18. Was the big bang hot

    International Nuclear Information System (INIS)

    Wright, E.L.

    1983-01-01

    The author considers experiments to confirm the substantial deviations from a Planck curve in the Woody and Richards spectrum of the microwave background, and search for conducting needles in our galaxy. Spectral deviations and needle-shaped grains are expected for a cold Big Bang, but are not required by a hot Big Bang. (Auth.)

  19. Ethische aspecten van big data

    NARCIS (Netherlands)

    N. (Niek) van Antwerpen; Klaas Jan Mollema

    2017-01-01

    Big data heeft niet alleen geleid tot uitdagende technische vraagstukken, ook gaat het gepaard met allerlei nieuwe ethische en morele kwesties. Om verantwoord met big data om te gaan, moet ook over deze kwesties worden nagedacht. Want slecht datagebruik kan nadelige gevolgen hebben voor

  20. Fremtidens landbrug bliver big business

    DEFF Research Database (Denmark)

    Hansen, Henning Otte

    2016-01-01

    Landbrugets omverdensforhold og konkurrencevilkår ændres, og det vil nødvendiggøre en udvikling i retning af “big business“, hvor landbrugene bliver endnu større, mere industrialiserede og koncentrerede. Big business bliver en dominerende udvikling i dansk landbrug - men ikke den eneste...

  1. Human factors in Big Data

    NARCIS (Netherlands)

    Boer, J. de

    2016-01-01

    Since 2014 I am involved in various (research) projects that try to make the hype around Big Data more concrete and tangible for the industry and government. Big Data is about multiple sources of (real-time) data that can be analysed, transformed to information and be used to make 'smart' decisions.

  2. Passport to the Big Bang

    CERN Multimedia

    De Melis, Cinzia

    2013-01-01

    Le 2 juin 2013, le CERN inaugure le projet Passeport Big Bang lors d'un grand événement public. Affiche et programme. On 2 June 2013 CERN launches a scientific tourist trail through the Pays de Gex and the Canton of Geneva known as the Passport to the Big Bang. Poster and Programme.

  3. Evolution of the Air Toxics under the Big Sky Program

    Science.gov (United States)

    Marra, Nancy; Vanek, Diana; Hester, Carolyn; Holian, Andrij; Ward, Tony; Adams, Earle; Knuth, Randy

    2011-01-01

    As a yearlong exploration of air quality and its relation to respiratory health, the "Air Toxics Under the Big Sky" program offers opportunities for students to learn and apply science process skills through self-designed inquiry-based research projects conducted within their communities. The program follows a systematic scope and sequence…

  4. NASA EOSDIS Evolution in the BigData Era

    Science.gov (United States)

    Lynnes, Christopher

    2015-01-01

    NASA's EOSDIS system faces several challenges in the Big Data Era. Although volumes are large (but not unmanageably so), the variety of different data collections is daunting. That variety also brings with it a large and diverse user community. One key evolution EOSDIS is working toward is to enable more science analysis to be performed close to the data.

  5. The Big Bang: UK Young Scientists' and Engineers' Fair 2010

    Science.gov (United States)

    Allison, Simon

    2010-01-01

    The Big Bang: UK Young Scientists' and Engineers' Fair is an annual three-day event designed to promote science, technology, engineering and maths (STEM) careers to young people aged 7-19 through experiential learning. It is supported by stakeholders from business and industry, government and the community, and brings together people from various…

  6. The Meaningful Use of Big Data: Four Perspectives - Four Challenges

    NARCIS (Netherlands)

    C. Bizer; P.A. Boncz (Peter); M Brodie; O. Erling (Orri)

    2011-01-01

    textabstractTwenty-five Semantic Web and Database researchers met at the 2011 STI Semantic Summit in Riga, Latvia July 6-8, 2011 to discuss the opportunities and challenges posed by Big Data for the Semantic Web, Semantic Technologies, and Database communities. The unanimous conclusion was that the

  7. Addressing big data challenges for scientific data infrastructure

    NARCIS (Netherlands)

    Demchenko, Y.; Zhao, Z.; Grosso, P.; Wibisono, A.; de Laat, C.

    2012-01-01

    This paper discusses the challenges that are imposed by Big Data Science on the modern and future Scientific Data Infrastructure (SDI). The paper refers to different scientific communities to define requirements on data management, access control and security. The paper introduces the Scientific

  8. Applications of Big Data in Education

    OpenAIRE

    Faisal Kalota

    2015-01-01

    Big Data and analytics have gained a huge momentum in recent years. Big Data feeds into the field of Learning Analytics (LA) that may allow academic institutions to better understand the learners' needs and proactively address them. Hence, it is important to have an understanding of Big Data and its applications. The purpose of this descriptive paper is to provide an overview of Big Data, the technologies used in Big Data, and some of the applications of Big Data in educa...

  9. Exploring complex and big data

    Directory of Open Access Journals (Sweden)

    Stefanowski Jerzy

    2017-12-01

    Full Text Available This paper shows how big data analysis opens a range of research and technological problems and calls for new approaches. We start with defining the essential properties of big data and discussing the main types of data involved. We then survey the dedicated solutions for storing and processing big data, including a data lake, virtual integration, and a polystore architecture. Difficulties in managing data quality and provenance are also highlighted. The characteristics of big data imply also specific requirements and challenges for data mining algorithms, which we address as well. The links with related areas, including data streams and deep learning, are discussed. The common theme that naturally emerges from this characterization is complexity. All in all, we consider it to be the truly defining feature of big data (posing particular research and technological challenges, which ultimately seems to be of greater importance than the sheer data volume.

  10. Database Resources of the BIG Data Center in 2018.

    Science.gov (United States)

    2018-01-04

    The BIG Data Center at Beijing Institute of Genomics (BIG) of the Chinese Academy of Sciences provides freely open access to a suite of database resources in support of worldwide research activities in both academia and industry. With the vast amounts of omics data generated at ever-greater scales and rates, the BIG Data Center is continually expanding, updating and enriching its core database resources through big-data integration and value-added curation, including BioCode (a repository archiving bioinformatics tool codes), BioProject (a biological project library), BioSample (a biological sample library), Genome Sequence Archive (GSA, a data repository for archiving raw sequence reads), Genome Warehouse (GWH, a centralized resource housing genome-scale data), Genome Variation Map (GVM, a public repository of genome variations), Gene Expression Nebulas (GEN, a database of gene expression profiles based on RNA-Seq data), Methylation Bank (MethBank, an integrated databank of DNA methylomes), and Science Wikis (a series of biological knowledge wikis for community annotations). In addition, three featured web services are provided, viz., BIG Search (search as a service; a scalable inter-domain text search engine), BIG SSO (single sign-on as a service; a user access control system to gain access to multiple independent systems with a single ID and password) and Gsub (submission as a service; a unified submission service for all relevant resources). All of these resources are publicly accessible through the home page of the BIG Data Center at http://bigd.big.ac.cn. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  11. Using Unmanned Aerial Vehicles to Assess Vegetative Cover and Identify Biotic Resources in Sagebrush Steppe Ecosystems: Preliminary Evaluation

    Energy Technology Data Exchange (ETDEWEB)

    Robert P. Breckenridge

    2006-04-01

    The Idaho National Laboratory (INL), in conjunction with the University of Idaho, is evaluating novel approaches for using unmanned aerial vehicles (UAVs) as a quicker and safer method for monitoring biotic resources. Evaluating vegetative cover is an important factor in understanding the sustainability of many ecosystems. In assessing vegetative cover, methods that improve accuracy and cost efficiency could revolutionize how biotic resources are monitored on western federal lands. Sagebrush steppe ecosystems provide important habitat for a variety of species, some of which are important indicator species (e.g., sage grouse). Improved methods are needed to support monitoring these habitats because there are not enough resource specialists or funds available for comprehensive ground evaluation of these ecosystems. In this project, two types of UAV platforms (fixed wing and helicopter) were used to collect still-frame imagery to assess cover in sagebrush steppe ecosystems. This paper discusses the process for collecting and analyzing imagery from the UAVs to (1) estimate total percent cover, (2) estimate percent cover for six different types of vegetation, and (3) locate sage grouse based on representative decoys. The field plots were located on the INL site west of Idaho Falls, Idaho, in areas with varying amounts and types of vegetative cover. A software program called SamplePoint developed by the U.S. Department of Agriculture, Agricultural Research Service was used to evaluate the imagery for percent cover for the six vegetation types (bare ground, litter, shrubs, dead shrubs, grasses, and forbs). Results were compared against standard field measurements to assess accuracy.

  12. The big data telescope

    International Nuclear Information System (INIS)

    Finkel, Elizabeth

    2017-01-01

    On a flat, red mulga plain in the outback of Western Australia, preparations are under way to build the most audacious telescope astronomers have ever dreamed of - the Square Kilometre Array (SKA). Next-generation telescopes usually aim to double the performance of their predecessors. The Australian arm of SKA will deliver a 168-fold leap on the best technology available today, to show us the universe as never before. It will tune into signals emitted just a million years after the Big Bang, when the universe was a sea of hydrogen gas, slowly percolating with the first galaxies. Their starlight illuminated the fledgling universe in what is referred to as the “cosmic dawn”.

  13. The Big Optical Array

    International Nuclear Information System (INIS)

    Mozurkewich, D.; Johnston, K.J.; Simon, R.S.

    1990-01-01

    This paper describes the design and the capabilities of the Naval Research Laboratory Big Optical Array (BOA), an interferometric optical array for high-resolution imaging of stars, stellar systems, and other celestial objects. There are four important differences between the BOA design and the design of Mark III Optical Interferometer on Mount Wilson (California). These include a long passive delay line which will be used in BOA to do most of the delay compensation, so that the fast delay line will have a very short travel; the beam combination in BOA will be done in triplets, to allow measurement of closure phase; the same light will be used for both star and fringe tracking; and the fringe tracker will use several wavelength channels

  14. Big nuclear accidents

    International Nuclear Information System (INIS)

    Marshall, W.

    1983-01-01

    Much of the debate on the safety of nuclear power focuses on the large number of fatalities that could, in theory, be caused by extremely unlikely but imaginable reactor accidents. This, along with the nuclear industry's inappropriate use of vocabulary during public debate, has given the general public a distorted impression of the safety of nuclear power. The way in which the probability and consequences of big nuclear accidents have been presented in the past is reviewed and recommendations for the future are made including the presentation of the long-term consequences of such accidents in terms of 'reduction in life expectancy', 'increased chance of fatal cancer' and the equivalent pattern of compulsory cigarette smoking. (author)

  15. Nonstandard big bang models

    International Nuclear Information System (INIS)

    Calvao, M.O.; Lima, J.A.S.

    1989-01-01

    The usual FRW hot big-bang cosmologies have been generalized by considering the equation of state ρ = Anm +(γ-1) -1 p, where m is the rest mass of the fluid particles and A is a dimensionless constant. Explicit analytic solutions are given for the flat case (ε=O). For large cosmological times these extended models behave as the standard Einstein-de Sitter universes regardless of the values of A and γ. Unlike the usual FRW flat case the deceleration parameter q is a time-dependent function and its present value, q≅ 1, obtained from the luminosity distance versus redshift relation, may be fitted by taking, for instance, A=1 and γ = 5/3 (monatomic relativistic gas with >> k B T). In all cases the universe cools obeying the same temperature law of the FRW models and it is shown that the age of the universe is only slightly modified. (author) [pt

  16. The Last Big Bang

    Energy Technology Data Exchange (ETDEWEB)

    McGuire, Austin D. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Meade, Roger Allen [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-09-13

    As one of the very few people in the world to give the “go/no go” decision to detonate a nuclear device, Austin “Mac” McGuire holds a very special place in the history of both the Los Alamos National Laboratory and the world. As Commander of Joint Task Force Unit 8.1.1, on Christmas Island in the spring and summer of 1962, Mac directed the Los Alamos data collection efforts for twelve of the last atmospheric nuclear detonations conducted by the United States. Since data collection was at the heart of nuclear weapon testing, it fell to Mac to make the ultimate decision to detonate each test device. He calls his experience THE LAST BIG BANG, since these tests, part of Operation Dominic, were characterized by the dramatic displays of the heat, light, and sounds unique to atmospheric nuclear detonations – never, perhaps, to be witnessed again.

  17. A matrix big bang

    International Nuclear Information System (INIS)

    Craps, Ben; Sethi, Savdeep; Verlinde, Erik

    2005-01-01

    The light-like linear dilaton background represents a particularly simple time-dependent 1/2 BPS solution of critical type-IIA superstring theory in ten dimensions. Its lift to M-theory, as well as its Einstein frame metric, are singular in the sense that the geometry is geodesically incomplete and the Riemann tensor diverges along a light-like subspace of codimension one. We study this background as a model for a big bang type singularity in string theory/M-theory. We construct the dual Matrix theory description in terms of a (1+1)-d supersymmetric Yang-Mills theory on a time-dependent world-sheet given by the Milne orbifold of (1+1)-d Minkowski space. Our model provides a framework in which the physics of the singularity appears to be under control

  18. A matrix big bang

    Energy Technology Data Exchange (ETDEWEB)

    Craps, Ben [Instituut voor Theoretische Fysica, Universiteit van Amsterdam, Valckenierstraat 65, 1018 XE Amsterdam (Netherlands); Sethi, Savdeep [Enrico Fermi Institute, University of Chicago, Chicago, IL 60637 (United States); Verlinde, Erik [Instituut voor Theoretische Fysica, Universiteit van Amsterdam, Valckenierstraat 65, 1018 XE Amsterdam (Netherlands)

    2005-10-15

    The light-like linear dilaton background represents a particularly simple time-dependent 1/2 BPS solution of critical type-IIA superstring theory in ten dimensions. Its lift to M-theory, as well as its Einstein frame metric, are singular in the sense that the geometry is geodesically incomplete and the Riemann tensor diverges along a light-like subspace of codimension one. We study this background as a model for a big bang type singularity in string theory/M-theory. We construct the dual Matrix theory description in terms of a (1+1)-d supersymmetric Yang-Mills theory on a time-dependent world-sheet given by the Milne orbifold of (1+1)-d Minkowski space. Our model provides a framework in which the physics of the singularity appears to be under control.

  19. DPF Big One

    International Nuclear Information System (INIS)

    Anon.

    1993-01-01

    At its latest venue at Fermilab from 10-14 November, the American Physical Society's Division of Particles and Fields meeting entered a new dimension. These regular meetings, which allow younger researchers to communicate with their peers, have been gaining popularity over the years (this was the seventh in the series), but nobody had expected almost a thousand participants and nearly 500 requests to give talks. Thus Fermilab's 800-seat auditorium had to be supplemented with another room with a video hookup, while the parallel sessions were organized into nine bewildering streams covering fourteen major physics topics. With the conventionality of the Standard Model virtually unchallenged, physics does not move fast these days. While most of the physics results had already been covered in principle at the International Conference on High Energy Physics held in Dallas in August (October, page 1), the Fermilab DPF meeting had a very different atmosphere. Major international meetings like Dallas attract big names from far and wide, and it is difficult in such an august atmosphere for young researchers to find a receptive audience. This was not the case at the DPF parallel sessions. The meeting also adopted a novel approach, with the parallels sandwiched between an initial day of plenaries to set the scene, and a final day of summaries. With the whole world waiting for the sixth ('top') quark to be discovered at Fermilab's Tevatron protonantiproton collider, the meeting began with updates from Avi Yagil and Ronald Madaras from the big detectors, CDF and DO respectively. Although rumours flew thick and fast, the Tevatron has not yet reached the top, although Yagil could show one intriguing event of a type expected from the heaviest quark

  20. DPF Big One

    Energy Technology Data Exchange (ETDEWEB)

    Anon.

    1993-01-15

    At its latest venue at Fermilab from 10-14 November, the American Physical Society's Division of Particles and Fields meeting entered a new dimension. These regular meetings, which allow younger researchers to communicate with their peers, have been gaining popularity over the years (this was the seventh in the series), but nobody had expected almost a thousand participants and nearly 500 requests to give talks. Thus Fermilab's 800-seat auditorium had to be supplemented with another room with a video hookup, while the parallel sessions were organized into nine bewildering streams covering fourteen major physics topics. With the conventionality of the Standard Model virtually unchallenged, physics does not move fast these days. While most of the physics results had already been covered in principle at the International Conference on High Energy Physics held in Dallas in August (October, page 1), the Fermilab DPF meeting had a very different atmosphere. Major international meetings like Dallas attract big names from far and wide, and it is difficult in such an august atmosphere for young researchers to find a receptive audience. This was not the case at the DPF parallel sessions. The meeting also adopted a novel approach, with the parallels sandwiched between an initial day of plenaries to set the scene, and a final day of summaries. With the whole world waiting for the sixth ('top') quark to be discovered at Fermilab's Tevatron protonantiproton collider, the meeting began with updates from Avi Yagil and Ronald Madaras from the big detectors, CDF and DO respectively. Although rumours flew thick and fast, the Tevatron has not yet reached the top, although Yagil could show one intriguing event of a type expected from the heaviest quark.

  1. Big bang and big crunch in matrix string theory

    International Nuclear Information System (INIS)

    Bedford, J.; Ward, J.; Papageorgakis, C.; Rodriguez-Gomez, D.

    2007-01-01

    Following the holographic description of linear dilaton null cosmologies with a big bang in terms of matrix string theory put forward by Craps, Sethi, and Verlinde, we propose an extended background describing a universe including both big bang and big crunch singularities. This belongs to a class of exact string backgrounds and is perturbative in the string coupling far away from the singularities, both of which can be resolved using matrix string theory. We provide a simple theory capable of describing the complete evolution of this closed universe

  2. Data resources for range-wide assessment of livestock grazing across the sagebrush biome

    Science.gov (United States)

    Assal, T.J.; Veblen, K.E.; Farinha, M.A.; Aldridge, Cameron L.; Casazza, Michael L.; Pyke, D.A.

    2012-01-01

    The data contained in this series were compiled, modified, and analyzed for the U.S. Geological Survey (USGS) report "Range-Wide Assessment of Livestock Grazing Across the Sagebrush Biome." This report can be accessed through the USGS Publications Warehouse (online linkage: http://pubs.usgs.gov/of/2011/1263/). The dataset contains spatial and tabular data related to Bureau of Land Management (BLM) Grazing Allotments. We reviewed the BLM national grazing allotment spatial dataset available from the GeoCommunicator National Integrated Land System (NILS) website in 2007 (http://www.geocommunicator.gov). We identified several limitations in those data and learned that some BLM State and/or field offices had updated their spatial data to rectify these limitations, but maintained the data outside of NILS. We contacted appropriate BLM offices (State or field, 25 in all) to obtain the most recent data, assessed the data, established a data development protocol, and compiled data into a topologically enforced dataset throughout the area of interest for this project (that is, the pre-settlement distribution of Greater Sage-Grouse in the Western United States). The final database includes three spatial datasets: Allotments (BLM Grazing Allotments), OUT_Polygons (nonallotment polygons used to ensure topology), and Duplicate_Polygon_Allotments. See Appendix 1 of the aforementioned report for complete methods. The tabular data presented here consists of information synthesized by the Land Health Standard (LHS) analysis (Appendix 2), and data obtained from the BLM Rangeland Administration System (http://www.blm.gov/ras/). In 2008, available LHS data for all allotments in all regions were compiled by BLM in response to a Freedom of Information Act (FOIA) request made by a private organization. The BLM provided us with a copy of these data. These data provided three major types of information that were of interest: (1) date(s) (if any) of the most recent LHS evaluation for each

  3. BigOP: Generating Comprehensive Big Data Workloads as a Benchmarking Framework

    OpenAIRE

    Zhu, Yuqing; Zhan, Jianfeng; Weng, Chuliang; Nambiar, Raghunath; Zhang, Jinchao; Chen, Xingzhen; Wang, Lei

    2014-01-01

    Big Data is considered proprietary asset of companies, organizations, and even nations. Turning big data into real treasure requires the support of big data systems. A variety of commercial and open source products have been unleashed for big data storage and processing. While big data users are facing the choice of which system best suits their needs, big data system developers are facing the question of how to evaluate their systems with regard to general big data processing needs. System b...

  4. From big bang to big crunch and beyond

    International Nuclear Information System (INIS)

    Elitzur, Shmuel; Rabinovici, Eliezer; Giveon, Amit; Kutasov, David

    2002-01-01

    We study a quotient Conformal Field Theory, which describes a 3+1 dimensional cosmological spacetime. Part of this spacetime is the Nappi-Witten (NW) universe, which starts at a 'big bang' singularity, expands and then contracts to a 'big crunch' singularity at a finite time. The gauged WZW model contains a number of copies of the NW spacetime, with each copy connected to the preceding one and to the next one at the respective big bang/big crunch singularities. The sequence of NW spacetimes is further connected at the singularities to a series of non-compact static regions with closed timelike curves. These regions contain boundaries, on which the observables of the theory live. This suggests a holographic interpretation of the physics. (author)

  5. Google BigQuery analytics

    CERN Document Server

    Tigani, Jordan

    2014-01-01

    How to effectively use BigQuery, avoid common mistakes, and execute sophisticated queries against large datasets Google BigQuery Analytics is the perfect guide for business and data analysts who want the latest tips on running complex queries and writing code to communicate with the BigQuery API. The book uses real-world examples to demonstrate current best practices and techniques, and also explains and demonstrates streaming ingestion, transformation via Hadoop in Google Compute engine, AppEngine datastore integration, and using GViz with Tableau to generate charts of query results. In addit

  6. Empathy and the Big Five

    OpenAIRE

    Paulus, Christoph

    2016-01-01

    Del Barrio et al. (2004) haben vor mehr als 10 Jahren versucht, eine direkte Beziehung zwischen Empathie und den Big Five herzustellen. Im Mittel hatten in ihrer Stichprobe Frauen höhere Werte in der Empathie und auf den Big Five-Faktoren mit Ausnahme des Faktors Neurotizismus. Zusammenhänge zu Empathie fanden sie in den Bereichen Offenheit, Verträglichkeit, Gewissenhaftigkeit und Extraversion. In unseren Daten besitzen Frauen sowohl in der Empathie als auch den Big Five signifikant höhere We...

  7. "Big data" in economic history.

    Science.gov (United States)

    Gutmann, Myron P; Merchant, Emily Klancher; Roberts, Evan

    2018-03-01

    Big data is an exciting prospect for the field of economic history, which has long depended on the acquisition, keying, and cleaning of scarce numerical information about the past. This article examines two areas in which economic historians are already using big data - population and environment - discussing ways in which increased frequency of observation, denser samples, and smaller geographic units allow us to analyze the past with greater precision and often to track individuals, places, and phenomena across time. We also explore promising new sources of big data: organically created economic data, high resolution images, and textual corpora.

  8. Big Data as Information Barrier

    Directory of Open Access Journals (Sweden)

    Victor Ya. Tsvetkov

    2014-07-01

    Full Text Available The article covers analysis of ‘Big Data’ which has been discussed over last 10 years. The reasons and factors for the issue are revealed. It has proved that the factors creating ‘Big Data’ issue has existed for quite a long time, and from time to time, would cause the informational barriers. Such barriers were successfully overcome through the science and technologies. The conducted analysis refers the “Big Data” issue to a form of informative barrier. This issue may be solved correctly and encourages development of scientific and calculating methods.

  9. Homogeneous and isotropic big rips?

    CERN Document Server

    Giovannini, Massimo

    2005-01-01

    We investigate the way big rips are approached in a fully inhomogeneous description of the space-time geometry. If the pressure and energy densities are connected by a (supernegative) barotropic index, the spatial gradients and the anisotropic expansion decay as the big rip is approached. This behaviour is contrasted with the usual big-bang singularities. A similar analysis is performed in the case of sudden (quiescent) singularities and it is argued that the spatial gradients may well be non-negligible in the vicinity of pressure singularities.

  10. Big Data in Space Science

    OpenAIRE

    Barmby, Pauline

    2018-01-01

    It seems like “big data” is everywhere these days. In planetary science and astronomy, we’ve been dealing with large datasets for a long time. So how “big” is our data? How does it compare to the big data that a bank or an airline might have? What new tools do we need to analyze big datasets, and how can we make better use of existing tools? What kinds of science problems can we address with these? I’ll address these questions with examples including ESA’s Gaia mission, ...

  11. Rate Change Big Bang Theory

    Science.gov (United States)

    Strickland, Ken

    2013-04-01

    The Rate Change Big Bang Theory redefines the birth of the universe with a dramatic shift in energy direction and a new vision of the first moments. With rate change graph technology (RCGT) we can look back 13.7 billion years and experience every step of the big bang through geometrical intersection technology. The analysis of the Big Bang includes a visualization of the first objects, their properties, the astounding event that created space and time as well as a solution to the mystery of anti-matter.

  12. Big Data is invading big places as CERN

    CERN Multimedia

    CERN. Geneva

    2017-01-01

    Big Data technologies are becoming more popular with the constant grow of data generation in different fields such as social networks, internet of things and laboratories like CERN. How is CERN making use of such technologies? How machine learning is applied at CERN with Big Data technologies? How much data we move and how it is analyzed? All these questions will be answered during the talk.

  13. The ethics of big data in big agriculture

    OpenAIRE

    Carbonell (Isabelle M.)

    2016-01-01

    This paper examines the ethics of big data in agriculture, focusing on the power asymmetry between farmers and large agribusinesses like Monsanto. Following the recent purchase of Climate Corp., Monsanto is currently the most prominent biotech agribusiness to buy into big data. With wireless sensors on tractors monitoring or dictating every decision a farmer makes, Monsanto can now aggregate large quantities of previously proprietary farming data, enabling a privileged position with unique in...

  14. Big climate data analysis

    Science.gov (United States)

    Mudelsee, Manfred

    2015-04-01

    The Big Data era has begun also in the climate sciences, not only in economics or molecular biology. We measure climate at increasing spatial resolution by means of satellites and look farther back in time at increasing temporal resolution by means of natural archives and proxy data. We use powerful supercomputers to run climate models. The model output of the calculations made for the IPCC's Fifth Assessment Report amounts to ~650 TB. The 'scientific evolution' of grid computing has started, and the 'scientific revolution' of quantum computing is being prepared. This will increase computing power, and data amount, by several orders of magnitude in the future. However, more data does not automatically mean more knowledge. We need statisticians, who are at the core of transforming data into knowledge. Statisticians notably also explore the limits of our knowledge (uncertainties, that is, confidence intervals and P-values). Mudelsee (2014 Climate Time Series Analysis: Classical Statistical and Bootstrap Methods. Second edition. Springer, Cham, xxxii + 454 pp.) coined the term 'optimal estimation'. Consider the hyperspace of climate estimation. It has many, but not infinite, dimensions. It consists of the three subspaces Monte Carlo design, method and measure. The Monte Carlo design describes the data generating process. The method subspace describes the estimation and confidence interval construction. The measure subspace describes how to detect the optimal estimation method for the Monte Carlo experiment. The envisaged large increase in computing power may bring the following idea of optimal climate estimation into existence. Given a data sample, some prior information (e.g. measurement standard errors) and a set of questions (parameters to be estimated), the first task is simple: perform an initial estimation on basis of existing knowledge and experience with such types of estimation problems. The second task requires the computing power: explore the hyperspace to

  15. Hey, big spender

    Energy Technology Data Exchange (ETDEWEB)

    Cope, G.

    2000-04-01

    Business to business electronic commerce is looming large in the future of the oil industry. It is estimated that by adopting e-commerce the industry could achieve bottom line savings of between $1.8 to $ 3.4 billion a year on annual gross revenues in excess of $ 30 billion. At present there are several teething problems to overcome such as inter-operability standards, which are at least two or three years away. Tying in electronically with specific suppliers is also an expensive proposition, although the big benefits are in fact in doing business with the same suppliers on a continuing basis. Despite these problems, 14 of the world's largest energy and petrochemical companies joined forces in mid-April to create a single Internet procurement marketplace for the industry's complex supply chain. The exchange was designed by B2B (business-to-business) software provider, Commerce One Inc., ; it will leverage the buying clout of these industry giants (BP Amoco, Royal Dutch Shell Group, Conoco, Occidental Petroleum, Phillips Petroleum, Unocal Corporation and Statoil among them), currently about $ 125 billion on procurement per year; they hope to save between 5 to 30 per cent depending on the product and the region involved. Other similar schemes such as Chevron and partners' Petrocosm Marketplace, Network Oil, a Houston-based Internet portal aimed at smaller petroleum companies, are also doing business in the $ 10 billion per annum range. e-Energy, a cooperative project between IBM Ericson and Telus Advertising is another neutral, virtual marketplace targeted at the oil and gas sector. PetroTRAX, a Calgary-based website plans to take online procurement and auction sales a big step forward by establishing a portal to handle any oil company's asset management needs. There are also a number of websites targeting specific needs: IndigoPool.com (acquisitions and divestitures) and WellBid.com (products related to upstream oil and gas operators) are just

  16. Hey, big spender

    International Nuclear Information System (INIS)

    Cope, G.

    2000-01-01

    Business to business electronic commerce is looming large in the future of the oil industry. It is estimated that by adopting e-commerce the industry could achieve bottom line savings of between $1.8 to $ 3.4 billion a year on annual gross revenues in excess of $ 30 billion. At present there are several teething problems to overcome such as inter-operability standards, which are at least two or three years away. Tying in electronically with specific suppliers is also an expensive proposition, although the big benefits are in fact in doing business with the same suppliers on a continuing basis. Despite these problems, 14 of the world's largest energy and petrochemical companies joined forces in mid-April to create a single Internet procurement marketplace for the industry's complex supply chain. The exchange was designed by B2B (business-to-business) software provider, Commerce One Inc., ; it will leverage the buying clout of these industry giants (BP Amoco, Royal Dutch Shell Group, Conoco, Occidental Petroleum, Phillips Petroleum, Unocal Corporation and Statoil among them), currently about $ 125 billion on procurement per year; they hope to save between 5 to 30 per cent depending on the product and the region involved. Other similar schemes such as Chevron and partners' Petrocosm Marketplace, Network Oil, a Houston-based Internet portal aimed at smaller petroleum companies, are also doing business in the $ 10 billion per annum range. e-Energy, a cooperative project between IBM Ericson and Telus Advertising is another neutral, virtual marketplace targeted at the oil and gas sector. PetroTRAX, a Calgary-based website plans to take online procurement and auction sales a big step forward by establishing a portal to handle any oil company's asset management needs. There are also a number of websites targeting specific needs: IndigoPool.com (acquisitions and divestitures) and WellBid.com (products related to upstream oil and gas operators) are just two examples. All in

  17. Methods and tools for big data visualization

    OpenAIRE

    Zubova, Jelena; Kurasova, Olga

    2015-01-01

    In this paper, methods and tools for big data visualization have been investigated. Challenges faced by the big data analysis and visualization have been identified. Technologies for big data analysis have been discussed. A review of methods and tools for big data visualization has been done. Functionalities of the tools have been demonstrated by examples in order to highlight their advantages and disadvantages.

  18. Measuring the Promise of Big Data Syllabi

    Science.gov (United States)

    Friedman, Alon

    2018-01-01

    Growing interest in Big Data is leading industries, academics and governments to accelerate Big Data research. However, how teachers should teach Big Data has not been fully examined. This article suggests criteria for redesigning Big Data syllabi in public and private degree-awarding higher education establishments. The author conducted a survey…

  19. Susceptibility and antibody response of Vesper Sparrows (Pooecetes gramineus) to West Nile virus: A potential amplification host in sagebrush-grassland habitat

    Science.gov (United States)

    Hofmeister, Erik K.; Dusek, Robert J.; Fassbinder-Orth, Carol; Owen, Benjamin; Franson, J. Christian

    2016-01-01

    West Nile virus (WNV) spread to the US western plains states in 2003, when a significant mortality event attributed to WNV occurred in Greater Sage-grouse ( Centrocercus urophasianus ). The role of avian species inhabiting sagebrush in the amplification of WNV in arid and semiarid regions of the North America is unknown. We conducted an experimental WNV challenge study in Vesper Sparrows ( Pooecetes gramineus ), a species common to sagebrush and grassland habitats found throughout much of North America. We found Vesper Sparrows to be moderately susceptible to WNV, developing viremia considered sufficient to transmit WNV to feeding mosquitoes, but the majority of birds were capable of surviving infection and developing a humoral immune response to the WNV nonstructural 1 and envelope proteins. Despite clearance of viremia, after 6 mo, WNV was detected molecularly in three birds and cultured from one bird. Surviving Vesper Sparrows were resistant to reinfection 6 mo after the initial challenge. Vesper sparrows could play a role in the amplification of WNV in sagebrush habitat and other areas of their range, but rapid clearance of WNV may limit their importance as competent amplification hosts of WNV.

  20. The BigBOSS Experiment

    Energy Technology Data Exchange (ETDEWEB)

    Schelgel, D.; Abdalla, F.; Abraham, T.; Ahn, C.; Allende Prieto, C.; Annis, J.; Aubourg, E.; Azzaro, M.; Bailey, S.; Baltay, C.; Baugh, C.; /APC, Paris /Brookhaven /IRFU, Saclay /Marseille, CPPM /Marseille, CPT /Durham U. / /IEU, Seoul /Fermilab /IAA, Granada /IAC, La Laguna

    2011-01-01

    BigBOSS will obtain observational constraints that will bear on three of the four 'science frontier' questions identified by the Astro2010 Cosmology and Fundamental Phyics Panel of the Decadal Survey: Why is the universe accelerating; what is dark matter and what are the properties of neutrinos? Indeed, the BigBOSS project was recommended for substantial immediate R and D support the PASAG report. The second highest ground-based priority from the Astro2010 Decadal Survey was the creation of a funding line within the NSF to support a 'Mid-Scale Innovations' program, and it used BigBOSS as a 'compelling' example for support. This choice was the result of the Decadal Survey's Program Priorization panels reviewing 29 mid-scale projects and recommending BigBOSS 'very highly'.

  1. Biophotonics: the big picture

    Science.gov (United States)

    Marcu, Laura; Boppart, Stephen A.; Hutchinson, Mark R.; Popp, Jürgen; Wilson, Brian C.

    2018-02-01

    The 5th International Conference on Biophotonics (ICOB) held April 30 to May 1, 2017, in Fremantle, Western Australia, brought together opinion leaders to discuss future directions for the field and opportunities to consider. The first session of the conference, "How to Set a Big Picture Biophotonics Agenda," was focused on setting the stage for developing a vision and strategies for translation and impact on society of biophotonic technologies. The invited speakers, panelists, and attendees engaged in discussions that focused on opportunities and promising applications for biophotonic techniques, challenges when working at the confluence of the physical and biological sciences, driving factors for advances of biophotonic technologies, and educational opportunities. We share a summary of the presentations and discussions. Three main themes from the conference are presented in this position paper that capture the current status, opportunities, challenges, and future directions of biophotonics research and key areas of applications: (1) biophotonics at the nano- to microscale level; (2) biophotonics at meso- to macroscale level; and (3) biophotonics and the clinical translation conundrum.

  2. Big Data, Small Sample.

    Science.gov (United States)

    Gerlovina, Inna; van der Laan, Mark J; Hubbard, Alan

    2017-05-20

    Multiple comparisons and small sample size, common characteristics of many types of "Big Data" including those that are produced by genomic studies, present specific challenges that affect reliability of inference. Use of multiple testing procedures necessitates calculation of very small tail probabilities of a test statistic distribution. Results based on large deviation theory provide a formal condition that is necessary to guarantee error rate control given practical sample sizes, linking the number of tests and the sample size; this condition, however, is rarely satisfied. Using methods that are based on Edgeworth expansions (relying especially on the work of Peter Hall), we explore the impact of departures of sampling distributions from typical assumptions on actual error rates. Our investigation illustrates how far the actual error rates can be from the declared nominal levels, suggesting potentially wide-spread problems with error rate control, specifically excessive false positives. This is an important factor that contributes to "reproducibility crisis". We also review some other commonly used methods (such as permutation and methods based on finite sampling inequalities) in their application to multiple testing/small sample data. We point out that Edgeworth expansions, providing higher order approximations to the sampling distribution, offer a promising direction for data analysis that could improve reliability of studies relying on large numbers of comparisons with modest sample sizes.

  3. Big bang darkleosynthesis

    Directory of Open Access Journals (Sweden)

    Gordan Krnjaic

    2015-12-01

    Full Text Available In a popular class of models, dark matter comprises an asymmetric population of composite particles with short range interactions arising from a confined nonabelian gauge group. We show that coupling this sector to a well-motivated light mediator particle yields efficient darkleosynthesis, a dark-sector version of big-bang nucleosynthesis (BBN, in generic regions of parameter space. Dark matter self-interaction bounds typically require the confinement scale to be above ΛQCD, which generically yields large (≫MeV/dark-nucleon binding energies. These bounds further suggest the mediator is relatively weakly coupled, so repulsive forces between dark-sector nuclei are much weaker than Coulomb repulsion between standard-model nuclei, which results in an exponential barrier-tunneling enhancement over standard BBN. Thus, darklei are easier to make and harder to break than visible species with comparable mass numbers. This process can efficiently yield a dominant population of states with masses significantly greater than the confinement scale and, in contrast to dark matter that is a fundamental particle, may allow the dominant form of dark matter to have high spin (S≫3/2, whose discovery would be smoking gun evidence for dark nuclei.

  4. Predicting big bang deuterium

    Energy Technology Data Exchange (ETDEWEB)

    Hata, N.; Scherrer, R.J.; Steigman, G.; Thomas, D.; Walker, T.P. [Department of Physics, Ohio State University, Columbus, Ohio 43210 (United States)

    1996-02-01

    We present new upper and lower bounds to the primordial abundances of deuterium and {sup 3}He based on observational data from the solar system and the interstellar medium. Independent of any model for the primordial production of the elements we find (at the 95{percent} C.L.): 1.5{times}10{sup {minus}5}{le}(D/H){sub {ital P}}{le}10.0{times}10{sup {minus}5} and ({sup 3}He/H){sub {ital P}}{le}2.6{times}10{sup {minus}5}. When combined with the predictions of standard big bang nucleosynthesis, these constraints lead to a 95{percent} C.L. bound on the primordial abundance deuterium: (D/H){sub best}=(3.5{sup +2.7}{sub {minus}1.8}){times}10{sup {minus}5}. Measurements of deuterium absorption in the spectra of high-redshift QSOs will directly test this prediction. The implications of this prediction for the primordial abundances of {sup 4}He and {sup 7}Li are discussed, as well as those for the universal density of baryons. {copyright} {ital 1996 The American Astronomical Society.}

  5. Big bang darkleosynthesis

    Science.gov (United States)

    Krnjaic, Gordan; Sigurdson, Kris

    2015-12-01

    In a popular class of models, dark matter comprises an asymmetric population of composite particles with short range interactions arising from a confined nonabelian gauge group. We show that coupling this sector to a well-motivated light mediator particle yields efficient darkleosynthesis, a dark-sector version of big-bang nucleosynthesis (BBN), in generic regions of parameter space. Dark matter self-interaction bounds typically require the confinement scale to be above ΛQCD, which generically yields large (≫MeV /dark-nucleon) binding energies. These bounds further suggest the mediator is relatively weakly coupled, so repulsive forces between dark-sector nuclei are much weaker than Coulomb repulsion between standard-model nuclei, which results in an exponential barrier-tunneling enhancement over standard BBN. Thus, darklei are easier to make and harder to break than visible species with comparable mass numbers. This process can efficiently yield a dominant population of states with masses significantly greater than the confinement scale and, in contrast to dark matter that is a fundamental particle, may allow the dominant form of dark matter to have high spin (S ≫ 3 / 2), whose discovery would be smoking gun evidence for dark nuclei.

  6. The role of big laboratories

    CERN Document Server

    Heuer, Rolf-Dieter

    2013-01-01

    This paper presents the role of big laboratories in their function as research infrastructures. Starting from the general definition and features of big laboratories, the paper goes on to present the key ingredients and issues, based on scientific excellence, for the successful realization of large-scale science projects at such facilities. The paper concludes by taking the example of scientific research in the field of particle physics and describing the structures and methods required to be implemented for the way forward.

  7. The role of big laboratories

    International Nuclear Information System (INIS)

    Heuer, R-D

    2013-01-01

    This paper presents the role of big laboratories in their function as research infrastructures. Starting from the general definition and features of big laboratories, the paper goes on to present the key ingredients and issues, based on scientific excellence, for the successful realization of large-scale science projects at such facilities. The paper concludes by taking the example of scientific research in the field of particle physics and describing the structures and methods required to be implemented for the way forward. (paper)

  8. Challenges of Big Data Analysis.

    Science.gov (United States)

    Fan, Jianqing; Han, Fang; Liu, Han

    2014-06-01

    Big Data bring new opportunities to modern society and challenges to data scientists. On one hand, Big Data hold great promises for discovering subtle population patterns and heterogeneities that are not possible with small-scale data. On the other hand, the massive sample size and high dimensionality of Big Data introduce unique computational and statistical challenges, including scalability and storage bottleneck, noise accumulation, spurious correlation, incidental endogeneity, and measurement errors. These challenges are distinguished and require new computational and statistical paradigm. This article gives overviews on the salient features of Big Data and how these features impact on paradigm change on statistical and computational methods as well as computing architectures. We also provide various new perspectives on the Big Data analysis and computation. In particular, we emphasize on the viability of the sparsest solution in high-confidence set and point out that exogeneous assumptions in most statistical methods for Big Data can not be validated due to incidental endogeneity. They can lead to wrong statistical inferences and consequently wrong scientific conclusions.

  9. Generalized formal model of Big Data

    OpenAIRE

    Shakhovska, N.; Veres, O.; Hirnyak, M.

    2016-01-01

    This article dwells on the basic characteristic features of the Big Data technologies. It is analyzed the existing definition of the “big data” term. The article proposes and describes the elements of the generalized formal model of big data. It is analyzed the peculiarities of the application of the proposed model components. It is described the fundamental differences between Big Data technology and business analytics. Big Data is supported by the distributed file system Google File System ...

  10. Nursing Knowledge: Big Data Science-Implications for Nurse Leaders.

    Science.gov (United States)

    Westra, Bonnie L; Clancy, Thomas R; Sensmeier, Joyce; Warren, Judith J; Weaver, Charlotte; Delaney, Connie W

    2015-01-01

    The integration of Big Data from electronic health records and other information systems within and across health care enterprises provides an opportunity to develop actionable predictive models that can increase the confidence of nursing leaders' decisions to improve patient outcomes and safety and control costs. As health care shifts to the community, mobile health applications add to the Big Data available. There is an evolving national action plan that includes nursing data in Big Data science, spearheaded by the University of Minnesota School of Nursing. For the past 3 years, diverse stakeholders from practice, industry, education, research, and professional organizations have collaborated through the "Nursing Knowledge: Big Data Science" conferences to create and act on recommendations for inclusion of nursing data, integrated with patient-generated, interprofessional, and contextual data. It is critical for nursing leaders to understand the value of Big Data science and the ways to standardize data and workflow processes to take advantage of newer cutting edge analytics to support analytic methods to control costs and improve patient quality and safety.

  11. A practical guide to big data research in psychology.

    Science.gov (United States)

    Chen, Eric Evan; Wojcik, Sean P

    2016-12-01

    The massive volume of data that now covers a wide variety of human behaviors offers researchers in psychology an unprecedented opportunity to conduct innovative theory- and data-driven field research. This article is a practical guide to conducting big data research, covering data management, acquisition, processing, and analytics (including key supervised and unsupervised learning data mining methods). It is accompanied by walkthrough tutorials on data acquisition, text analysis with latent Dirichlet allocation topic modeling, and classification with support vector machines. Big data practitioners in academia, industry, and the community have built a comprehensive base of tools and knowledge that makes big data research accessible to researchers in a broad range of fields. However, big data research does require knowledge of software programming and a different analytical mindset. For those willing to acquire the requisite skills, innovative analyses of unexpected or previously untapped data sources can offer fresh ways to develop, test, and extend theories. When conducted with care and respect, big data research can become an essential complement to traditional research. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  12. Evaluating greater sage-grouse seasonal space use relative to leks: Implications for surface use designations in sagebrush ecosystems

    Science.gov (United States)

    Casazza, Michael L.; Coates, Peter S.

    2013-01-01

    The development of anthropogenic structures, especially those related to energy resources, in sagebrush ecosystems is an important concern among developers, conservationists, and land managers in relation to greater sage-grouse (Centrocercus urophasianus; hereafter, sage-grouse) populations. Sage-grouse are dependent on sagebrush ecosystems to meet their seasonal life-phase requirements, and research indicates that anthropogenic structures can adversely affect sage-grouse populations. Land management agencies have attempted to reduce the negative effects of anthropogenic development by assigning surface use (SU) designations, such as no surface occupancy, to areas around leks (breeding grounds). However, rationale for the size of these areas is often challenged. To help inform this issue, we used a spatial analysis of sage-grouse utilization distributions (UDs) to quantify seasonal (spring, summer and fall, winter) sage-grouse space use in relation to leks. We sampled UDs from 193 sage-grouse (11,878 telemetry locations) across 4 subpopulations within the Bi-State Distinct Population Segment (DPS, bordering California and Nevada) during 2003–2009. We quantified the volume of each UD (vUD) within a range of areas that varied in size and were centered on leks, up to a distance of 30 km from leks. We also quantified the percentage of nests within those areas. We then estimated the diminishing gains of vUD as area increased and produced continuous response curves that allow for flexibility in land management decisions. We found nearly 90% of the total vUD (all seasons combined) was contained within 5 km of leks, and we identified variation in vUD for a given distance related to season and migratory status. Five kilometers also represented the 95th percentile of the distribution of nesting distances. Because diminishing gains of vUD was not substantial until distances exceeded 8 km, managers should consider the theoretical optimal distances for SU designation

  13. BigData as a Driver for Capacity Building in Astrophysics

    Science.gov (United States)

    Shastri, Prajval

    2015-08-01

    Exciting public interest in astrophysics acquires new significance in the era of Big Data. Since Big Data involves advanced technologies of both software and hardware, astrophysics with Big Data has the potential to inspire young minds with diverse inclinations - i.e., not just those attracted to physics but also those pursuing engineering careers. Digital technologies have become steadily cheaper, which can enable expansion of the Big Data user pool considerably, especially to communities that may not yet be in the astrophysics mainstream, but have high potential because of access to thesetechnologies. For success, however, capacity building at the early stages becomes key. The development of on-line pedagogical resources in astrophysics, astrostatistics, data-mining and data visualisation that are designed around the big facilities of the future can be an important effort that drives such capacity building, especially if facilitated by the IAU.

  14. [Big data in official statistics].

    Science.gov (United States)

    Zwick, Markus

    2015-08-01

    The concept of "big data" stands to change the face of official statistics over the coming years, having an impact on almost all aspects of data production. The tasks of future statisticians will not necessarily be to produce new data, but rather to identify and make use of existing data to adequately describe social and economic phenomena. Until big data can be used correctly in official statistics, a lot of questions need to be answered and problems solved: the quality of data, data protection, privacy, and the sustainable availability are some of the more pressing issues to be addressed. The essential skills of official statisticians will undoubtedly change, and this implies a number of challenges to be faced by statistical education systems, in universities, and inside the statistical offices. The national statistical offices of the European Union have concluded a concrete strategy for exploring the possibilities of big data for official statistics, by means of the Big Data Roadmap and Action Plan 1.0. This is an important first step and will have a significant influence on implementing the concept of big data inside the statistical offices of Germany.

  15. GEOSS: Addressing Big Data Challenges

    Science.gov (United States)

    Nativi, S.; Craglia, M.; Ochiai, O.

    2014-12-01

    In the sector of Earth Observation, the explosion of data is due to many factors including: new satellite constellations, the increased capabilities of sensor technologies, social media, crowdsourcing, and the need for multidisciplinary and collaborative research to face Global Changes. In this area, there are many expectations and concerns about Big Data. Vendors have attempted to use this term for their commercial purposes. It is necessary to understand whether Big Data is a radical shift or an incremental change for the existing digital infrastructures. This presentation tries to explore and discuss the impact of Big Data challenges and new capabilities on the Global Earth Observation System of Systems (GEOSS) and particularly on its common digital infrastructure called GCI. GEOSS is a global and flexible network of content providers allowing decision makers to access an extraordinary range of data and information at their desk. The impact of the Big Data dimensionalities (commonly known as 'V' axes: volume, variety, velocity, veracity, visualization) on GEOSS is discussed. The main solutions and experimentation developed by GEOSS along these axes are introduced and analyzed. GEOSS is a pioneering framework for global and multidisciplinary data sharing in the Earth Observation realm; its experience on Big Data is valuable for the many lessons learned.

  16. Official statistics and Big Data

    Directory of Open Access Journals (Sweden)

    Peter Struijs

    2014-07-01

    Full Text Available The rise of Big Data changes the context in which organisations producing official statistics operate. Big Data provides opportunities, but in order to make optimal use of Big Data, a number of challenges have to be addressed. This stimulates increased collaboration between National Statistical Institutes, Big Data holders, businesses and universities. In time, this may lead to a shift in the role of statistical institutes in the provision of high-quality and impartial statistical information to society. In this paper, the changes in context, the opportunities, the challenges and the way to collaborate are addressed. The collaboration between the various stakeholders will involve each partner building on and contributing different strengths. For national statistical offices, traditional strengths include, on the one hand, the ability to collect data and combine data sources with statistical products and, on the other hand, their focus on quality, transparency and sound methodology. In the Big Data era of competing and multiplying data sources, they continue to have a unique knowledge of official statistical production methods. And their impartiality and respect for privacy as enshrined in law uniquely position them as a trusted third party. Based on this, they may advise on the quality and validity of information of various sources. By thus positioning themselves, they will be able to play their role as key information providers in a changing society.

  17. Big data for bipolar disorder.

    Science.gov (United States)

    Monteith, Scott; Glenn, Tasha; Geddes, John; Whybrow, Peter C; Bauer, Michael

    2016-12-01

    The delivery of psychiatric care is changing with a new emphasis on integrated care, preventative measures, population health, and the biological basis of disease. Fundamental to this transformation are big data and advances in the ability to analyze these data. The impact of big data on the routine treatment of bipolar disorder today and in the near future is discussed, with examples that relate to health policy, the discovery of new associations, and the study of rare events. The primary sources of big data today are electronic medical records (EMR), claims, and registry data from providers and payers. In the near future, data created by patients from active monitoring, passive monitoring of Internet and smartphone activities, and from sensors may be integrated with the EMR. Diverse data sources from outside of medicine, such as government financial data, will be linked for research. Over the long term, genetic and imaging data will be integrated with the EMR, and there will be more emphasis on predictive models. Many technical challenges remain when analyzing big data that relates to size, heterogeneity, complexity, and unstructured text data in the EMR. Human judgement and subject matter expertise are critical parts of big data analysis, and the active participation of psychiatrists is needed throughout the analytical process.

  18. Quantum fields in a big-crunch-big-bang spacetime

    International Nuclear Information System (INIS)

    Tolley, Andrew J.; Turok, Neil

    2002-01-01

    We consider quantum field theory on a spacetime representing the big-crunch-big-bang transition postulated in ekpyrotic or cyclic cosmologies. We show via several independent methods that an essentially unique matching rule holds connecting the incoming state, in which a single extra dimension shrinks to zero, to the outgoing state in which it reexpands at the same rate. For free fields in our construction there is no particle production from the incoming adiabatic vacuum. When interactions are included the particle production for fixed external momentum is finite at the tree level. We discuss a formal correspondence between our construction and quantum field theory on de Sitter spacetime

  19. Poker Player Behavior After Big Wins and Big Losses

    OpenAIRE

    Gary Smith; Michael Levere; Robert Kurtzman

    2009-01-01

    We find that experienced poker players typically change their style of play after winning or losing a big pot--most notably, playing less cautiously after a big loss, evidently hoping for lucky cards that will erase their loss. This finding is consistent with Kahneman and Tversky's (Kahneman, D., A. Tversky. 1979. Prospect theory: An analysis of decision under risk. Econometrica 47(2) 263-292) break-even hypothesis and suggests that when investors incur a large loss, it might be time to take ...

  20. Turning big bang into big bounce: II. Quantum dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Malkiewicz, Przemyslaw; Piechocki, Wlodzimierz, E-mail: pmalk@fuw.edu.p, E-mail: piech@fuw.edu.p [Theoretical Physics Department, Institute for Nuclear Studies, Hoza 69, 00-681 Warsaw (Poland)

    2010-11-21

    We analyze the big bounce transition of the quantum Friedmann-Robertson-Walker model in the setting of the nonstandard loop quantum cosmology (LQC). Elementary observables are used to quantize composite observables. The spectrum of the energy density operator is bounded and continuous. The spectrum of the volume operator is bounded from below and discrete. It has equally distant levels defining a quantum of the volume. The discreteness may imply a foamy structure of spacetime at a semiclassical level which may be detected in astro-cosmo observations. The nonstandard LQC method has a free parameter that should be fixed in some way to specify the big bounce transition.

  1. Big Data Analytics in Medicine and Healthcare.

    Science.gov (United States)

    Ristevski, Blagoj; Chen, Ming

    2018-05-10

    This paper surveys big data with highlighting the big data analytics in medicine and healthcare. Big data characteristics: value, volume, velocity, variety, veracity and variability are described. Big data analytics in medicine and healthcare covers integration and analysis of large amount of complex heterogeneous data such as various - omics data (genomics, epigenomics, transcriptomics, proteomics, metabolomics, interactomics, pharmacogenomics, diseasomics), biomedical data and electronic health records data. We underline the challenging issues about big data privacy and security. Regarding big data characteristics, some directions of using suitable and promising open-source distributed data processing software platform are given.

  2. Ocean Networks Canada's "Big Data" Initiative

    Science.gov (United States)

    Dewey, R. K.; Hoeberechts, M.; Moran, K.; Pirenne, B.; Owens, D.

    2013-12-01

    Ocean Networks Canada operates two large undersea observatories that collect, archive, and deliver data in real time over the Internet. These data contribute to our understanding of the complex changes taking place on our ocean planet. Ocean Networks Canada's VENUS was the world's first cabled seafloor observatory to enable researchers anywhere to connect in real time to undersea experiments and observations. Its NEPTUNE observatory is the largest cabled ocean observatory, spanning a wide range of ocean environments. Most recently, we installed a new small observatory in the Arctic. Together, these observatories deliver "Big Data" across many disciplines in a cohesive manner using the Oceans 2.0 data management and archiving system that provides national and international users with open access to real-time and archived data while also supporting a collaborative work environment. Ocean Networks Canada operates these observatories to support science, innovation, and learning in four priority areas: study of the impact of climate change on the ocean; the exploration and understanding the unique life forms in the extreme environments of the deep ocean and below the seafloor; the exchange of heat, fluids, and gases that move throughout the ocean and atmosphere; and the dynamics of earthquakes, tsunamis, and undersea landslides. To date, the Ocean Networks Canada archive contains over 130 TB (collected over 7 years) and the current rate of data acquisition is ~50 TB per year. This data set is complex and diverse. Making these "Big Data" accessible and attractive to users is our priority. In this presentation, we share our experience as a "Big Data" institution where we deliver simple and multi-dimensional calibrated data cubes to a diverse pool of users. Ocean Networks Canada also conducts extensive user testing. Test results guide future tool design and development of "Big Data" products. We strive to bridge the gap between the raw, archived data and the needs and

  3. Big Data Analytics in Healthcare.

    Science.gov (United States)

    Belle, Ashwin; Thiagarajan, Raghuram; Soroushmehr, S M Reza; Navidi, Fatemeh; Beard, Daniel A; Najarian, Kayvan

    2015-01-01

    The rapidly expanding field of big data analytics has started to play a pivotal role in the evolution of healthcare practices and research. It has provided tools to accumulate, manage, analyze, and assimilate large volumes of disparate, structured, and unstructured data produced by current healthcare systems. Big data analytics has been recently applied towards aiding the process of care delivery and disease exploration. However, the adoption rate and research development in this space is still hindered by some fundamental problems inherent within the big data paradigm. In this paper, we discuss some of these major challenges with a focus on three upcoming and promising areas of medical research: image, signal, and genomics based analytics. Recent research which targets utilization of large volumes of medical data while combining multimodal data from disparate sources is discussed. Potential areas of research within this field which have the ability to provide meaningful impact on healthcare delivery are also examined.

  4. Calibration of remotely sensed, coarse resolution NDVI to CO2 fluxes in a sagebrush-steppe ecosystem

    Science.gov (United States)

    Wylie, B.K.; Johnson, D.A.; Laca, Emilio; Saliendra, Nicanor Z.; Gilmanov, T.G.; Reed, B.C.; Tieszen, L.L.; Worstell, B.B.

    2003-01-01

    The net ecosystem exchange (NEE) of carbon flux can be partitioned into gross primary productivity (GPP) and respiration (R). The contribution of remote sensing and modeling holds the potential to predict these components and map them spatially and temporally. This has obvious utility to quantify carbon sink and source relationships and to identify improved land management strategies for optimizing carbon sequestration. The objective of our study was to evaluate prediction of 14-day average daytime CO2 fluxes (Fday) and nighttime CO2 fluxes (Rn) using remote sensing and other data. Fday and Rn were measured with a Bowen ratio-energy balance (BREB) technique in a sagebrush (Artemisia spp.)-steppe ecosystem in northeast Idaho, USA, during 1996-1999. Micrometeorological variables aggregated across 14-day periods and time-integrated Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (iNDVI) were determined during four growing seasons (1996-1999) and used to predict Fday and Rn. We found that iNDVI was a strong predictor of Fday (R2 = 0.79, n = 66, P improved predictions of Fday (R2= 0.82, n = 66, P management strategies, carbon certification, and validation and calibration of carbon flux models. ?? 2003 Elsevier Science Inc. All rights reserved.

  5. Big Book of Windows Hacks

    CERN Document Server

    Gralla, Preston

    2008-01-01

    Bigger, better, and broader in scope, the Big Book of Windows Hacks gives you everything you need to get the most out of your Windows Vista or XP system, including its related applications and the hardware it runs on or connects to. Whether you want to tweak Vista's Aero interface, build customized sidebar gadgets and run them from a USB key, or hack the "unhackable" screensavers, you'll find quick and ingenious ways to bend these recalcitrant operating systems to your will. The Big Book of Windows Hacks focuses on Vista, the new bad boy on Microsoft's block, with hacks and workarounds that

  6. Sosiaalinen asiakassuhdejohtaminen ja big data

    OpenAIRE

    Toivonen, Topi-Antti

    2015-01-01

    Tässä tutkielmassa käsitellään sosiaalista asiakassuhdejohtamista sekä hyötyjä, joita siihen voidaan saada big datan avulla. Sosiaalinen asiakassuhdejohtaminen on terminä uusi ja monille tuntematon. Tutkimusta motivoi aiheen vähäinen tutkimus, suomenkielisen tutkimuksen puuttuminen kokonaan sekä sosiaalisen asiakassuhdejohtamisen mahdollinen olennainen rooli yritysten toiminnassa tulevaisuudessa. Big dataa käsittelevissä tutkimuksissa keskitytään monesti sen tekniseen puoleen, eikä sovellutuk...

  7. Do big gods cause anything?

    DEFF Research Database (Denmark)

    Geertz, Armin W.

    2014-01-01

    Dette er et bidrag til et review symposium vedrørende Ara Norenzayans bog Big Gods: How Religion Transformed Cooperation and Conflict (Princeton University Press 2013). Bogen er spændende men problematisk i forhold til kausalitet, ateisme og stereotyper om jægere-samlere.......Dette er et bidrag til et review symposium vedrørende Ara Norenzayans bog Big Gods: How Religion Transformed Cooperation and Conflict (Princeton University Press 2013). Bogen er spændende men problematisk i forhold til kausalitet, ateisme og stereotyper om jægere-samlere....

  8. Big Data and Social Media

    CERN Multimedia

    CERN. Geneva

    2018-01-01

    A critical analysis of the "keep everything" Big Data era, the impact on our lives of the information, at first glance "convenient for future use" that we make known about ourselves on the network. NB! The lecture will be recorded like all Academic Training lectures. Lecturer's biography: Father of the Internet, see https://internethalloffame.org/inductees/vint-cerf or https://en.wikipedia.org/wiki/Vint_Cerf The video on slide number 9 is from page https://www.gapminder.org/tools/#$state$time$value=2018&value;;&chart-type=bubbles   Keywords: Big Data, Internet, History, Applications, tools, privacy, technology, preservation, surveillance, google, Arpanet, CERN, Web  

  9. Baryon symmetric big bang cosmology

    International Nuclear Information System (INIS)

    Stecker, F.W.

    1978-01-01

    It is stated that the framework of baryon symmetric big bang (BSBB) cosmology offers our greatest potential for deducting the evolution of the Universe because its physical laws and processes have the minimum number of arbitrary assumptions about initial conditions in the big-bang. In addition, it offers the possibility of explaining the photon-baryon ratio in the Universe and how galaxies and galaxy clusters are formed. BSBB cosmology also provides the only acceptable explanation at present for the origin of the cosmic γ-ray background radiation. (author)

  10. Release plan for Big Pete

    International Nuclear Information System (INIS)

    Edwards, T.A.

    1996-11-01

    This release plan is to provide instructions for the Radiological Control Technician (RCT) to conduct surveys for the unconditional release of ''Big Pete,'' which was used in the removal of ''Spacers'' from the N-Reactor. Prior to performing surveys on the rear end portion of ''Big Pete,'' it shall be cleaned (i.e., free of oil, grease, caked soil, heavy dust). If no contamination is found, the vehicle may be released with the permission of the area RCT Supervisor. If contamination is found by any of the surveys, contact the cognizant Radiological Engineer for decontamination instructions

  11. Small quarks make big nuggets

    International Nuclear Information System (INIS)

    Deligeorges, S.

    1985-01-01

    After a brief recall on the classification of subatomic particles, this paper deals with quark nuggets, particle with more than three quarks, a big bag, which is called ''nuclearite''. Neutron stars, in fact, are big sacks of quarks, gigantic nuggets. Now, physicists try to calculate which type of nuggets of strange quark matter is stable, what has been the influence of quark nuggets on the primordial nucleosynthesis. At the present time, one says that if these ''nuggets'' exist, and in a large proportion, they may be candidates for the missing mass [fr

  12. [Big Data- challenges and risks].

    Science.gov (United States)

    Krauß, Manuela; Tóth, Tamás; Hanika, Heinrich; Kozlovszky, Miklós; Dinya, Elek

    2015-12-06

    The term "Big Data" is commonly used to describe the growing mass of information being created recently. New conclusions can be drawn and new services can be developed by the connection, processing and analysis of these information. This affects all aspects of life, including health and medicine. The authors review the application areas of Big Data, and present examples from health and other areas. However, there are several preconditions of the effective use of the opportunities: proper infrastructure, well defined regulatory environment with particular emphasis on data protection and privacy. These issues and the current actions for solution are also presented.

  13. Towards a big crunch dual

    Energy Technology Data Exchange (ETDEWEB)

    Hertog, Thomas E-mail: hertog@vulcan2.physics.ucsb.edu; Horowitz, Gary T

    2004-07-01

    We show there exist smooth asymptotically anti-de Sitter initial data which evolve to a big crunch singularity in a low energy supergravity limit of string theory. This opens up the possibility of using the dual conformal field theory to obtain a fully quantum description of the cosmological singularity. A preliminary study of this dual theory suggests that the big crunch is an endpoint of evolution even in the full string theory. We also show that any theory with scalar solitons must have negative energy solutions. The results presented here clarify our earlier work on cosmic censorship violation in N=8 supergravity. (author)

  14. The Inverted Big-Bang

    OpenAIRE

    Vaas, Ruediger

    2004-01-01

    Our universe appears to have been created not out of nothing but from a strange space-time dust. Quantum geometry (loop quantum gravity) makes it possible to avoid the ominous beginning of our universe with its physically unrealistic (i.e. infinite) curvature, extreme temperature, and energy density. This could be the long sought after explanation of the big-bang and perhaps even opens a window into a time before the big-bang: Space itself may have come from an earlier collapsing universe tha...

  15. Big Data in HEP: A comprehensive use case study

    OpenAIRE

    Gutsche, Oliver; Cremonesi, Matteo; Elmer, Peter; Jayatilaka, Bo; Kowalkowski, Jim; Pivarski, Jim; Sehrish, Saba; Surez, Cristina Mantilla; Svyatkovskiy, Alexey; Tran, Nhan

    2017-01-01

    Experimental Particle Physics has been at the forefront of analyzing the worlds largest datasets for decades. The HEP community was the first to develop suitable software and computing tools for this task. In recent times, new toolkits and systems collectively called Big Data technologies have emerged to support the analysis of Petabyte and Exabyte datasets in industry. While the principles of data analysis in HEP have not changed (filtering and transforming experiment-specific data formats),...

  16. Big Cities, Big Problems: Reason for the Elderly to Move?

    NARCIS (Netherlands)

    Fokkema, T.; de Jong-Gierveld, J.; Nijkamp, P.

    1996-01-01

    In many European countries, data on geographical patterns of internal elderly migration show that the elderly (55+) are more likely to leave than to move to the big cities. Besides emphasising the attractive features of the destination areas (pull factors), it is often assumed that this negative

  17. Big-Eyed Bugs Have Big Appetite for Pests

    Science.gov (United States)

    Many kinds of arthropod natural enemies (predators and parasitoids) inhabit crop fields in Arizona and can have a large negative impact on several pest insect species that also infest these crops. Geocoris spp., commonly known as big-eyed bugs, are among the most abundant insect predators in field c...

  18. Understanding Big Data for Industrial Innovation and Design: The Missing Information Systems Perspective

    Directory of Open Access Journals (Sweden)

    Miguel Baptista Nunes

    2017-12-01

    Full Text Available This paper identifies a need to complement the current rich technical and mathematical research agenda on big data with a more information systems and information science strand, which focuses on the business value of big data. An agenda of research for information systems would explore motives for using big data in real organizational contexts, and consider proposed benefits, such as increased effectiveness and efficiency, production of high-quality products/services, creation of added business value, and stimulation of innovation and design. Impacts of such research on the academic community, the industrial and business world, and policy-makers are discussed.

  19. BIG DATA AND E-LEARNING: THE IMPACT ON THE FUTURE OF LEARNING INDUSTRY

    Directory of Open Access Journals (Sweden)

    Valentin PAU

    2015-11-01

    Full Text Available In nowadays, one of the most interesting aspects of e-Learning is that he is continuously evolving, where, the big data architecture represents an important component over which the e-Learning communities has stopped more and more. In our work paper we will analyze the technological benefits of the big data concept and the impact on the future of e-Learning but also we will mention the critical aspects regarding the integrity of the data.

  20. A survey on Big Data Stream Mining

    African Journals Online (AJOL)

    pc

    2018-03-05

    Mar 5, 2018 ... Big Data can be static on one machine or distributed ... decision making, and process automation. Big data .... Concept Drifting: concept drifting mean the classifier .... transactions generated by a prefix tree structure. EstDec ...

  1. BIG DATA-DRIVEN MARKETING: AN ABSTRACT

    OpenAIRE

    Suoniemi, Samppa; Meyer-Waarden, Lars; Munzel, Andreas

    2017-01-01

    Customer information plays a key role in managing successful relationships with valuable customers. Big data customer analytics use (BD use), i.e., the extent to which customer information derived from big data analytics guides marketing decisions, helps firms better meet customer needs for competitive advantage. This study addresses three research questions: What are the key antecedents of big data customer analytics use? How, and to what extent, does big data customer an...

  2. Big data in Finnish financial services

    OpenAIRE

    Laurila, M. (Mikko)

    2017-01-01

    Abstract This thesis aims to explore the concept of big data, and create understanding of big data maturity in the Finnish financial services industry. The research questions of this thesis are “What kind of big data solutions are being implemented in the Finnish financial services sector?” and “Which factors impede faster implementation of big data solutions in the Finnish financial services sector?”. ...

  3. Soil water repellency and infiltration in coarse-textured soils of burned and unburned sagebrush ecosystems

    Science.gov (United States)

    F. B. Pierson; P. R. Robichaud; C. A. Moffet; K. E. Spaeth; C. J. Williams; S. P. Hardegree; P. E. Clark

    2008-01-01

    Millions of dollars are spent each year in the United States to mitigate the effects of wildfires and reduce the risk of flash floods and debris flows. Research from forested, chaparral, and rangeland communities indicate that severe wildfires can cause significant increases in soil water repellency resulting in increased runoff and erosion. Few data are available to...

  4. Ecosystem water availability in juniper versus sagebrush snow-dominated rangelands

    Science.gov (United States)

    Western Juniper (J. occidentalis Hook.) now dominates over 3.6 million ha of rangeland in the Intermountain Western US. Critical ecological relationships among snow distribution, water budgets, plant community transitions, and habitat requirements for wildlife, such as sage grouse, remain poorly und...

  5. A molecular phylogenetic approach to western North America endemic Artemisia and allies (Asteraceae): Untangling the sagebrushes

    Science.gov (United States)

    Sonia Garcia; E. Durant McArthur; Jaume Pellicer; Stewart C. Sanderson; Joan Valles; Teresa Garnatje

    2011-01-01

    Premise of the study: Artemisia subgenus Tridentatae plants characterize the North American Intermountain West. These are landscape-dominant constituents of important ecological communities and habitats for endemic wildlife. Together with allied species and genera (Picrothamnus and Sphaeromeria), they make up an intricate series of taxa whose limits are uncertain,...

  6. China: Big Changes Coming Soon

    Science.gov (United States)

    Rowen, Henry S.

    2011-01-01

    Big changes are ahead for China, probably abrupt ones. The economy has grown so rapidly for many years, over 30 years at an average of nine percent a year, that its size makes it a major player in trade and finance and increasingly in political and military matters. This growth is not only of great importance internationally, it is already having…

  7. Big data and urban governance

    NARCIS (Netherlands)

    Taylor, L.; Richter, C.; Gupta, J.; Pfeffer, K.; Verrest, H.; Ros-Tonen, M.

    2015-01-01

    This chapter examines the ways in which big data is involved in the rise of smart cities. Mobile phones, sensors and online applications produce streams of data which are used to regulate and plan the city, often in real time, but which presents challenges as to how the city’s functions are seen and

  8. Big Data for personalized healthcare

    NARCIS (Netherlands)

    Siemons, Liseth; Sieverink, Floor; Vollenbroek, Wouter; van de Wijngaert, Lidwien; Braakman-Jansen, Annemarie; van Gemert-Pijnen, Lisette

    2016-01-01

    Big Data, often defined according to the 5V model (volume, velocity, variety, veracity and value), is seen as the key towards personalized healthcare. However, it also confronts us with new technological and ethical challenges that require more sophisticated data management tools and data analysis

  9. Big data en gelijke behandeling

    NARCIS (Netherlands)

    Lammerant, Hans; de Hert, Paul; Blok, P.H.; Blok, P.H.

    2017-01-01

    In dit hoofdstuk bekijken we allereerst de voornaamste basisbegrippen inzake gelijke behandeling en discriminatie (paragraaf 6.2). Vervolgens kijken we haar het Nederlandse en Europese juridisch kader inzake non-discriminatie (paragraaf 6.3-6.5) en hoe die regels moeten worden toegepast op big

  10. Research Ethics in Big Data.

    Science.gov (United States)

    Hammer, Marilyn J

    2017-05-01

    The ethical conduct of research includes, in part, patient agreement to participate in studies and the protection of health information. In the evolving world of data science and the accessibility of large quantities of web-based data created by millions of individuals, novel methodologic approaches to answering research questions are emerging. This article explores research ethics in the context of big data.

  11. Big data e data science

    OpenAIRE

    Cavique, Luís

    2014-01-01

    Neste artigo foram apresentados os conceitos básicos de Big Data e a nova área a que deu origem, a Data Science. Em Data Science foi discutida e exemplificada a noção de redução da dimensionalidade dos dados.

  12. The Case for "Big History."

    Science.gov (United States)

    Christian, David

    1991-01-01

    Urges an approach to the teaching of history that takes the largest possible perspective, crossing time as well as space. Discusses the problems and advantages of such an approach. Describes a course on "big" history that begins with time, creation myths, and astronomy, and moves on to paleontology and evolution. (DK)

  13. Finding errors in big data

    NARCIS (Netherlands)

    Puts, Marco; Daas, Piet; de Waal, A.G.

    No data source is perfect. Mistakes inevitably creep in. Spotting errors is hard enough when dealing with survey responses from several thousand people, but the difficulty is multiplied hugely when that mysterious beast Big Data comes into play. Statistics Netherlands is about to publish its first

  14. Sampling Operations on Big Data

    Science.gov (United States)

    2015-11-29

    gories. These include edge sampling methods where edges are selected by a predetermined criteria; snowball sampling methods where algorithms start... Sampling Operations on Big Data Vijay Gadepally, Taylor Herr, Luke Johnson, Lauren Milechin, Maja Milosavljevic, Benjamin A. Miller Lincoln...process and disseminate information for discovery and exploration under real-time constraints. Common signal processing operations such as sampling and

  15. The International Big History Association

    Science.gov (United States)

    Duffy, Michael; Duffy, D'Neil

    2013-01-01

    IBHA, the International Big History Association, was organized in 2010 and "promotes the unified, interdisciplinary study and teaching of history of the Cosmos, Earth, Life, and Humanity." This is the vision that Montessori embraced long before the discoveries of modern science fleshed out the story of the evolving universe. "Big…

  16. NASA's Big Data Task Force

    Science.gov (United States)

    Holmes, C. P.; Kinter, J. L.; Beebe, R. F.; Feigelson, E.; Hurlburt, N. E.; Mentzel, C.; Smith, G.; Tino, C.; Walker, R. J.

    2017-12-01

    Two years ago NASA established the Ad Hoc Big Data Task Force (BDTF - https://science.nasa.gov/science-committee/subcommittees/big-data-task-force), an advisory working group with the NASA Advisory Council system. The scope of the Task Force included all NASA Big Data programs, projects, missions, and activities. The Task Force focused on such topics as exploring the existing and planned evolution of NASA's science data cyber-infrastructure that supports broad access to data repositories for NASA Science Mission Directorate missions; best practices within NASA, other Federal agencies, private industry and research institutions; and Federal initiatives related to big data and data access. The BDTF has completed its two-year term and produced several recommendations plus four white papers for NASA's Science Mission Directorate. This presentation will discuss the activities and results of the TF including summaries of key points from its focused study topics. The paper serves as an introduction to the papers following in this ESSI session.

  17. Big Math for Little Kids

    Science.gov (United States)

    Greenes, Carole; Ginsburg, Herbert P.; Balfanz, Robert

    2004-01-01

    "Big Math for Little Kids," a comprehensive program for 4- and 5-year-olds, develops and expands on the mathematics that children know and are capable of doing. The program uses activities and stories to develop ideas about number, shape, pattern, logical reasoning, measurement, operations on numbers, and space. The activities introduce the…

  18. BIG DATA IN BUSINESS ENVIRONMENT

    Directory of Open Access Journals (Sweden)

    Logica BANICA

    2015-06-01

    Full Text Available In recent years, dealing with a lot of data originating from social media sites and mobile communications among data from business environments and institutions, lead to the definition of a new concept, known as Big Data. The economic impact of the sheer amount of data produced in a last two years has increased rapidly. It is necessary to aggregate all types of data (structured and unstructured in order to improve current transactions, to develop new business models, to provide a real image of the supply and demand and thereby, generate market advantages. So, the companies that turn to Big Data have a competitive advantage over other firms. Looking from the perspective of IT organizations, they must accommodate the storage and processing Big Data, and provide analysis tools that are easily integrated into business processes. This paper aims to discuss aspects regarding the Big Data concept, the principles to build, organize and analyse huge datasets in the business environment, offering a three-layer architecture, based on actual software solutions. Also, the article refers to the graphical tools for exploring and representing unstructured data, Gephi and NodeXL.

  19. From Big Bang to Eternity?

    Indian Academy of Sciences (India)

    at different distances (that is, at different epochs in the past) to come to this ... that the expansion started billions of years ago from an explosive Big Bang. Recent research sheds new light on the key cosmological question about the distant ...

  20. Big Data: Implications for Health System Pharmacy.

    Science.gov (United States)

    Stokes, Laura B; Rogers, Joseph W; Hertig, John B; Weber, Robert J

    2016-07-01

    Big Data refers to datasets that are so large and complex that traditional methods and hardware for collecting, sharing, and analyzing them are not possible. Big Data that is accurate leads to more confident decision making, improved operational efficiency, and reduced costs. The rapid growth of health care information results in Big Data around health services, treatments, and outcomes, and Big Data can be used to analyze the benefit of health system pharmacy services. The goal of this article is to provide a perspective on how Big Data can be applied to health system pharmacy. It will define Big Data, describe the impact of Big Data on population health, review specific implications of Big Data in health system pharmacy, and describe an approach for pharmacy leaders to effectively use Big Data. A few strategies involved in managing Big Data in health system pharmacy include identifying potential opportunities for Big Data, prioritizing those opportunities, protecting privacy concerns, promoting data transparency, and communicating outcomes. As health care information expands in its content and becomes more integrated, Big Data can enhance the development of patient-centered pharmacy services.

  1. Big data: een zoektocht naar instituties

    NARCIS (Netherlands)

    van der Voort, H.G.; Crompvoets, J

    2016-01-01

    Big data is a well-known phenomenon, even a buzzword nowadays. It refers to an abundance of data and new possibilities to process and use them. Big data is subject of many publications. Some pay attention to the many possibilities of big data, others warn us for their consequences. This special

  2. A SWOT Analysis of Big Data

    Science.gov (United States)

    Ahmadi, Mohammad; Dileepan, Parthasarati; Wheatley, Kathleen K.

    2016-01-01

    This is the decade of data analytics and big data, but not everyone agrees with the definition of big data. Some researchers see it as the future of data analysis, while others consider it as hype and foresee its demise in the near future. No matter how it is defined, big data for the time being is having its glory moment. The most important…

  3. Data, Data, Data : Big, Linked & Open

    NARCIS (Netherlands)

    Folmer, E.J.A.; Krukkert, D.; Eckartz, S.M.

    2013-01-01

    De gehele business en IT-wereld praat op dit moment over Big Data, een trend die medio 2013 Cloud Computing is gepasseerd (op basis van Google Trends). Ook beleidsmakers houden zich actief bezig met Big Data. Neelie Kroes, vice-president van de Europese Commissie, spreekt over de ‘Big Data

  4. A survey of big data research

    Science.gov (United States)

    Fang, Hua; Zhang, Zhaoyang; Wang, Chanpaul Jin; Daneshmand, Mahmoud; Wang, Chonggang; Wang, Honggang

    2015-01-01

    Big data create values for business and research, but pose significant challenges in terms of networking, storage, management, analytics and ethics. Multidisciplinary collaborations from engineers, computer scientists, statisticians and social scientists are needed to tackle, discover and understand big data. This survey presents an overview of big data initiatives, technologies and research in industries and academia, and discusses challenges and potential solutions. PMID:26504265

  5. The BigBoss Experiment

    Energy Technology Data Exchange (ETDEWEB)

    Schelgel, D.; Abdalla, F.; Abraham, T.; Ahn, C.; Allende Prieto, C.; Annis, J.; Aubourg, E.; Azzaro, M.; Bailey, S.; Baltay, C.; Baugh, C.; Bebek, C.; Becerril, S.; Blanton, M.; Bolton, A.; Bromley, B.; Cahn, R.; Carton, P.-H.; Cervanted-Cota, J.L.; Chu, Y.; Cortes, M.; /APC, Paris /Brookhaven /IRFU, Saclay /Marseille, CPPM /Marseille, CPT /Durham U. / /IEU, Seoul /Fermilab /IAA, Granada /IAC, La Laguna / /IAC, Mexico / / /Madrid, IFT /Marseille, Lab. Astrophys. / / /New York U. /Valencia U.

    2012-06-07

    BigBOSS is a Stage IV ground-based dark energy experiment to study baryon acoustic oscillations (BAO) and the growth of structure with a wide-area galaxy and quasar redshift survey over 14,000 square degrees. It has been conditionally accepted by NOAO in response to a call for major new instrumentation and a high-impact science program for the 4-m Mayall telescope at Kitt Peak. The BigBOSS instrument is a robotically-actuated, fiber-fed spectrograph capable of taking 5000 simultaneous spectra over a wavelength range from 340 nm to 1060 nm, with a resolution R = {lambda}/{Delta}{lambda} = 3000-4800. Using data from imaging surveys that are already underway, spectroscopic targets are selected that trace the underlying dark matter distribution. In particular, targets include luminous red galaxies (LRGs) up to z = 1.0, extending the BOSS LRG survey in both redshift and survey area. To probe the universe out to even higher redshift, BigBOSS will target bright [OII] emission line galaxies (ELGs) up to z = 1.7. In total, 20 million galaxy redshifts are obtained to measure the BAO feature, trace the matter power spectrum at smaller scales, and detect redshift space distortions. BigBOSS will provide additional constraints on early dark energy and on the curvature of the universe by measuring the Ly-alpha forest in the spectra of over 600,000 2.2 < z < 3.5 quasars. BigBOSS galaxy BAO measurements combined with an analysis of the broadband power, including the Ly-alpha forest in BigBOSS quasar spectra, achieves a FOM of 395 with Planck plus Stage III priors. This FOM is based on conservative assumptions for the analysis of broad band power (k{sub max} = 0.15), and could grow to over 600 if current work allows us to push the analysis to higher wave numbers (k{sub max} = 0.3). BigBOSS will also place constraints on theories of modified gravity and inflation, and will measure the sum of neutrino masses to 0.024 eV accuracy.

  6. Big Data - Smart Health Strategies

    Science.gov (United States)

    2014-01-01

    Summary Objectives To select best papers published in 2013 in the field of big data and smart health strategies, and summarize outstanding research efforts. Methods A systematic search was performed using two major bibliographic databases for relevant journal papers. The references obtained were reviewed in a two-stage process, starting with a blinded review performed by the two section editors, and followed by a peer review process operated by external reviewers recognized as experts in the field. Results The complete review process selected four best papers, illustrating various aspects of the special theme, among them: (a) using large volumes of unstructured data and, specifically, clinical notes from Electronic Health Records (EHRs) for pharmacovigilance; (b) knowledge discovery via querying large volumes of complex (both structured and unstructured) biological data using big data technologies and relevant tools; (c) methodologies for applying cloud computing and big data technologies in the field of genomics, and (d) system architectures enabling high-performance access to and processing of large datasets extracted from EHRs. Conclusions The potential of big data in biomedicine has been pinpointed in various viewpoint papers and editorials. The review of current scientific literature illustrated a variety of interesting methods and applications in the field, but still the promises exceed the current outcomes. As we are getting closer towards a solid foundation with respect to common understanding of relevant concepts and technical aspects, and the use of standardized technologies and tools, we can anticipate to reach the potential that big data offer for personalized medicine and smart health strategies in the near future. PMID:25123721

  7. Health level seven interoperability strategy: big data, incrementally structured.

    Science.gov (United States)

    Dolin, R H; Rogers, B; Jaffe, C

    2015-01-01

    Describe how the HL7 Clinical Document Architecture (CDA), a foundational standard in US Meaningful Use, contributes to a "big data, incrementally structured" interoperability strategy, whereby data structured incrementally gets large amounts of data flowing faster. We present cases showing how this approach is leveraged for big data analysis. To support the assertion that semi-structured narrative in CDA format can be a useful adjunct in an overall big data analytic approach, we present two case studies. The first assesses an organization's ability to generate clinical quality reports using coded data alone vs. coded data supplemented by CDA narrative. The second leverages CDA to construct a network model for referral management, from which additional observations can be gleaned. The first case shows that coded data supplemented by CDA narrative resulted in significant variances in calculated performance scores. In the second case, we found that the constructed network model enables the identification of differences in patient characteristics among different referral work flows. The CDA approach goes after data indirectly, by focusing first on the flow of narrative, which is then incrementally structured. A quantitative assessment of whether this approach will lead to a greater flow of data and ultimately a greater flow of structured data vs. other approaches is planned as a future exercise. Along with growing adoption of CDA, we are now seeing the big data community explore the standard, particularly given its potential to supply analytic en- gines with volumes of data previously not possible.

  8. Data privacy foundations, new developments and the big data challenge

    CERN Document Server

    Torra, Vicenç

    2017-01-01

    This book offers a broad, cohesive overview of the field of data privacy. It discusses, from a technological perspective, the problems and solutions of the three main communities working on data privacy: statistical disclosure control (those with a statistical background), privacy-preserving data mining (those working with data bases and data mining), and privacy-enhancing technologies (those involved in communications and security) communities. Presenting different approaches, the book describes alternative privacy models and disclosure risk measures as well as data protection procedures for respondent, holder and user privacy. It also discusses specific data privacy problems and solutions for readers who need to deal with big data.

  9. Big-Leaf Mahogany on CITES Appendix II: Big Challenge, Big Opportunity

    Science.gov (United States)

    JAMES GROGAN; PAULO BARRETO

    2005-01-01

    On 15 November 2003, big-leaf mahogany (Swietenia macrophylla King, Meliaceae), the most valuable widely traded Neotropical timber tree, gained strengthened regulatory protection from its listing on Appendix II of the Convention on International Trade in Endangered Species ofWild Fauna and Flora (CITES). CITES is a United Nations-chartered agreement signed by 164...

  10. Big Bang Day : The Great Big Particle Adventure - 3. Origins

    CERN Multimedia

    2008-01-01

    In this series, comedian and physicist Ben Miller asks the CERN scientists what they hope to find. If the LHC is successful, it will explain the nature of the Universe around us in terms of a few simple ingredients and a few simple rules. But the Universe now was forged in a Big Bang where conditions were very different, and the rules were very different, and those early moments were crucial to determining how things turned out later. At the LHC they can recreate conditions as they were billionths of a second after the Big Bang, before atoms and nuclei existed. They can find out why matter and antimatter didn't mutually annihilate each other to leave behind a Universe of pure, brilliant light. And they can look into the very structure of space and time - the fabric of the Universe

  11. Antigravity and the big crunch/big bang transition

    Science.gov (United States)

    Bars, Itzhak; Chen, Shih-Hung; Steinhardt, Paul J.; Turok, Neil

    2012-08-01

    We point out a new phenomenon which seems to be generic in 4d effective theories of scalar fields coupled to Einstein gravity, when applied to cosmology. A lift of such theories to a Weyl-invariant extension allows one to define classical evolution through cosmological singularities unambiguously, and hence construct geodesically complete background spacetimes. An attractor mechanism ensures that, at the level of the effective theory, generic solutions undergo a big crunch/big bang transition by contracting to zero size, passing through a brief antigravity phase, shrinking to zero size again, and re-emerging into an expanding normal gravity phase. The result may be useful for the construction of complete bouncing cosmologies like the cyclic model.

  12. Antigravity and the big crunch/big bang transition

    Energy Technology Data Exchange (ETDEWEB)

    Bars, Itzhak [Department of Physics and Astronomy, University of Southern California, Los Angeles, CA 90089-2535 (United States); Chen, Shih-Hung [Perimeter Institute for Theoretical Physics, Waterloo, ON N2L 2Y5 (Canada); Department of Physics and School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287-1404 (United States); Steinhardt, Paul J., E-mail: steinh@princeton.edu [Department of Physics and Princeton Center for Theoretical Physics, Princeton University, Princeton, NJ 08544 (United States); Turok, Neil [Perimeter Institute for Theoretical Physics, Waterloo, ON N2L 2Y5 (Canada)

    2012-08-29

    We point out a new phenomenon which seems to be generic in 4d effective theories of scalar fields coupled to Einstein gravity, when applied to cosmology. A lift of such theories to a Weyl-invariant extension allows one to define classical evolution through cosmological singularities unambiguously, and hence construct geodesically complete background spacetimes. An attractor mechanism ensures that, at the level of the effective theory, generic solutions undergo a big crunch/big bang transition by contracting to zero size, passing through a brief antigravity phase, shrinking to zero size again, and re-emerging into an expanding normal gravity phase. The result may be useful for the construction of complete bouncing cosmologies like the cyclic model.

  13. Antigravity and the big crunch/big bang transition

    International Nuclear Information System (INIS)

    Bars, Itzhak; Chen, Shih-Hung; Steinhardt, Paul J.; Turok, Neil

    2012-01-01

    We point out a new phenomenon which seems to be generic in 4d effective theories of scalar fields coupled to Einstein gravity, when applied to cosmology. A lift of such theories to a Weyl-invariant extension allows one to define classical evolution through cosmological singularities unambiguously, and hence construct geodesically complete background spacetimes. An attractor mechanism ensures that, at the level of the effective theory, generic solutions undergo a big crunch/big bang transition by contracting to zero size, passing through a brief antigravity phase, shrinking to zero size again, and re-emerging into an expanding normal gravity phase. The result may be useful for the construction of complete bouncing cosmologies like the cyclic model.

  14. Solution of a braneworld big crunch/big bang cosmology

    International Nuclear Information System (INIS)

    McFadden, Paul L.; Turok, Neil; Steinhardt, Paul J.

    2007-01-01

    We solve for the cosmological perturbations in a five-dimensional background consisting of two separating or colliding boundary branes, as an expansion in the collision speed V divided by the speed of light c. Our solution permits a detailed check of the validity of four-dimensional effective theory in the vicinity of the event corresponding to the big crunch/big bang singularity. We show that the four-dimensional description fails at the first nontrivial order in (V/c) 2 . At this order, there is nontrivial mixing of the two relevant four-dimensional perturbation modes (the growing and decaying modes) as the boundary branes move from the narrowly separated limit described by Kaluza-Klein theory to the well-separated limit where gravity is confined to the positive-tension brane. We comment on the cosmological significance of the result and compute other quantities of interest in five-dimensional cosmological scenarios

  15. The ethics of big data in big agriculture

    Directory of Open Access Journals (Sweden)

    Isabelle M. Carbonell

    2016-03-01

    Full Text Available This paper examines the ethics of big data in agriculture, focusing on the power asymmetry between farmers and large agribusinesses like Monsanto. Following the recent purchase of Climate Corp., Monsanto is currently the most prominent biotech agribusiness to buy into big data. With wireless sensors on tractors monitoring or dictating every decision a farmer makes, Monsanto can now aggregate large quantities of previously proprietary farming data, enabling a privileged position with unique insights on a field-by-field basis into a third or more of the US farmland. This power asymmetry may be rebalanced through open-sourced data, and publicly-funded data analytic tools which rival Climate Corp. in complexity and innovation for use in the public domain.

  16. Big Data – Big Deal for Organization Design?

    OpenAIRE

    Janne J. Korhonen

    2014-01-01

    Analytics is an increasingly important source of competitive advantage. It has even been posited that big data will be the next strategic emphasis of organizations and that analytics capability will be manifested in organizational structure. In this article, I explore how analytics capability might be reflected in organizational structure using the notion of  “requisite organization” developed by Jaques (1998). Requisite organization argues that a new strategic emphasis requires the addition ...

  17. Nowcasting using news topics Big Data versus big bank

    OpenAIRE

    Thorsrud, Leif Anders

    2016-01-01

    The agents in the economy use a plethora of high frequency information, including news media, to guide their actions and thereby shape aggregate economic fluctuations. Traditional nowcasting approches have to a relatively little degree made use of such information. In this paper, I show how unstructured textual information in a business newspaper can be decomposed into daily news topics and used to nowcast quarterly GDP growth. Compared with a big bank of experts, here represented by o cial c...

  18. Big Data in Medicine is Driving Big Changes

    Science.gov (United States)

    Verspoor, K.

    2014-01-01

    Summary Objectives To summarise current research that takes advantage of “Big Data” in health and biomedical informatics applications. Methods Survey of trends in this work, and exploration of literature describing how large-scale structured and unstructured data sources are being used to support applications from clinical decision making and health policy, to drug design and pharmacovigilance, and further to systems biology and genetics. Results The survey highlights ongoing development of powerful new methods for turning that large-scale, and often complex, data into information that provides new insights into human health, in a range of different areas. Consideration of this body of work identifies several important paradigm shifts that are facilitated by Big Data resources and methods: in clinical and translational research, from hypothesis-driven research to data-driven research, and in medicine, from evidence-based practice to practice-based evidence. Conclusions The increasing scale and availability of large quantities of health data require strategies for data management, data linkage, and data integration beyond the limits of many existing information systems, and substantial effort is underway to meet those needs. As our ability to make sense of that data improves, the value of the data will continue to increase. Health systems, genetics and genomics, population and public health; all areas of biomedicine stand to benefit from Big Data and the associated technologies. PMID:25123716

  19. Big data is not a monolith

    CERN Document Server

    Ekbia, Hamid R; Mattioli, Michael

    2016-01-01

    Big data is ubiquitous but heterogeneous. Big data can be used to tally clicks and traffic on web pages, find patterns in stock trades, track consumer preferences, identify linguistic correlations in large corpuses of texts. This book examines big data not as an undifferentiated whole but contextually, investigating the varied challenges posed by big data for health, science, law, commerce, and politics. Taken together, the chapters reveal a complex set of problems, practices, and policies. The advent of big data methodologies has challenged the theory-driven approach to scientific knowledge in favor of a data-driven one. Social media platforms and self-tracking tools change the way we see ourselves and others. The collection of data by corporations and government threatens privacy while promoting transparency. Meanwhile, politicians, policy makers, and ethicists are ill-prepared to deal with big data's ramifications. The contributors look at big data's effect on individuals as it exerts social control throu...

  20. Big Data for Precision Medicine

    Directory of Open Access Journals (Sweden)

    Daniel Richard Leff

    2015-09-01

    Full Text Available This article focuses on the potential impact of big data analysis to improve health, prevent and detect disease at an earlier stage, and personalize interventions. The role that big data analytics may have in interrogating the patient electronic health record toward improved clinical decision support is discussed. We examine developments in pharmacogenetics that have increased our appreciation of the reasons why patients respond differently to chemotherapy. We also assess the expansion of online health communications and the way in which this data may be capitalized on in order to detect public health threats and control or contain epidemics. Finally, we describe how a new generation of wearable and implantable body sensors may improve wellbeing, streamline management of chronic diseases, and improve the quality of surgical implants.

  1. Big Data hvor N=1

    DEFF Research Database (Denmark)

    Bardram, Jakob Eyvind

    2017-01-01

    Forskningen vedrørende anvendelsen af ’big data’ indenfor sundhed er kun lige begyndt, og kan på sigt blive en stor hjælp i forhold til at tilrettelægge en mere personlig og helhedsorienteret sundhedsindsats for multisyge. Personlig sundhedsteknologi, som kort præsenteres i dette kapital, rummer et...... stor potentiale for at gennemføre ’big data’ analyser for den enkelte person, det vil sige hvor N=1. Der er store teknologiske udfordringer i at få lavet teknologier og metoder til at indsamle og håndtere personlige data, som kan deles, på tværs på en standardiseret, forsvarlig, robust, sikker og ikke...

  2. George and the big bang

    CERN Document Server

    Hawking, Lucy; Parsons, Gary

    2012-01-01

    George has problems. He has twin baby sisters at home who demand his parents’ attention. His beloved pig Freddy has been exiled to a farm, where he’s miserable. And worst of all, his best friend, Annie, has made a new friend whom she seems to like more than George. So George jumps at the chance to help Eric with his plans to run a big experiment in Switzerland that seeks to explore the earliest moment of the universe. But there is a conspiracy afoot, and a group of evildoers is planning to sabotage the experiment. Can George repair his friendship with Annie and piece together the clues before Eric’s experiment is destroyed forever? This engaging adventure features essays by Professor Stephen Hawking and other eminent physicists about the origins of the universe and ends with a twenty-page graphic novel that explains how the Big Bang happened—in reverse!

  3. Did the Big Bang begin?

    International Nuclear Information System (INIS)

    Levy-Leblond, J.

    1990-01-01

    It is argued that the age of the universe may well be numerically finite (20 billion years or so) and conceptually infinite. A new and natural time scale is defined on a physical basis using group-theoretical arguments. An additive notion of time is obtained according to which the age of the universe is indeed infinite. In other words, never did the Big Bang begin. This new time scale is not supposed to replace the ordinary cosmic time scale, but to supplement it (in the same way as rapidity has taken a place by the side of velocity in Einsteinian relativity). The question is discussed within the framework of conventional (big-bang) and classical (nonquantum) cosmology, but could easily be extended to more elaborate views, as the purpose is not so much to modify present theories as to reach a deeper understanding of their meaning

  4. Big Data and central banks

    OpenAIRE

    David Bholat

    2015-01-01

    This commentary recaps a Centre for Central Banking Studies event held at the Bank of England on 2–3 July 2014. The article covers three main points. First, it situates the Centre for Central Banking Studies event within the context of the Bank’s Strategic Plan and initiatives. Second, it summarises and reflects on major themes from the event. Third, the article links central banks’ emerging interest in Big Data approaches with their broader uptake by other economic agents.

  5. Big Bang or vacuum fluctuation

    International Nuclear Information System (INIS)

    Zel'dovich, Ya.B.

    1980-01-01

    Some general properties of vacuum fluctuations in quantum field theory are described. The connection between the ''energy dominance'' of the energy density of vacuum fluctuations in curved space-time and the presence of singularity is discussed. It is pointed out that a de-Sitter space-time (with the energy density of the vacuum fluctuations in the Einstein equations) that matches the expanding Friedman solution may describe the history of the Universe before the Big Bang. (P.L.)

  6. Big bang is not needed

    Energy Technology Data Exchange (ETDEWEB)

    Allen, A.D.

    1976-02-01

    Recent computer simulations indicate that a system of n gravitating masses breaks up, even when the total energy is negative. As a result, almost any initial phase-space distribution results in a universe that eventually expands under the Hubble law. Hence Hubble expansion implies little regarding an initial cosmic state. Especially it does not imply the singularly dense superpositioned state used in the big bang model.

  7. Personality correlates of pathological gambling derived from Big Three and Big Five personality models.

    Science.gov (United States)

    Miller, Joshua D; Mackillop, James; Fortune, Erica E; Maples, Jessica; Lance, Charles E; Keith Campbell, W; Goodie, Adam S

    2013-03-30

    Personality traits have proved to be consistent and important factors in a variety of externalizing behaviors including addiction, aggression, and antisocial behavior. Given the comorbidity of these behaviors with pathological gambling (PG), it is important to test the degree to which PG shares these trait correlates. In a large community sample of regular gamblers (N=354; 111 with diagnoses of pathological gambling), the relations between measures of two major models of personality - Big Three and Big Five - were examined in relation to PG symptoms derived from a semi-structured diagnostic interview. Across measures, traits related to the experience of strong negative emotions were the most consistent correlates of PG, regardless of whether they were analyzed using bivariate or multivariate analyses. In several instances, however, the relations between personality and PG were moderated by demographic variable such as gender, race, and age. It will be important for future empirical work of this nature to pay closer attention to potentially important moderators of these relations. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  8. Big data: the management revolution.

    Science.gov (United States)

    McAfee, Andrew; Brynjolfsson, Erik

    2012-10-01

    Big data, the authors write, is far more powerful than the analytics of the past. Executives can measure and therefore manage more precisely than ever before. They can make better predictions and smarter decisions. They can target more-effective interventions in areas that so far have been dominated by gut and intuition rather than by data and rigor. The differences between big data and analytics are a matter of volume, velocity, and variety: More data now cross the internet every second than were stored in the entire internet 20 years ago. Nearly real-time information makes it possible for a company to be much more agile than its competitors. And that information can come from social networks, images, sensors, the web, or other unstructured sources. The managerial challenges, however, are very real. Senior decision makers have to learn to ask the right questions and embrace evidence-based decision making. Organizations must hire scientists who can find patterns in very large data sets and translate them into useful business information. IT departments have to work hard to integrate all the relevant internal and external sources of data. The authors offer two success stories to illustrate how companies are using big data: PASSUR Aerospace enables airlines to match their actual and estimated arrival times. Sears Holdings directly analyzes its incoming store data to make promotions much more precise and faster.

  9. Big Data Comes to School

    Directory of Open Access Journals (Sweden)

    Bill Cope

    2016-03-01

    Full Text Available The prospect of “big data” at once evokes optimistic views of an information-rich future and concerns about surveillance that adversely impacts our personal and private lives. This overview article explores the implications of big data in education, focusing by way of example on data generated by student writing. We have chosen writing because it presents particular complexities, highlighting the range of processes for collecting and interpreting evidence of learning in the era of computer-mediated instruction and assessment as well as the challenges. Writing is significant not only because it is central to the core subject area of literacy; it is also an ideal medium for the representation of deep disciplinary knowledge across a number of subject areas. After defining what big data entails in education, we map emerging sources of evidence of learning that separately and together have the potential to generate unprecedented amounts of data: machine assessments, structured data embedded in learning, and unstructured data collected incidental to learning activity. Our case is that these emerging sources of evidence of learning have significant implications for the traditional relationships between assessment and instruction. Moreover, for educational researchers, these data are in some senses quite different from traditional evidentiary sources, and this raises a number of methodological questions. The final part of the article discusses implications for practice in an emerging field of education data science, including publication of data, data standards, and research ethics.

  10. Direct and indirect effects of petroleum production activities on the western fence lizard (Sceloporus occidentalis) as a surrogate for the dunes sagebrush lizard (Sceloporus arenicolus).

    Science.gov (United States)

    Weir, Scott M; Knox, Ami; Talent, Larry G; Anderson, Todd A; Salice, Christopher J

    2016-05-01

    The dunes sagebrush lizard (Sceloporus arenicolus) is a habitat specialist of conservation concern limited to shin oak sand dune systems of New Mexico and Texas (USA). Because much of the dunes sagebrush lizard's habitat occurs in areas of high oil and gas production, there may be direct and indirect effects of these activities. The congeneric Western fence lizard (Sceloporus occidentalis) was used as a surrogate species to determine direct effects of 2 contaminants associated with oil and gas drilling activities in the Permian Basin (NM and TX, USA): herbicide formulations (Krovar and Quest) and hydrogen sulfide gas (H2S). Lizards were exposed to 2 concentrations of H2 S (30 ppm or 90 ppm) and herbicide formulations (1× or 2× label application rate) representing high-end exposure scenarios. Sublethal behavioral endpoints were evaluated, including sprint speed and time to prey detection and capture. Neither H2S nor herbicide formulations caused significant behavioral effects compared to controls. To understand potential indirect effects of oil and gas drilling on the prey base, terrestrial invertebrate biomass and order diversity were quantified at impacted sites to compare with nonimpacted sites. A significant decrease in biomass was found at impacted sites, but no significant effects on diversity. The results suggest little risk from direct toxic effects, but the potential for indirect effects should be further explored. © 2015 SETAC.

  11. Big Data Analytics Tools as Applied to ATLAS Event Data

    CERN Document Server

    Vukotic, Ilija; The ATLAS collaboration

    2016-01-01

    Big Data technologies have proven to be very useful for storage, processing and visualization of derived metrics associated with ATLAS distributed computing (ADC) services. Log file data and database records, and metadata from a diversity of systems have been aggregated and indexed to create an analytics platform for ATLAS ADC operations analysis. Dashboards, wide area data access cost metrics, user analysis patterns, and resource utilization efficiency charts are produced flexibly through queries against a powerful analytics cluster. Here we explore whether these techniques and analytics ecosystem can be applied to add new modes of open, quick, and pervasive access to ATLAS event data so as to simplify access and broaden the reach of ATLAS public data to new communities of users. An ability to efficiently store, filter, search and deliver ATLAS data at the event and/or sub-event level in a widely supported format would enable or significantly simplify usage of big data, statistical and machine learning tools...

  12. Development and validation of Big Four personality scales for the Schedule for Nonadaptive and Adaptive Personality--Second Edition (SNAP-2).

    Science.gov (United States)

    Calabrese, William R; Rudick, Monica M; Simms, Leonard J; Clark, Lee Anna

    2012-09-01

    Recently, integrative, hierarchical models of personality and personality disorder (PD)--such as the Big Three, Big Four, and Big Five trait models--have gained support as a unifying dimensional framework for describing PD. However, no measures to date can simultaneously represent each of these potentially interesting levels of the personality hierarchy. To unify these measurement models psychometrically, we sought to develop Big Five trait scales within the Schedule for Nonadaptive and Adaptive Personality--Second Edition (SNAP-2). Through structural and content analyses, we examined relations between the SNAP-2, the Big Five Inventory (BFI), and the NEO Five-Factor Inventory (NEO-FFI) ratings in a large data set (N = 8,690), including clinical, military, college, and community participants. Results yielded scales consistent with the Big Four model of personality (i.e., Neuroticism, Conscientiousness, Introversion, and Antagonism) and not the Big Five, as there were insufficient items related to Openness. Resulting scale scores demonstrated strong internal consistency and temporal stability. Structural validity and external validity were supported by strong convergent and discriminant validity patterns between Big Four scale scores and other personality trait scores and expectable patterns of self-peer agreement. Descriptive statistics and community-based norms are provided. The SNAP-2 Big Four Scales enable researchers and clinicians to assess personality at multiple levels of the trait hierarchy and facilitate comparisons among competing big-trait models. PsycINFO Database Record (c) 2012 APA, all rights reserved.

  13. Development and Validation of Big Four Personality Scales for the Schedule for Nonadaptive and Adaptive Personality-2nd Edition (SNAP-2)

    Science.gov (United States)

    Calabrese, William R.; Rudick, Monica M.; Simms, Leonard J.; Clark, Lee Anna

    2012-01-01

    Recently, integrative, hierarchical models of personality and personality disorder (PD)—such as the Big Three, Big Four and Big Five trait models—have gained support as a unifying dimensional framework for describing PD. However, no measures to date can simultaneously represent each of these potentially interesting levels of the personality hierarchy. To unify these measurement models psychometrically, we sought to develop Big Five trait scales within the Schedule for Adaptive and Nonadaptive Personality–2nd Edition (SNAP-2). Through structural and content analyses, we examined relations between the SNAP-2, Big Five Inventory (BFI), and NEO-Five Factor Inventory (NEO-FFI) ratings in a large data set (N = 8,690), including clinical, military, college, and community participants. Results yielded scales consistent with the Big Four model of personality (i.e., Neuroticism, Conscientiousness, Introversion, and Antagonism) and not the Big Five as there were insufficient items related to Openness. Resulting scale scores demonstrated strong internal consistency and temporal stability. Structural and external validity was supported by strong convergent and discriminant validity patterns between Big Four scale scores and other personality trait scores and expectable patterns of self-peer agreement. Descriptive statistics and community-based norms are provided. The SNAP-2 Big Four Scales enable researchers and clinicians to assess personality at multiple levels of the trait hierarchy and facilitate comparisons among competing “Big Trait” models. PMID:22250598

  14. Turning big bang into big bounce. I. Classical dynamics

    Science.gov (United States)

    Dzierżak, Piotr; Małkiewicz, Przemysław; Piechocki, Włodzimierz

    2009-11-01

    The big bounce (BB) transition within a flat Friedmann-Robertson-Walker model is analyzed in the setting of loop geometry underlying the loop cosmology. We solve the constraint of the theory at the classical level to identify physical phase space and find the Lie algebra of the Dirac observables. We express energy density of matter and geometrical functions in terms of the observables. It is the modification of classical theory by the loop geometry that is responsible for BB. The classical energy scale specific to BB depends on a parameter that should be fixed either by cosmological data or determined theoretically at quantum level, otherwise the energy scale stays unknown.

  15. A peek into the future of radiology using big data applications

    Directory of Open Access Journals (Sweden)

    Amit T Kharat

    2017-01-01

    Full Text Available Big data is extremely large amount of data which is available in the radiology department. Big data is identified by four Vs – Volume, Velocity, Variety, and Veracity. By applying different algorithmic tools and converting raw data to transformed data in such large datasets, there is a possibility of understanding and using radiology data for gaining new knowledge and insights. Big data analytics consists of 6Cs – Connection, Cloud, Cyber, Content, Community, and Customization. The global technological prowess and per-capita capacity to save digital information has roughly doubled every 40 months since the 1980's. By using big data, the planning and implementation of radiological procedures in radiology departments can be given a great boost. Potential applications of big data in the future are scheduling of scans, creating patient-specific personalized scanning protocols, radiologist decision support, emergency reporting, virtual quality assurance for the radiologist, etc. Targeted use of big data applications can be done for images by supporting the analytic process. Screening software tools designed on big data can be used to highlight a region of interest, such as subtle changes in parenchymal density, solitary pulmonary nodule, or focal hepatic lesions, by plotting its multidimensional anatomy. Following this, we can run more complex applications such as three-dimensional multi planar reconstructions (MPR, volumetric rendering (VR, and curved planar reconstruction, which consume higher system resources on targeted data subsets rather than querying the complete cross-sectional imaging dataset. This pre-emptive selection of dataset can substantially reduce the system requirements such as system memory, server load and provide prompt results. However, a word of caution, “big data should not become “dump data” due to inadequate and poor analysis and non-structured improperly stored data. In the near future, big data can ring in the

  16. A peek into the future of radiology using big data applications.

    Science.gov (United States)

    Kharat, Amit T; Singhal, Shubham

    2017-01-01

    Big data is extremely large amount of data which is available in the radiology department. Big data is identified by four Vs - Volume, Velocity, Variety, and Veracity. By applying different algorithmic tools and converting raw data to transformed data in such large datasets, there is a possibility of understanding and using radiology data for gaining new knowledge and insights. Big data analytics consists of 6Cs - Connection, Cloud, Cyber, Content, Community, and Customization. The global technological prowess and per-capita capacity to save digital information has roughly doubled every 40 months since the 1980's. By using big data, the planning and implementation of radiological procedures in radiology departments can be given a great boost. Potential applications of big data in the future are scheduling of scans, creating patient-specific personalized scanning protocols, radiologist decision support, emergency reporting, virtual quality assurance for the radiologist, etc. Targeted use of big data applications can be done for images by supporting the analytic process. Screening software tools designed on big data can be used to highlight a region of interest, such as subtle changes in parenchymal density, solitary pulmonary nodule, or focal hepatic lesions, by plotting its multidimensional anatomy. Following this, we can run more complex applications such as three-dimensional multi planar reconstructions (MPR), volumetric rendering (VR), and curved planar reconstruction, which consume higher system resources on targeted data subsets rather than querying the complete cross-sectional imaging dataset. This pre-emptive selection of dataset can substantially reduce the system requirements such as system memory, server load and provide prompt results. However, a word of caution, "big data should not become "dump data" due to inadequate and poor analysis and non-structured improperly stored data. In the near future, big data can ring in the era of personalized and

  17. A peek into the future of radiology using big data applications

    Science.gov (United States)

    Kharat, Amit T.; Singhal, Shubham

    2017-01-01

    Big data is extremely large amount of data which is available in the radiology department. Big data is identified by four Vs – Volume, Velocity, Variety, and Veracity. By applying different algorithmic tools and converting raw data to transformed data in such large datasets, there is a possibility of understanding and using radiology data for gaining new knowledge and insights. Big data analytics consists of 6Cs – Connection, Cloud, Cyber, Content, Community, and Customization. The global technological prowess and per-capita capacity to save digital information has roughly doubled every 40 months since the 1980's. By using big data, the planning and implementation of radiological procedures in radiology departments can be given a great boost. Potential applications of big data in the future are scheduling of scans, creating patient-specific personalized scanning protocols, radiologist decision support, emergency reporting, virtual quality assurance for the radiologist, etc. Targeted use of big data applications can be done for images by supporting the analytic process. Screening software tools designed on big data can be used to highlight a region of interest, such as subtle changes in parenchymal density, solitary pulmonary nodule, or focal hepatic lesions, by plotting its multidimensional anatomy. Following this, we can run more complex applications such as three-dimensional multi planar reconstructions (MPR), volumetric rendering (VR), and curved planar reconstruction, which consume higher system resources on targeted data subsets rather than querying the complete cross-sectional imaging dataset. This pre-emptive selection of dataset can substantially reduce the system requirements such as system memory, server load and provide prompt results. However, a word of caution, “big data should not become “dump data” due to inadequate and poor analysis and non-structured improperly stored data. In the near future, big data can ring in the era of personalized

  18. Big Data Knowledge in Global Health Education.

    Science.gov (United States)

    Olayinka, Olaniyi; Kekeh, Michele; Sheth-Chandra, Manasi; Akpinar-Elci, Muge

    The ability to synthesize and analyze massive amounts of data is critical to the success of organizations, including those that involve global health. As countries become highly interconnected, increasing the risk for pandemics and outbreaks, the demand for big data is likely to increase. This requires a global health workforce that is trained in the effective use of big data. To assess implementation of big data training in global health, we conducted a pilot survey of members of the Consortium of Universities of Global Health. More than half the respondents did not have a big data training program at their institution. Additionally, the majority agreed that big data training programs will improve global health deliverables, among other favorable outcomes. Given the observed gap and benefits, global health educators may consider investing in big data training for students seeking a career in global health. Copyright © 2017 Icahn School of Medicine at Mount Sinai. Published by Elsevier Inc. All rights reserved.

  19. Big Data Strategy for Telco: Network Transformation

    OpenAIRE

    F. Amin; S. Feizi

    2014-01-01

    Big data has the potential to improve the quality of services; enable infrastructure that businesses depend on to adapt continually and efficiently; improve the performance of employees; help organizations better understand customers; and reduce liability risks. Analytics and marketing models of fixed and mobile operators are falling short in combating churn and declining revenue per user. Big Data presents new method to reverse the way and improve profitability. The benefits of Big Data and ...

  20. Big Data in Shipping - Challenges and Opportunities

    OpenAIRE

    Rødseth, Ørnulf Jan; Perera, Lokukaluge Prasad; Mo, Brage

    2016-01-01

    Big Data is getting popular in shipping where large amounts of information is collected to better understand and improve logistics, emissions, energy consumption and maintenance. Constraints to the use of big data include cost and quality of on-board sensors and data acquisition systems, satellite communication, data ownership and technical obstacles to effective collection and use of big data. New protocol standards may simplify the process of collecting and organizing the data, including in...

  1. Big Data in Action for Government : Big Data Innovation in Public Services, Policy, and Engagement

    OpenAIRE

    World Bank

    2017-01-01

    Governments have an opportunity to harness big data solutions to improve productivity, performance and innovation in service delivery and policymaking processes. In developing countries, governments have an opportunity to adopt big data solutions and leapfrog traditional administrative approaches

  2. Big data optimization recent developments and challenges

    CERN Document Server

    2016-01-01

    The main objective of this book is to provide the necessary background to work with big data by introducing some novel optimization algorithms and codes capable of working in the big data setting as well as introducing some applications in big data optimization for both academics and practitioners interested, and to benefit society, industry, academia, and government. Presenting applications in a variety of industries, this book will be useful for the researchers aiming to analyses large scale data. Several optimization algorithms for big data including convergent parallel algorithms, limited memory bundle algorithm, diagonal bundle method, convergent parallel algorithms, network analytics, and many more have been explored in this book.

  3. Medical big data: promise and challenges

    Directory of Open Access Journals (Sweden)

    Choong Ho Lee

    2017-03-01

    Full Text Available The concept of big data, commonly characterized by volume, variety, velocity, and veracity, goes far beyond the data type and includes the aspects of data analysis, such as hypothesis-generating, rather than hypothesis-testing. Big data focuses on temporal stability of the association, rather than on causal relationship and underlying probability distribution assumptions are frequently not required. Medical big data as material to be analyzed has various features that are not only distinct from big data of other disciplines, but also distinct from traditional clinical epidemiology. Big data technology has many areas of application in healthcare, such as predictive modeling and clinical decision support, disease or safety surveillance, public health, and research. Big data analytics frequently exploits analytic methods developed in data mining, including classification, clustering, and regression. Medical big data analyses are complicated by many technical issues, such as missing values, curse of dimensionality, and bias control, and share the inherent limitations of observation study, namely the inability to test causality resulting from residual confounding and reverse causation. Recently, propensity score analysis and instrumental variable analysis have been introduced to overcome these limitations, and they have accomplished a great deal. Many challenges, such as the absence of evidence of practical benefits of big data, methodological issues including legal and ethical issues, and clinical integration and utility issues, must be overcome to realize the promise of medical big data as the fuel of a continuous learning healthcare system that will improve patient outcome and reduce waste in areas including nephrology.

  4. Traffic information computing platform for big data

    Energy Technology Data Exchange (ETDEWEB)

    Duan, Zongtao, E-mail: ztduan@chd.edu.cn; Li, Ying, E-mail: ztduan@chd.edu.cn; Zheng, Xibin, E-mail: ztduan@chd.edu.cn; Liu, Yan, E-mail: ztduan@chd.edu.cn; Dai, Jiting, E-mail: ztduan@chd.edu.cn; Kang, Jun, E-mail: ztduan@chd.edu.cn [Chang' an University School of Information Engineering, Xi' an, China and Shaanxi Engineering and Technical Research Center for Road and Traffic Detection, Xi' an (China)

    2014-10-06

    Big data environment create data conditions for improving the quality of traffic information service. The target of this article is to construct a traffic information computing platform for big data environment. Through in-depth analysis the connotation and technology characteristics of big data and traffic information service, a distributed traffic atomic information computing platform architecture is proposed. Under the big data environment, this type of traffic atomic information computing architecture helps to guarantee the traffic safety and efficient operation, more intelligent and personalized traffic information service can be used for the traffic information users.

  5. Medical big data: promise and challenges.

    Science.gov (United States)

    Lee, Choong Ho; Yoon, Hyung-Jin

    2017-03-01

    The concept of big data, commonly characterized by volume, variety, velocity, and veracity, goes far beyond the data type and includes the aspects of data analysis, such as hypothesis-generating, rather than hypothesis-testing. Big data focuses on temporal stability of the association, rather than on causal relationship and underlying probability distribution assumptions are frequently not required. Medical big data as material to be analyzed has various features that are not only distinct from big data of other disciplines, but also distinct from traditional clinical epidemiology. Big data technology has many areas of application in healthcare, such as predictive modeling and clinical decision support, disease or safety surveillance, public health, and research. Big data analytics frequently exploits analytic methods developed in data mining, including classification, clustering, and regression. Medical big data analyses are complicated by many technical issues, such as missing values, curse of dimensionality, and bias control, and share the inherent limitations of observation study, namely the inability to test causality resulting from residual confounding and reverse causation. Recently, propensity score analysis and instrumental variable analysis have been introduced to overcome these limitations, and they have accomplished a great deal. Many challenges, such as the absence of evidence of practical benefits of big data, methodological issues including legal and ethical issues, and clinical integration and utility issues, must be overcome to realize the promise of medical big data as the fuel of a continuous learning healthcare system that will improve patient outcome and reduce waste in areas including nephrology.

  6. Traffic information computing platform for big data

    International Nuclear Information System (INIS)

    Duan, Zongtao; Li, Ying; Zheng, Xibin; Liu, Yan; Dai, Jiting; Kang, Jun

    2014-01-01

    Big data environment create data conditions for improving the quality of traffic information service. The target of this article is to construct a traffic information computing platform for big data environment. Through in-depth analysis the connotation and technology characteristics of big data and traffic information service, a distributed traffic atomic information computing platform architecture is proposed. Under the big data environment, this type of traffic atomic information computing architecture helps to guarantee the traffic safety and efficient operation, more intelligent and personalized traffic information service can be used for the traffic information users

  7. Big Data's Role in Precision Public Health.

    Science.gov (United States)

    Dolley, Shawn

    2018-01-01

    Precision public health is an emerging practice to more granularly predict and understand public health risks and customize treatments for more specific and homogeneous subpopulations, often using new data, technologies, and methods. Big data is one element that has consistently helped to achieve these goals, through its ability to deliver to practitioners a volume and variety of structured or unstructured data not previously possible. Big data has enabled more widespread and specific research and trials of stratifying and segmenting populations at risk for a variety of health problems. Examples of success using big data are surveyed in surveillance and signal detection, predicting future risk, targeted interventions, and understanding disease. Using novel big data or big data approaches has risks that remain to be resolved. The continued growth in volume and variety of available data, decreased costs of data capture, and emerging computational methods mean big data success will likely be a required pillar of precision public health into the future. This review article aims to identify the precision public health use cases where big data has added value, identify classes of value that big data may bring, and outline the risks inherent in using big data in precision public health efforts.

  8. Big data analytics with R and Hadoop

    CERN Document Server

    Prajapati, Vignesh

    2013-01-01

    Big Data Analytics with R and Hadoop is a tutorial style book that focuses on all the powerful big data tasks that can be achieved by integrating R and Hadoop.This book is ideal for R developers who are looking for a way to perform big data analytics with Hadoop. This book is also aimed at those who know Hadoop and want to build some intelligent applications over Big data with R packages. It would be helpful if readers have basic knowledge of R.

  9. Big Data; A Management Revolution : The emerging role of big data in businesses

    OpenAIRE

    Blasiak, Kevin

    2014-01-01

    Big data is a term that was coined in 2012 and has since then emerged to one of the top trends in business and technology. Big data is an agglomeration of different technologies resulting in data processing capabilities that have been unreached before. Big data is generally characterized by 4 factors. Volume, velocity and variety. These three factors distinct it from the traditional data use. The possibilities to utilize this technology are vast. Big data technology has touch points in differ...

  10. The faces of Big Science.

    Science.gov (United States)

    Schatz, Gottfried

    2014-06-01

    Fifty years ago, academic science was a calling with few regulations or financial rewards. Today, it is a huge enterprise confronted by a plethora of bureaucratic and political controls. This change was not triggered by specific events or decisions but reflects the explosive 'knee' in the exponential growth that science has sustained during the past three-and-a-half centuries. Coming to terms with the demands and benefits of 'Big Science' is a major challenge for today's scientific generation. Since its foundation 50 years ago, the European Molecular Biology Organization (EMBO) has been of invaluable help in meeting this challenge.

  11. Big Data and central banks

    Directory of Open Access Journals (Sweden)

    David Bholat

    2015-04-01

    Full Text Available This commentary recaps a Centre for Central Banking Studies event held at the Bank of England on 2–3 July 2014. The article covers three main points. First, it situates the Centre for Central Banking Studies event within the context of the Bank’s Strategic Plan and initiatives. Second, it summarises and reflects on major themes from the event. Third, the article links central banks’ emerging interest in Big Data approaches with their broader uptake by other economic agents.

  12. Inhomogeneous Big Bang Nucleosynthesis Revisited

    OpenAIRE

    Lara, J. F.; Kajino, T.; Mathews, G. J.

    2006-01-01

    We reanalyze the allowed parameters for inhomogeneous big bang nucleosynthesis in light of the WMAP constraints on the baryon-to-photon ratio and a recent measurement which has set the neutron lifetime to be 878.5 +/- 0.7 +/- 0.3 seconds. For a set baryon-to-photon ratio the new lifetime reduces the mass fraction of He4 by 0.0015 but does not significantly change the abundances of other isotopes. This enlarges the region of concordance between He4 and deuterium in the parameter space of the b...

  13. Comparative validity of brief to medium-length Big Five and Big Six personality questionnaires

    NARCIS (Netherlands)

    Thalmayer, A.G.; Saucier, G.; Eigenhuis, A.

    2011-01-01

    A general consensus on the Big Five model of personality attributes has been highly generative for the field of personality psychology. Many important psychological and life outcome correlates with Big Five trait dimensions have been established. But researchers must choose between multiple Big Five

  14. Comparative Validity of Brief to Medium-Length Big Five and Big Six Personality Questionnaires

    Science.gov (United States)

    Thalmayer, Amber Gayle; Saucier, Gerard; Eigenhuis, Annemarie

    2011-01-01

    A general consensus on the Big Five model of personality attributes has been highly generative for the field of personality psychology. Many important psychological and life outcome correlates with Big Five trait dimensions have been established. But researchers must choose between multiple Big Five inventories when conducting a study and are…

  15. Big Data en surveillance, deel 1 : Definities en discussies omtrent Big Data

    NARCIS (Netherlands)

    Timan, Tjerk

    2016-01-01

    Naar aanleiding van een (vrij kort) college over surveillance en Big Data, werd me gevraagd iets dieper in te gaan op het thema, definities en verschillende vraagstukken die te maken hebben met big data. In dit eerste deel zal ik proberen e.e.a. uiteen te zetten betreft Big Data theorie en

  16. 77 FR 27245 - Big Stone National Wildlife Refuge, Big Stone and Lac Qui Parle Counties, MN

    Science.gov (United States)

    2012-05-09

    ... DEPARTMENT OF THE INTERIOR Fish and Wildlife Service [FWS-R3-R-2012-N069; FXRS1265030000S3-123-FF03R06000] Big Stone National Wildlife Refuge, Big Stone and Lac Qui Parle Counties, MN AGENCY: Fish and... plan (CCP) and environmental assessment (EA) for Big Stone National Wildlife Refuge (Refuge, NWR) for...

  17. Big game hunting practices, meanings, motivations and constraints: a survey of Oregon big game hunters

    Science.gov (United States)

    Suresh K. Shrestha; Robert C. Burns

    2012-01-01

    We conducted a self-administered mail survey in September 2009 with randomly selected Oregon hunters who had purchased big game hunting licenses/tags for the 2008 hunting season. Survey questions explored hunting practices, the meanings of and motivations for big game hunting, the constraints to big game hunting participation, and the effects of age, years of hunting...

  18. An analysis of cross-sectional differences in big and non-big public accounting firms' audit programs

    NARCIS (Netherlands)

    Blokdijk, J.H. (Hans); Drieenhuizen, F.; Stein, M.T.; Simunic, D.A.

    2006-01-01

    A significant body of prior research has shown that audits by the Big 5 (now Big 4) public accounting firms are quality differentiated relative to non-Big 5 audits. This result can be derived analytically by assuming that Big 5 and non-Big 5 firms face different loss functions for "audit failures"

  19. Baryon symmetric big bang cosmology

    Science.gov (United States)

    Stecker, F. W.

    1978-01-01

    Both the quantum theory and Einsteins theory of special relativity lead to the supposition that matter and antimatter were produced in equal quantities during the big bang. It is noted that local matter/antimatter asymmetries may be reconciled with universal symmetry by assuming (1) a slight imbalance of matter over antimatter in the early universe, annihilation, and a subsequent remainder of matter; (2) localized regions of excess for one or the other type of matter as an initial condition; and (3) an extremely dense, high temperature state with zero net baryon number; i.e., matter/antimatter symmetry. Attention is given to the third assumption, which is the simplest and the most in keeping with current knowledge of the cosmos, especially as pertains the universality of 3 K background radiation. Mechanisms of galaxy formation are discussed, whereby matter and antimatter might have collided and annihilated each other, or have coexisted (and continue to coexist) at vast distances. It is pointed out that baryon symmetric big bang cosmology could probably be proved if an antinucleus could be detected in cosmic radiation.

  20. Georges et le big bang

    CERN Document Server

    Hawking, Lucy; Parsons, Gary

    2011-01-01

    Georges et Annie, sa meilleure amie, sont sur le point d'assister à l'une des plus importantes expériences scientifiques de tous les temps : explorer les premiers instants de l'Univers, le Big Bang ! Grâce à Cosmos, leur super ordinateur, et au Grand Collisionneur de hadrons créé par Éric, le père d'Annie, ils vont enfin pouvoir répondre à cette question essentielle : pourquoi existons nous ? Mais Georges et Annie découvrent qu'un complot diabolique se trame. Pire, c'est toute la recherche scientifique qui est en péril ! Entraîné dans d'incroyables aventures, Georges ira jusqu'aux confins de la galaxie pour sauver ses amis...Une plongée passionnante au coeur du Big Bang. Les toutes dernières théories de Stephen Hawking et des plus grands scientifiques actuels.

  1. Astronomical Surveys and Big Data

    Directory of Open Access Journals (Sweden)

    Mickaelian Areg M.

    2016-03-01

    Full Text Available Recent all-sky and large-area astronomical surveys and their catalogued data over the whole range of electromagnetic spectrum, from γ-rays to radio waves, are reviewed, including such as Fermi-GLAST and INTEGRAL in γ-ray, ROSAT, XMM and Chandra in X-ray, GALEX in UV, SDSS and several POSS I and POSS II-based catalogues (APM, MAPS, USNO, GSC in the optical range, 2MASS in NIR, WISE and AKARI IRC in MIR, IRAS and AKARI FIS in FIR, NVSS and FIRST in radio range, and many others, as well as the most important surveys giving optical images (DSS I and II, SDSS, etc., proper motions (Tycho, USNO, Gaia, variability (GCVS, NSVS, ASAS, Catalina, Pan-STARRS, and spectroscopic data (FBS, SBS, Case, HQS, HES, SDSS, CALIFA, GAMA. An overall understanding of the coverage along the whole wavelength range and comparisons between various surveys are given: galaxy redshift surveys, QSO/AGN, radio, Galactic structure, and Dark Energy surveys. Astronomy has entered the Big Data era, with Astrophysical Virtual Observatories and Computational Astrophysics playing an important role in using and analyzing big data for new discoveries.

  2. Big data in oncologic imaging.

    Science.gov (United States)

    Regge, Daniele; Mazzetti, Simone; Giannini, Valentina; Bracco, Christian; Stasi, Michele

    2017-06-01

    Cancer is a complex disease and unfortunately understanding how the components of the cancer system work does not help understand the behavior of the system as a whole. In the words of the Greek philosopher Aristotle "the whole is greater than the sum of parts." To date, thanks to improved information technology infrastructures, it is possible to store data from each single cancer patient, including clinical data, medical images, laboratory tests, and pathological and genomic information. Indeed, medical archive storage constitutes approximately one-third of total global storage demand and a large part of the data are in the form of medical images. The opportunity is now to draw insight on the whole to the benefit of each individual patient. In the oncologic patient, big data analysis is at the beginning but several useful applications can be envisaged including development of imaging biomarkers to predict disease outcome, assessing the risk of X-ray dose exposure or of renal damage following the administration of contrast agents, and tracking and optimizing patient workflow. The aim of this review is to present current evidence of how big data derived from medical images may impact on the diagnostic pathway of the oncologic patient.

  3. Big Data and Intelligence: Applications, Human Capital, and Education

    Directory of Open Access Journals (Sweden)

    Michael Landon-Murray

    2016-06-01

    Full Text Available The potential for big data to contribute to the US intelligence mission goes beyond bulk collection, social media and counterterrorism. Applications will speak to a range of issues of major concern to intelligence agencies, from military operations to climate change to cyber security. There are challenges too: procurement lags, data stovepiping, separating signal from noise, sources and methods, a range of normative issues, and central to managing these challenges, human capital. These potential applications and challenges are discussed and a closer look at what data scientists do in the Intelligence Community (IC is offered. Effectively filling the ranks of the IC’s data science workforce will depend on the provision of well-trained data scientists from the higher education system. Program offerings at America’s top fifty universities will thus be surveyed (just a few years ago there were reportedly no degrees in data science. One Master’s program that has melded data science with intelligence is examined as well as a university big data research center focused on security and intelligence. This discussion goes a long way to clarify the prospective uses of data science in intelligence while probing perhaps the key challenge to optimal application of big data in the IC.

  4. Leveraging Big Data for Exploring Occupational Diseases-Related Interest at the Level of Scientific Community, Media Coverage and Novel Data Streams: The Example of Silicosis as a Pilot Study.

    Science.gov (United States)

    Bragazzi, Nicola Luigi; Dini, Guglielmo; Toletone, Alessandra; Brigo, Francesco; Durando, Paolo

    2016-01-01

    Silicosis is an untreatable but preventable occupational disease, caused by exposure to silica. It can progressively evolve to lung impairment, respiratory failure and death, even after exposure has ceased. However, little is known about occupational diseases-related interest at the level of scientific community, media coverage and web behavior. This article aims at filling in this gap of knowledge, taking the silicosis as a case study. We investigated silicosis-related web-activities using Google Trends (GT) for capturing the Internet behavior worldwide in the years 2004-2015. GT-generated data were, then, compared with the silicosis-related scientific production (i.e., PubMed and Google Scholar), the media coverage (i.e., Google news), the Wikipedia traffic (i.e, Wikitrends) and the usage of new media (i.e., YouTube and Twitter). A peak in silicosis-related web searches was noticed in 2010-2011: interestingly, both scientific articles production and media coverage markedly increased after these years in a statistically significant way. The public interest and the level of the public engagement were witnessed by an increase in likes, comments, hashtags, and re-tweets. However, it was found that only a small fraction of the posted/uploaded material contained accurate scientific information. GT could be useful to assess the reaction of the public and the level of public engagement both to novel risk-factors associated to occupational diseases, and possibly related changes in disease natural history, and to the effectiveness of preventive workplace practices and legislative measures adopted to improve occupational health. Further, occupational clinicians should become aware of the topics most frequently searched by patients and proactively address these concerns during the medical examination. Institutional bodies and organisms should be more present and active in digital tools and media to disseminate and communicate scientifically accurate information. This

  5. Leveraging Big Data for Exploring Occupational Diseases-Related Interest at the Level of Scientific Community, Media Coverage and Novel Data Streams: The Example of Silicosis as a Pilot Study

    Science.gov (United States)

    Bragazzi, Nicola Luigi; Toletone, Alessandra; Brigo, Francesco; Durando, Paolo

    2016-01-01

    Objective Silicosis is an untreatable but preventable occupational disease, caused by exposure to silica. It can progressively evolve to lung impairment, respiratory failure and death, even after exposure has ceased. However, little is known about occupational diseases-related interest at the level of scientific community, media coverage and web behavior. This article aims at filling in this gap of knowledge, taking the silicosis as a case study. Methods We investigated silicosis-related web-activities using Google Trends (GT) for capturing the Internet behavior worldwide in the years 2004–2015. GT-generated data were, then, compared with the silicosis-related scientific production (i.e., PubMed and Google Scholar), the media coverage (i.e., Google news), the Wikipedia traffic (i.e, Wikitrends) and the usage of new media (i.e., YouTube and Twitter). Results A peak in silicosis-related web searches was noticed in 2010–2011: interestingly, both scientific articles production and media coverage markedly increased after these years in a statistically significant way. The public interest and the level of the public engagement were witnessed by an increase in likes, comments, hashtags, and re-tweets. However, it was found that only a small fraction of the posted/uploaded material contained accurate scientific information. Conclusions GT could be useful to assess the reaction of the public and the level of public engagement both to novel risk-factors associated to occupational diseases, and possibly related changes in disease natural history, and to the effectiveness of preventive workplace practices and legislative measures adopted to improve occupational health. Further, occupational clinicians should become aware of the topics most frequently searched by patients and proactively address these concerns during the medical examination. Institutional bodies and organisms should be more present and active in digital tools and media to disseminate and communicate

  6. Big Data viewed through the lens of management fashion theory

    OpenAIRE

    Madsen, Dag Øivind; Stenheim, Tonny

    2016-01-01

    Big Data (BD) is currently one of the most talked about management ideas in the business community. Many call it the “buzzword of the day.” In books and media articles, BD has been referred to as a “revolution” and “new era.” There is lots of optimistic and upbeat rhetoric surrounding BD. This has led some to question whether BD is a hyped-up management fashion. In this paper, the BD phenomenon is viewed through the lens of management fashion theory. Management fashion provides an analytical ...

  7. Leveraging Mobile Network Big Data for Developmental Policy ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    Some argue that big data and big data users offer advantages to generate evidence. ... Supported by IDRC, this research focused on transportation planning in urban ... Using mobile network big data for land use classification CPRsouth 2015.

  8. A New Look at Big History

    Science.gov (United States)

    Hawkey, Kate

    2014-01-01

    The article sets out a "big history" which resonates with the priorities of our own time. A globalizing world calls for new spacial scales to underpin what the history curriculum addresses, "big history" calls for new temporal scales, while concern over climate change calls for a new look at subject boundaries. The article…

  9. A little big history of Tiananmen

    NARCIS (Netherlands)

    Quaedackers, E.; Grinin, L.E.; Korotayev, A.V.; Rodrigue, B.H.

    2011-01-01

    This contribution aims at demonstrating the usefulness of studying small-scale subjects such as Tiananmen, or the Gate of Heavenly Peace, in Beijing - from a Big History perspective. By studying such a ‘little big history’ of Tiananmen, previously overlooked yet fundamental explanations for why

  10. What is beyond the big five?

    Science.gov (United States)

    Saucier, G; Goldberg, L R

    1998-08-01

    Previous investigators have proposed that various kinds of person-descriptive content--such as differences in attitudes or values, in sheer evaluation, in attractiveness, or in height and girth--are not adequately captured by the Big Five Model. We report on a rather exhaustive search for reliable sources of Big Five-independent variation in data from person-descriptive adjectives. Fifty-three candidate clusters were developed in a college sample using diverse approaches and sources. In a nonstudent adult sample, clusters were evaluated with respect to a minimax criterion: minimum multiple correlation with factors from Big Five markers and maximum reliability. The most clearly Big Five-independent clusters referred to Height, Girth, Religiousness, Employment Status, Youthfulness and Negative Valence (or low-base-rate attributes). Clusters referring to Fashionableness, Sensuality/Seductiveness, Beauty, Masculinity, Frugality, Humor, Wealth, Prejudice, Folksiness, Cunning, and Luck appeared to be potentially beyond the Big Five, although each of these clusters demonstrated Big Five multiple correlations of .30 to .45, and at least one correlation of .20 and over with a Big Five factor. Of all these content areas, Religiousness, Negative Valence, and the various aspects of Attractiveness were found to be represented by a substantial number of distinct, common adjectives. Results suggest directions for supplementing the Big Five when one wishes to extend variable selection outside the domain of personality traits as conventionally defined.

  11. Big Data Analytics and Its Applications

    Directory of Open Access Journals (Sweden)

    Mashooque A. Memon

    2017-10-01

    Full Text Available The term, Big Data, has been authored to refer to the extensive heave of data that can't be managed by traditional data handling methods or techniques. The field of Big Data plays an indispensable role in various fields, such as agriculture, banking, data mining, education, chemistry, finance, cloud computing, marketing, health care stocks. Big data analytics is the method for looking at big data to reveal hidden patterns, incomprehensible relationship and other important data that can be utilize to resolve on enhanced decisions. There has been a perpetually expanding interest for big data because of its fast development and since it covers different areas of applications. Apache Hadoop open source technology created in Java and keeps running on Linux working framework was used. The primary commitment of this exploration is to display an effective and free solution for big data application in a distributed environment, with its advantages and indicating its easy use. Later on, there emerge to be a required for an analytical review of new developments in the big data technology. Healthcare is one of the best concerns of the world. Big data in healthcare imply to electronic health data sets that are identified with patient healthcare and prosperity. Data in the healthcare area is developing past managing limit of the healthcare associations and is relied upon to increment fundamentally in the coming years.

  12. Big data and software defined networks

    CERN Document Server

    Taheri, Javid

    2018-01-01

    Big Data Analytics and Software Defined Networking (SDN) are helping to drive the management of data usage of the extraordinary increase of computer processing power provided by Cloud Data Centres (CDCs). This new book investigates areas where Big-Data and SDN can help each other in delivering more efficient services.

  13. Big Science and Long-tail Science

    CERN Document Server

    2008-01-01

    Jim Downing and I were privileged to be the guests of Salavtore Mele at CERN yesterday and to see the Atlas detector of the Large Hadron Collider . This is a wow experience - although I knew it was big, I hadnt realised how big.

  14. The Death of the Big Men

    DEFF Research Database (Denmark)

    Martin, Keir

    2010-01-01

    Recently Tolai people og Papua New Guinea have adopted the term 'Big Shot' to decribe an emerging post-colonial political elite. The mergence of the term is a negative moral evaluation of new social possibilities that have arisen as a consequence of the Big Shots' privileged position within a glo...

  15. An embedding for the big bang

    Science.gov (United States)

    Wesson, Paul S.

    1994-01-01

    A cosmological model is given that has good physical properties for the early and late universe but is a hypersurface in a flat five-dimensional manifold. The big bang can therefore be regarded as an effect of a choice of coordinates in a truncated higher-dimensional geometry. Thus the big bang is in some sense a geometrical illusion.

  16. Probing the pre-big bang universe

    International Nuclear Information System (INIS)

    Veneziano, G.

    2000-01-01

    Superstring theory suggests a new cosmology whereby a long inflationary phase preceded a non singular big bang-like event. After discussing how pre-big bang inflation naturally arises from an almost trivial initial state of the Universe, I will describe how present or near-future experiments can provide sensitive probes of how the Universe behaved in the pre-bang era

  17. Starting Small, Thinking Big - Continuum Magazine | NREL

    Science.gov (United States)

    , Thinking Big Stories NREL Helps Agencies Target New Federal Sustainability Goals Student Engagements Help solar power in the territory. Photo by Don Buchanan, VIEO Starting Small, Thinking Big NREL helps have used these actions to optimize that energy use.'" NREL's cross-organizational work supports

  18. Exploiting big data for critical care research.

    Science.gov (United States)

    Docherty, Annemarie B; Lone, Nazir I

    2015-10-01

    Over recent years the digitalization, collection and storage of vast quantities of data, in combination with advances in data science, has opened up a new era of big data. In this review, we define big data, identify examples of critical care research using big data, discuss the limitations and ethical concerns of using these large datasets and finally consider scope for future research. Big data refers to datasets whose size, complexity and dynamic nature are beyond the scope of traditional data collection and analysis methods. The potential benefits to critical care are significant, with faster progress in improving health and better value for money. Although not replacing clinical trials, big data can improve their design and advance the field of precision medicine. However, there are limitations to analysing big data using observational methods. In addition, there are ethical concerns regarding maintaining confidentiality of patients who contribute to these datasets. Big data have the potential to improve medical care and reduce costs, both by individualizing medicine, and bringing together multiple sources of data about individual patients. As big data become increasingly mainstream, it will be important to maintain public confidence by safeguarding data security, governance and confidentiality.

  19. Practice variation in Big-4 transparency reports

    NARCIS (Netherlands)

    Girdhar, Sakshi; Jeppesen, K.K.

    2018-01-01

    Purpose The purpose of this paper is to examine the transparency reports published by the Big-4 public accounting firms in the UK, Germany and Denmark to understand the determinants of their content within the networks of big accounting firms. Design/methodology/approach The study draws on a

  20. Big data analysis for smart farming

    NARCIS (Netherlands)

    Kempenaar, C.; Lokhorst, C.; Bleumer, E.J.B.; Veerkamp, R.F.; Been, Th.; Evert, van F.K.; Boogaardt, M.J.; Ge, L.; Wolfert, J.; Verdouw, C.N.; Bekkum, van Michael; Feldbrugge, L.; Verhoosel, Jack P.C.; Waaij, B.D.; Persie, van M.; Noorbergen, H.

    2016-01-01

    In this report we describe results of a one-year TO2 institutes project on the development of big data technologies within the milk production chain. The goal of this project is to ‘create’ an integration platform for big data analysis for smart farming and to develop a show case. This includes both

  1. Big-Data-Driven Stem Cell Science and Tissue Engineering: Vision and Unique Opportunities.

    Science.gov (United States)

    Del Sol, Antonio; Thiesen, Hans J; Imitola, Jaime; Carazo Salas, Rafael E

    2017-02-02

    Achieving the promises of stem cell science to generate precise disease models and designer cell samples for personalized therapeutics will require harnessing pheno-genotypic cell-level data quantitatively and predictively in the lab and clinic. Those requirements could be met by developing a Big-Data-driven stem cell science strategy and community. Copyright © 2017 Elsevier Inc. All rights reserved.

  2. Long-Term Developmental Changes in Children's Lower-Order Big Five Personality Facets

    NARCIS (Netherlands)

    A.D. de Haan (Amaranta); S.S.W. de Pauw (Sarah); A.L. van den Akker (Alithe); M. Deković (Maja); P.J. Prinzie (Peter)

    2016-01-01

    markdownabstract__Objective:__ This study examined long-term developmental changes in mother-rated lower-order facets of children's Big Five dimensions. __Method:__ Two independent community samples covering early childhood (2-4.5 years; N=365, 39% girls) and middle childhood to the end of middle

  3. Long-term developmental changes in children's lower-order Big Five personality facets

    NARCIS (Netherlands)

    Haan, A.D. de; Pauw, S. de; Akker, A.J. van den; Dekovic, M.; Prinzie, P.

    2017-01-01

    Objective: This study examined long-term developmental changes in mother-rated lower-order facets of children's Big Five dimensions. Method: Two independent community samples covering early childhood (2-4.5 years; N = 365, 39% girls) and middle childhood to the end of middle adolescence (6-17 years;

  4. Long-term developmental changes in children’s lower-order big five personality facets

    NARCIS (Netherlands)

    de Haan, A.; de Pauw, S.; van den Akker, A.; Deković, M.; Prinzie, P.

    2017-01-01

    Objective This study examined long-term developmental changes in mother-rated lower-order facets of children's Big Five dimensions. Method Two independent community samples covering early childhood (2–4.5 years; N = 365, 39% girls) and middle childhood to the end of middle adolescence (6–17 years;

  5. Long-term developmental changes in children’s lower-order Big Five personality facets

    NARCIS (Netherlands)

    de Haan, A.D.; de Pauw, S.; van den Akker, A.L.; Dekovic, M.; Prinzie, Peter

    2017-01-01

    Objective This study examined long-term developmental changes in mother-rated lower-order facets of children's Big Five dimensions. Method Two independent community samples covering early childhood (2–4.5 years; N = 365, 39% girls) and middle childhood to the end of middle adolescence (6–17 years;

  6. GraphStore: A Distributed Graph Storage System for Big Data Networks

    Science.gov (United States)

    Martha, VenkataSwamy

    2013-01-01

    Networks, such as social networks, are a universal solution for modeling complex problems in real time, especially in the Big Data community. While previous studies have attempted to enhance network processing algorithms, none have paved a path for the development of a persistent storage system. The proposed solution, GraphStore, provides an…

  7. BigNeuron: Large-Scale 3D Neuron Reconstruction from Optical Microscopy Images

    NARCIS (Netherlands)

    H. Peng (Hanchuan); M. Hawrylycz (Michael); J. Roskams (Jane); S. Hill (Sean); N. Spruston (Nelson); E. Meijering (Erik); G.A. Ascoli (Giorgio A.)

    2015-01-01

    textabstractUnderstanding the structure of single neurons is critical for understanding how they function within neural circuits. BigNeuron is a new community effort that combines modern bioimaging informatics, recent leaps in labeling and microscopy, and the widely recognized need for openness and

  8. Rethinking climate change adaptation and place through a situated pathways framework: A case study from the Big Hole Valley, USA

    Science.gov (United States)

    Daniel J. Murphy; Laurie Yung; Carina Wyborn; Daniel R. Williams

    2017-01-01

    This paper critically examines the temporal and spatial dynamics of adaptation in climate change science and explores how dynamic notions of 'place' elucidate novel ways of understanding community vulnerability and adaptation. Using data gathered from a narrative scenario-building process carried out among communities of the Big Hole Valley in Montana, the...

  9. Cloud Based Big Data Infrastructure: Architectural Components and Automated Provisioning

    OpenAIRE

    Demchenko, Yuri; Turkmen, Fatih; Blanchet, Christophe; Loomis, Charles; Laat, Caees de

    2016-01-01

    This paper describes the general architecture and functional components of the cloud based Big Data Infrastructure (BDI). The proposed BDI architecture is based on the analysis of the emerging Big Data and data intensive technologies and supported by the definition of the Big Data Architecture Framework (BDAF) that defines the following components of the Big Data technologies: Big Data definition, Data Management including data lifecycle and data structures, Big Data Infrastructure (generical...

  10. The ethics of biomedical big data

    CERN Document Server

    Mittelstadt, Brent Daniel

    2016-01-01

    This book presents cutting edge research on the new ethical challenges posed by biomedical Big Data technologies and practices. ‘Biomedical Big Data’ refers to the analysis of aggregated, very large datasets to improve medical knowledge and clinical care. The book describes the ethical problems posed by aggregation of biomedical datasets and re-use/re-purposing of data, in areas such as privacy, consent, professionalism, power relationships, and ethical governance of Big Data platforms. Approaches and methods are discussed that can be used to address these problems to achieve the appropriate balance between the social goods of biomedical Big Data research and the safety and privacy of individuals. Seventeen original contributions analyse the ethical, social and related policy implications of the analysis and curation of biomedical Big Data, written by leading experts in the areas of biomedical research, medical and technology ethics, privacy, governance and data protection. The book advances our understan...

  11. Big data analytics methods and applications

    CERN Document Server

    Rao, BLS; Rao, SB

    2016-01-01

    This book has a collection of articles written by Big Data experts to describe some of the cutting-edge methods and applications from their respective areas of interest, and provides the reader with a detailed overview of the field of Big Data Analytics as it is practiced today. The chapters cover technical aspects of key areas that generate and use Big Data such as management and finance; medicine and healthcare; genome, cytome and microbiome; graphs and networks; Internet of Things; Big Data standards; bench-marking of systems; and others. In addition to different applications, key algorithmic approaches such as graph partitioning, clustering and finite mixture modelling of high-dimensional data are also covered. The varied collection of themes in this volume introduces the reader to the richness of the emerging field of Big Data Analytics.

  12. 2nd INNS Conference on Big Data

    CERN Document Server

    Manolopoulos, Yannis; Iliadis, Lazaros; Roy, Asim; Vellasco, Marley

    2017-01-01

    The book offers a timely snapshot of neural network technologies as a significant component of big data analytics platforms. It promotes new advances and research directions in efficient and innovative algorithmic approaches to analyzing big data (e.g. deep networks, nature-inspired and brain-inspired algorithms); implementations on different computing platforms (e.g. neuromorphic, graphics processing units (GPUs), clouds, clusters); and big data analytics applications to solve real-world problems (e.g. weather prediction, transportation, energy management). The book, which reports on the second edition of the INNS Conference on Big Data, held on October 23–25, 2016, in Thessaloniki, Greece, depicts an interesting collaborative adventure of neural networks with big data and other learning technologies.

  13. Practice Variation in Big-4 Transparency Reports

    DEFF Research Database (Denmark)

    Girdhar, Sakshi; Klarskov Jeppesen, Kim

    2018-01-01

    Purpose: The purpose of this paper is to examine the transparency reports published by the Big-4 public accounting firms in the UK, Germany and Denmark to understand the determinants of their content within the networks of big accounting firms. Design/methodology/approach: The study draws...... on a qualitative research approach, in which the content of transparency reports is analyzed and semi-structured interviews are conducted with key people from the Big-4 firms who are responsible for developing the transparency reports. Findings: The findings show that the content of transparency reports...... is inconsistent and the transparency reporting practice is not uniform within the Big-4 networks. Differences were found in the way in which the transparency reporting practices are coordinated globally by the respective central governing bodies of the Big-4. The content of the transparency reports...

  14. Epidemiology in the Era of Big Data

    Science.gov (United States)

    Mooney, Stephen J; Westreich, Daniel J; El-Sayed, Abdulrahman M

    2015-01-01

    Big Data has increasingly been promoted as a revolutionary development in the future of science, including epidemiology. However, the definition and implications of Big Data for epidemiology remain unclear. We here provide a working definition of Big Data predicated on the so-called ‘3 Vs’: variety, volume, and velocity. From this definition, we argue that Big Data has evolutionary and revolutionary implications for identifying and intervening on the determinants of population health. We suggest that as more sources of diverse data become publicly available, the ability to combine and refine these data to yield valid answers to epidemiologic questions will be invaluable. We conclude that, while epidemiology as practiced today will continue to be practiced in the Big Data future, a component of our field’s future value lies in integrating subject matter knowledge with increased technical savvy. Our training programs and our visions for future public health interventions should reflect this future. PMID:25756221

  15. Ethics and Epistemology in Big Data Research.

    Science.gov (United States)

    Lipworth, Wendy; Mason, Paul H; Kerridge, Ian; Ioannidis, John P A

    2017-12-01

    Biomedical innovation and translation are increasingly emphasizing research using "big data." The hope is that big data methods will both speed up research and make its results more applicable to "real-world" patients and health services. While big data research has been embraced by scientists, politicians, industry, and the public, numerous ethical, organizational, and technical/methodological concerns have also been raised. With respect to technical and methodological concerns, there is a view that these will be resolved through sophisticated information technologies, predictive algorithms, and data analysis techniques. While such advances will likely go some way towards resolving technical and methodological issues, we believe that the epistemological issues raised by big data research have important ethical implications and raise questions about the very possibility of big data research achieving its goals.

  16. The Big bang and the Quantum

    Science.gov (United States)

    Ashtekar, Abhay

    2010-06-01

    General relativity predicts that space-time comes to an end and physics comes to a halt at the big-bang. Recent developments in loop quantum cosmology have shown that these predictions cannot be trusted. Quantum geometry effects can resolve singularities, thereby opening new vistas. Examples are: The big bang is replaced by a quantum bounce; the `horizon problem' disappears; immediately after the big bounce, there is a super-inflationary phase with its own phenomenological ramifications; and, in presence of a standard inflation potential, initial conditions are naturally set for a long, slow roll inflation independently of what happens in the pre-big bang branch. As in my talk at the conference, I will first discuss the foundational issues and then the implications of the new Planck scale physics near the Big Bang.

  17. Where Big Data and Prediction Meet

    Energy Technology Data Exchange (ETDEWEB)

    Ahrens, James [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Brase, Jim M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Hart, Bill [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Kusnezov, Dimitri [USDOE, Washington, DC (United States); Shalf, John [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2014-09-11

    Our ability to assemble and analyze massive data sets, often referred to under the title of “big data”, is an increasingly important tool for shaping national policy. This in turn has introduced issues from privacy concerns to cyber security. But as IBM’s John Kelly emphasized in the last Innovation, making sense of the vast arrays of data will require radically new computing tools. In the past, technologies and tools for analysis of big data were viewed as quite different from the traditional realm of high performance computing (HPC) with its huge models of phenomena such as global climate or supporting the nuclear test moratorium. Looking ahead, this will change with very positive benefits for both worlds. Societal issues such as global security, economic planning and genetic analysis demand increased understanding that goes beyond existing data analysis and reduction. The modeling world often produces simulations that are complex compositions of mathematical models and experimental data. This has resulted in outstanding successes such as the annual assessment of the state of the US nuclear weapons stockpile without underground nuclear testing. Ironically, while there were historically many test conducted, this body of data provides only modest insight into the underlying physics of the system. A great deal of emphasis was thus placed on the level of confidence we can develop for the predictions. As data analytics and simulation come together, there is a growing need to assess the confidence levels in both data being gathered and the complex models used to make predictions. An example of this is assuring the security or optimizing the performance of critical infrastructure systems such as the power grid. If one wants to understand the vulnerabilities of the system or impacts of predicted threats, full scales tests of the grid against threat scenarios are unlikely. Preventive measures would need to be predicated on well-defined margins of confidence in order

  18. BigNeuron: Large-scale 3D Neuron Reconstruction from Optical Microscopy Images

    OpenAIRE

    Peng, Hanchuan; Hawrylycz, Michael; Roskams, Jane; Hill, Sean; Spruston, Nelson; Meijering, Erik; Ascoli, Giorgio A.

    2015-01-01

    textabstractUnderstanding the structure of single neurons is critical for understanding how they function within neural circuits. BigNeuron is a new community effort that combines modern bioimaging informatics, recent leaps in labeling and microscopy, and the widely recognized need for openness and standardization to provide a community resource for automated reconstruction of dendritic and axonal morphology of single neurons. Understanding the structure of single neurons is critical for unde...

  19. The Power of Thinking Big

    Science.gov (United States)

    Celeste, Eric

    2016-01-01

    Communities of practice have become important tools for districts striving to improve teacher quality in a way that improves student outcomes, but scaling the benefits of these communities requires a more rigorous, intentional approach. That's why Learning Forward, with support from the Bill & Melinda Gates Foundation, created the Redesign PD…

  20. Intelligent search in Big Data

    Science.gov (United States)

    Birialtsev, E.; Bukharaev, N.; Gusenkov, A.

    2017-10-01

    An approach to data integration, aimed on the ontology-based intelligent search in Big Data, is considered in the case when information objects are represented in the form of relational databases (RDB), structurally marked by their schemes. The source of information for constructing an ontology and, later on, the organization of the search are texts in natural language, treated as semi-structured data. For the RDBs, these are comments on the names of tables and their attributes. Formal definition of RDBs integration model in terms of ontologies is given. Within framework of the model universal RDB representation ontology, oil production subject domain ontology and linguistic thesaurus of subject domain language are built. Technique of automatic SQL queries generation for subject domain specialists is proposed. On the base of it, information system for TATNEFT oil-producing company RDBs was implemented. Exploitation of the system showed good relevance with majority of queries.