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...

Transdisciplinary Perspectives in Bioethics: A Co-evolutionary Introduction from the Big History

Directory of Open Access Journals (Sweden)

Javier Collado-Ruano

2016-10-01

Full Text Available The main objective of this work is to expand the bioethics notion expressed in the Article 17th of the Universal Declaration on Bioethics and Human Rights, concerning the interconnections between human beings and other life forms. For this purpose, it is combined the transdisciplinary methodology with the theoretical framework of the “Big History” to approach the co-evolutionary phenomena that life is developing on Earth for some 3.8 billion years. As a result, the study introduces us to the unification, integration and inclusion of the history of the universe, the solar system, Earth, and life with the history of human beings. In conclusion, I consider to safeguard the cosmic miracle that represents the emergence of life we must adopt new transdisciplinary perspectives into bioethics to address the ecosystem complexity of co-evolutionary processes of life on Gaia as a whole.

Strategic Self-Ignorance

DEFF Research Database (Denmark)

Thunström, Linda; Nordström, Leif Jonas; Shogren, Jason F.

We examine strategic self-ignorance—the use of ignorance as an excuse to overindulge in pleasurable activities that may be harmful to one’s future self. Our model shows that guilt aversion provides a behavioral rationale for present-biased agents to avoid information about negative future impacts...... of such activities. We then confront our model with data from an experiment using prepared, restaurant-style meals — a good that is transparent in immediate pleasure (taste) but non-transparent in future harm (calories). Our results support the notion that strategic self-ignorance matters: nearly three of five...... subjects (58 percent) chose to ignore free information on calorie content, leading at-risk subjects to consume significantly more calories. We also find evidence consistent with our model on the determinants of strategic self-ignorance....

Strategic self-ignorance

DEFF Research Database (Denmark)

Thunström, Linda; Nordström, Leif Jonas; Shogren, Jason F.

2016-01-01

We examine strategic self-ignorance—the use of ignorance as an excuse to over-indulge in pleasurable activities that may be harmful to one’s future self. Our model shows that guilt aversion provides a behavioral rationale for present-biased agents to avoid information about negative future impacts...... of such activities. We then confront our model with data from an experiment using prepared, restaurant-style meals—a good that is transparent in immediate pleasure (taste) but non-transparent in future harm (calories). Our results support the notion that strategic self-ignorance matters: nearly three of five...... subjects (58%) chose to ignore free information on calorie content, leading at-risk subjects to consume significantly more calories. We also find evidence consistent with our model on the determinants of strategic self-ignorance....

Pre-big bang cosmology: A long history of time?

International Nuclear Information System (INIS)

Veneziano, G.

1999-01-01

The popular myth according to which the Universe - and time itself - started with/near a big bang singularity is questioned. After claiming that the two main puzzles of standard cosmology allow for two possible logical answers, I will argue that superstring theory strongly favours the the pre-big bang (PBB) alternative. I will then explain why PBB inflation is as generic as classical gravitational collapse, and why, as a result of symmetries in the latter problem, recent fine-tuning objections to the PBB scenario are unfounded. A hot big bang state naturally results from the powerful amplification of vacuum quantum fluctuations before the big bang, a phenomenon whose observable consequences will be briefly summarized. (author)

Clash of Ignorance

Directory of Open Access Journals (Sweden)

Mahmoud Eid

2012-06-01

Full Text Available The clash of ignorance thesis presents a critique of the clash of civilizations theory. It challenges the assumptions that civilizations are monolithic entities that do not interact and that the Self and the Other are always opposed to each other. Despite some significantly different values and clashes between Western and Muslim civilizations, they overlap with each other in many ways and have historically demonstrated the capacity for fruitful engagement. The clash of ignorance thesis makes a significant contribution to the understanding of intercultural and international communication as well as to the study of inter-group relations in various other areas of scholarship. It does this by bringing forward for examination the key impediments to mutually beneficial interaction between groups. The thesis directly addresses the particular problem of ignorance that other epistemological approaches have not raised in a substantial manner. Whereas the critique of Orientalism deals with the hegemonic construction of knowledge, the clash of ignorance paradigm broadens the inquiry to include various actors whose respective distortions of knowledge symbiotically promote conflict with each other. It also augments the power-knowledge model to provide conceptual and analytical tools for understanding the exploitation of ignorance for the purposes of enhancing particular groups’ or individuals’ power. Whereas academics, policymakers, think tanks, and religious leaders have referred to the clash of ignorance concept, this essay contributes to its development as a theory that is able to provide a valid basis to explain the empirical evidence drawn from relevant cases.

Ignore and Conquer.

Science.gov (United States)

Conroy, Mary

1989-01-01

Discusses how teachers can deal with student misbehavior by ignoring negative behavior that is motivated by a desire for attention. Practical techniques are described for pinpointing attention seekers, enlisting classmates to deal with misbehaving students, ignoring misbehavior, and distinguishing behavior that responds to this technique from…

Algorithmic design considerations for geospatial and/or temporal big data

CSIR Research Space (South Africa)

Van Zyl, T

2014-02-01

Full Text Available Mining. In addition, ignoring the spatiotemporal autocorrelation in the data can lead to spurious results, for instance, the salt and pepper effect when clustering. The solution to the big data challenge is simple to describe yet in most cases...

Women in the History of Astronomy

Science.gov (United States)

Álvarez, M. Álvarez; Díaz, Ángeles I.

1998-06-01

We think about the History of Astronomy as the History of men. As the History of a few men: Ptolemy, Copernicus, Kepler, Newton,...- men who have changed our way of looking at the sky. But the History of Astronomy is more than that, it is the History of thousand of people whose daily work has allowed the development of knowledge and scientific theories at the time they lived. This, sometimes, "tedious work" permitted the big steps. Many of these people were women, as Theano who married Pythagoras and taught mathematics and astronomy in his school, Hypatia who managed the Library of Alexandria and wrote several astronomical treatises, Hildegard of Bingen who developed a theory on the origin and structure of the Universe in the 12th century, or Sofie Brahe who, worked with her famous brother. And so many privileged women who after a long process of study, were able to develop their scientific interests in spite of been excluded from most of the educational installations and formal and informal groups of men scientist. Most of the works done by these women have been ignored, or wrongly attributed to men throughout History. It often happens that although they have been recognized as good scientists in their own times, women have been discredited by posterior historians who refused to believe that important women scientist ever existed. Here we intend to make a short summary on the lives of some of these women and their astronomical works.

Ignorability for categorical data

DEFF Research Database (Denmark)

Jaeger, Manfred

2005-01-01

We study the problem of ignorability in likelihood-based inference from incomplete categorical data. Two versions of the coarsened at random assumption (car) are distinguished, their compatibility with the parameter distinctness assumption is investigated and several conditions for ignorability...

Eyewitness Culture and History: Primary Written Sources. The Iconoclast.

Science.gov (United States)

McMurtry, John

1995-01-01

Asserts that contemporary history and historiography is "official" history that ignores the daily struggles of people for their continued survival. Argues that, while public illiteracy has nearly disappeared, individuals are ignorant of the wealth of primary-source materials of other cultures' histories. (CFR)

Big data in forensic science and medicine.

Science.gov (United States)

Lefèvre, Thomas

2018-07-01

In less than a decade, big data in medicine has become quite a phenomenon and many biomedical disciplines got their own tribune on the topic. Perspectives and debates are flourishing while there is a lack for a consensual definition for big data. The 3Vs paradigm is frequently evoked to define the big data principles and stands for Volume, Variety and Velocity. Even according to this paradigm, genuine big data studies are still scarce in medicine and may not meet all expectations. On one hand, techniques usually presented as specific to the big data such as machine learning techniques are supposed to support the ambition of personalized, predictive and preventive medicines. These techniques are mostly far from been new and are more than 50 years old for the most ancient. On the other hand, several issues closely related to the properties of big data and inherited from other scientific fields such as artificial intelligence are often underestimated if not ignored. Besides, a few papers temper the almost unanimous big data enthusiasm and are worth attention since they delineate what is at stakes. In this context, forensic science is still awaiting for its position papers as well as for a comprehensive outline of what kind of contribution big data could bring to the field. The present situation calls for definitions and actions to rationally guide research and practice in big data. It is an opportunity for grounding a true interdisciplinary approach in forensic science and medicine that is mainly based on evidence. Copyright © 2017 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Moving Forward, Looking Back--Historical Perspective, "Big History" and the Return of the "Longue Durée": Time to Develop Our Scale Hopping Muscles

Science.gov (United States)

Hawkey, Kate

2015-01-01

"Big history" is a term receiving a great deal of attention at present, particularly in North America where considerable sums of money have been invested in designing curricula and assessment tools to help teachers teach history at far larger scales of time than normal. Hawkey considers the pros and cons of incorporating components of…

Inflated granularity: Spatial “Big Data” and geodemographics

Directory of Open Access Journals (Sweden)

Craig M Dalton

2015-08-01

Full Text Available Data analytics, particularly the current rhetoric around “Big Data”, tend to be presented as new and innovative, emerging ahistorically to revolutionize modern life. In this article, we situate one branch of Big Data analytics, spatial Big Data, through a historical predecessor, geodemographic analysis, to help develop a critical approach to current data analytics. Spatial Big Data promises an epistemic break in marketing, a leap from targeting geodemographic areas to targeting individuals. Yet it inherits characteristics and problems from geodemographics, including a justification through the market, and a process of commodification through the black-boxing of technology. As researchers develop sustained critiques of data analytics and its effects on everyday life, we must so with a grounding in the cultural and historical contexts from which data technologies emerged. This article and others (Barnes and Wilson, 2014 develop a historically situated, critical approach to spatial Big Data. This history illustrates connections to the critical issues of surveillance, redlining, and the production of consumer subjects and geographies. The shared histories and structural logics of spatial Big Data and geodemographics create the space for a continued critique of data analyses’ role in society.

The logic of strategic ignorance.

Science.gov (United States)

McGoey, Linsey

2012-09-01

Ignorance and knowledge are often thought of as opposite phenomena. Knowledge is seen as a source of power, and ignorance as a barrier to consolidating authority in political and corporate arenas. This article disputes this, exploring the ways that ignorance serves as a productive asset, helping individuals and institutions to command resources, deny liability in the aftermath of crises, and to assert expertise in the face of unpredictable outcomes. Through a focus on the Food and Drug Administration's licensing of Ketek, an antibiotic drug manufactured by Sanofi-Aventis and linked to liver failure, I suggest that in drug regulation, different actors, from physicians to regulators to manufacturers, often battle over who can attest to the least knowledge of the efficacy and safety of different drugs - a finding that raises new insights about the value of ignorance as an organizational resource. © London School of Economics and Political Science 2012.

Statistical model selection with “Big Data”

Directory of Open Access Journals (Sweden)

Jurgen A. Doornik

2015-12-01

Full Text Available Big Data offer potential benefits for statistical modelling, but confront problems including an excess of false positives, mistaking correlations for causes, ignoring sampling biases and selecting by inappropriate methods. We consider the many important requirements when searching for a data-based relationship using Big Data, and the possible role of Autometrics in that context. Paramount considerations include embedding relationships in general initial models, possibly restricting the number of variables to be selected over by non-statistical criteria (the formulation problem, using good quality data on all variables, analyzed with tight significance levels by a powerful selection procedure, retaining available theory insights (the selection problem while testing for relationships being well specified and invariant to shifts in explanatory variables (the evaluation problem, using a viable approach that resolves the computational problem of immense numbers of possible models.

From dissecting ignorance to solving algebraic problems

International Nuclear Information System (INIS)

Ayyub, Bilal M.

2004-01-01

Engineers and scientists are increasingly required to design, test, and validate new complex systems in simulation environments and/or with limited experimental results due to international and/or budgetary restrictions. Dealing with complex systems requires assessing knowledge and information by critically evaluating them in terms relevance, completeness, non-distortion, coherence, and other key measures. Using the concepts and definitions from evolutionary knowledge and epistemology, ignorance is examined and classified in the paper. Two ignorance states for a knowledge agent are identified: (1) non-reflective (or blind) state, i.e. the person does not know of self-ignorance, a case of ignorance of ignorance; and (2) reflective state, i.e. the person knows and recognizes self-ignorance. Ignorance can be viewed to have a hierarchal classification based on its sources and nature as provided in the paper. The paper also explores limits on knowledge construction, closed and open world assumptions, and fundamentals of evidential reasoning using belief revision and diagnostics within the framework of ignorance analysis for knowledge construction. The paper also examines an algebraic problem set as identified by Sandia National Laboratories to be a basic building block for uncertainty propagation in computational mechanics. Solution algorithms are provided for the problem set for various assumptions about the state of knowledge about its parameters

From dissecting ignorance to solving algebraic problems

Energy Technology Data Exchange (ETDEWEB)

Ayyub, Bilal M

2004-09-01

Engineers and scientists are increasingly required to design, test, and validate new complex systems in simulation environments and/or with limited experimental results due to international and/or budgetary restrictions. Dealing with complex systems requires assessing knowledge and information by critically evaluating them in terms relevance, completeness, non-distortion, coherence, and other key measures. Using the concepts and definitions from evolutionary knowledge and epistemology, ignorance is examined and classified in the paper. Two ignorance states for a knowledge agent are identified: (1) non-reflective (or blind) state, i.e. the person does not know of self-ignorance, a case of ignorance of ignorance; and (2) reflective state, i.e. the person knows and recognizes self-ignorance. Ignorance can be viewed to have a hierarchal classification based on its sources and nature as provided in the paper. The paper also explores limits on knowledge construction, closed and open world assumptions, and fundamentals of evidential reasoning using belief revision and diagnostics within the framework of ignorance analysis for knowledge construction. The paper also examines an algebraic problem set as identified by Sandia National Laboratories to be a basic building block for uncertainty propagation in computational mechanics. Solution algorithms are provided for the problem set for various assumptions about the state of knowledge about its parameters.

Is Ignorance of Climate Change Culpable?

Science.gov (United States)

Robichaud, Philip

2017-10-01

Sometimes ignorance is an excuse. If an agent did not know and could not have known that her action would realize some bad outcome, then it is plausible to maintain that she is not to blame for realizing that outcome, even when the act that leads to this outcome is wrong. This general thought can be brought to bear in the context of climate change insofar as we think (a) that the actions of individual agents play some role in realizing climate harms and (b) that these actions are apt targets for being considered right or wrong. Are agents who are ignorant about climate change and the way their actions contribute to it excused because of their ignorance, or is their ignorance culpable? In this paper I examine these questions from the perspective of recent developments in the theories of responsibility for ignorant action and characterize their verdicts. After developing some objections to existing attempts to explore these questions, I characterize two influential theories of moral responsibility and discuss their implications for three different types of ignorance about climate change. I conclude with some recommendations for how we should react to the face of the theories' conflicting verdicts. The answer to the question posed in the title, then, is: "Well, it's complicated."

Ignorance, information and autonomy

OpenAIRE

Harris, J.; Keywood, K.

2001-01-01

People have a powerful interest in genetic privacy and its associated claim to ignorance, and some equally powerful desires to be shielded from disturbing information are often voiced. We argue, however, that there is no such thing as a right to remain in ignorance, where a right is understood as an entitlement that trumps competing claims. This does not of course mean that information must always be forced upon unwilling recipients, only that there is no prima facie entitlement to be protect...

From Punched Cards to "Big Data": A Social History of Database Populism

Directory of Open Access Journals (Sweden)

Kevin Driscoll

2012-08-01

Full Text Available Since the diffusion of the punched card tabulator following the 1890 U.S. Census, mass-scale information processing has been alternately a site of opportunity, ambivalence and fear in the American imagination. While large bureaucracies have tended to deploy database technology toward purposes of surveillance and control, the rise of personal computing made databases accessible to individuals and small businesses for the first time. Today, the massive collection of trace communication data by public and private institutions has renewed popular anxiety about the role of the database in society. This essay traces the social history of database technology across three periods that represent significant changes in the accessibility and infrastructure of information processing systems. Although many proposed uses of "big data" seem to threaten individual privacy, a largely-forgotten database populism from the 1970s and 1980s suggests that a reclamation of small-scale data processing might lead to sharper popular critique in the future.

Growth history and crown vine coverage are principal factors influencing growth and mortality rates of big-leaf mahogany Swietenia macrophylla in Brazil

Science.gov (United States)

James Grogan; R. Matthew Landis

2009-01-01

1. Current efforts to model population dynamics of high-value tropical timber species largely assume that individual growth history is unimportant to population dynamics, yet growth autocorrelation is known to adversely affect model predictions. In this study, we analyse a decade of annual census data from a natural population of big-leaf mahogany Swietenia macrophylla...

The Power of Ignorance | Code | Philosophical Papers

African Journals Online (AJOL)

Taking my point of entry from George Eliot's reference to 'the power of Ignorance', I analyse some manifestations of that power as she portrays it in the life of a young woman of affluence, in her novel Daniel Deronda. Comparing and contrasting this kind of ignorance with James Mill's avowed ignorance of local tradition and ...

On the Rationality of Pluralistic Ignorance

DEFF Research Database (Denmark)

Bjerring, Jens Christian Krarup; Hansen, Jens Ulrik; Pedersen, Nikolaj Jang Lee Linding

2014-01-01

Pluralistic ignorance is a socio-psychological phenomenon that involves a systematic discrepancy between people’s private beliefs and public behavior in cer- tain social contexts. Recently, pluralistic ignorance has gained increased attention in formal and social epistemology. But to get clear...

Ignorance, information and autonomy.

Science.gov (United States)

Harris, J; Keywood, K

2001-09-01

People have a powerful interest in genetic privacy and its associated claim to ignorance, and some equally powerful desires to be shielded from disturbing information are often voiced. We argue, however, that there is no such thing as a right to remain in ignorance, where a fight is understood as an entitlement that trumps competing claims. This does not of course mean that information must always be forced upon unwilling recipients, only that there is no prima facie entitlement to be protected from true or honest information about oneself. Any claims to be shielded from information about the self must compete on equal terms with claims based in the rights and interests of others. In balancing the weight and importance of rival considerations about giving or withholding information, if rights claims have any place, rights are more likely to be defensible on the side of honest communication of information rather than in defence of ignorance. The right to free speech and the right to decline to accept responsibility to take decisions for others imposed by those others seem to us more plausible candidates for fully fledged rights in this field than any purported right to ignorance. Finally, and most importantly, if the right to autonomy is invoked, a proper understanding of the distinction between claims to liberty and claims to autonomy show that the principle of autonomy, as it is understood in contemporary social ethics and English law, supports the giving rather than the withholding of information in most circumstances.

Data as an asset: What the oil and gas sector can learn from other industries about “Big Data”

International Nuclear Information System (INIS)

Perrons, Robert K.; Jensen, Jesse W.

2015-01-01

The upstream oil and gas industry has been contending with massive data sets and monolithic files for many years, but “Big Data” is a relatively new concept that has the potential to significantly re-shape the industry. Despite the impressive amount of value that is being realized by Big Data technologies in other parts of the marketplace, however, much of the data collected within the oil and gas sector tends to be discarded, ignored, or analyzed in a very cursory way. This viewpoint examines existing data management practices in the upstream oil and gas industry, and compares them to practices and philosophies that have emerged in organizations that are leading the way in Big Data. The comparison shows that, in companies that are widely considered to be leaders in Big Data analytics, data is regarded as a valuable asset—but this is usually not true within the oil and gas industry insofar as data is frequently regarded there as descriptive information about a physical asset rather than something that is valuable in and of itself. The paper then discusses how the industry could potentially extract more value from data, and concludes with a series of policy-related questions to this end. -- Highlights: •Upstream oil and gas industry frequently discards or ignores the data it collects •The sector tends to view data as descriptive information about the state of assets •Leaders in Big Data, by stark contrast, regard data as an asset in and of itself •Industry should use Big Data tools to extract more value from digital information

Big Data in Caenorhabditis elegans: quo vadis?

Science.gov (United States)

Hutter, Harald; Moerman, Donald

2015-11-05

A clear definition of what constitutes "Big Data" is difficult to identify, but we find it most useful to define Big Data as a data collection that is complete. By this criterion, researchers on Caenorhabditis elegans have a long history of collecting Big Data, since the organism was selected with the idea of obtaining a complete biological description and understanding of development. The complete wiring diagram of the nervous system, the complete cell lineage, and the complete genome sequence provide a framework to phrase and test hypotheses. Given this history, it might be surprising that the number of "complete" data sets for this organism is actually rather small--not because of lack of effort, but because most types of biological experiments are not currently amenable to complete large-scale data collection. Many are also not inherently limited, so that it becomes difficult to even define completeness. At present, we only have partial data on mutated genes and their phenotypes, gene expression, and protein-protein interaction--important data for many biological questions. Big Data can point toward unexpected correlations, and these unexpected correlations can lead to novel investigations; however, Big Data cannot establish causation. As a result, there is much excitement about Big Data, but there is also a discussion on just what Big Data contributes to solving a biological problem. Because of its relative simplicity, C. elegans is an ideal test bed to explore this issue and at the same time determine what is necessary to build a multicellular organism from a single cell. © 2015 Hutter and Moerman. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Learning to ignore: acquisition of sustained attentional suppression.

Science.gov (United States)

Dixon, Matthew L; Ruppel, Justin; Pratt, Jay; De Rosa, Eve

2009-04-01

We examined whether the selection mechanisms committed to the suppression of ignored stimuli can be modified by experience to produce a sustained, rather than transient, change in behavior. Subjects repeatedly ignored the shape of stimuli, while attending to their color. On subsequent attention to shape, there was a robust and sustained decrement in performance that was selective to when shape was ignored across multiple-color-target contexts, relative to a single-color-target context. Thus, amount of time ignored was not sufficient to induce a sustained performance decrement. Moreover, in this group, individual differences in initial color target selection were associated with the subsequent performance decrement when attending to previously ignored stimuli. Accompanying this sustained decrement in performance was a transfer in the locus of suppression from an exemplar (e.g., a circle) to a feature (i.e., shape) level of representation. These data suggest that learning can influence attentional selection by sustained attentional suppression of ignored stimuli.

The Evolution of a Big Idea: Why Don't We Know Anything about Africa?

Science.gov (United States)

Meyer, Michael James

2009-01-01

This article is about my experiences as a ninth grade history teacher trying to implement a "big idea" unit on ancient African history. My experiences as a first year teacher and also my experience in seeing this unit develop over three years are chronicled. I conclude that implementing a big idea strategy of instruction is possible in a…

The virtues of ignorance.

Science.gov (United States)

Son, Lisa K; Kornell, Nate

2010-02-01

Although ignorance and uncertainty are usually unwelcome feelings, they have unintuitive advantages for both human and non-human animals, which we review here. We begin with the perils of too much information: expertise and knowledge can come with illusions (and delusions) of knowing. We then describe how withholding information can counteract these perils: providing people with less information enables them to judge more precisely what they know and do not know, which in turn enhances long-term memory. Data are presented from a new experiment that illustrates how knowing what we do not know can result in helpful choices and enhanced learning. We conclude by showing that ignorance can be a virtue, as long as it is recognized and rectified. Copyright 2009 Elsevier B.V. All rights reserved.

A Quantum Universe Before the Big Bang(s)?

Science.gov (United States)

Veneziano, Gabriele

2017-08-01

The predictions of general relativity have been verified by now in a variety of different situations, setting strong constraints on any alternative theory of gravity. Nonetheless, there are strong indications that general relativity has to be regarded as an approximation of a more complete theory. Indeed theorists have long been looking for ways to connect general relativity, which describes the cosmos and the infinitely large, to quantum physics, which has been remarkably successful in explaining the infinitely small world of elementary particles. These two worlds, however, come closer and closer to each other as we go back in time all the way up to the big bang. Actually, modern cosmology has changed completely the old big bang paradigm: we now have to talk about (at least) two (big?) bangs. If we know quite something about the one closer to us, at the end of inflation, we are much more ignorant about the one that may have preceded inflation and possibly marked the beginning of time. No one doubts that quantum mechanics plays an essential role in answering these questions: unfortunately a unified theory of gravity and quantum mechanics is still under construction. Finding such a synthesis and confirming it experimentally will no doubt be one of the biggest challenges of this century’s physics.

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  

Framing Big Data: The discursive construction of a radio cell query in Germany

Directory of Open Access Journals (Sweden)

Christian Pentzold

2017-11-01

Full Text Available The article examines the construction of “Big Data” in media discourse. Rather than asking what Big Data really is or is not, it deals with the discursive work that goes into making Big Data a socially relevant phenomenon and problem in the first place. It starts from the idea that in modern societies the public understanding of technology is largely driven by a media-based discourse, which is a key arena for circulating collectively shared meanings. This largely ignored dimension invites us to appreciate what matters to journalists and the wider public when discussing the collection and use of data. To this end, our study looks at how Big Data is framed in terms of the governmental use of large datasets as a contentious area of data application. It reconstructs the perspectives surrounding the so-called “Handygate” affair in Germany based on broadcast news and social media conversations. In this incident, state authorities collected and analyzed mobile phone data through a radio cell query during events to commemorate the Dresden bombing in February 2011. We employ a qualitative discourse analysis that allows us to reconstruct the conceptualizations of Big Data as a proper instrument for criminal prosecution or an unjustified infringement of constitutional rights.

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

Aspiring to Spectral Ignorance in Earth Observation

Science.gov (United States)

Oliver, S. A.

2016-12-01

Enabling robust, defensible and integrated decision making in the Era of Big Earth Data requires the fusion of data from multiple and diverse sensor platforms and networks. While the application of standardised global grid systems provides a common spatial analytics framework that facilitates the computationally efficient and statistically valid integration and analysis of these various data sources across multiple scales, there remains the challenge of sensor equivalency; particularly when combining data from different earth observation satellite sensors (e.g. combining Landsat and Sentinel-2 observations). To realise the vision of a sensor ignorant analytics platform for earth observation we require automation of spectral matching across the available sensors. Ultimately, the aim is to remove the requirement for the user to possess any sensor knowledge in order to undertake analysis. This paper introduces the concept of spectral equivalence and proposes a methodology through which equivalent bands may be sourced from a set of potential target sensors through application of equivalence metrics and thresholds. A number of parameters can be used to determine whether a pair of spectra are equivalent for the purposes of analysis. A baseline set of thresholds for these parameters and how to apply them systematically to enable relation of spectral bands amongst numerous different sensors is proposed. The base unit for comparison in this work is the relative spectral response. From this input, determination of a what may constitute equivalence can be related by a user, based on their own conceptualisation of equivalence.

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…

On strategic ignorance of environmental harm and social norms

DEFF Research Database (Denmark)

Thunström, Linda; van 't Veld, Klaas; Shogren, Jason

, and that they use ignorance as an excuse to engage in less pro-environmental behavior. It also predicts that the cost of ignorance increases if people can learn about the social norm from the information. We test the model predictions empirically with an experiment that involves an imaginary long- distance flight...... and an option to buy offsets for the flight’s carbon footprint. More than half (53 percent) of the subjects choose to ignore information on the carbon footprint alone before deciding their offset purchase, but ignorance significantly decreases (to 29 percent) when the information additionally reveals the social...

Improving Healthcare Using Big Data Analytics

Directory of Open Access Journals (Sweden)

Revanth Sonnati

2017-03-01

Full Text Available In daily terms we call the current era as Modern Era which can also be named as the era of Big Data in the field of Information Technology. Our daily lives in todays world are rapidly advancing never quenching ones thirst. The fields of science engineering and technology are producing data at an exponential rate leading to Exabytes of data every day. Big data helps us to explore and re-invent many areas not limited to education health and law. The primary purpose of this paper is to provide an in-depth analysis in the area of Healthcare using the big data and analytics. The main purpose is to emphasize on the usage of the big data which is being stored all the time helping to look back in the history but this is the time to emphasize on the analyzation to improve the medication and services. Although many big data implementations happen to be in-house development this proposed implementation aims to propose a broader extent using Hadoop which just happen to be the tip of the iceberg. The focus of this paper is not limited to the improvement and analysis of the data it also focusses on the strengths and drawbacks compared to the conventional techniques available.

DMPD: TLR ignores methylated RNA? [Dynamic Macrophage Pathway CSML Database

Lifescience Database Archive (English)

Full Text Available 16111629 TLR ignores methylated RNA? Ishii KJ, Akira S. Immunity. 2005 Aug;23(2):11...1-3. (.png) (.svg) (.html) (.csml) Show TLR ignores methylated RNA? PubmedID 16111629 Title TLR ignores methylated

Big Sites, Big Questions, Big Data, Big Problems: Scales of Investigation and Changing Perceptions of Archaeological Practice in the Southeastern United States

Directory of Open Access Journals (Sweden)

Cameron B Wesson

2014-08-01

Full Text Available Since at least the 1930s, archaeological investigations in the southeastern United States have placed a priority on expansive, near-complete, excavations of major sites throughout the region. Although there are considerable advantages to such large–scale excavations, projects conducted at this scale are also accompanied by a series of challenges regarding the comparability, integrity, and consistency of data recovery, analysis, and publication. We examine the history of large–scale excavations in the southeast in light of traditional views within the discipline that the region has contributed little to the ‘big questions’ of American archaeology. Recently published analyses of decades old data derived from Southeastern sites reveal both the positive and negative aspects of field research conducted at scales much larger than normally undertaken in archaeology. Furthermore, given the present trend toward the use of big data in the social sciences, we predict an increased use of large pre–existing datasets developed during the New Deal and other earlier periods of archaeological practice throughout the region.

Knowledge, responsibility, decision making and ignorance

DEFF Research Database (Denmark)

Huniche, Lotte

2001-01-01

of and ignoring) seems to be commonly applicable to describing persons living at risk for Huntington´s Disease (HD). So what does everyday conduct of life look like from an "ignorance" perspective? And how can we discuss and argue about morality and ethics taking these seemingly diverse ways of living at risk...... into account? Posing this question, I hope to contribute to new reflections on possibilities and constraints in people´s lives with HD as well as in research and to open up new ways of discussing "right and wrong"....

Infectious Disease Surveillance in the Big Data Era

DEFF Research Database (Denmark)

Simonsen, Lone; Gog, Julia R.; Olson, Don

2016-01-01

, flexible, and local tracking of infectious diseases, especially for emerging pathogens. In this opinion piece, we reflect on the long and distinguished history of disease surveillance and discuss recent developments related to use of big data. We start with a brief review of traditional systems relying...... of Google Flu Trends. We conclude by advocating for increased use of hybrid systems combining information from traditional surveillance and big data sources, which seems the most promising option moving forward. Throughout the article, we use influenza as an exemplar of an emerging and reemerging infection...

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.

On strategic ignorance of environmental harm and social norms

DEFF Research Database (Denmark)

Thunström, Linda; van’t Veld, Klaas; Shogren, Jason. F.

2014-01-01

decreases (to 29 percent) when the information additionally reveals the share of air travelers who buy carbon offsets. We find evidence that some people use ignorance as an excuse to reduce pro-environmental behavior—ignorance significantly decreases the probability of buying carbon offsets.......Are people strategically ignorant of the negative externalities their activities cause the environment? Herein we examine if people avoid costless information on those externalities and use ignorance as an excuse to reduce pro-environmental behavior. We develop a theoretical framework in which...... people feel internal pressure (“guilt”) from causing harm to the environment (e.g., emitting carbon dioxide) as well as external pressure to conform to the social norm for pro-environmental behavior (e.g., offsetting carbon emissions). Our model predicts that people may benefit from avoiding information...

Mes chers collègues, les moines, ou le partage de l’ignorance

Directory of Open Access Journals (Sweden)

Laurence Caillet

2009-03-01

Full Text Available Mes chers collègues, les moines, ou le partage de l’ignorance. Aucun statut ne m’a autant étonnée que celui de collègue qui me fut conféré par les moines du Grand monastère de l’Est, à Nara. Après avoir testé mes connaissances en matière de rituel, ces moines fort savants manifestèrent en effet, avec ostentation, leur ignorance. Pointant pour moi des détails liturgiques qu’ils tenaient pour incompréhensibles, ils prirent un plaisir évident à bavarder histoire et théologie, comme si je pouvais apporter quoi que ce soit. Cette mise en scène du caractère incompréhensible du rituel soulignait le caractère ineffable de cérémonies jadis accomplies au ciel par des entités supérieures. Je fournissais prétexte à décrire la vanité de l’érudition face à l’accomplissement des mystères et aussi l’importance de cette érudition pour renouer avec un sens originel irrémédiablement inconnaissable.My dear colleagues the monks, or the sharing of ignorance. No status has ever surprised me as much as that of “colleague” conferred on me by the monks of the Great Eastern Monastery of Nara. After testing my knowledge of ritual, these very learned monks made great show of their ignorance. Drawing my attention to liturgical details that they held to be incomprehensible, they took obvious pleasure in chatting about history and theology, as if I were capable of making the slightest contribution. This staging of the impenetrable nature of the ritual highlighted the ineffable character of the ceremonies performed in heaven long ago by superior beings. I provided a convenient pretext for describing the vanity of erudition in the face of the accomplishment of the mysteries, and also the importance of this erudition for renewing an original, irreparably unknowable meaning.

Big Bang Cosmic Titanic: Cause for Concern?

Science.gov (United States)

Gentry, Robert

2013-04-01

This abstract alerts physicists to a situation that, unless soon addressed, may yet affect PRL integrity. I refer to Stanley Brown's and DAE Robert Caldwell's rejection of PRL submission LJ12135, A Cosmic Titanic: Big Bang Cosmology Unravels Upon Discovery of Serious Flaws in Its Foundational Expansion Redshift Assumption, by their claim that BB is an established theory while ignoring our paper's Titanic, namely, that BB's foundational spacetime expansion redshifts assumption has now been proven to be irrefutably false because it is contradicted by our seminal discovery that GPS operation unequivocally proves that GR effects do not produce in-flight photon wavelength changes demanded by this central assumption. This discovery causes the big bang to collapse as quickly as did Ptolemaic cosmology when Copernicus discovered its foundational assumption was heliocentric, not geocentric. Additional evidence that something is amiss in PRL's treatment of LJ12135 comes from both Brown and EiC Gene Spouse agreeing to meet at my exhibit during last year's Atlanta APS to discuss this cover-up issue. Sprouse kept his commitment; Brown didn't. Question: If Brown could have refuted my claim of a cover-up, why didn't he come to present it before Gene Sprouse? I am appealing LJ12135's rejection.

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…

Molecular ecology of the big brown bat (Eptesicus fuscus): Genetic and natural history variation in a hybrid zone

Science.gov (United States)

Neubaum, M.A.; Douglas, M.R.; Douglas, M.E.; O'Shea, T.J.

2007-01-01

Several geographically distinct mitochondrial DNA (mtDNA) lineages of the big brown bat (Eptesicus fuscus) have been documented in North America. Individuals from 2 of these lineages, an eastern and a western form, co-occur within maternity colonies in Colorado. The discovery of 2 divergent mtDNA lineages in sympatry prompted a set of questions regarding possible biological differences between haplotypes. We captured big brown bats at maternity roosts in Colorado and recorded data on body size, pelage color, litter size, roosting and overwintering behaviors, and local distributions. Wing biopsies were collected for genetic analysis. The ND2 region of the mtDNA molecule was used to determine lineage of the bats. In addition, nuclear DNA (nDNA) intron 1 of the ??-globin gene was used to determine if mtDNA lineages are hybridizing. Eastern and western mtDNA lineages differed by 10.3% sequence divergence and examination of genetic data suggests recent population expansion for both lineages. Differences in distribution occur along the Colorado Front Range, with an increasing proportion of western haplotypes farther south. Results from nDNA analyses demonstrated hybridization between the 2 lineages. Additionally, no outstanding distinctiveness was found between the mtDNA lineages in natural history characters examined. We speculate that historical climate changes separated this species into isolated eastern and western populations, and that secondary contact with subsequent interbreeding was facilitated by European settlement. ?? 2007 American Society of Mammalogists.

Le big bang n'est pas une théorie comme les autres

CERN Document Server

Bonnet-Bidaud, Jean-Marc; Leglu, Dominique; Reinisch, Gilbert

2009-01-01

Le big bang n'est pas une théorie comme les autres. Ce n'est d'ailleurs pas une théorie physique au sens propre du terme, mais un scénario cosmologique issu des équations de la relativité générale. Il est le modèle qui s'ajuste le mieux aux observations actuelles, mais à quel prix ? Il nous livre un Univers composé à 96 % de matière et d'énergie noires inconnues. C'est donc un euphémisme que de dire que le big bang semble poser autant - sinon plus - de questions qu'il n'en résout. En ce sens, le big bang apparaît davantage comme une paramétrisation de notre ignorance plutôt que comme une modélisation d'un phénomène. Pourtant, le succès du big bang et l'adhésion qu'il suscite, tant dans la sphère scientifique que dans la sphère médiatique, ne se démentent pas. Surmédiatisé, son statut dépasse celui de modèle théorique, et la simple évocation de son nom suffit pour justifier des opérations de marketing scientifique ou rejeter des cosmologies alternatives. Pour éclaircir les pr...

The Ethics of Big Data: Current and Foreseeable Issues in Biomedical Contexts.

Science.gov (United States)

Mittelstadt, Brent Daniel; Floridi, Luciano

2016-04-01

The capacity to collect and analyse data is growing exponentially. Referred to as 'Big Data', this scientific, social and technological trend has helped create destabilising amounts of information, which can challenge accepted social and ethical norms. Big Data remains a fuzzy idea, emerging across social, scientific, and business contexts sometimes seemingly related only by the gigantic size of the datasets being considered. As is often the case with the cutting edge of scientific and technological progress, understanding of the ethical implications of Big Data lags behind. In order to bridge such a gap, this article systematically and comprehensively analyses academic literature concerning the ethical implications of Big Data, providing a watershed for future ethical investigations and regulations. Particular attention is paid to biomedical Big Data due to the inherent sensitivity of medical information. By means of a meta-analysis of the literature, a thematic narrative is provided to guide ethicists, data scientists, regulators and other stakeholders through what is already known or hypothesised about the ethical risks of this emerging and innovative phenomenon. Five key areas of concern are identified: (1) informed consent, (2) privacy (including anonymisation and data protection), (3) ownership, (4) epistemology and objectivity, and (5) 'Big Data Divides' created between those who have or lack the necessary resources to analyse increasingly large datasets. Critical gaps in the treatment of these themes are identified with suggestions for future research. Six additional areas of concern are then suggested which, although related have not yet attracted extensive debate in the existing literature. It is argued that they will require much closer scrutiny in the immediate future: (6) the dangers of ignoring group-level ethical harms; (7) the importance of epistemology in assessing the ethics of Big Data; (8) the changing nature of fiduciary relationships that

Ignorance-Based Instruction in Higher Education.

Science.gov (United States)

Stocking, S. Holly

1992-01-01

Describes how three groups of educators (in a medical school, a psychology department, and a journalism school) are helping instructors and students to recognize, manage, and use ignorance to promote learning. (SR)

The universe before the Big Bang cosmology and string theory

CERN Document Server

Gasperini, Maurizio

2008-01-01

Terms such as "expanding Universe", "big bang", and "initial singularity", are nowadays part of our common language. The idea that the Universe we observe today originated from an enormous explosion (big bang) is now well known and widely accepted, at all levels, in modern popular culture. But what happens to the Universe before the big bang? And would it make any sense at all to ask such a question? In fact, recent progress in theoretical physics, and in particular in String Theory, suggests answers to the above questions, providing us with mathematical tools able in principle to reconstruct the history of the Universe even for times before the big bang. In the emerging cosmological scenario the Universe, at the epoch of the big bang, instead of being a "new born baby" was actually a rather "aged" creature in the middle of its possibly infinitely enduring evolution. The aim of this book is to convey this picture in non-technical language accessibile also to non-specialists. The author, himself a leading cosm...

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."

Big Impacts and Transient Oceans on Titan

Science.gov (United States)

Zahnle, K. J.; Korycansky, D. G.; Nixon, C. A.

2014-01-01

We have studied the thermal consequences of very big impacts on Titan [1]. Titan's thick atmosphere and volatile-rich surface cause it to respond to big impacts in a somewhat Earth-like manner. Here we construct a simple globally-averaged model that tracks the flow of energy through the environment in the weeks, years, and millenia after a big comet strikes Titan. The model Titan is endowed with 1.4 bars of N2 and 0.07 bars of CH4, methane lakes, a water ice crust, and enough methane underground to saturate the regolith to the surface. We assume that half of the impact energy is immediately available to the atmosphere and surface while the other half is buried at the site of the crater and is unavailable on time scales of interest. The atmosphere and surface are treated as isothermal. We make the simplifying assumptions that the crust is everywhere as methane saturated as it was at the Huygens landing site, that the concentration of methane in the regolith is the same as it is at the surface, and that the crust is made of water ice. Heat flow into and out of the crust is approximated by step-functions. If the impact is great enough, ice melts. The meltwater oceans cool to the atmosphere conductively through an ice lid while at the base melting their way into the interior, driven down in part through Rayleigh-Taylor instabilities between the dense water and the warm ice. Topography, CO2, and hydrocarbons other than methane are ignored. Methane and ethane clathrate hydrates are discussed quantitatively but not fully incorporated into the model.

Postmodernism, historical denial, and history education:

Directory of Open Access Journals (Sweden)

Robert John Parkes

2015-12-01

Full Text Available History educators frequently ignore, or engage only reluctantly and cautiously with postmodernism. This is arguably because postmodernism is frequently accused of assaulting the epistemological foundations of history as an academic discipline, fostering a climate of cultural relativism, encouraging the proliferation of revisionist histories, and providing fertile ground for historical denial. In the Philosophy of History discipline, Frank Ankersmit has become one of those scholars most closely associated with ‘postmodern history’. This paper explores Ankersmit’s ‘postmodern’ philosophy of history, particularly his key notion of ‘narrative substances’; what it might do for our approach to a problem such as historical denial; and what possibilities it presents for history didactics.

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.

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.)

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

Too big to ignore the business case for big data

CERN Document Server

Simon, Phil

2013-01-01

Residents in Boston, Massachusetts are automatically reporting potholes and road hazards via their smartphones. Progressive Insurance tracks real-time customer driving patterns and uses that information to offer rates truly commensurate with individual safety. Google accurately predicts local flu outbreaks based upon thousands of user search queries. Amazon provides remarkably insightful, relevant, and timely product recommendations to its hundreds of millions of customers. Quantcast lets companies target precise audiences and key demographics throughout the Web. NASA runs contests via gami

Mid-adolescent neurocognitive development of ignoring and attending emotional stimuli

Directory of Open Access Journals (Sweden)

Nora C. Vetter

2015-08-01

Full Text Available Appropriate reactions toward emotional stimuli depend on the distribution of prefrontal attentional resources. In mid-adolescence, prefrontal top-down control systems are less engaged, while subcortical bottom-up emotional systems are more engaged. We used functional magnetic resonance imaging to follow the neural development of attentional distribution, i.e. attending versus ignoring emotional stimuli, in adolescence. 144 healthy adolescents were studied longitudinally at age 14 and 16 while performing a perceptual discrimination task. Participants viewed two pairs of stimuli – one emotional, one abstract – and reported on one pair whether the items were the same or different, while ignoring the other pair. Hence, two experimental conditions were created: “attending emotion/ignoring abstract” and “ignoring emotion/attending abstract”. Emotional valence varied between negative, positive, and neutral. Across conditions, reaction times and error rates decreased and activation in the anterior cingulate and inferior frontal gyrus increased from age 14 to 16. In contrast, subcortical regions showed no developmental effect. Activation of the anterior insula increased across ages for attending positive and ignoring negative emotions. Results suggest an ongoing development of prefrontal top-down resources elicited by emotional attention from age 14 to 16 while activity of subcortical regions representing bottom-up processing remains stable.

Astronomy in the Big Data Era

Directory of Open Access Journals (Sweden)

Yanxia Zhang

2015-05-01

Full Text Available The fields of Astrostatistics and Astroinformatics are vital for dealing with the big data issues now faced by astronomy. Like other disciplines in the big data era, astronomy has many V characteristics. In this paper, we list the different data mining algorithms used in astronomy, along with data mining software and tools related to astronomical applications. We present SDSS, a project often referred to by other astronomical projects, as the most successful sky survey in the history of astronomy and describe the factors influencing its success. We also discuss the success of Astrostatistics and Astroinformatics organizations and the conferences and summer schools on these issues that are held annually. All the above indicates that astronomers and scientists from other areas are ready to face the challenges and opportunities provided by massive data volume.

Inflationary and deflationary branches in extended pre-big-bang cosmology

International Nuclear Information System (INIS)

Lidsey, J.E.

1997-01-01

The pre-big-bang cosmological scenario is studied within the context of the Brans-Dicke theory of gravity. An epoch of superinflationary expansion may occur in the pre-big-bang phase of the Universe close-quote s history in a certain region of parameter space. Two models are considered that contain a cosmological constant in the gravitational and matter sectors of the theory, respectively. Classical pre- and post-big-bang solutions are found for both models. The existence of a curvature singularity forbids a classical transition between the two branches. On the other hand, a quantum cosmological approach based on the tunneling boundary condition results in a nonzero transition probability. The transition may be interpreted as a spatial reflection of the wave function in minisuperspace. copyright 1997 The American Physical Society

Inflationary and deflationary branches in extended pre-big-bang cosmology

Energy Technology Data Exchange (ETDEWEB)

Lidsey, J.E. [Astronomy Unit, School of Mathematical Sciences, Queen Mary Westfield, Mile End Road, London, E1 4NS (United Kingdom)

1997-03-01

The pre-big-bang cosmological scenario is studied within the context of the Brans-Dicke theory of gravity. An epoch of superinflationary expansion may occur in the pre-big-bang phase of the Universe{close_quote}s history in a certain region of parameter space. Two models are considered that contain a cosmological constant in the gravitational and matter sectors of the theory, respectively. Classical pre- and post-big-bang solutions are found for both models. The existence of a curvature singularity forbids a classical transition between the two branches. On the other hand, a quantum cosmological approach based on the tunneling boundary condition results in a nonzero transition probability. The transition may be interpreted as a spatial reflection of the wave function in minisuperspace. {copyright} {ital 1997} {ital The American Physical Society}

Fault-ignorant quantum search

International Nuclear Information System (INIS)

Vrana, Péter; Reeb, David; Reitzner, Daniel; Wolf, Michael M

2014-01-01

We investigate the problem of quantum searching on a noisy quantum computer. Taking a fault-ignorant approach, we analyze quantum algorithms that solve the task for various different noise strengths, which are possibly unknown beforehand. We prove lower bounds on the runtime of such algorithms and thereby find that the quadratic speedup is necessarily lost (in our noise models). However, for low but constant noise levels the algorithms we provide (based on Grover's algorithm) still outperform the best noiseless classical search algorithm. (paper)

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...

2013 strategic petroleum reserve big hill well integrity grading report.

Energy Technology Data Exchange (ETDEWEB)

Lord, David L.; Roberts, Barry L.; Lord, Anna C. Snider; Bettin, Giorgia; Sobolik, Steven Ronald; Park, Byoung Yoon; Rudeen, David Keith; Eldredge, Lisa; Wynn, Karen; Checkai, Dean; Perry, James Thomas

2014-02-01

This report summarizes the work performed in developing a framework for the prioritization of cavern access wells for remediation and monitoring at the Big Hill Strategic Petroleum Reserve site. This framework was then applied to all 28 wells at the Big Hill site with each well receiving a grade for remediation and monitoring. Numerous factors affecting well integrity were incorporated into the grading framework including casing survey results, cavern pressure history, results from geomechanical simulations, and site geologic factors. The framework was developed in a way as to be applicable to all four of the Strategic Petroleum Reserve sites.

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…

Surveillance, Snowden, and Big Data: Capacities, consequences, critique

Directory of Open Access Journals (Sweden)

David Lyon

2014-07-01

Full Text Available The Snowden revelations about National Security Agency surveillance, starting in 2013, along with the ambiguous complicity of internet companies and the international controversies that followed provide a perfect segue into contemporary conundrums of surveillance and Big Data. Attention has shifted from late C20th information technologies and networks to a C21st focus on data, currently crystallized in “Big Data.” Big Data intensifies certain surveillance trends associated with information technology and networks, and is thus implicated in fresh but fluid configurations. This is considered in three main ways: One, the capacities of Big Data (including metadata intensify surveillance by expanding interconnected datasets and analytical tools. Existing dynamics of influence, risk-management, and control increase their speed and scope through new techniques, especially predictive analytics. Two, while Big Data appears to be about size, qualitative change in surveillance practices is also perceptible, accenting consequences. Important trends persist – the control motif, faith in technology, public-private synergies, and user-involvement – but the future-orientation increasingly severs surveillance from history and memory and the quest for pattern-discovery is used to justify unprecedented access to data. Three, the ethical turn becomes more urgent as a mode of critique. Modernity's predilection for certain definitions of privacy betrays the subjects of surveillance who, so far from conforming to the abstract, disembodied image of both computing and legal practices, are engaged and embodied users-in-relation whose activities both fuel and foreclose surveillance.

Big Bang, Blowup, and Modular Curves: Algebraic Geometry in Cosmology

Science.gov (United States)

Manin, Yuri I.; Marcolli, Matilde

2014-07-01

We introduce some algebraic geometric models in cosmology related to the ''boundaries'' of space-time: Big Bang, Mixmaster Universe, Penrose's crossovers between aeons. We suggest to model the kinematics of Big Bang using the algebraic geometric (or analytic) blow up of a point x. This creates a boundary which consists of the projective space of tangent directions to x and possibly of the light cone of x. We argue that time on the boundary undergoes the Wick rotation and becomes purely imaginary. The Mixmaster (Bianchi IX) model of the early history of the universe is neatly explained in this picture by postulating that the reverse Wick rotation follows a hyperbolic geodesic connecting imaginary time axis to the real one. Penrose's idea to see the Big Bang as a sign of crossover from ''the end of previous aeon'' of the expanding and cooling Universe to the ''beginning of the next aeon'' is interpreted as an identification of a natural boundary of Minkowski space at infinity with the Big Bang boundary.

Leadership in the Big Bangs of European Integration

DEFF Research Database (Denmark)

? and, more importantly, what factors allowed specific actors to provide leadership in a given context? These conclusions provide a major step forward in the literature on the history-making bargains in the EU, allowing us to answer with more confidence the question of which actors have guided the big...... bangs in the European integration process in the past two decades, and why.  ...

Big Bang Titanic: New Dark Energy (Vacuum Gravity) Cosmic Model Emerges Upon Falsification of The Big Bang By Disproof of Its Central Assumptions

Science.gov (United States)

Gentry, Robert

2011-04-01

Physicists who identify the big bang with the early universe should have first noted from Hawking's A Brief History of Time, p. 42, that he ties Hubble's law to Doppler shifts from galaxy recession from a nearby center, not to bb's unvalidated and thus problematical expansion redshifts. Our PRL submission LJ12135 describes such a model, but in it Hubble's law is due to Doppler and vacuum gravity effects, the 2.73K CBR is vacuum gravity shifted blackbody cavity radiation from an outer galactic shell, and its (1 + z)-1 dilation and (M,z) relations closely fit high-z SNe Ia data; all this strongly implies our model's vacuum energy is the elusive dark energy. We also find GPS operation's GR effects falsify big bang's in-flight expansion redshift paradigm, and hence the big bang, by showing λ changes occur only at emission. Surprisingly we also discover big bang's CBR prediction is T 0, while galactic photons shrink dλ/dt < 0. Contrary to a PRL editor's claim, the above results show LJ12135 fits PRL guidelines for papers that replace established theories. For details see alphacosmos.net.

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.

Putting the five-factor model into context: evidence linking big five traits to narrative identity.

Science.gov (United States)

Raggatt, Peter

2006-10-01

The study examined relationships between the Big Five personality traits and thematic content extracted from self-reports of life history data. One hundred and five "mature age" university students (M=30.1 years) completed the NEO PI-R trait measure, and the Personality Web Protocol. The protocol examines constituents of identity by asking participants to describe 24 key "attachments" from their life histories (significant events, people, places, objects, and possessions). Participants sorted these attachments into clusters and provided a self-descriptive label for each cluster (e.g., "adventurous self"). It was predicted that the thematic content of these cluster labels would be systematically related to Big Five trait scores (e.g., that labels referring to strength or positive emotions would be linked to Extraversion). The hypothesized links were obtained for each of the Big Five trait domains except Conscientiousness. Results are discussed with a view to broadening our understanding of the Five-Factor Model in relation to units of personality other than traits.

The concept of ignorance in a risk assessment and risk management context

International Nuclear Information System (INIS)

Aven, T.; Steen, R.

2010-01-01

There are many definitions of ignorance in the context of risk assessment and risk management. Most refer to situations in which there are lack of knowledge, poor basis for probability assignments and possible outcomes not (fully) known. The purpose of this paper is to discuss the ignorance concept in this setting. Based on a set of risk and uncertainty features, we establish conceptual structures characterising the level of ignorance. These features include the definition of chances (relative frequency-interpreted probabilities) and the existence of scientific uncertainties. Based on these structures, we suggest a definition of ignorance linked to scientific uncertainties, i.e. the lack of understanding of how consequences of the activity are influenced by the underlying factors. In this way, ignorance can be viewed as a condition for applying the precautionary principle. The discussion is also linked to the use and boundaries of risk assessments in the case of large uncertainties, and the methods for classifying risk and uncertainty problems.

What Is Hospitality in the Academy? Epistemic Ignorance and the (Im)possible Gift

Science.gov (United States)

Kuokkanen, Rauna

2008-01-01

The academy is considered by many as the major Western institution of knowledge. This article, however, argues that the academy is characterized by prevalent "epistemic ignorance"--a concept informed by Spivak's discussion of "sanctioned ignorance." Epistemic ignorance refers to academic practices and discourses that enable the continued exclusion…

Experiences of Being Ignored by Peers during Late Adolescence: Linkages to Psychological Maladjustment

Science.gov (United States)

Bowker, Julie C.; Adams, Ryan E.; Fredstrom, Bridget K.; Gilman, Rich

2014-01-01

In this study on being ignored by peers, 934 twelfth-grade students reported on their experiences of being ignored, victimized, and socially withdrawn, and completed measures of friendship and psychological adjustment (depression, self-esteem, and global satisfaction). Peer nominations of being ignored, victimized, and accepted by peers were also…

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...

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

Vertical landscraping, a big regionalism for Dubai.

Science.gov (United States)

Wilson, Matthew

2010-01-01

Dubai's ecologic and economic complications are exacerbated by six years of accelerated expansion, a fixed top-down approach to urbanism and the construction of iconic single-phase mega-projects. With recent construction delays, project cancellations and growing landscape issues, Dubai's tower typologies have been unresponsive to changing environmental, socio-cultural and economic patterns (BBC, 2009; Gillet, 2009; Lewis, 2009). In this essay, a theory of "Big Regionalism" guides an argument for an economically and ecologically linked tower typology called the Condenser. This phased "box-to-tower" typology is part of a greater Landscape Urbanist strategy called Vertical Landscraping. Within this strategy, the Condenser's role is to densify the city, facilitating the creation of ecologic voids that order the urban region. Delineating "Big Regional" principles, the Condenser provides a time-based, global-local urban growth approach that weaves Bigness into a series of urban-regional, economic and ecological relationships, builds upon the environmental performance of the city's regional architecture and planning, promotes a continuity of Dubai's urban history, and responds to its landscape issues while condensing development. These speculations permit consideration of the overlooked opportunities embedded within Dubai's mega-projects and their long-term impact on the urban morphology.

Global fluctuation spectra in big-crunch-big-bang string vacua

International Nuclear Information System (INIS)

Craps, Ben; Ovrut, Burt A.

2004-01-01

We study big-crunch-big-bang cosmologies that correspond to exact world-sheet superconformal field theories of type II strings. The string theory spacetime contains a big crunch and a big bang cosmology, as well as additional 'whisker' asymptotic and intermediate regions. Within the context of free string theory, we compute, unambiguously, the scalar fluctuation spectrum in all regions of spacetime. Generically, the big crunch fluctuation spectrum is altered while passing through the bounce singularity. The change in the spectrum is characterized by a function Δ, which is momentum and time dependent. We compute Δ explicitly and demonstrate that it arises from the whisker regions. The whiskers are also shown to lead to 'entanglement' entropy in the big bang region. Finally, in the Milne orbifold limit of our superconformal vacua, we show that Δ→1 and, hence, the fluctuation spectrum is unaltered by the big-crunch-big-bang singularity. We comment on, but do not attempt to resolve, subtleties related to gravitational back reaction and light winding modes when interactions are taken into account

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.

From the Big Bang to the Nobel Prize and on to the James Webb Space Telescope

Science.gov (United States)

Mather, John C.

2008-01-01

The history of the universe in a nutshell, from the Big Bang to now. and on to the future - John Mather will tell the story of how we got here, how the Universe began with a Big Bang, how it could have produced an Earth where sentient beings can live, and how those beings are discovering their history. Mather was Project Scientist for NASA's Cosmic Background Explorer (COBE) satellite, which measured the spectrum (the color) of the heat radiation from the Big Bang, discovered hot and cold spots in that radiation, and hunted for the first objects that formed after the great explosion. He will explain Einstein's biggest mistake, show how Edwin Hubble discovered the expansion of the univerre, how the COBE mission was built, and how the COBE data support the Big Bang theory. He will also show NASA's plans for the next great telescope in space, the Jarnes Webb Space Telescope. It will look even farther back in time than the Hubble Space Telescope, and will look inside the dusty cocoons where rtars and planets are being born today. Planned for launch in 2013, it may lead to another Nobel Prize for some lucky observer.

Modelling non-ignorable missing data mechanisms with item response theory models

NARCIS (Netherlands)

Holman, Rebecca; Glas, Cornelis A.W.

2005-01-01

A model-based procedure for assessing the extent to which missing data can be ignored and handling non-ignorable missing data is presented. The procedure is based on item response theory modelling. As an example, the approach is worked out in detail in conjunction with item response data modelled

Modelling non-ignorable missing-data mechanisms with item response theory models

NARCIS (Netherlands)

Holman, Rebecca; Glas, Cees A. W.

2005-01-01

A model-based procedure for assessing the extent to which missing data can be ignored and handling non-ignorable missing data is presented. The procedure is based on item response theory modelling. As an example, the approach is worked out in detail in conjunction with item response data modelled

From the Big Bang to the Nobel Prize and on to James Webb Space Telescope

Science.gov (United States)

Mather, John C.

2009-01-01

The history of the universe in a nutshell, from the Big Bang to now, and on to the future - John Mather will tell the story of how we got here, how the Universe began with a Big Bang, how it could have produced an Earth where sentient beings can live, and how those beings are discovering their history. Mather was Project Scientist for NASA s Cosmic Background Explorer (COBE) satellite, which measured the spectrum (the color) of the heat radiation from the Big Bang, discovered hot and cold spots in that radiation, and hunted for the first objects that formed after the great explosion. He will explain Einstein s biggest mistake, show how Edwin Hubble discovered the expansion of the universe, how the COBE mission was built, and how the COBE data support the Big Bang theory. He will also show NASA s plans for the next great telescope in space, the James Webb Space Telescope. It will look even farther back in time than the Hubble Space Telescope, and will look inside the dusty cocoons where stars and planets are being born today. Planned for launch in 2013, it may lead to another Nobel Prize for some lucky observer.

Günther Grass and the Pirates: The Stuff of Myth and the Baltic Sea

Directory of Open Access Journals (Sweden)

Kenneth J Knoespel

2013-04-01

Full Text Available Grass’s Flounder contributes to our work of locating, dislocating, and relocating literature in the Baltic Sea region by challenging us to give attention to the lost or hidden stories that are ignored or played off against each other in the official versions of history that would fix our position in space. While Grass counters the seduction of the big story — universal history — he also reveals himself by getting caught in the contradiction of his own storytelling.

Science Big Bang comes to the Alps

CERN Multimedia

2008-01-01

The most extensive and expensive scientific instrument in history is due to start working this summer at Cern, the European particle physics laboratory near Geneva. Two beams of protons will accelerate in opposite directions around a 27km tunnel under the Alpine foothills until they are travelling almost at the speed of light - and then smash together, reproducing on a tiny scale the intense energy of the new-born universe after the inaugural Big Bang 15bn years ago.

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

Can history improve big bang health reform? Commentary.

Science.gov (United States)

Marchildon, Gregory P

2018-01-26

At present, the professional skills of the historian are rarely relied upon when health policies are being formulated. There are numerous reasons for this, one of which is the natural desire of decision-makers to break with the past when enacting big bang policy change. This article identifies the strengths professional historians bring to bear on policy development using the establishment and subsequent reform of universal health coverage as an example. Historians provide pertinent and historically informed context; isolate the forces that have historically allowed for major reform; and separate the truly novel reforms from those attempted or implemented in the past. In addition, the historian's use of primary sources allows potentially new and highly salient facts to guide the framing of the policy problem and its solution. This paper argues that historians are critical for constructing a viable narrative of the establishment and evolution of universal health coverage policies. The lack of this narrative makes it difficult to achieve an accurate assessment of systemic gaps in coverage and access, and the design or redesign of universal health coverage that can successfully close these gaps.

BRIEF HISTORY OF FFAG ACCELERATORS

International Nuclear Information System (INIS)

RUGGIERO, A.

2006-01-01

Colleagues of mine have asked me few times why we have today so much interest in Fixed-Field Alternating-Gradient (FFAG) accelerators when these were invented a long time ago, and have always been ignored since then. I try here to give a reply with a short history of FFAG accelerators, at least as I know it. I take also the opportunity to clarify few definitions

BRIEF HISTORY OF FFAG ACCELERATORS.

Energy Technology Data Exchange (ETDEWEB)

RUGGIERO, A.

2006-12-04

Colleagues of mine have asked me few times why we have today so much interest in Fixed-Field Alternating-Gradient (FFAG) accelerators when these were invented a long time ago, and have always been ignored since then. I try here to give a reply with a short history of FFAG accelerators, at least as I know it. I take also the opportunity to clarify few definitions.

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)

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...

Should general psychiatry ignore somatization and hypochondriasis?

Science.gov (United States)

Creed, Francis

2006-10-01

This paper examines the tendency for general psychiatry to ignore somatization and hypochondriasis. These disorders are rarely included in national surveys of mental health and are not usually regarded as a concern of general psychiatrists; yet primary care doctors and other physicians often feel let down by psychiatry's failure to offer help in this area of medical practice. Many psychiatrists are unaware of the suffering, impaired function and high costs that can result from these disorders, because these occur mainly within primary care and secondary medical services. Difficulties in diagnosis and a tendency to regard them as purely secondary phenomena of depression, anxiety and related disorders mean that general psychiatry may continue to ignore somatization and hypochondriasis. If general psychiatry embraced these disorders more fully, however, it might lead to better prevention and treatment of depression as well as helping to prevent the severe disability that may arise in association with these disorders.

A brief history of the universe

International Nuclear Information System (INIS)

Sinha, K.K.

1992-10-01

The failure of the Big Bang Theory to explain the experimental (cosmological) data is well known. Attempts have been made to give a new interpretation of the above theory to explain the existing cosmological problems and a brief history of the universe. (author). 2 refs, 1 fig

Science: Big Bang comes to the Alps

CERN Multimedia

Cookson, Clive

2008-01-01

"The most extensive and expensive scientific instrument in history is due to start working this summer at CERN, the European particle physics laboratory near Geneva. Two beams of protons will accelerate in opposite directions around a 27 km tunnel under the alpine foothills until they are travelling almost at the speed of light - and then smash together, reproducing on a tiny scale the intense energy of the new-born universe after the inaugural Big Bang 15bn years ago. (1 page)

Novel Readings: The History of a Writing Community by a Partial, Prejudiced, & Ignorant Historian

Science.gov (United States)

King, Virginia

2013-01-01

In this article, I explore the history of a higher education writing community from its establishment in 2005 to the present day. In order to provide a model of community development which may be generalizable, this inherently "partial" and "prejudiced" Autoethnographic account is framed by themes taken from three of the novels of Jane Austen…

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.

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.

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...

Questioning the "big assumptions". Part II: recognizing organizational contradictions that impede institutional change.

Science.gov (United States)

Bowe, Constance M; Lahey, Lisa; Kegan, Robert; Armstrong, Elizabeth

2003-08-01

Well-designed medical curriculum reforms can fall short of their primary objectives during implementation when unanticipated or unaddressed organizational resistance surfaces. This typically occurs if the agents for change ignore faculty concerns during the planning stage or when the provision of essential institutional safeguards to support new behaviors are neglected. Disappointing outcomes in curriculum reforms then result in the perpetuation of or reversion to the status quo despite the loftiest of goals. Institutional resistance to change, much like that observed during personal development, does not necessarily indicate a communal lack of commitment to the organization's newly stated goals. It may reflect the existence of competing organizational objectives that must be addressed before substantive advances in a new direction can be accomplished. The authors describe how the Big Assumptions process (see previous article) was adapted and applied at the institutional level during a school of medicine's curriculum reform. Reform leaders encouraged faculty participants to articulate their reservations about considered changes to provided insights into the organization's competing commitments. The line of discussion provided an opportunity for faculty to appreciate the gridlock that existed until appropriate test of the school's long held Big Assumptions could be conducted. The Big Assumptions process proved useful in moving faculty groups to recognize and questions the validity of unchallenged institutional beliefs that were likely to undermine efforts toward change. The process also allowed the organization to put essential institutional safeguards in place that ultimately insured that substantive reforms could be sustained.

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.

Transdisciplinary Perspectives in Bioethics: A Co-evolutionary Introduction from the Big History

OpenAIRE

Javier Collado-Ruano

2016-01-01

The main objective of this work is to expand the bioethics notion expressed in the Article 17th of the Universal Declaration on Bioethics and Human Rights, concerning the interconnections between human beings and other life forms. For this purpose, it is combined the transdisciplinary methodology with the theoretical framework of the “Big History” to approach the co-evolutionary phenomena that life is developing on Earth for some 3.8 billion years. As a result, the study introduces us to t...

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.

Maximizing the Educational Power of History Movies in the Classroom

Science.gov (United States)

Metzger, Scott Alan

2010-01-01

Cinematic feature films are a big part of youth popular culture. When blockbuster movies are about historical topics, it is reasonable for teachers to be drawn to using them in the classroom to motivate students interest. This article overviews research on film in the history classroom and describes three learning functions that history movies can…

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.

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).

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...

Inattentional blindness for ignored words: comparison of explicit and implicit memory tasks.

Science.gov (United States)

Butler, Beverly C; Klein, Raymond

2009-09-01

Inattentional blindness is described as the failure to perceive a supra-threshold stimulus when attention is directed away from that stimulus. Based on performance on an explicit recognition memory test and concurrent functional imaging data Rees, Russell, Frith, and Driver [Rees, G., Russell, C., Frith, C. D., & Driver, J. (1999). Inattentional blindness versus inattentional amnesia for fixated but ignored words. Science, 286, 2504-2507] reported inattentional blindness for word stimuli that were fixated but ignored. The present study examined both explicit and implicit memory for fixated but ignored words using a selective-attention task in which overlapping picture/word stimuli were presented at fixation. No explicit awareness of the unattended words was apparent on a recognition memory test. Analysis of an implicit memory task, however, indicated that unattended words were perceived at a perceptual level. Thus, the selective-attention task did not result in perfect filtering as suggested by Rees et al. While there was no evidence of conscious perception, subjects were not blind to the implicit perceptual properties of fixated but ignored words.

An unofficial history of Japanese accelerators. Part four

International Nuclear Information System (INIS)

Inoue, Makoto

2005-01-01

History of accelerator development in Japan is overviewed for a period after 1980. In the first part, big accelerator projects including Japan-U.S. Science and Technology Cooperation Program, participation in SSC project, Big Hadron Project and RCNP ring cyclotron project are looked back. In the second part, the spread of small- and medium-scale accelerator utilization are overviewed. The third part is devoted to view the relation between the atomic energy research and accelerators. Organizations of Japanese accelerator society are surveyed in the last section. (K.Y.)

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....

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.

The Mathematical Miseducation of America's Youth: Ignoring Research and Scientific Study in Education.

Science.gov (United States)

Battista, Michael T.

1999-01-01

Because traditional instruction ignores students' personal construction of mathematical meaning, mathematical thought development is not properly nurtured. Several issues must be addressed, including adults' ignorance of math- and student-learning processes, identification of math-education research specialists, the myth of coverage, testing…

Infectious Disease Surveillance in the Big Data Era: Towards Faster and Locally Relevant Systems

Science.gov (United States)

Simonsen, Lone; Gog, Julia R.; Olson, Don; Viboud, Cécile

2016-01-01

While big data have proven immensely useful in fields such as marketing and earth sciences, public health is still relying on more traditional surveillance systems and awaiting the fruits of a big data revolution. A new generation of big data surveillance systems is needed to achieve rapid, flexible, and local tracking of infectious diseases, especially for emerging pathogens. In this opinion piece, we reflect on the long and distinguished history of disease surveillance and discuss recent developments related to use of big data. We start with a brief review of traditional systems relying on clinical and laboratory reports. We then examine how large-volume medical claims data can, with great spatiotemporal resolution, help elucidate local disease patterns. Finally, we review efforts to develop surveillance systems based on digital and social data streams, including the recent rise and fall of Google Flu Trends. We conclude by advocating for increased use of hybrid systems combining information from traditional surveillance and big data sources, which seems the most promising option moving forward. Throughout the article, we use influenza as an exemplar of an emerging and reemerging infection which has traditionally been considered a model system for surveillance and modeling. PMID:28830112

[Blood transfusion, an investigation on its brief history].

Science.gov (United States)

Wang, B; Peng, X

2000-07-01

Transfusion has developed as a practical clinical technique. Its development has experienced from ignorance to science and from cruelty to civilization for hundreds of year. Transfusion has made great contribution for saving lives and expanding operation coverage. To understand the history of transfusion, we can have reference to promote again the development of transfusion technique.

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.

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

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.

Tuberculosis control in big cities and urban risk groups in the European Union: a consensus statement.

Science.gov (United States)

van Hest, N A; Aldridge, R W; de Vries, G; Sandgren, A; Hauer, B; Hayward, A; Arrazola de Oñate, W; Haas, W; Codecasa, L R; Caylà, J A; Story, A; Antoine, D; Gori, A; Quabeck, L; Jonsson, J; Wanlin, M; Orcau, Å; Rodes, A; Dedicoat, M; Antoun, F; van Deutekom, H; Keizer, St; Abubakar, I

2014-03-06

In low-incidence countries in the European Union (EU), tuberculosis (TB) is concentrated in big cities, especially among certain urban high-risk groups including immigrants from TB high-incidence countries, homeless people, and those with a history of drug and alcohol misuse. Elimination of TB in European big cities requires control measures focused on multiple layers of the urban population. The particular complexities of major EU metropolises, for example high population density and social structure, create specific opportunities for transmission, but also enable targeted TB control interventions, not efficient in the general population, to be effective or cost effective. Lessons can be learnt from across the EU and this consensus statement on TB control in big cities and urban risk groups was prepared by a working group representing various EU big cities, brought together on the initiative of the European Centre for Disease Prevention and Control. The consensus statement describes general and specific social, educational, operational, organisational, legal and monitoring TB control interventions in EU big cities, as well as providing recommendations for big city TB control, based upon a conceptual TB transmission and control model.

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,

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

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

Investigating Deviance Distraction and the Impact of the Modality of the To-Be-Ignored Stimuli.

Science.gov (United States)

Marsja, Erik; Neely, Gregory; Ljungberg, Jessica K

2018-03-01

It has been suggested that deviance distraction is caused by unexpected sensory events in the to-be-ignored stimuli violating the cognitive system's predictions of incoming stimuli. The majority of research has used methods where the to-be-ignored expected (standards) and the unexpected (deviants) stimuli are presented within the same modality. Less is known about the behavioral impact of deviance distraction when the to-be-ignored stimuli are presented in different modalities (e.g., standard and deviants presented in different modalities). In three experiments using cross-modal oddball tasks with mixed-modality to-be-ignored stimuli, we examined the distractive role of unexpected auditory deviants presented in a continuous stream of expected standard vibrations. The results showed that deviance distraction seems to be dependent upon the to-be-ignored stimuli being presented within the same modality, and that the simplest omission of something expected; in this case, a standard vibration may be enough to capture attention and distract performance.

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...

A History of Dark Matter

Energy Technology Data Exchange (ETDEWEB)

Bertone, Gianfranco [U. Amsterdam, GRAPPA; Hooper, Dan [Fermilab

2016-05-16

Although dark matter is a central element of modern cosmology, the history of how it became accepted as part of the dominant paradigm is often ignored or condensed into a brief anecdotical account focused around the work of a few pioneering scientists. The aim of this review is to provide the reader with a broader historical perspective on the observational discoveries and the theoretical arguments that led the scientific community to adopt dark matter as an essential part of the standard cosmological model.

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)...

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"

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.

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.)

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

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.

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.

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...

History Writ Large: Big-character Posters, Red Logorrhoea and the Art of Words

OpenAIRE

Barmé, Geremie R.

2012-01-01

The starting point of this paper is the 1986 artwork of the then Xiamen-based artist Wu Shanzhuan, called ‘Red Humor’, which reworked references to big-character posters (dazi bao 大字报) and other Mao-era forms of political discourse, recalling the Cultural Revolution. It explains how Wu’s installation offered a provocative microcosm of the overwhelming mood engendered by a logocentric movement to ‘paint the nation red’ with word-images during the years 1966-1967. This discussion of the hyper-r...

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.

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

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.

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....

Non-ignorable missingness item response theory models for choice effects in examinee-selected items.

Science.gov (United States)

Liu, Chen-Wei; Wang, Wen-Chung

2017-11-01

Examinee-selected item (ESI) design, in which examinees are required to respond to a fixed number of items in a given set, always yields incomplete data (i.e., when only the selected items are answered, data are missing for the others) that are likely non-ignorable in likelihood inference. Standard item response theory (IRT) models become infeasible when ESI data are missing not at random (MNAR). To solve this problem, the authors propose a two-dimensional IRT model that posits one unidimensional IRT model for observed data and another for nominal selection patterns. The two latent variables are assumed to follow a bivariate normal distribution. In this study, the mirt freeware package was adopted to estimate parameters. The authors conduct an experiment to demonstrate that ESI data are often non-ignorable and to determine how to apply the new model to the data collected. Two follow-up simulation studies are conducted to assess the parameter recovery of the new model and the consequences for parameter estimation of ignoring MNAR data. The results of the two simulation studies indicate good parameter recovery of the new model and poor parameter recovery when non-ignorable missing data were mistakenly treated as ignorable. © 2017 The British Psychological Society.

Can Strategic Ignorance Explain the Evolution of Love?

Science.gov (United States)

Bear, Adam; Rand, David G

2018-04-24

People's devotion to, and love for, their romantic partners poses an evolutionary puzzle: Why is it better to stop your search for other partners once you enter a serious relationship when you could continue to search for somebody better? A recent formal model based on "strategic ignorance" suggests that such behavior can be adaptive and favored by natural selection, so long as you can signal your unwillingness to "look" for other potential mates to your current partner. Here, we re-examine this conclusion with a more detailed model designed to capture specific features of romantic relationships. We find, surprisingly, that devotion does not typically evolve in our model: Selection favors agents who choose to "look" while in relationships and who allow their partners to do the same. Non-looking is only expected to evolve if there is an extremely large cost associated with being left by your partner. Our results therefore raise questions about the role of strategic ignorance in explaining the evolution of love. Copyright © 2018 Cognitive Science Society, Inc.

The end of ignorance multiplying our human potential

CERN Document Server

Mighton, John

2008-01-01

A revolutionary call for a new understanding of how people learn. The End of Ignorance conceives of a world in which no child is left behind – a world based on the assumption that each child has the potential to be successful in every subject. John Mighton argues that by recognizing the barriers that we have experienced in our own educational development, by identifying the moment that we became disenchanted with a certain subject and forever closed ourselves off to it, we will be able to eliminate these same barriers from standing in the way of our children. A passionate examination of our present education system, The End of Ignorance shows how we all can work together to reinvent the way that we are taught. John Mighton, the author of The Myth of Ability, is the founder of JUMP Math, a system of learning based on the fostering of emergent intelligence. The program has proved so successful an entire class of Grade 3 students, including so-called slow learners, scored over 90% on a Grade 6 math test. A ...

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.

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.

Should general psychiatry ignore somatization and hypochondriasis?

OpenAIRE

CREED, FRANCIS

2006-01-01

This paper examines the tendency for general psychiatry to ignore somatization and hypochondriasis. These disorders are rarely included in national surveys of mental health and are not usually regarded as a concern of general psychiatrists; yet primary care doctors and other physicians often feel let down by psychiatry's failure to offer help in this area of medical practice. Many psychiatrists are unaware of the suffering, impaired function and high costs that can result fr...

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....

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

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...

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

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...

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...

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...

Psycho-informatics: Big Data shaping modern psychometrics.

Science.gov (United States)

Markowetz, Alexander; Błaszkiewicz, Konrad; Montag, Christian; Switala, Christina; Schlaepfer, Thomas E

2014-04-01

For the first time in history, it is possible to study human behavior on great scale and in fine detail simultaneously. Online services and ubiquitous computational devices, such as smartphones and modern cars, record our everyday activity. The resulting Big Data offers unprecedented opportunities for tracking and analyzing behavior. This paper hypothesizes the applicability and impact of Big Data technologies in the context of psychometrics both for research and clinical applications. It first outlines the state of the art, including the severe shortcomings with respect to quality and quantity of the resulting data. It then presents a technological vision, comprised of (i) numerous data sources such as mobile devices and sensors, (ii) a central data store, and (iii) an analytical platform, employing techniques from data mining and machine learning. To further illustrate the dramatic benefits of the proposed methodologies, the paper then outlines two current projects, logging and analyzing smartphone usage. One such study attempts to thereby quantify severity of major depression dynamically; the other investigates (mobile) Internet Addiction. Finally, the paper addresses some of the ethical issues inherent to Big Data technologies. In summary, the proposed approach is about to induce the single biggest methodological shift since the beginning of psychology or psychiatry. The resulting range of applications will dramatically shape the daily routines of researches and medical practitioners alike. Indeed, transferring techniques from computer science to psychiatry and psychology is about to establish Psycho-Informatics, an entire research direction of its own. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

From Big Data to Smart Data for Pharmacovigilance: The Role of Healthcare Databases and Other Emerging Sources.

Science.gov (United States)

Trifirò, Gianluca; Sultana, Janet; Bate, Andrew

2018-02-01

In the last decade 'big data' has become a buzzword used in several industrial sectors, including but not limited to telephony, finance and healthcare. Despite its popularity, it is not always clear what big data refers to exactly. Big data has become a very popular topic in healthcare, where the term primarily refers to the vast and growing volumes of computerized medical information available in the form of electronic health records, administrative or health claims data, disease and drug monitoring registries and so on. This kind of data is generally collected routinely during administrative processes and clinical practice by different healthcare professionals: from doctors recording their patients' medical history, drug prescriptions or medical claims to pharmacists registering dispensed prescriptions. For a long time, this data accumulated without its value being fully recognized and leveraged. Today big data has an important place in healthcare, including in pharmacovigilance. The expanding role of big data in pharmacovigilance includes signal detection, substantiation and validation of drug or vaccine safety signals, and increasingly new sources of information such as social media are also being considered. The aim of the present paper is to discuss the uses of big data for drug safety post-marketing assessment.

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

To See the Unseen: A History of Planetary Radar Astronomy

Science.gov (United States)

Butrica, Andrew J.

1996-01-01

This book relates the history of planetary radar astronomy from its origins in radar to the present day and secondarily to bring to light that history as a case of 'Big Equipment but not Big Science'. Chapter One sketches the emergence of radar astronomy as an ongoing scientific activity at Jodrell Bank, where radar research revealed that meteors were part of the solar system. The chief Big Science driving early radar astronomy experiments was ionospheric research. Chapter Two links the Cold War and the Space Race to the first radar experiments attempted on planetary targets, while recounting the initial achievements of planetary radar, namely, the refinement of the astronomical unit and the rotational rate and direction of Venus. Chapter Three discusses early attempts to organize radar astronomy and the efforts at MIT's Lincoln Laboratory, in conjunction with Harvard radio astronomers, to acquire antenna time unfettered by military priorities. Here, the chief Big Science influencing the development of planetary radar astronomy was radio astronomy. Chapter Four spotlights the evolution of planetary radar astronomy at the Jet Propulsion Laboratory, a NASA facility, at Cornell University's Arecibo Observatory, and at Jodrell Bank. A congeries of funding from the military, the National Science Foundation, and finally NASA marked that evolution, which culminated in planetary radar astronomy finding a single Big Science patron, NASA. Chapter Five analyzes planetary radar astronomy as a science using the theoretical framework provided by philosopher of science Thomas Kuhn. Chapter Six explores the shift in planetary radar astronomy beginning in the 1970s that resulted from its financial and institutional relationship with NASA Big Science. Chapter Seven addresses the Magellan mission and its relation to the evolution of planetary radar astronomy from a ground-based to a space-based activity. Chapters Eight and Nine discuss the research carried out at ground

Tiempo, espacio y el futuro del pasado: los horizontes de la Historia = Time, space and the future of the past: The horizons of History

Directory of Open Access Journals (Sweden)

David Armitage

2016-12-01

Full Text Available Es mucho lo que ha quedado atrás en un amplio abanico de campos históricos. Numerosos historiadores están ensanchando los espacios para crear historias internacionales, transnacionales y globales. Otros están expandiendo el tiempo, para perseguir una Big History, una Deep History y la historia del Antropoceno. ¿Cuál es la explicación para esta expansión de los horizontes? ¿Y que significa para el futuro de la Historia? Este artículo presenta un alegato para la consideración de la historia como una disciplina de las transformaciones sociales y políticas en medio de las crisis de gobernanza global, creciente desigualdad y cambio climático antropogénico.Big is back across a wide range of historical fields. Many historians are stretching space, to create international, transnational and global histories. Others are expanding time, to pursue Big History, Deep History and the history of the Anthropocene. What explains this broadening of horizons? And what does it mean for the future of history? This article makes a case for history as a discipline of social and political transformation amid crises of global governance, rising inequality, and anthropogenic climate change.

Infectious Disease Surveillance in the Big Data Era: Towards Faster and Locally Relevant Systems.

Science.gov (United States)

Simonsen, Lone; Gog, Julia R; Olson, Don; Viboud, Cécile

2016-12-01

While big data have proven immensely useful in fields such as marketing and earth sciences, public health is still relying on more traditional surveillance systems and awaiting the fruits of a big data revolution. A new generation of big data surveillance systems is needed to achieve rapid, flexible, and local tracking of infectious diseases, especially for emerging pathogens. In this opinion piece, we reflect on the long and distinguished history of disease surveillance and discuss recent developments related to use of big data. We start with a brief review of traditional systems relying on clinical and laboratory reports. We then examine how large-volume medical claims data can, with great spatiotemporal resolution, help elucidate local disease patterns. Finally, we review efforts to develop surveillance systems based on digital and social data streams, including the recent rise and fall of Google Flu Trends. We conclude by advocating for increased use of hybrid systems combining information from traditional surveillance and big data sources, which seems the most promising option moving forward. Throughout the article, we use influenza as an exemplar of an emerging and reemerging infection which has traditionally been considered a model system for surveillance and modeling. Published by Oxford University Press for the Infectious Diseases Society of America 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

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.

Professional orientation and pluralistic ignorance among jail correctional officers.

Science.gov (United States)

Cook, Carrie L; Lane, Jodi

2014-06-01

Research about the attitudes and beliefs of correctional officers has historically been conducted in prison facilities while ignoring jail settings. This study contributes to our understanding of correctional officers by examining the perceptions of those who work in jails, specifically measuring professional orientations about counseling roles, punitiveness, corruption of authority by inmates, and social distance from inmates. The study also examines whether officers are accurate in estimating these same perceptions of their peers, a line of inquiry that has been relatively ignored. Findings indicate that the sample was concerned about various aspects of their job and the management of inmates. Specifically, officers were uncertain about adopting counseling roles, were somewhat punitive, and were concerned both with maintaining social distance from inmates and with an inmate's ability to corrupt their authority. Officers also misperceived the professional orientation of their fellow officers and assumed their peer group to be less progressive than they actually were.

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.

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....

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.

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

2011-12-01

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 faced with a variety of options as to inventory length. Furthermore, a 6-factor model has been proposed to extend and update the Big Five model, in part by adding a dimension of Honesty/Humility or Honesty/Propriety. In this study, 3 popular brief to medium-length Big Five measures (NEO Five Factor Inventory, Big Five Inventory [BFI], and International Personality Item Pool), and 3 six-factor measures (HEXACO Personality Inventory, Questionnaire Big Six Scales, and a 6-factor version of the BFI) were placed in competition to best predict important student life outcomes. The effect of test length was investigated by comparing brief versions of most measures (subsets of items) with original versions. Personality questionnaires were administered to undergraduate students (N = 227). Participants' college transcripts and student conduct records were obtained 6-9 months after data was collected. Six-factor inventories demonstrated better predictive ability for life outcomes than did some Big Five inventories. Additional behavioral observations made on participants, including their Facebook profiles and cell-phone text usage, were predicted similarly by Big Five and 6-factor measures. A brief version of the BFI performed surprisingly well; across inventory platforms, increasing test length had little effect on predictive validity. Comparative validity of the models and measures in terms of outcome prediction and parsimony is discussed.

Big Machines and Big Science: 80 Years of Accelerators at Stanford

Energy Technology Data Exchange (ETDEWEB)

Loew, Gregory

2008-12-16

Longtime SLAC physicist Greg Loew will present a trip through SLAC's origins, highlighting its scientific achievements, and provide a glimpse of the lab's future in 'Big Machines and Big Science: 80 Years of Accelerators at Stanford.'

'More is less'. The tax effects of ignoring flow externalities

International Nuclear Information System (INIS)

Sandal, Leif K.; Steinshamn, Stein Ivar; Grafton, R. Quentin

2003-01-01

Using a model of non-linear, non-monotone decay of the stock pollutant, and starting from the same initial conditions, the paper shows that an optimal tax that corrects for both stock and flow externalities may result in a lower tax, fewer cumulative emissions (less decay in emissions) and higher output at the steady state than a corrective tax that ignores the flow externality. This 'more is less' result emphasizes that setting a corrective tax that ignores the flow externality, or imposing a corrective tax at too low a level where there exists only a stock externality, may affect both transitory and steady-state output, tax payments and cumulative emissions. The result has important policy implications for decision makers setting optimal corrective taxes and targeted emission limits whenever stock externalities exist

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

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.

Behavioural responses to human-induced change: Why fishing should not be ignored.

Science.gov (United States)

Diaz Pauli, Beatriz; Sih, Andrew

2017-03-01

Change in behaviour is usually the first response to human-induced environmental change and key for determining whether a species adapts to environmental change or becomes maladapted. Thus, understanding the behavioural response to human-induced changes is crucial in the interplay between ecology, evolution, conservation and management. Yet the behavioural response to fishing activities has been largely ignored. We review studies contrasting how fish behaviour affects catch by passive (e.g., long lines, angling) versus active gears (e.g., trawls, seines). We show that fishing not only targets certain behaviours, but it leads to a multitrait response including behavioural, physiological and life-history traits with population, community and ecosystem consequences. Fisheries-driven change (plastic or evolutionary) of fish behaviour and its correlated traits could impact fish populations well beyond their survival per se , affecting predation risk, foraging behaviour, dispersal, parental care, etc., and hence numerous ecological issues including population dynamics and trophic cascades . In particular, we discuss implications of behavioural responses to fishing for fisheries management and population resilience. More research on these topics, however, is needed to draw general conclusions, and we suggest fruitful directions for future studies.

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…

The Shepherd, the Doctor and the Big Data

Directory of Open Access Journals (Sweden)

Alejandro Segura Vázquez

2014-08-01

Full Text Available The rise of the Internet as a space for global interaction makes the political subjectivation of automated surveillance especially important for understanding the mechanisms of social control in our current culture. This essay approaches mass electronic surveillance from the perspective of the processes of production of subjectivities among users of the Net. It will briefly outline a history of the production of subjects as related to the necessity of expressing a certain truth about themselves, of confessing and conforming to a normality regulated by the strategic frameworks of power. At the same time, it will attempt to associate the logic of that history with the rise of Big Data as a device for the tracking, discrimination and management of personal data. Finally, the paper will provide some reflections on the significance of resistance to the loss of privacy in digital culture.

Cartography in the Age of Spatio-temporal Big Data

Directory of Open Access Journals (Sweden)

WANG Jiayao

2017-10-01

Full Text Available Cartography is an ancient science with almost the same long history as the world's oldest culture.Since ancient times,the movement and change of anything and any phenomena,including human activities,have been carried out in a certain time and space.The development of science and technology and the progress of social civilization have made social management and governance more and more dependent on time and space.The information source,theme,content,carrier,form,production methods and application methods of map are different in different historical periods,so that its all-round value is different. With the arrival of the big data age,the scientific paradigm has now entered the era of "data-intensive" paradigm,so is the cartography,with obvious characteristics of big data science.All big data are caused by movement and change of all things and phenomena in the geographic world,so they have space and time characteristics and thus cannot be separated from the spatial reference and time reference.Therefore,big data is big spatio-temporal data essentially.Since the late 1950s and early 1960s,modern cartography,that is,the cartography in the information age,takes spatio-temporal data as the object,and focuses on the processing and expression of spatio-temporal data,but not in the face of the large scale multi-source heterogeneous and multi-dimensional dynamic data flow(or flow datafrom sky to the sea.The real-time dynamic nature,the theme pertinence,the content complexity,the carrier diversification,the expression form personalization,the production method modernization,the application ubiquity of the map,is incomparable in the past period,which leads to the great changes of the theory,technology and application system of cartography.And all these changes happen to occur in the 60 years since the late 1950s and early 1960s,so this article was written to commemorate the 60th anniversary of the "Acta Geodaetica et Cartographica Sinica".

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.

Persistence of Memory for Ignored Lists of Digits: Areas of Developmental Constancy and Change.

Science.gov (United States)

Cowan, Nelson; Nugent, Lara D.; Elliott, Emily M.; Saults, J. Scott

2000-01-01

Examined persistence of sensory memory by studying developmental differences in recall of attended and ignored lists of digits for second-graders, fifth-graders, and adults. Found developmental increase in the persistence of memory only for the final item in an ignored list, which is the item for which sensory memory is thought to be the most…

Willful Ignorance and the Death Knell of Critical Thought

Science.gov (United States)

Rubin, Daniel Ian

2018-01-01

Independent, critical thought has never been more important in the United States. In the Age of Trump, political officials spout falsehoods called "alternative facts" as if they were on equal footing with researchable, scientific data. At the same time, an unquestioning populace engages in acts of "willful ignorance" on a daily…

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.

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 ...

BigWig and BigBed: enabling browsing of large distributed datasets.

Science.gov (United States)

Kent, W J; Zweig, A S; Barber, G; Hinrichs, A S; Karolchik, D

2010-09-01

BigWig and BigBed files are compressed binary indexed files containing data at several resolutions that allow the high-performance display of next-generation sequencing experiment results in the UCSC Genome Browser. The visualization is implemented using a multi-layered software approach that takes advantage of specific capabilities of web-based protocols and Linux and UNIX operating systems files, R trees and various indexing and compression tricks. As a result, only the data needed to support the current browser view is transmitted rather than the entire file, enabling fast remote access to large distributed data sets. Binaries for the BigWig and BigBed creation and parsing utilities may be downloaded at http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/. Source code for the creation and visualization software is freely available for non-commercial use at http://hgdownload.cse.ucsc.edu/admin/jksrc.zip, implemented in C and supported on Linux. The UCSC Genome Browser is available at http://genome.ucsc.edu.

Taking of history

DEFF Research Database (Denmark)

Langebæk, Rikke

2007-01-01

the smartest student. So the more familiar a student can become with these situations the better. Since september 2006, veterinary students at Faculty of Life Sciences, University of Copenhagen, have received training in the discipline of history taking, using innovative educational methods: Online......, the students won’t be intimidated by the situation, as they are already familiar with the ‘client’. The ‘client’/teacher must be able to perform as different types of clients to make the sessions more interesting, colourful and fun. During these Live Role sessions, the students will get help and good advice......Learning how to take a history is an extremely important discipline in the education of veterinary students. In our opinion the fact that this discipline is often neglected in traditional teaching is a big mistake. The mere thought of facing a real client can be almost paralysing to even...

Has the universe an origin?

International Nuclear Information System (INIS)

Alfven, H.

1988-07-01

In the cosmological discussion it has during the last few decades been taken for granted that the Lemaitre-Gamov cosmology - usually referred to as the Big Band is the only acceptable one. The Universe must have been created ex nihilo in a singular point. Criticism of the Big Bang hypothesis is usually answered by: And how do you create the Universe? Most people seem to be so ignorant of the history of science and philosophy that they do not remember that most scolars have considered the Universe to be 'ungenerated and indestructable'. The only exceptions seem to be some Christian theologicans in the first centuries AD and their school, to which Lemaitre and Gamov and their Big Bang hypothesis belongs. It is demonstrated that there are no observational facts which unquestionable speak in favour of the Big Bang hypothesis. The 'Sputnik revolution' makes it necessary to revise important parts of astrophysics, and is also fatal to the Big Bang. It seems necessary to turn back to the view of an 'ungenerated' (and indestructable) Universe. (author)

L'Univers avant le Big Bang

CERN Document Server

Rouat, Sylvie

2003-01-01

"Tout n'a pas commencé par une explosion. L'historie du cosmos avait débuté biena vant le Big Bang, si l'on suit la théorie défendue par les partisans d'une nouvelle cosmologie issue de la mystérieuse théorie des cordes. A l'heure où vacillent les scénarios classiques du XXe siècle, se prépare un grand chamboulement de nos idées sur la naissance de l'Univers et son devenir, sur l'existence possible d'univers parallèles. Des théories séduisantes qui seront mises à l'épreuve au cours de la prochaine décennie" (11 pages)

Big data-driven business how to use big data to win customers, beat competitors, and boost profits

CERN Document Server

Glass, Russell

2014-01-01

Get the expert perspective and practical advice on big data The Big Data-Driven Business: How to Use Big Data to Win Customers, Beat Competitors, and Boost Profits makes the case that big data is for real, and more than just big hype. The book uses real-life examples-from Nate Silver to Copernicus, and Apple to Blackberry-to demonstrate how the winners of the future will use big data to seek the truth. Written by a marketing journalist and the CEO of a multi-million-dollar B2B marketing platform that reaches more than 90% of the U.S. business population, this book is a comprehens

Traffic forecasts ignoring induced demand

DEFF Research Database (Denmark)

Næss, Petter; Nicolaisen, Morten Skou; Strand, Arvid

2012-01-01

the model calculations included only a part of the induced traffic, the difference in cost-benefit results compared to the model excluding all induced traffic was substantial. The results show lower travel time savings, more adverse environmental impacts and a considerably lower benefitcost ratio when...... induced traffic is partly accounted for than when it is ignored. By exaggerating the economic benefits of road capacity increase and underestimating its negative effects, omission of induced traffic can result in over-allocation of public money on road construction and correspondingly less focus on other...... performance of a proposed road project in Copenhagen with and without short-term induced traffic included in the transport model. The available transport model was not able to include long-term induced traffic resulting from changes in land use and in the level of service of public transport. Even though...

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...

Egoism, ignorance and choice : on society's lethal infection

OpenAIRE

Camilleri, Jonathan

2015-01-01

The ability to choose and our innate selfish, or rather, self-preservative urges are a recipe for disaster. Combining this with man's ignorance by definition and especially his general refusal to accept it, inevitably leads to Man's demise as a species. It is our false notion of freedom which contributes directly to our collective death, and therefore, man's trying to escape death is, in the largest of ways, counterproductive.

The importance of ignoring: Alpha oscillations protect selectivity

OpenAIRE

Payne, Lisa; Sekuler, Robert

2014-01-01

Selective attention is often thought to entail an enhancement of some task-relevant stimulus or attribute. We discuss the perspective that ignoring irrelevant, distracting information plays a complementary role in information processing. Cortical oscillations within the alpha (8–14 Hz) frequency band have emerged as a marker of sensory suppression. This suppression is linked to selective attention for visual, auditory, somatic, and verbal stimuli. Inhibiting processing of irrelevant input mak...

"Big data" and "open data": What kind of access should researchers enjoy?

Science.gov (United States)

Chatellier, Gilles; Varlet, Vincent; Blachier-Poisson, Corinne

2016-02-01

The healthcare sector is currently facing a new paradigm, the explosion of "big data". Coupled with advances in computer technology, the field of "big data" appears promising, allowing us to better understand the natural history of diseases, to follow-up new technologies (devices, drugs) implementation and to participate in precision medicine, etc. Data sources are multiple (medical and administrative data, electronic medical records, data from rapidly developing technologies such as DNA sequencing, connected devices, etc.) and heterogeneous while their use requires complex methods for accurate analysis. Moreover, faced with this new paradigm, we must determine who could (or should) have access to which data, how to combine collective interest and protection of personal data and how to finance in the long-term both operating costs and databases interrogation. This article analyses the opportunities and challenges related to the use of open and/or "big data", from the viewpoint of pharmacologists and representatives of the pharmaceutical and medical device industry. Copyright © 2016 Société française de pharmacologie et de thérapeutique. Published by Elsevier Masson SAS. All rights reserved.

Five Big, Big Five Issues : Rationale, Content, Structure, Status, and Crosscultural Assessment

NARCIS (Netherlands)

De Raad, Boele

1998-01-01

This article discusses the rationale, content, structure, status, and crosscultural assessment of the Big Five trait factors, focusing on topics of dispute and misunderstanding. Taxonomic restrictions of the original Big Five forerunner, the "Norman Five," are discussed, and criticisms regarding the

Tunnel Vision: New England Higher Education Ignores Demographic Peril

Science.gov (United States)

Hodgkinson, Harold L.

2004-01-01

This author states that American higher education ignores about 90 percent of the environment in which it operates. Colleges change admissions requirements without even informing high schools in their service areas. Community college graduates are denied access to four-year programs because of policy changes made only after it was too late for the…

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....

Big Data and HPC collocation: Using HPC idle resources for Big Data Analytics

OpenAIRE

MERCIER , Michael; Glesser , David; Georgiou , Yiannis; Richard , Olivier

2017-01-01

International audience; Executing Big Data workloads upon High Performance Computing (HPC) infrastractures has become an attractive way to improve their performances. However, the collocation of HPC and Big Data workloads is not an easy task, mainly because of their core concepts' differences. This paper focuses on the challenges related to the scheduling of both Big Data and HPC workloads on the same computing platform. In classic HPC workloads, the rigidity of jobs tends to create holes in ...

Earth Science Data Analysis in the Era of Big Data

Science.gov (United States)

Kuo, K.-S.; Clune, T. L.; Ramachandran, R.

2014-01-01

Anyone with even a cursory interest in information technology cannot help but recognize that "Big Data" is one of the most fashionable catchphrases of late. From accurate voice and facial recognition, language translation, and airfare prediction and comparison, to monitoring the real-time spread of flu, Big Data techniques have been applied to many seemingly intractable problems with spectacular successes. They appear to be a rewarding way to approach many currently unsolved problems. Few fields of research can claim a longer history with problems involving voluminous data than Earth science. The problems we are facing today with our Earth's future are more complex and carry potentially graver consequences than the examples given above. How has our climate changed? Beside natural variations, what is causing these changes? What are the processes involved and through what mechanisms are these connected? How will they impact life as we know it? In attempts to answer these questions, we have resorted to observations and numerical simulations with ever-finer resolutions, which continue to feed the "data deluge." Plausibly, many Earth scientists are wondering: How will Big Data technologies benefit Earth science research? As an example from the global water cycle, one subdomain among many in Earth science, how would these technologies accelerate the analysis of decades of global precipitation to ascertain the changes in its characteristics, to validate these changes in predictive climate models, and to infer the implications of these changes to ecosystems, economies, and public health? Earth science researchers need a viable way to harness the power of Big Data technologies to analyze large volumes and varieties of data with velocity and veracity. Beyond providing speedy data analysis capabilities, Big Data technologies can also play a crucial, albeit indirect, role in boosting scientific productivity by facilitating effective collaboration within an analysis environment

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....

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.

From the Big Bang to the Nobel Prize and the JWST

Science.gov (United States)

Mather, John C.

2007-01-01

I will describe the history of the universe, from the Big Bang to 2013, when the JWST is to be launched to look back towards our beginnings. I will discuss how the COBE results led to the Nobel Prize, how the COBE results have been confirmed and extended, and their implications for future observations. The James Webb Space Telescope will be used to examine every part of our history from the first stars and galaxies to the formation of individual stars and planets and the delivery of life-supporting materials to the Earth. I will describe the plans for the JWST and how observers may use it. With luck, the JWST may produce a Nobel Prize for some discovery we can only guess today.

Big data - a 21st century science Maginot Line? No-boundary thinking: shifting from the big data paradigm.

Science.gov (United States)

Huang, Xiuzhen; Jennings, Steven F; Bruce, Barry; Buchan, Alison; Cai, Liming; Chen, Pengyin; Cramer, Carole L; Guan, Weihua; Hilgert, Uwe Kk; Jiang, Hongmei; Li, Zenglu; McClure, Gail; McMullen, Donald F; Nanduri, Bindu; Perkins, Andy; Rekepalli, Bhanu; Salem, Saeed; Specker, Jennifer; Walker, Karl; Wunsch, Donald; Xiong, Donghai; Zhang, Shuzhong; Zhang, Yu; Zhao, Zhongming; Moore, Jason H

2015-01-01

Whether your interests lie in scientific arenas, the corporate world, or in government, you have certainly heard the praises of big data: Big data will give you new insights, allow you to become more efficient, and/or will solve your problems. While big data has had some outstanding successes, many are now beginning to see that it is not the Silver Bullet that it has been touted to be. Here our main concern is the overall impact of big data; the current manifestation of big data is constructing a Maginot Line in science in the 21st century. Big data is not "lots of data" as a phenomena anymore; The big data paradigm is putting the spirit of the Maginot Line into lots of data. Big data overall is disconnecting researchers and science challenges. We propose No-Boundary Thinking (NBT), applying no-boundary thinking in problem defining to address science challenges.

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...

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.

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.

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...

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....

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 ...

What's Manifest in the History of SciTech: Reflections on The History Manifesto.

Science.gov (United States)

Kevles, Daniel J

2016-06-01

Making nuts-and-bolts public policy is not--and never has been--the long suit of professional historians, but general historical work, whatever its durée, has done a good deal to shape discourse on public issues. Jo Guldi and David Armitage neglect that fact, as well as the opinion-shaping influence of history conveyed via nonprint media. They also ignore the large body of scholarship produced in all media during recent decades in the history of science, technology, and science-related medicine (SciTech), even though SciTech itself looms enormously large in the modern era as an instrument of national and international security, a driver of the economy, and a transformer of medicine, public health, and the environment. Much of this scholarship, even though of short durée, can illuminate salient contemporary issues, including innovation; patronage and practice; government and policy; imperialism and globalization; intellectual property; science and religion; and human rights, environment, energy, and disasters.

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…

Players Off the Field. How Jim Delany and Roy Kramer Took over Big-Time College Sports.

Science.gov (United States)

Suggs, Welch

2000-01-01

Traces the history of the college football bowl system and describes the movement toward replacing the bowl game system with a national championship playoff system. Focuses on the roles of J. Delany, commission of the Big Ten Conference and R. Kramer, commissioner of the Southeastern Conference, in perpetuating the current college football bowl…

Ignoring correlation in uncertainty and sensitivity analysis in life cycle assessment: what is the risk?

Energy Technology Data Exchange (ETDEWEB)

Groen, E.A., E-mail: Evelyne.Groen@gmail.com [Wageningen University, P.O. Box 338, Wageningen 6700 AH (Netherlands); Heijungs, R. [Vrije Universiteit Amsterdam, De Boelelaan 1105, Amsterdam 1081 HV (Netherlands); Leiden University, Einsteinweg 2, Leiden 2333 CC (Netherlands)

2017-01-15

Life cycle assessment (LCA) is an established tool to quantify the environmental impact of a product. A good assessment of uncertainty is important for making well-informed decisions in comparative LCA, as well as for correctly prioritising data collection efforts. Under- or overestimation of output uncertainty (e.g. output variance) will lead to incorrect decisions in such matters. The presence of correlations between input parameters during uncertainty propagation, can increase or decrease the the output variance. However, most LCA studies that include uncertainty analysis, ignore correlations between input parameters during uncertainty propagation, which may lead to incorrect conclusions. Two approaches to include correlations between input parameters during uncertainty propagation and global sensitivity analysis were studied: an analytical approach and a sampling approach. The use of both approaches is illustrated for an artificial case study of electricity production. Results demonstrate that both approaches yield approximately the same output variance and sensitivity indices for this specific case study. Furthermore, we demonstrate that the analytical approach can be used to quantify the risk of ignoring correlations between input parameters during uncertainty propagation in LCA. We demonstrate that: (1) we can predict if including correlations among input parameters in uncertainty propagation will increase or decrease output variance; (2) we can quantify the risk of ignoring correlations on the output variance and the global sensitivity indices. Moreover, this procedure requires only little data. - Highlights: • Ignoring correlation leads to under- or overestimation of the output variance. • We demonstrated that the risk of ignoring correlation can be quantified. • The procedure proposed is generally applicable in life cycle assessment. • In some cases, ignoring correlation has a minimal effect on decision-making tools.

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?”. ...

Gathering the forgotten voices: an oral history of the CFHT's early years

Science.gov (United States)

Laychak, Mary Beth; Bryson, Liz

2011-06-01

They came to the Big Island from as far away as Murrumbeena, Australia, and as near by as Hilo, Hawaii. They were progeny of Scottish coal miners, French physicists, Chicago truck drivers, Japanese samurai and Big Island cane workers. Together, these men and women would build and commission one of the most dynamic and productive 3.6 meter telescopes in the world that remains in the forefront of science and technology. The CFHT oral history DVD preserves the stories of the first decade and a half of the observatory.

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.

A Perplexed Economist Confronts 'too Big to Fail'

Directory of Open Access Journals (Sweden)

Scherer, F. M.

2010-12-01

Full Text Available This paper examines premises and data underlying the assertion that some financial institutions in the U.S. economy were "too big to fail" and hence warranted government bailout. It traces the merger histories enhancing the dominance of six leading firms in the U. S. banking industry and he sharp increases in the concentration of financial institution assets accompanying that merger wave. Financial institution profits are found to have soared in tandem with rising concentration. The paper advances hypotheses why these phenomena might be related and surveys relevant empirical literature on the relationships between market concentration, interest rates received and charged by banks, and economies of scale in banking.

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.

Changing the personality of a face: Perceived Big Two and Big Five personality factors modeled in real photographs.

Science.gov (United States)

Walker, Mirella; Vetter, Thomas

2016-04-01

General, spontaneous evaluations of strangers based on their faces have been shown to reflect judgments of these persons' intention and ability to harm. These evaluations can be mapped onto a 2D space defined by the dimensions trustworthiness (intention) and dominance (ability). Here we go beyond general evaluations and focus on more specific personality judgments derived from the Big Two and Big Five personality concepts. In particular, we investigate whether Big Two/Big Five personality judgments can be mapped onto the 2D space defined by the dimensions trustworthiness and dominance. Results indicate that judgments of the Big Two personality dimensions almost perfectly map onto the 2D space. In contrast, at least 3 of the Big Five dimensions (i.e., neuroticism, extraversion, and conscientiousness) go beyond the 2D space, indicating that additional dimensions are necessary to describe more specific face-based personality judgments accurately. Building on this evidence, we model the Big Two/Big Five personality dimensions in real facial photographs. Results from 2 validation studies show that the Big Two/Big Five are perceived reliably across different samples of faces and participants. Moreover, results reveal that participants differentiate reliably between the different Big Two/Big Five dimensions. Importantly, this high level of agreement and differentiation in personality judgments from faces likely creates a subjective reality which may have serious consequences for those being perceived-notably, these consequences ensue because the subjective reality is socially shared, irrespective of the judgments' validity. The methodological approach introduced here might prove useful in various psychological disciplines. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

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'.

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...

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

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

Tachyon cosmology, supernovae data, and the big brake singularity

International Nuclear Information System (INIS)

Keresztes, Z.; Gergely, L. A.; Gorini, V.; Moschella, U.; Kamenshchik, A. Yu.

2009-01-01

We compare the existing observational data on type Ia supernovae with the evolutions of the Universe predicted by a one-parameter family of tachyon models which we have introduced recently [Phys. Rev. D 69, 123512 (2004)]. Among the set of the trajectories of the model which are compatible with the data there is a consistent subset for which the Universe ends up in a new type of soft cosmological singularity dubbed big brake. This opens up yet another scenario for the future history of the Universe besides the one predicted by the standard ΛCDM model.

Ignorance Is Bliss, But for Whom? The Persistent Effect of Good Will on Cooperation

Directory of Open Access Journals (Sweden)

Mike Farjam

2016-10-01

Full Text Available Who benefits from the ignorance of others? We address this question from the point of view of a policy maker who can induce some ignorance into a system of agents competing for resources. Evolutionary game theory shows that when unconditional cooperators or ignorant agents compete with defectors in two-strategy settings, unconditional cooperators get exploited and are rendered extinct. In contrast, conditional cooperators, by utilizing some kind of reciprocity, are able to survive and sustain cooperation when competing with defectors. We study how cooperation thrives in a three-strategy setting where there are unconditional cooperators, conditional cooperators and defectors. By means of simulation on various kinds of graphs, we show that conditional cooperators benefit from the existence of unconditional cooperators in the majority of cases. However, in worlds that make cooperation hard to evolve, defectors benefit.

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.

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.)

Crimes commited by indigeno us people in ignorance of the law

Directory of Open Access Journals (Sweden)

Diego Fernando Chimbo Villacorte

2017-07-01

Full Text Available This analysis focuses specifically When the Indian commits crimes in ignorance of the law, not only because it ignores absolutely the unlawfulness of their conduct but when he believes he is acting in strict accordance with their beliefs and ancestral customs which –in squabble some cases– with positive law. Likewise the impossibility of imposing a penalty –when the offense is committed outside the community– or indigenous purification –when it marks an act that disturbs social peace within the indigenous– community is committed but mainly focuses on the impossibility to impose a security measure when it has committed a crime outside their community, because doing so is as unimpeachable and returns to his community, generating a discriminating treatment that prevents the culturally different self-determination.

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...

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.

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

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.

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...

Exploitation of commercial remote sensing images: reality ignored?

Science.gov (United States)

Allen, Paul C.

1999-12-01

The remote sensing market is on the verge of being awash in commercial high-resolution images. Market estimates are based on the growing numbers of planned commercial remote sensing electro-optical, radar, and hyperspectral satellites and aircraft. EarthWatch, Space Imaging, SPOT, and RDL among others are all working towards launch and service of one to five meter panchromatic or radar-imaging satellites. Additionally, new advances in digital air surveillance and reconnaissance systems, both manned and unmanned, are also expected to expand the geospatial customer base. Regardless of platform, image type, or location, each system promises images with some combination of increased resolution, greater spectral coverage, reduced turn-around time (request-to- delivery), and/or reduced image cost. For the most part, however, market estimates for these new sources focus on the raw digital images (from collection to the ground station) while ignoring the requirements for a processing and exploitation infrastructure comprised of exploitation tools, exploitation training, library systems, and image management systems. From this it would appear the commercial imaging community has failed to learn the hard lessons of national government experience choosing instead to ignore reality and replicate the bias of collection over processing and exploitation. While this trend may be not impact the small quantity users that exist today it will certainly adversely affect the mid- to large-sized users of the future.

Effects of Demographic History on the Detection of Recombination Hotspots from Linkage Disequilibrium.

Science.gov (United States)

Dapper, Amy L; Payseur, Bret A

2018-02-01

In some species, meiotic recombination is concentrated in small genomic regions. These "recombination hotspots" leave signatures in fine-scale patterns of linkage disequilibrium, raising the prospect that the genomic landscape of hotspots can be characterized from sequence variation. This approach has led to the inference that hotspots evolve rapidly in some species, but are conserved in others. Historic demographic events, such as population bottlenecks, are known to affect patterns of linkage disequilibrium across the genome, violating population genetic assumptions of this approach. Although such events are prevalent, demographic history is generally ignored when making inferences about the evolution of recombination hotspots. To determine the effect of demography on the detection of recombination hotspots, we use the coalescent to simulate haplotypes with a known recombination landscape. We measure the ability of popular linkage disequilibrium-based programs to detect hotspots across a range of demographic histories, including population bottlenecks, hidden population structure, population expansions, and population contractions. We find that demographic events have the potential to greatly reduce the power and increase the false positive rate of hotspot discovery. Neither the power nor the false positive rate of hotspot detection can be predicted without also knowing the demographic history of the sample. Our results suggest that ignoring demographic history likely overestimates the power to detect hotspots and therefore underestimates the degree of hotspot sharing between species. We suggest strategies for incorporating demographic history into population genetic inferences about recombination hotspots. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

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.

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.

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.

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.

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…

The history of the priority di∫pute between Newton and Leibniz mathematics in history and culture

CERN Document Server

Sonar, Thomas

2018-01-01

This book provides a thrilling history of the famous priority dispute between Gottfried Wilhelm Leibniz and Isaac Newton, presenting the episode for the first time in the context of cultural history. It introduces readers to the background of the dispute, details its escalation, and discusses the aftermath of the big divide, which extended well into recent times. One of the unique features of the book is that the mathematics behind the story is very intelligibly explained – an approach that offers general readers interested in the history of sciences and mathematics a window into the world of these two giants in their field. From the epilogue to the German edition by Eberhard Knobloch: Thomas Sonar has traced the emergence and the escalation of this conflict, which was heightened by Leibniz’s rejection of Newton’s gravitation theory, in a grandiose, excitingly written monograph. With absolute competence, he also explains the mathematical context so that non-mathematicians will also profit from the book....

On uncertainty in information and ignorance in knowledge

Science.gov (United States)

Ayyub, Bilal M.

2010-05-01

This paper provides an overview of working definitions of knowledge, ignorance, information and uncertainty and summarises formalised philosophical and mathematical framework for their analyses. It provides a comparative examination of the generalised information theory and the generalised theory of uncertainty. It summarises foundational bases for assessing the reliability of knowledge constructed as a collective set of justified true beliefs. It discusses system complexity for ancestor simulation potentials. It offers value-driven communication means of knowledge and contrarian knowledge using memes and memetics.

History, philosophy, and science teaching: The present rapprochement

Science.gov (United States)

Matthews, Michael R.

1992-03-01

This paper traces the use of, and arguments for, the history and philosophy of science in school science courses. Specific attention is paid to the British National Curriculum proposals and to the recommendations of the US Project 2061 curriculum guidelines. Some objections to the inclusion of historical material in science courses are outlined and answered. Mention is made of the Piagetian thesis that individual psychological development mirrors the development of concepts in the history of science. This introduces the topic of idealisation in science. Some significant instances are itemised where science education has, at its considerable cost, ignored work in philosophy of science. Arguments for the inclusion of the history and philosophy of science in science teacher education programmes are given. The paper finishes with a list of topical issues in present science education where collaboration between science teachers, historians, philosophers, and sociologists would be of considerable benefit.

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...

Maggots in the Brain: Sequelae of Ignored Scalp Wound.

Science.gov (United States)

Aggarwal, Ashish; Maskara, Prasant

2018-01-01

A 26-year-old male had suffered a burn injury to his scalp in childhood and ignored it. He presented with a complaint of something crawling on his head. Inspection of his scalp revealed multiple maggots on the brain surface with erosion of overlying bone and scalp. He was successfully managed by surgical debridement and regular dressing. Copyright © 2017 Elsevier Inc. All rights reserved.

Ignoring alarming news brings indifference: Learning about the world and the self.

Science.gov (United States)

Paluck, Elizabeth Levy; Shafir, Eldar; Wu, Sherry Jueyu

2017-10-01

The broadcast of media reports about moral crises such as famine can subtly depress rather than activate moral concern. Whereas much research has examined the effects of media reports that people attend to, social psychological analysis suggests that what goes unattended can also have an impact. We test the idea that when vivid news accounts of human suffering are broadcast in the background but ignored, people infer from their choice to ignore these accounts that they care less about the issue, compared to those who pay attention and even to those who were not exposed. Consistent with research on self-perception and attribution, three experiments demonstrate that participants who were nudged to distract themselves in front of a television news program about famine in Niger (Study 1), or to skip an online promotional video for the Niger famine program (Study 2), or who chose to ignore the famine in Niger television program in more naturalistic settings (Study 3) all assigned lower importance to poverty and to hunger reduction compared to participants who watched with no distraction or opportunity to skip the program, or to those who did not watch at all. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

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...

Some southern African entry points into global history

Directory of Open Access Journals (Sweden)

Neil Parsons

2009-04-01

Full Text Available So-called Global History has taken off in the Unites States to liberate undergraduates from Big Power parochialism, and has been the topic of a major conference held in London in May this year. The key element of Global Studies is to demonstrate the connectedness between different peoples and lands and periods of time. This paper is an attempt to crack the small-end of the egg by starting studies in one familiar region of the world, rather than the big-end approach of starting with general explanations or theory and then relating them back to particulars. It suggests three ways in which Southern Africa could be used as the starting point to throw more general light upon the world’s history. First, by taking cues from and asking questions about the latest genetic research which suggests that modern human population dispersal about 60 000 years ago began in Angola-Namibia frontier region. Second, by taking cues and asking questions about Indonesian contact with Africa and coastal settlement that may account for significant influences on southern African societies. Third, by tracing the biographies of real individuals whose careers encompass not only southern Africa but other parts of the world and in doing so demonstrate not only inter- connectedness of cultural, social, political and economic histories but also significant points of comparison in the experience of global trends and events.

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...

From darwin to the census of marine life: marine biology as big science.

Science.gov (United States)

Vermeulen, Niki

2013-01-01

With the development of the Human Genome Project, a heated debate emerged on biology becoming 'big science'. However, biology already has a long tradition of collaboration, as natural historians were part of the first collective scientific efforts: exploring the variety of life on earth. Such mappings of life still continue today, and if field biology is gradually becoming an important subject of studies into big science, research into life in the world's oceans is not taken into account yet. This paper therefore explores marine biology as big science, presenting the historical development of marine research towards the international 'Census of Marine Life' (CoML) making an inventory of life in the world's oceans. Discussing various aspects of collaboration--including size, internationalisation, research practice, technological developments, application, and public communication--I will ask if CoML still resembles traditional collaborations to collect life. While showing both continuity and change, I will argue that marine biology is a form of natural history: a specific way of working together in biology that has transformed substantially in interaction with recent developments in the life sciences and society. As a result, the paper does not only give an overview of transformations towards large scale research in marine biology, but also shines a new light on big biology, suggesting new ways to deepen the understanding of collaboration in the life sciences by distinguishing between different 'collective ways of knowing'.

From darwin to the census of marine life: marine biology as big science.

Directory of Open Access Journals (Sweden)

Niki Vermeulen

Full Text Available With the development of the Human Genome Project, a heated debate emerged on biology becoming 'big science'. However, biology already has a long tradition of collaboration, as natural historians were part of the first collective scientific efforts: exploring the variety of life on earth. Such mappings of life still continue today, and if field biology is gradually becoming an important subject of studies into big science, research into life in the world's oceans is not taken into account yet. This paper therefore explores marine biology as big science, presenting the historical development of marine research towards the international 'Census of Marine Life' (CoML making an inventory of life in the world's oceans. Discussing various aspects of collaboration--including size, internationalisation, research practice, technological developments, application, and public communication--I will ask if CoML still resembles traditional collaborations to collect life. While showing both continuity and change, I will argue that marine biology is a form of natural history: a specific way of working together in biology that has transformed substantially in interaction with recent developments in the life sciences and society. As a result, the paper does not only give an overview of transformations towards large scale research in marine biology, but also shines a new light on big biology, suggesting new ways to deepen the understanding of collaboration in the life sciences by distinguishing between different 'collective ways of knowing'.

Market Segmentation in (In)Action: Marketing and ‘Yet to Be Installed’ Role of Big and Social Media Data.

NARCIS (Netherlands)

J.H. Pridmore (Jason); Hämäläinen, L.E.

2017-01-01

textabstract(In)Aktive Marktsegmentierung: Marketing und noch zu installierende Rolle von Big- und Social-Media-Data«. Marketing has always been dependent on the input of new forms of consumer data throughout its history, relying on translations of this data into more and more effective means

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.

The Ignorant Facilitator: Education, Politics and Theatre in Co-Communities

Science.gov (United States)

Lev-Aladgem, Shulamith

2015-01-01

This article discusses the book "The Ignorant Schoolmaster: Five Lessons in Intellectual Emancipation" by the French philosopher, Jacques Rancière. Its intention is to study the potential contribution of this text to the discourse of applied theatre (theatre in co-communities) in general, and the role of the facilitator in particular. It…

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.

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.

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.

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.

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

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

Multinational History of Strasbourg Astronomical Observatory

CERN Document Server

Heck, André

2005-01-01

Strasbourg Astronomical Observatory is quite an interesting place for historians: several changes of nationality between France and Germany, high-profile scientists having been based there, big projects born or installed in its walls, and so on. Most of the documents circulating on the history of the Observatory and on related matters have however been so far poorly referenced, if at all. This made necessary the compilation of a volume such as this one, offering fully-documented historical facts and references on the first decades of the Observatory history, authored by both French and German specialists. The experts contributing to this book have done their best to write in a way understandable to readers not necessarily hyperspecialized in astronomy nor in the details of European history. After an introductory chapter by the Editor, contributions by Wolfschmidt and by Duerbeck respectively deal extensively with the German periods and review people and instrumentation, while another paper by Duerbeck is more...

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.

Roles of dark energy perturbations in dynamical dark energy models: can we ignore them?

Science.gov (United States)

Park, Chan-Gyung; Hwang, Jai-chan; Lee, Jae-heon; Noh, Hyerim

2009-10-09

We show the importance of properly including the perturbations of the dark energy component in the dynamical dark energy models based on a scalar field and modified gravity theories in order to meet with present and future observational precisions. Based on a simple scaling scalar field dark energy model, we show that observationally distinguishable substantial differences appear by ignoring the dark energy perturbation. By ignoring it the perturbed system of equations becomes inconsistent and deviations in (gauge-invariant) power spectra depend on the gauge choice.

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.

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.

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)

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.

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...

Big domains are novel Ca²+-binding modules: evidences from big domains of Leptospira immunoglobulin-like (Lig) proteins.

Science.gov (United States)

Raman, Rajeev; Rajanikanth, V; Palaniappan, Raghavan U M; Lin, Yi-Pin; He, Hongxuan; McDonough, Sean P; Sharma, Yogendra; Chang, Yung-Fu

2010-12-29

Many bacterial surface exposed proteins mediate the host-pathogen interaction more effectively in the presence of Ca²+. Leptospiral immunoglobulin-like (Lig) proteins, LigA and LigB, are surface exposed proteins containing Bacterial immunoglobulin like (Big) domains. The function of proteins which contain Big fold is not known. Based on the possible similarities of immunoglobulin and βγ-crystallin folds, we here explore the important question whether Ca²+ binds to a Big domains, which would provide a novel functional role of the proteins containing Big fold. We selected six individual Big domains for this study (three from the conserved part of LigA and LigB, denoted as Lig A3, Lig A4, and LigBCon5; two from the variable region of LigA, i.e., 9(th) (Lig A9) and 10(th) repeats (Lig A10); and one from the variable region of LigB, i.e., LigBCen2. We have also studied the conserved region covering the three and six repeats (LigBCon1-3 and LigCon). All these proteins bind the calcium-mimic dye Stains-all. All the selected four domains bind Ca²+ with dissociation constants of 2-4 µM. Lig A9 and Lig A10 domains fold well with moderate thermal stability, have β-sheet conformation and form homodimers. Fluorescence spectra of Big domains show a specific doublet (at 317 and 330 nm), probably due to Trp interaction with a Phe residue. Equilibrium unfolding of selected Big domains is similar and follows a two-state model, suggesting the similarity in their fold. We demonstrate that the Lig are Ca²+-binding proteins, with Big domains harbouring the binding motif. We conclude that despite differences in sequence, a Big motif binds Ca²+. This work thus sets up a strong possibility for classifying the proteins containing Big domains as a novel family of Ca²+-binding proteins. Since Big domain is a part of many proteins in bacterial kingdom, we suggest a possible function these proteins via Ca²+ binding.

Inferring Demographic History Using Two-Locus Statistics.

Science.gov (United States)

Ragsdale, Aaron P; Gutenkunst, Ryan N

2017-06-01

Population demographic history may be learned from contemporary genetic variation data. Methods based on aggregating the statistics of many single loci into an allele frequency spectrum (AFS) have proven powerful, but such methods ignore potentially informative patterns of linkage disequilibrium (LD) between neighboring loci. To leverage such patterns, we developed a composite-likelihood framework for inferring demographic history from aggregated statistics of pairs of loci. Using this framework, we show that two-locus statistics are more sensitive to demographic history than single-locus statistics such as the AFS. In particular, two-locus statistics escape the notorious confounding of depth and duration of a bottleneck, and they provide a means to estimate effective population size based on the recombination rather than mutation rate. We applied our approach to a Zambian population of Drosophila melanogaster Notably, using both single- and two-locus statistics, we inferred a substantially lower ancestral effective population size than previous works and did not infer a bottleneck history. Together, our results demonstrate the broad potential for two-locus statistics to enable powerful population genetic inference. Copyright © 2017 by the Genetics Society of America.

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...

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

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.

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

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.

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.

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.

The effects of systemic crises when investors can be crisis ignorant

NARCIS (Netherlands)

H.J.W.G. Kole (Erik); C.G. Koedijk (Kees); M.J.C.M. Verbeek (Marno)

2004-01-01

textabstractSystemic crises can largely affect asset allocations due to the rapid deterioration of the risk-return trade-off. We investigate the effects of systemic crises, interpreted as global simultaneous shocks to financial markets, by introducing an investor adopting a crisis ignorant or crisis

Intelligent Test Mechanism Design of Worn Big Gear

Directory of Open Access Journals (Sweden)

Hong-Yu LIU

2014-10-01

Full Text Available With the continuous development of national economy, big gear was widely applied in metallurgy and mine domains. So, big gear plays an important role in above domains. In practical production, big gear abrasion and breach take place often. It affects normal production and causes unnecessary economic loss. A kind of intelligent test method was put forward on worn big gear mainly aimed at the big gear restriction conditions of high production cost, long production cycle and high- intensity artificial repair welding work. The measure equations transformations were made on involute straight gear. Original polar coordinate equations were transformed into rectangular coordinate equations. Big gear abrasion measure principle was introduced. Detection principle diagram was given. Detection route realization method was introduced. OADM12 laser sensor was selected. Detection on big gear abrasion area was realized by detection mechanism. Tested data of unworn gear and worn gear were led in designed calculation program written by Visual Basic language. Big gear abrasion quantity can be obtained. It provides a feasible method for intelligent test and intelligent repair welding on worn big gear.

[Big data in medicine and healthcare].

Science.gov (United States)

Rüping, Stefan

2015-08-01

Healthcare is one of the business fields with the highest Big Data potential. According to the prevailing definition, Big Data refers to the fact that data today is often too large and heterogeneous and changes too quickly to be stored, processed, and transformed into value by previous technologies. The technological trends drive Big Data: business processes are more and more executed electronically, consumers produce more and more data themselves - e.g. in social networks - and finally ever increasing digitalization. Currently, several new trends towards new data sources and innovative data analysis appear in medicine and healthcare. From the research perspective, omics-research is one clear Big Data topic. In practice, the electronic health records, free open data and the "quantified self" offer new perspectives for data analytics. Regarding analytics, significant advances have been made in the information extraction from text data, which unlocks a lot of data from clinical documentation for analytics purposes. At the same time, medicine and healthcare is lagging behind in the adoption of Big Data approaches. This can be traced to particular problems regarding data complexity and organizational, legal, and ethical challenges. The growing uptake of Big Data in general and first best-practice examples in medicine and healthcare in particular, indicate that innovative solutions will be coming. This paper gives an overview of the potentials of Big Data in medicine and healthcare.

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...

World History on the World Wide Web: A Student Satisfaction Survey and a Blinding Flash of the Obvious

Science.gov (United States)

Longhurst, James

2003-01-01

A colleague of the author once observed that papers from first-year history students often feature blinding flashes of the obvious: (1) sweeping declarations that war is bad; (2) social inequality is unfair; or (3) that China is a big place. These sorts of papers sometimes begin with mind-boggling generalizations like "Throughout history, all…

Making big sense from big data in toxicology by read-across.

Science.gov (United States)

Hartung, Thomas

2016-01-01

Modern information technologies have made big data available in safety sciences, i.e., extremely large data sets that may be analyzed only computationally to reveal patterns, trends and associations. This happens by (1) compilation of large sets of existing data, e.g., as a result of the European REACH regulation, (2) the use of omics technologies and (3) systematic robotized testing in a high-throughput manner. All three approaches and some other high-content technologies leave us with big data--the challenge is now to make big sense of these data. Read-across, i.e., the local similarity-based intrapolation of properties, is gaining momentum with increasing data availability and consensus on how to process and report it. It is predominantly applied to in vivo test data as a gap-filling approach, but can similarly complement other incomplete datasets. Big data are first of all repositories for finding similar substances and ensure that the available data is fully exploited. High-content and high-throughput approaches similarly require focusing on clusters, in this case formed by underlying mechanisms such as pathways of toxicity. The closely connected properties, i.e., structural and biological similarity, create the confidence needed for predictions of toxic properties. Here, a new web-based tool under development called REACH-across, which aims to support and automate structure-based read-across, is presented among others.

[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.

How Big Science Came to Long Island: the Birth of Brookhaven Lab (429th Brookhaven Lecture)

International Nuclear Information System (INIS)

Crease, Robert P.

2007-01-01

Robert P. Crease, historian for the U.S. Department of Energy's Brookhaven National Laboratory and Chair of the Philosophy Department at Stony Brook University, will give two talks on the Laboratory's history on October 31 and December 12. Crease's October 31 talk, titled 'How Big Science Came to Long Island: The Birth of Brookhaven Lab,' will cover the founding of the Laboratory soon after World War II as a peacetime facility to construct and maintain basic research facilities, such as nuclear reactors and particle accelerators, that were too large for single institutions to build and operate. He will discuss the key figures involved in starting the Laboratory, including Nobel laureates I.I. Rabi and Norman Ramsey, as well as Donald Dexter Van Slyke, one of the most renowned medical researchers in American history. Crease also will focus on the many problems that had to be overcome in creating the Laboratory and designing its first big machines, as well as the evolving relations of the Laboratory with the surrounding Long Island community and news media. Throughout his talk, Crease will tell fascinating stories about Brookhaven's scientists and their research.

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...

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.

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, ...

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

Forgotten and Ignored: Special Education in First Nations Schools in Canada

Science.gov (United States)

Phillips, Ron

2010-01-01

Usually reviews of special education in Canada describe the special education programs, services, policies, and legislation that are provided by the provinces and territories. The reviews consistently ignore the special education programs, services, policies, and legislation that are provided by federal government of Canada. The federal government…

Geographies of knowing, geographies of ignorance: jumping scale in Southeast Asia

NARCIS (Netherlands)

van Schendel, W.

2002-01-01

'Area studies' use a geographical metaphor to visualise and naturalise particular social spaces as well as a particular scale of analysis. They produce specific geographies of knowing but also create geographies of ignorance. Taking Southeast Asia as an example, in this paper I explore how areas are

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.

Computational perspectives in the history of science: to the memory of Peter Damerow.

Science.gov (United States)

Laubichler, Manfred D; Maienschein, Jane; Renn, Jürgen

2013-03-01

Computational methods and perspectives can transform the history of science by enabling the pursuit of novel types of questions, dramatically expanding the scale of analysis (geographically and temporally), and offering novel forms of publication that greatly enhance access and transparency. This essay presents a brief summary of a computational research system for the history of science, discussing its implications for research, education, and publication practices and its connections to the open-access movement and similar transformations in the natural and social sciences that emphasize big data. It also argues that computational approaches help to reconnect the history of science to individual scientific disciplines.

Innovative and applied research on big data platforms of smart heritage

Science.gov (United States)

Qiu, J.; Li, J.; Sun, H.

2015-08-01

Big data has huge commercial value and potential. Under the background of big data, a heritage site is faced with a number of questions and challenges such as, how to accelerate industrial innovation, benign competition and the creation of new business value. Based on the analysis of service data from the national archaeological site and park, Yuan Ming Yuan, this paper investigates the common problems of site management operations such as, inappropriate cultural interpretation, insufficient consumer demand and so on. In order to solve these operational problems, a new service system called the "one platform - three systems" was put forward. This system includes the smart heritage platform and three management systems: the smart heritage management system, the 3-O (Online-Offline-Onsite) service system and the digital explanation system. Combined with the 3-O marketing operation, the platform can realize bidirectional interaction between heritage site management units and tourists, which can also benefit visitors to the heritage site by explaining the culture and history of the heritage site, bring about more demand for cultural information and expand the social and economic benefits.

Early humans' egalitarian politics: runaway synergistic competition under an adapted veil of ignorance.

Science.gov (United States)

Harvey, Marc

2014-09-01

This paper proposes a model of human uniqueness based on an unusual distinction between two contrasted kinds of political competition and political status: (1) antagonistic competition, in quest of dominance (antagonistic status), a zero-sum, self-limiting game whose stake--who takes what, when, how--summarizes a classical definition of politics (Lasswell 1936), and (2) synergistic competition, in quest of merit (synergistic status), a positive-sum, self-reinforcing game whose stake becomes "who brings what to a team's common good." In this view, Rawls's (1971) famous virtual "veil of ignorance" mainly conceals politics' antagonistic stakes so as to devise the principles of a just, egalitarian society, yet without providing any means to enforce these ideals (Sen 2009). Instead, this paper proposes that human uniqueness flourished under a real "adapted veil of ignorance" concealing the steady inflation of synergistic politics which resulted from early humans' sturdy egalitarianism. This proposition divides into four parts: (1) early humans first stumbled on a purely cultural means to enforce a unique kind of within-team antagonistic equality--dyadic balanced deterrence thanks to handheld weapons (Chapais 2008); (2) this cultural innovation is thus closely tied to humans' darkest side, but it also launched the cumulative evolution of humans' brightest qualities--egalitarian team synergy and solidarity, together with the associated synergistic intelligence, culture, and communications; (3) runaway synergistic competition for differential merit among antagonistically equal obligate teammates is the single politically selective mechanism behind the cumulative evolution of all these brighter qualities, but numerous factors to be clarified here conceal this mighty evolutionary driver; (4) this veil of ignorance persists today, which explains why humans' unique prosocial capacities are still not clearly understood by science. The purpose of this paper is to start lifting

Harnessing the Power of Big Data to Improve Graduate Medical Education: Big Idea or Bust?

Science.gov (United States)

Arora, Vineet M

2018-06-01

With the advent of electronic medical records (EMRs) fueling the rise of big data, the use of predictive analytics, machine learning, and artificial intelligence are touted as transformational tools to improve clinical care. While major investments are being made in using big data to transform health care delivery, little effort has been directed toward exploiting big data to improve graduate medical education (GME). Because our current system relies on faculty observations of competence, it is not unreasonable to ask whether big data in the form of clinical EMRs and other novel data sources can answer questions of importance in GME such as when is a resident ready for independent practice.The timing is ripe for such a transformation. A recent National Academy of Medicine report called for reforms to how GME is delivered and financed. While many agree on the need to ensure that GME meets our nation's health needs, there is little consensus on how to measure the performance of GME in meeting this goal. During a recent workshop at the National Academy of Medicine on GME outcomes and metrics in October 2017, a key theme emerged: Big data holds great promise to inform GME performance at individual, institutional, and national levels. In this Invited Commentary, several examples are presented, such as using big data to inform clinical experience and provide clinically meaningful data to trainees, and using novel data sources, including ambient data, to better measure the quality of GME training.

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…

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

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

Lessons in Equality: From Ignorant Schoolmaster to Chinese Aesthetics

Directory of Open Access Journals (Sweden)

Ernest Ženko

2017-09-01

Full Text Available The postponement of equality is not only a recurring topic in Jacques Rancière’s writings, but also the most defining feature of modern Chinese aesthetics. Particularly in the period after 1980’s, when the country opened its doors to Western ideas, Chinese aesthetics extensively played a subordinate role in an imbalanced knowledge transfer, in which structural inequality was only reinforced. Aesthetics in China plays an important role and is expected not only to interpret literature and art, but also to help building a harmonious society within globalized world. This is the reason why some commentators – Wang Jianjiang being one of them – point out that it is of utmost importance to eliminate this imbalance and develop proper Chinese aesthetics. Since the key issue in this development is the problem of inequality, an approach developed by Jacques Rancière, “the philosopher of equality”, is proposed. Even though Rancière wrote extensively about literature, art and aesthetics, in order to confront the problem of Chinese aesthetics, it seems that a different approach, found in his repertoire, could prove to be more fruitful. In 1987, he published a book titled The Ignorant Schoolmaster, which contributed to his ongoing philosophical emancipatory project, and focused on inequality and its conditions in the realm of education. The Ignorant Schoolmaster, nonetheless, stretches far beyond the walls of classroom or even educational system, and brings to the fore political implications that cluster around the fundamental core of Rancière's political philosophy: the definition of politics as the verification of the presupposition of the equality of intelligence. Equality cannot be postponed as a goal to be only attained in the future and, therefore, has to be considered as a premise of egalitarian politics that needs to operate as a presupposition.   Article received: May 21, 2017; Article accepted: May 28, 2017; Published online

78 FR 3911 - Big Stone National Wildlife Refuge, Big Stone and Lac Qui Parle Counties, MN; Final Comprehensive...

Science.gov (United States)

2013-01-17

... DEPARTMENT OF THE INTERIOR Fish and Wildlife Service [FWS-R3-R-2012-N259; FXRS1265030000-134-FF03R06000] Big Stone National Wildlife Refuge, Big Stone and Lac Qui Parle Counties, MN; Final Comprehensive... significant impact (FONSI) for the environmental assessment (EA) for Big Stone National Wildlife Refuge...

Big domains are novel Ca²+-binding modules: evidences from big domains of Leptospira immunoglobulin-like (Lig proteins.

Directory of Open Access Journals (Sweden)

Rajeev Raman

Full Text Available BACKGROUND: Many bacterial surface exposed proteins mediate the host-pathogen interaction more effectively in the presence of Ca²+. Leptospiral immunoglobulin-like (Lig proteins, LigA and LigB, are surface exposed proteins containing Bacterial immunoglobulin like (Big domains. The function of proteins which contain Big fold is not known. Based on the possible similarities of immunoglobulin and βγ-crystallin folds, we here explore the important question whether Ca²+ binds to a Big domains, which would provide a novel functional role of the proteins containing Big fold. PRINCIPAL FINDINGS: We selected six individual Big domains for this study (three from the conserved part of LigA and LigB, denoted as Lig A3, Lig A4, and LigBCon5; two from the variable region of LigA, i.e., 9(th (Lig A9 and 10(th repeats (Lig A10; and one from the variable region of LigB, i.e., LigBCen2. We have also studied the conserved region covering the three and six repeats (LigBCon1-3 and LigCon. All these proteins bind the calcium-mimic dye Stains-all. All the selected four domains bind Ca²+ with dissociation constants of 2-4 µM. Lig A9 and Lig A10 domains fold well with moderate thermal stability, have β-sheet conformation and form homodimers. Fluorescence spectra of Big domains show a specific doublet (at 317 and 330 nm, probably due to Trp interaction with a Phe residue. Equilibrium unfolding of selected Big domains is similar and follows a two-state model, suggesting the similarity in their fold. CONCLUSIONS: We demonstrate that the Lig are Ca²+-binding proteins, with Big domains harbouring the binding motif. We conclude that despite differences in sequence, a Big motif binds Ca²+. This work thus sets up a strong possibility for classifying the proteins containing Big domains as a novel family of Ca²+-binding proteins. Since Big domain is a part of many proteins in bacterial kingdom, we suggest a possible function these proteins via Ca²+ binding.

Intelligent Management System of Power Network Information Collection Under Big Data Storage

Directory of Open Access Journals (Sweden)

Qin Yingying

2017-01-01

Full Text Available With the development of economy and society, big data storage in enterprise management has become a problem that can’t be ignored. How to manage and optimize the allocation of tasks better is an important factor in the sustainable development of an enterprise. Now the enterprise information intelligent management has become a hot spot of management mode and concept in the information age. It presents information to the business managers in a more efficient, lower cost, and global form. The system uses the SG-UAP development tools, which is based on Eclipse development environment, and suits for Windows operating system, with Oracle as database development platform, Tomcat network information service for application server. The system uses SOA service-oriented architecture, provides RESTful style service, and HTTP(S as the communication protocol, and JSON as the data format. The system is divided into two parts, the front-end and the backs-end, achieved functions like user login, registration, password retrieving, enterprise internal personnel information management and internal data display and other functions.

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

Semipalatinsk nuclear test site: History of building and function

International Nuclear Information System (INIS)

Sergazina, G.M.; Balmukhanov, S.B.

1999-01-01

A vast materials on history of Semipalatinsk nuclear test site creation and it building and function are presented. Authors with big reliability report one page of Kazakhstan's history. In steppe on naked place thousands of soldiers and officers, construct and military specialists have built the nuclear site on which during 40 years were conducting nuclear tests . Prolonged chronic radiation on population living near by site results to tragedy which is confessed by General Assembly of United Nations. In the book aspects of test site conversion and rehabilitation of injured population are considered. The book consists of introduction, three chapters and conclusion. The book is intended to wide circle of readers. (author)

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.

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...

Scalable privacy-preserving big data aggregation mechanism

Directory of Open Access Journals (Sweden)

Dapeng Wu

2016-08-01

Full Text Available As the massive sensor data generated by large-scale Wireless Sensor Networks (WSNs recently become an indispensable part of ‘Big Data’, the collection, storage, transmission and analysis of the big sensor data attract considerable attention from researchers. Targeting the privacy requirements of large-scale WSNs and focusing on the energy-efficient collection of big sensor data, a Scalable Privacy-preserving Big Data Aggregation (Sca-PBDA method is proposed in this paper. Firstly, according to the pre-established gradient topology structure, sensor nodes in the network are divided into clusters. Secondly, sensor data is modified by each node according to the privacy-preserving configuration message received from the sink. Subsequently, intra- and inter-cluster data aggregation is employed during the big sensor data reporting phase to reduce energy consumption. Lastly, aggregated results are recovered by the sink to complete the privacy-preserving big data aggregation. Simulation results validate the efficacy and scalability of Sca-PBDA and show that the big sensor data generated by large-scale WSNs is efficiently aggregated to reduce network resource consumption and the sensor data privacy is effectively protected to meet the ever-growing application requirements.

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

Epidemiology in wonderland: Big Data and precision medicine.

Science.gov (United States)

Saracci, Rodolfo

2018-03-01

Big Data and precision medicine, two major contemporary challenges for epidemiology, are critically examined from two different angles. In Part 1 Big Data collected for research purposes (Big research Data) and Big Data used for research although collected for other primary purposes (Big secondary Data) are discussed in the light of the fundamental common requirement of data validity, prevailing over "bigness". Precision medicine is treated developing the key point that high relative risks are as a rule required to make a variable or combination of variables suitable for prediction of disease occurrence, outcome or response to treatment; the commercial proliferation of allegedly predictive tests of unknown or poor validity is commented. Part 2 proposes a "wise epidemiology" approach to: (a) choosing in a context imprinted by Big Data and precision medicine-epidemiological research projects actually relevant to population health, (b) training epidemiologists, (c) investigating the impact on clinical practices and doctor-patient relation of the influx of Big Data and computerized medicine and (d) clarifying whether today "health" may be redefined-as some maintain in purely technological terms.

Big Data and Analytics in Healthcare.

Science.gov (United States)

Tan, S S-L; Gao, G; Koch, S

2015-01-01

This editorial is part of the Focus Theme of Methods of Information in Medicine on "Big Data and Analytics in Healthcare". The amount of data being generated in the healthcare industry is growing at a rapid rate. This has generated immense interest in leveraging the availability of healthcare data (and "big data") to improve health outcomes and reduce costs. However, the nature of healthcare data, and especially big data, presents unique challenges in processing and analyzing big data in healthcare. This Focus Theme aims to disseminate some novel approaches to address these challenges. More specifically, approaches ranging from efficient methods of processing large clinical data to predictive models that could generate better predictions from healthcare data are presented.

Big Data for Business Ecosystem Players

Directory of Open Access Journals (Sweden)

Perko Igor

2016-06-01

Full Text Available In the provided research, some of the Big Data most prospective usage domains connect with distinguished player groups found in the business ecosystem. Literature analysis is used to identify the state of the art of Big Data related research in the major domains of its use-namely, individual marketing, health treatment, work opportunities, financial services, and security enforcement. System theory was used to identify business ecosystem major player types disrupted by Big Data: individuals, small and mid-sized enterprises, large organizations, information providers, and regulators. Relationships between the domains and players were explained through new Big Data opportunities and threats and by players’ responsive strategies. System dynamics was used to visualize relationships in the provided model.

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.

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.

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.

BIG DATA IN TAMIL: OPPORTUNITIES, BENEFITS AND CHALLENGES

OpenAIRE

R.S. Vignesh Raj; Babak Khazaei; Ashik Ali

2015-01-01

This paper gives an overall introduction on big data and has tried to introduce Big Data in Tamil. It discusses the potential opportunities, benefits and likely challenges from a very Tamil and Tamil Nadu perspective. The paper has also made original contribution by proposing the ‘big data’s’ terminology in Tamil. The paper further suggests a few areas to explore using big data Tamil on the lines of the Tamil Nadu Government ‘vision 2023’. Whilst, big data has something to offer everyone, it ...

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.

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. PMID:29594091

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.

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.

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.

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

The Berlin Inventory of Gambling behavior - Screening (BIG-S): Validation using a clinical sample.

Science.gov (United States)

Wejbera, Martin; Müller, Kai W; Becker, Jan; Beutel, Manfred E

2017-05-18

Published diagnostic questionnaires for gambling disorder in German are either based on DSM-III criteria or focus on aspects other than life time prevalence. This study was designed to assess the usability of the DSM-IV criteria based Berlin Inventory of Gambling Behavior Screening tool in a clinical sample and adapt it to DSM-5 criteria. In a sample of 432 patients presenting for behavioral addiction assessment at the University Medical Center Mainz, we checked the screening tool's results against clinical diagnosis and compared a subsample of n=300 clinically diagnosed gambling disorder patients with a comparison group of n=132. The BIG-S produced a sensitivity of 99.7% and a specificity of 96.2%. The instrument's unidimensionality and the diagnostic improvements of DSM-5 criteria were verified by exploratory and confirmatory factor analysis as well as receiver operating characteristic analysis. The BIG-S is a reliable and valid screening tool for gambling disorder and demonstrated its concise and comprehensible operationalization of current DSM-5 criteria in a clinical setting.

Mathematical Practice as Sculpture of Utopia: Models, Ignorance, and the Emancipated Spectator

Science.gov (United States)

Appelbaum, Peter

2012-01-01

This article uses Ranciere's notion of the ignorant schoolmaster and McElheny's differentiation of artist's models from those of the architect and scientist to propose the reconceptualization of mathematics education as the support of emancipated spectators and sculptors of utopia.

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.

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

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...

Quantum nature of the big bang.

Science.gov (United States)

Ashtekar, Abhay; Pawlowski, Tomasz; Singh, Parampreet

2006-04-14

Some long-standing issues concerning the quantum nature of the big bang are resolved in the context of homogeneous isotropic models with a scalar field. Specifically, the known results on the resolution of the big-bang singularity in loop quantum cosmology are significantly extended as follows: (i) the scalar field is shown to serve as an internal clock, thereby providing a detailed realization of the "emergent time" idea; (ii) the physical Hilbert space, Dirac observables, and semiclassical states are constructed rigorously; (iii) the Hamiltonian constraint is solved numerically to show that the big bang is replaced by a big bounce. Thanks to the nonperturbative, background independent methods, unlike in other approaches the quantum evolution is deterministic across the deep Planck regime.

Mentoring in Schools: An Impact Study of Big Brothers Big Sisters School-Based Mentoring

Science.gov (United States)

Herrera, Carla; Grossman, Jean Baldwin; Kauh, Tina J.; McMaken, Jennifer

2011-01-01

This random assignment impact study of Big Brothers Big Sisters School-Based Mentoring involved 1,139 9- to 16-year-old students in 10 cities nationwide. Youth were randomly assigned to either a treatment group (receiving mentoring) or a control group (receiving no mentoring) and were followed for 1.5 school years. At the end of the first school…

Big data processing in the cloud - Challenges and platforms

Science.gov (United States)

Zhelev, Svetoslav; Rozeva, Anna

2017-12-01

Choosing the appropriate architecture and technologies for a big data project is a difficult task, which requires extensive knowledge in both the problem domain and in the big data landscape. The paper analyzes the main big data architectures and the most widely implemented technologies used for processing and persisting big data. Clouds provide for dynamic resource scaling, which makes them a natural fit for big data applications. Basic cloud computing service models are presented. Two architectures for processing big data are discussed, Lambda and Kappa architectures. Technologies for big data persistence are presented and analyzed. Stream processing as the most important and difficult to manage is outlined. The paper highlights main advantages of cloud and potential problems.

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.

Issues ignored in laboratory quality surveillance

International Nuclear Information System (INIS)

Zeng Jing; Li Xingyuan; Zhang Tingsheng

2008-01-01

According to the work requirement of the related laboratory quality surveillance in ISO17025, this paper analyzed and discussed the issued ignored in the laboratory quality surveillance. In order to solve the present problem, it is required to understand the work responsibility in the quality surveillance correctly, to establish the effective working routine in the quality surveillance, and to conduct, the quality surveillance work. The object in the quality surveillance shall be 'the operator' who engaged in the examination/calibration directly in the laboratory, especially the personnel in training (who is engaged in the examination/calibration). The quality supervisors shall be fully authorized, so that they can correctly understand the work responsibility in quality surveillance, and are with the rights for 'full supervision'. The laboratory also shall arrange necessary training to the quality supervisor, so that they can obtain sufficient guide in time and are with required qualification or occupation prerequisites. (authors)

New perspectives in film reception of Ancient History: the example of «Dacii / Les guerriers» (Sergiu Nicolaescu, Romania / France 1966

Directory of Open Access Journals (Sweden)

Óscar LAPEÑA MARCHENA

2011-03-01

Full Text Available This paper analyzes a film that deals with an episode in the history of the Roman Empire practicaly ignored by the cinema: the military campaigns undertaken by the emperor Domitian in the province of Dacia.

Victoria Stodden: Scholarly Communication in the Era of Big Data and Big Computation

OpenAIRE

Stodden, Victoria

2015-01-01

Victoria Stodden gave the keynote address for Open Access Week 2015. "Scholarly communication in the era of big data and big computation" was sponsored by the University Libraries, Computational Modeling and Data Analytics, the Department of Computer Science, the Department of Statistics, the Laboratory for Interdisciplinary Statistical Analysis (LISA), and the Virginia Bioinformatics Institute. Victoria Stodden is an associate professor in the Graduate School of Library and Information Scien...

Big Data: Concept, Potentialities and Vulnerabilities

Directory of Open Access Journals (Sweden)

Fernando Almeida

2018-03-01

Full Text Available The evolution of information systems and the growth in the use of the Internet and social networks has caused an explosion in the amount of available data relevant to the activities of the companies. Therefore, the treatment of these available data is vital to support operational, tactical and strategic decisions. This paper aims to present the concept of big data and the main technologies that support the analysis of large data volumes. The potential of big data is explored considering nine sectors of activity, such as financial, retail, healthcare, transports, agriculture, energy, manufacturing, public, and media and entertainment. In addition, the main current opportunities, vulnerabilities and privacy challenges of big data are discussed. It was possible to conclude that despite the potential for using the big data to grow in the previously identified areas, there are still some challenges that need to be considered and mitigated, namely the privacy of information, the existence of qualified human resources to work with Big Data and the promotion of a data-driven organizational culture.

Big data analytics a management perspective

CERN Document Server

Corea, Francesco

2016-01-01

This book is about innovation, big data, and data science seen from a business perspective. Big data is a buzzword nowadays, and there is a growing necessity within practitioners to understand better the phenomenon, starting from a clear stated definition. This book aims to be a starting reading for executives who want (and need) to keep the pace with the technological breakthrough introduced by new analytical techniques and piles of data. Common myths about big data will be explained, and a series of different strategic approaches will be provided. By browsing the book, it will be possible to learn how to implement a big data strategy and how to use a maturity framework to monitor the progress of the data science team, as well as how to move forward from one stage to the next. Crucial challenges related to big data will be discussed, where some of them are more general - such as ethics, privacy, and ownership – while others concern more specific business situations (e.g., initial public offering, growth st...

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.

Slaves to Big Data. Or Are We?

Directory of Open Access Journals (Sweden)

Mireille Hildebrandt

2013-10-01

Full Text Available

In this contribution, the notion of Big Data is discussed in relation to the monetisation of personal data. The claim of some proponents, as well as adversaries, that Big Data implies that ‘n = all’, meaning that we no longer need to rely on samples because we have all the data, is scrutinised and found to be both overly optimistic and unnecessarily pessimistic. A set of epistemological and ethical issues is presented, focusing on the implications of Big Data for our perception, cognition, fairness, privacy and due process. The article then looks into the idea of user-centric personal data management to investigate to what extent it provides solutions for some of the problems triggered by the Big Data conundrum. Special attention is paid to the core principle of data protection legislation, namely purpose binding. Finally, this contribution seeks to inquire into the influence of Big Data politics on self, mind and society, and asks how we can prevent ourselves from becoming slaves to Big Data.

Will Organization Design Be Affected By Big Data?

Directory of Open Access Journals (Sweden)

Giles Slinger

2014-12-01

Full Text Available Computing power and analytical methods allow us to create, collate, and analyze more data than ever before. When datasets are unusually large in volume, velocity, and variety, they are referred to as “big data.” Some observers have suggested that in order to cope with big data (a organizational structures will need to change and (b the processes used to design organizations will be different. In this article, we differentiate big data from relatively slow-moving, linked people data. We argue that big data will change organizational structures as organizations pursue the opportunities presented by big data. The processes by which organizations are designed, however, will be relatively unaffected by big data. Instead, organization design processes will be more affected by the complex links found in people data.

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.

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 ...

Ewing sarcoma of the left big toe with trans-articular skip lesion

Directory of Open Access Journals (Sweden)

Ahmad F. Kamal

2009-06-01

Full Text Available We report the case of the patient who had Ewing Sarcoma in whom radiological and hystopathological appearances revealed a tumor mass in the left big toe along with trans-artikular skip lesion on the left diaphysis of tibia. In Cipto Mangunkusomo Hospital since 1995 until 2004 we have found 20 Ewing sarcoma cases, but only one skip lesion Ewing sarcoma was found. The diagnosis of transarticular skip lesion in association of Ewing sarcoma was confirmed in clinicopathological conferrence. The initial evaluation of all patients included the recording of the medical history, physical examination, and hematological studies. Radiographs of the chest and the site of the primary tumor were made routinely. Systemic staging was performed with use of total-body bone scan. Ray amputation of left big toe and open biopsy from mass of mid-shaft of tibia had been done to confirm the diagnosis. The patient underwent induction chemotherapy and above knee amputation. Ten months after diagnosis, he died because of advanced-distant metastasis. (Med J Indones 2008; 18: 139-44Key words: Ewing sarcoma, trans-articular skip lesion

History Writ Large: Big-character Posters, Red Logorrhoea and the Art of Words

Directory of Open Access Journals (Sweden)

Geremie R. Barmé

2013-01-01

Full Text Available The starting point of this paper is the 1986 artwork of the then Xiamen-based artist Wu Shanzhuan, called ‘Red Humor’, which reworked references to big-character posters (dazi bao 大字报 and other Mao-era forms of political discourse, recalling the Cultural Revolution. It explains how Wu’s installation offered a provocative microcosm of the overwhelming mood engendered by a logocentric movement to ‘paint the nation red’ with word-images during the years 1966-1967. This discussion of the hyper-real use of the dazi bao during China’s Cultural Revolution era (c.1964-1978 allows us to probe into ‘the legacies of the word made image’ in modern China. The paper argues that, since the 1980s, Wu Shanzhuan has had many emulators and ‘avant-garde successors’, since we have seen multiple examples of parodic deconstructions of the cultural authority of the Chinese character (zi in recent decades.

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

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.

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...

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.

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.)

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.

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...

Integrating R and Hadoop for Big Data Analysis

OpenAIRE

Bogdan Oancea; Raluca Mariana Dragoescu

2014-01-01

Analyzing and working with big data could be very diffi cult using classical means like relational database management systems or desktop software packages for statistics and visualization. Instead, big data requires large clusters with hundreds or even thousands of computing nodes. Offi cial statistics is increasingly considering big data for deriving new statistics because big data sources could produce more relevant and timely statistics than traditional sources. One of the software tools ...

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.

About How Did the First Ever Big Economic Crisis Look Like

Directory of Open Access Journals (Sweden)

Liviu C. ANDREI

2010-02-01

Full Text Available The obsession about the current economic crisis is pretty understandable. But being obsessed about the current moment, in the economic crisis matter, might become a scientific mistake. As for instance, the real results of the current period will be available in just a couple of years. Moreover, we used to believe up to recently that the previous big crisis of 1929-1933 might be nearly an accident and would not repeat, due to its lesson applied: the policy makers made functional, vigilant, diligent and acting. May be such a lesson was not enough. But equally, every crisis would claim a specific lesson of this kind, and the present one would do the same, whereas the 1929-1933 and current crises lessons would not be enough, partly because the economic history has more in such a topic area. In other words, let us more deeply search for crisis elements in the world economic history.

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...

Physics with Big Karl Brainstorming. Abstracts

International Nuclear Information System (INIS)

Machner, H.; Lieb, J.

2000-08-01

Before summarizing details of the meeting, a short description of the spectrometer facility Big Karl is given. The facility is essentially a new instrument using refurbished dipole magnets from its predecessor. The large acceptance quadrupole magnets and the beam optics are new. Big Karl has a design very similar as the focussing spectrometers at MAMI (Mainz), AGOR (Groningen) and the high resolution spectrometer (HRS) in Hall A at Jefferson Laboratory with ΔE/E = 10 -4 but at some lower maximum momentum. The focal plane detectors consisting of multiwire drift chambers and scintillating hodoscopes are similar. Unlike HRS, Big Karl still needs Cerenkov counters and polarimeters in its focal plane; detectors which are necessary to perform some of the experiments proposed during the brainstorming. In addition, BIG KARL allows emission angle reconstruction via track measurements in its focal plane with high resolution. In the following the physics highlights, the proposed and potential experiments are summarized. During the meeting it became obvious that the physics to be explored at Big Karl can be grouped into five distinct categories, and this summary is organized accordingly. (orig.)

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.

Toward Embracing Multiple Perspectives in World History Curricula: Interrogating Representations of Intercultural Exchanges between Ancient Civilizations in Quebec Textbooks

Science.gov (United States)

Abdou, Ehaab D.

2017-01-01

Guided by critical discourse analysis, this study analyzes how ancient civilizations are constructed in high school history textbooks used in Quebec, Canada. The findings suggest that the narrative generally ignores 2-way intercultural exchanges. The narrative is also Eurocentric, silencing sub-Saharan Africa's contributions and nonmaterial…

Application and Prospect of Big Data in Water Resources

Science.gov (United States)

Xi, Danchi; Xu, Xinyi

2017-04-01

Because of developed information technology and affordable data storage, we h ave entered the era of data explosion. The term "Big Data" and technology relate s to it has been created and commonly applied in many fields. However, academic studies just got attention on Big Data application in water resources recently. As a result, water resource Big Data technology has not been fully developed. This paper introduces the concept of Big Data and its key technologies, including the Hadoop system and MapReduce. In addition, this paper focuses on the significance of applying the big data in water resources and summarizing prior researches by others. Most studies in this field only set up theoretical frame, but we define the "Water Big Data" and explain its tridimensional properties which are time dimension, spatial dimension and intelligent dimension. Based on HBase, the classification system of Water Big Data is introduced: hydrology data, ecology data and socio-economic data. Then after analyzing the challenges in water resources management, a series of solutions using Big Data technologies such as data mining and web crawler, are proposed. Finally, the prospect of applying big data in water resources is discussed, it can be predicted that as Big Data technology keeps developing, "3D" (Data Driven Decision) will be utilized more in water resources management in the future.

Big Data in food and agriculture

Directory of Open Access Journals (Sweden)

Kelly Bronson

2016-06-01

Full Text Available Farming is undergoing a digital revolution. Our existing review of current Big Data applications in the agri-food sector has revealed several collection and analytics tools that may have implications for relationships of power between players in the food system (e.g. between farmers and large corporations. For example, Who retains ownership of the data generated by applications like Monsanto Corproation's Weed I.D . “app”? Are there privacy implications with the data gathered by John Deere's precision agricultural equipment? Systematically tracing the digital revolution in agriculture, and charting the affordances as well as the limitations of Big Data applied to food and agriculture, should be a broad research goal for Big Data scholarship. Such a goal brings data scholarship into conversation with food studies and it allows for a focus on the material consequences of big data in society.

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.

Una aproximación a Big Data = An approach to Big Data

OpenAIRE

Puyol Moreno, Javier

2014-01-01

Big Data puede ser considerada como una tendencia en el avance de la tecnología que ha abierto la puerta a un nuevo enfoque para la comprensión y la toma de decisiones, que se utiliza para describir las enormes cantidades de datos (estructurados, no estructurados y semi- estructurados) que sería demasiado largo y costoso para cargar una base de datos relacional para su análisis. Así, el concepto de Big Data se aplica a toda la información que no puede ser procesada o analizada utilizando herr...

Toward a Literature-Driven Definition of Big Data in Healthcare.

Science.gov (United States)

Baro, Emilie; Degoul, Samuel; Beuscart, Régis; Chazard, Emmanuel

2015-01-01

The aim of this study was to provide a definition of big data in healthcare. A systematic search of PubMed literature published until May 9, 2014, was conducted. We noted the number of statistical individuals (n) and the number of variables (p) for all papers describing a dataset. These papers were classified into fields of study. Characteristics attributed to big data by authors were also considered. Based on this analysis, a definition of big data was proposed. A total of 196 papers were included. Big data can be defined as datasets with Log(n∗p) ≥ 7. Properties of big data are its great variety and high velocity. Big data raises challenges on veracity, on all aspects of the workflow, on extracting meaningful information, and on sharing information. Big data requires new computational methods that optimize data management. Related concepts are data reuse, false knowledge discovery, and privacy issues. Big data is defined by volume. Big data should not be confused with data reuse: data can be big without being reused for another purpose, for example, in omics. Inversely, data can be reused without being necessarily big, for example, secondary use of Electronic Medical Records (EMR) data.

Big Data Analytic, Big Step for Patient Management and Care in Puerto Rico.

Science.gov (United States)

Borrero, Ernesto E

2018-01-01

This letter provides an overview of the application of big data in health care system to improve quality of care, including predictive modelling for risk and resource use, precision medicine and clinical decision support, quality of care and performance measurement, public health and research applications, among others. The author delineates the tremendous potential for big data analytics and discuss how it can be successfully implemented in clinical practice, as an important component of a learning health-care system.

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

Big data governance an emerging imperative

CERN Document Server

Soares, Sunil

2012-01-01

Written by a leading expert in the field, this guide focuses on the convergence of two major trends in information management-big data and information governance-by taking a strategic approach oriented around business cases and industry imperatives. With the advent of new technologies, enterprises are expanding and handling very large volumes of data; this book, nontechnical in nature and geared toward business audiences, encourages the practice of establishing appropriate governance over big data initiatives and addresses how to manage and govern big data, highlighting the relevant processes,

Big Data and historical social science

Directory of Open Access Journals (Sweden)

Peter Bearman

2015-11-01

Full Text Available “Big Data” can revolutionize historical social science if it arises from substantively important contexts and is oriented towards answering substantively important questions. Such data may be especially important for answering previously largely intractable questions about the timing and sequencing of events, and of event boundaries. That said, “Big Data” makes no difference for social scientists and historians whose accounts rest on narrative sentences. Since such accounts are the norm, the effects of Big Data on the practice of historical social science may be more limited than one might wish.

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...

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.

Classical propagation of strings across a big crunch/big bang singularity

International Nuclear Information System (INIS)

Niz, Gustavo; Turok, Neil

2007-01-01

One of the simplest time-dependent solutions of M theory consists of nine-dimensional Euclidean space times 1+1-dimensional compactified Milne space-time. With a further modding out by Z 2 , the space-time represents two orbifold planes which collide and re-emerge, a process proposed as an explanation of the hot big bang [J. Khoury, B. A. Ovrut, P. J. Steinhardt, and N. Turok, Phys. Rev. D 64, 123522 (2001).][P. J. Steinhardt and N. Turok, Science 296, 1436 (2002).][N. Turok, M. Perry, and P. J. Steinhardt, Phys. Rev. D 70, 106004 (2004).]. When the two planes are near, the light states of the theory consist of winding M2-branes, describing fundamental strings in a particular ten-dimensional background. They suffer no blue-shift as the M theory dimension collapses, and their equations of motion are regular across the transition from big crunch to big bang. In this paper, we study the classical evolution of fundamental strings across the singularity in some detail. We also develop a simple semiclassical approximation to the quantum evolution which allows one to compute the quantum production of excitations on the string and implement it in a simplified example

"small problems, Big Trouble": An Art and Science Collaborative Exhibition Reflecting Seemingly small problems Leading to Big Threats

Science.gov (United States)

Waller, J. L.; Brey, J. A.

2014-12-01

"small problems, Big Trouble" (spBT) is an exhibition of artist Judith Waller's paintings accompanied by text panels written by Earth scientist Dr. James A. Brey and several science researchers and educators. The text panels' message is as much the focus of the show as the art--true interdisciplinarity! Waller and Brey's history of art and earth science collaborations include the successful exhibition "Layers: Places in Peril". New in spBT is extended collaboration with other scientists in order to create awareness of geoscience and other subjects (i.e. soil, parasites, dust, pollutants, invasive species, carbon, ground water contaminants, solar wind) small in scale which pose significant threats. The paintings are the size of a mirror, a symbol suggesting the problems depicted are those we increasingly need to face, noting our collective reflections of shared current and future reality. Naturalistic rendering and abstract form in the art helps reach a broad audience including those familiar with art and those familiar with science. The goal is that gallery visitors gain greater appreciation and understanding of both—and of the sober content of the show as a whole. "small problems, Big Trouble" premiers in Wisconsin April, 2015. As in previous collaborations, Waller and Brey actively utilize art and science (specifically geoscience) as an educational vehicle for active student learning. Planned are interdisciplinary university and area high school activities linked through spBT. The exhibition in a public gallery offers a means to enhance community awareness of and action on scientific issues through art's power to engage people on an emotional level. This AGU presentation includes a description of past Waller and Brey activities: incorporating art and earth science in lab and studio classrooms, producing gallery and museum exhibitions and delivering workshops and other presentations. They also describe how walking the paths of several past earth science

Dirt, disgust and disease: a natural history of hygiene.

Science.gov (United States)

Curtis, Valerie A

2007-08-01

Hygiene has been studied from multiple perspectives, including that of history. I define hygiene as the set of behaviours that animals, including humans, use to avoid infection. I argue that it has an ancient evolutionary history, and that most animals exhibit such behaviours because they were adaptive. In humans, the avoidance of infectious threats is motivated by the emotion of disgust. Intuition about hygiene, dirt and disease can be found underlying belief about health and disease throughout history. Purification ritual, miasma, contagion, zymotic and germ theories of disease are ideas that spread through society because they are intuitively attractive, because they are supported by evidence either from direct experience or from authoritative report and because they are consistent with existing beliefs. In contrast to much historical and anthropological assertion, I argue that hygiene behaviour and disgust predate culture and so cannot fully be explained as its product. The history of ideas about disease thus is neither entirely socially constructed nor an "heroic progress" of scientists leading the ignorant into the light. As an animal behaviour the proper domain of hygiene is biology, and without this perspective attempts at explanation are incomplete. The approaches of biological anthropology have much to offer the practice of cultural history.

Ignoring Memory Hints: The Stubborn Influence of Environmental Cues on Recognition Memory

Science.gov (United States)

Selmeczy, Diana; Dobbins, Ian G.

2017-01-01

Recognition judgments can benefit from the use of environmental cues that signal the general likelihood of encountering familiar versus unfamiliar stimuli. While incorporating such cues is often adaptive, there are circumstances (e.g., eyewitness testimony) in which observers should fully ignore environmental cues in order to preserve memory…

Prospects for determination of thermal history after inflation with future gravitational wave detectors

International Nuclear Information System (INIS)

Kuroyanagi, Sachiko; Nakayama, Kazunori; Saito, Shun

2011-01-01

Thermal history of the Universe between inflation and big-bang nucleosynthesis has not yet been revealed observationally. It will be probed by the detection of primordial gravitational waves generated during inflation, which contain information on the reheating temperature as well as the equation of state of the Universe after inflation. Based on the Fisher information formalism, we examine how accurately the tensor-to-scalar ratio and reheating temperature after inflation can be simultaneously determined with space-based gravitational wave detectors such as the DECI-hertz Interferometer Gravitational-wave Observatory and the Big-Bang Observer. We show that the reheating temperature is best determined if it is around 10 7 GeV for tensor-to-scalar ratio of around 0.1, and explore the detectable parameter space. We also find that equation of state of the early Universe can be also determined accurately enough to distinguish different equation-of-state parameters if the inflationary gravitational waves are successfully detected. Thus, future gravitational wave detectors provide a unique and promising opportunity to reveal the thermal history of the Universe around 10 7 GeV.

The Information Panopticon in the Big Data Era

Directory of Open Access Journals (Sweden)

Martin Berner

2014-04-01

Full Text Available Taking advantage of big data opportunities is challenging for traditional organizations. In this article, we take a panoptic view of big data – obtaining information from more sources and making it visible to all organizational levels. We suggest that big data requires the transformation from command and control hierarchies to post-bureaucratic organizational structures wherein employees at all levels can be empowered while simultaneously being controlled. We derive propositions that show how to best exploit big data technologies in organizations.

``All that Matter ... in One Big Bang ...'', &Other Cosmological Singularities

Science.gov (United States)

Elizalde, Emilio

2018-02-01

The first part of this paper contains a brief description of the beginnings of modern cosmology, which, the author will argue, was most likely born in the Year 1912. Some of the pieces of evidence presented here have emerged from recent research in the history of science, and are not usually shared with the general audiences in popular science books. In special, the issue of the correct formulation of the original Big Bang concept, according to the precise words of Fred Hoyle, is discussed. Too often, this point is very deficiently explained (when not just misleadingly) in most of the available generalist literature. Other frequent uses of the same words, Big Bang, as to name the initial singularity of the cosmos, and also whole cosmological models, are then addressed, as evolutions of its original meaning. Quantum and inflationary additions to the celebrated singularity theorems by Penrose, Geroch, Hawking and others led to subsequent results by Borde, Guth and Vilenkin. And corresponding corrections to the Einstein field equations have originated, in particular, $R^2$, $f(R)$, and scalar-tensor gravities, giving rise to a plethora of new singularities. For completeness, an updated table with a classification of the same is given.

WE-H-BRB-00: Big Data in Radiation Oncology

Energy Technology Data Exchange (ETDEWEB)

NONE

2016-06-15

Big Data in Radiation Oncology: (1) Overview of the NIH 2015 Big Data Workshop, (2) Where do we stand in the applications of big data in radiation oncology?, and (3) Learning Health Systems for Radiation Oncology: Needs and Challenges for Future Success The overriding goal of this trio panel of presentations is to improve awareness of the wide ranging opportunities for big data impact on patient quality care and enhancing potential for research and collaboration opportunities with NIH and a host of new big data initiatives. This presentation will also summarize the Big Data workshop that was held at the NIH Campus on August 13–14, 2015 and sponsored by AAPM, ASTRO, and NIH. The workshop included discussion of current Big Data cancer registry initiatives, safety and incident reporting systems, and other strategies that will have the greatest impact on radiation oncology research, quality assurance, safety, and outcomes analysis. Learning Objectives: To discuss current and future sources of big data for use in radiation oncology research To optimize our current data collection by adopting new strategies from outside radiation oncology To determine what new knowledge big data can provide for clinical decision support for personalized medicine L. Xing, NIH/NCI Google Inc.

WE-H-BRB-00: Big Data in Radiation Oncology

International Nuclear Information System (INIS)

2016-01-01

Big Data in Radiation Oncology: (1) Overview of the NIH 2015 Big Data Workshop, (2) Where do we stand in the applications of big data in radiation oncology?, and (3) Learning Health Systems for Radiation Oncology: Needs and Challenges for Future Success The overriding goal of this trio panel of presentations is to improve awareness of the wide ranging opportunities for big data impact on patient quality care and enhancing potential for research and collaboration opportunities with NIH and a host of new big data initiatives. This presentation will also summarize the Big Data workshop that was held at the NIH Campus on August 13–14, 2015 and sponsored by AAPM, ASTRO, and NIH. The workshop included discussion of current Big Data cancer registry initiatives, safety and incident reporting systems, and other strategies that will have the greatest impact on radiation oncology research, quality assurance, safety, and outcomes analysis. Learning Objectives: To discuss current and future sources of big data for use in radiation oncology research To optimize our current data collection by adopting new strategies from outside radiation oncology To determine what new knowledge big data can provide for clinical decision support for personalized medicine L. Xing, NIH/NCI Google Inc.

De impact van Big Data op Internationale Betrekkingen

NARCIS (Netherlands)

Zwitter, Andrej

Big Data changes our daily lives, but does it also change international politics? In this contribution, Andrej Zwitter (NGIZ chair at Groningen University) argues that Big Data impacts on international relations in ways that we only now start to understand. To comprehend how Big Data influences

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

Big data and analytics strategic and organizational impacts

CERN Document Server

Morabito, Vincenzo

2015-01-01

This book presents and discusses the main strategic and organizational challenges posed by Big Data and analytics in a manner relevant to both practitioners and scholars. The first part of the book analyzes strategic issues relating to the growing relevance of Big Data and analytics for competitive advantage, which is also attributable to empowerment of activities such as consumer profiling, market segmentation, and development of new products or services. Detailed consideration is also given to the strategic impact of Big Data and analytics on innovation in domains such as government and education and to Big Data-driven business models. The second part of the book addresses the impact of Big Data and analytics on management and organizations, focusing on challenges for governance, evaluation, and change management, while the concluding part reviews real examples of Big Data and analytics innovation at the global level. The text is supported by informative illustrations and case studies, so that practitioners...

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.

Toward a Literature-Driven Definition of Big Data in Healthcare

Directory of Open Access Journals (Sweden)

Emilie Baro

2015-01-01

Full Text Available Objective. The aim of this study was to provide a definition of big data in healthcare. Methods. A systematic search of PubMed literature published until May 9, 2014, was conducted. We noted the number of statistical individuals (n and the number of variables (p for all papers describing a dataset. These papers were classified into fields of study. Characteristics attributed to big data by authors were also considered. Based on this analysis, a definition of big data was proposed. Results. A total of 196 papers were included. Big data can be defined as datasets with Log⁡(n*p≥7. Properties of big data are its great variety and high velocity. Big data raises challenges on veracity, on all aspects of the workflow, on extracting meaningful information, and on sharing information. Big data requires new computational methods that optimize data management. Related concepts are data reuse, false knowledge discovery, and privacy issues. Conclusion. Big data is defined by volume. Big data should not be confused with data reuse: data can be big without being reused for another purpose, for example, in omics. Inversely, data can be reused without being necessarily big, for example, secondary use of Electronic Medical Records (EMR data.

Toward a Literature-Driven Definition of Big Data in Healthcare

Science.gov (United States)

Baro, Emilie; Degoul, Samuel; Beuscart, Régis; Chazard, Emmanuel

2015-01-01

Objective. The aim of this study was to provide a definition of big data in healthcare. Methods. A systematic search of PubMed literature published until May 9, 2014, was conducted. We noted the number of statistical individuals (n) and the number of variables (p) for all papers describing a dataset. These papers were classified into fields of study. Characteristics attributed to big data by authors were also considered. Based on this analysis, a definition of big data was proposed. Results. A total of 196 papers were included. Big data can be defined as datasets with Log⁡(n∗p) ≥ 7. Properties of big data are its great variety and high velocity. Big data raises challenges on veracity, on all aspects of the workflow, on extracting meaningful information, and on sharing information. Big data requires new computational methods that optimize data management. Related concepts are data reuse, false knowledge discovery, and privacy issues. Conclusion. Big data is defined by volume. Big data should not be confused with data reuse: data can be big without being reused for another purpose, for example, in omics. Inversely, data can be reused without being necessarily big, for example, secondary use of Electronic Medical Records (EMR) data. PMID:26137488

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...

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.

Research on information security in big data era

Science.gov (United States)

Zhou, Linqi; Gu, Weihong; Huang, Cheng; Huang, Aijun; Bai, Yongbin

2018-05-01

Big data is becoming another hotspot in the field of information technology after the cloud computing and the Internet of Things. However, the existing information security methods can no longer meet the information security requirements in the era of big data. This paper analyzes the challenges and a cause of data security brought by big data, discusses the development trend of network attacks under the background of big data, and puts forward my own opinions on the development of security defense in technology, strategy and product.

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.

Illiteracy, Ignorance, and Willingness to Quit Smoking among Villagers in India

Science.gov (United States)

Gorty, Prasad V. S. N. R.; Allam, Apparao

1992-01-01

During the field work to control oral cancer, difficulty in communication was encountered with illiterates. A study to define the role of illiteracy, ignorance and willingness to quit smoking among the villagers was undertaken in a rural area surrounding Doddipatla Village, A.P., India. Out of a total population of 3,550, 272 (7.7%) persons, mostly in the age range of 21–50 years, attended a cancer detection camp. There were 173 (63.6%) females and 99 (36.4%) males, among whom 66 (M53 + F13) were smokers; 36.4% of males and 63% of females were illiterate. Among the illiterates, it was observed that smoking rate was high (56%) and 47.7% were ignorant of health effects of smoking. The attitude of illiterate smokers was encouraging, as 83.6% were willing to quit smoking. Further research is necessary to design health education material for 413.5 million illiterates living in India (1991 Indian Census). A community health worker, trained in the use of mass media coupled with a person‐to‐person approach, may help the smoker to quit smoking. PMID:1506267

Fuzzy 2-partition entropy threshold selection based on Big Bang–Big Crunch Optimization algorithm

Directory of Open Access Journals (Sweden)

Baljit Singh Khehra

2015-03-01

Full Text Available The fuzzy 2-partition entropy approach has been widely used to select threshold value for image segmenting. This approach used two parameterized fuzzy membership functions to form a fuzzy 2-partition of the image. The optimal threshold is selected by searching an optimal combination of parameters of the membership functions such that the entropy of fuzzy 2-partition is maximized. In this paper, a new fuzzy 2-partition entropy thresholding approach based on the technology of the Big Bang–Big Crunch Optimization (BBBCO is proposed. The new proposed thresholding approach is called the BBBCO-based fuzzy 2-partition entropy thresholding algorithm. BBBCO is used to search an optimal combination of parameters of the membership functions for maximizing the entropy of fuzzy 2-partition. BBBCO is inspired by the theory of the evolution of the universe; namely the Big Bang and Big Crunch Theory. The proposed algorithm is tested on a number of standard test images. For comparison, three different algorithms included Genetic Algorithm (GA-based, Biogeography-based Optimization (BBO-based and recursive approaches are also implemented. From experimental results, it is observed that the performance of the proposed algorithm is more effective than GA-based, BBO-based and recursion-based approaches.

Addressing big data issues in Scientific Data Infrastructure

NARCIS (Netherlands)

Demchenko, Y.; Membrey, P.; Grosso, P.; de Laat, C.; Smari, W.W.; Fox, G.C.

2013-01-01

Big Data are becoming a new technology focus both in science and in industry. This paper discusses the challenges that are imposed by Big Data on the modern and future Scientific Data Infrastructure (SDI). The paper discusses a nature and definition of Big Data that include such features as Volume,

A big bang in a little room the quest to create new universes

CERN Document Server

Merali, Zeeya

2017-01-01

What if you could become God, with the ability to build a whole new universe? As startling as it sounds, modern physics suggests that within the next two decades, scientists may be able to perform this seemingly divine feat-to concoct an entirely new baby universe, complete with its own physical laws, star systems, galaxies, and even intelligent life. A Big Bang in a Little Room takes the reader on a journey through the history of cosmology and unravels-particle by particle, theory by theory, and experiment by experiment-the ideas behind this provocative claim made by some of the most respected physicists alive today. Beyond simply explaining the science, A Big Bang in a Little Room also tells the story of the people who have been laboring for more than thirty years to make this seemingly impossible dream a reality. What has driven them to continue on what would seem, at first glance, to be a quixotic quest? This mind-boggling book reveals that we can nurse other worlds in the tiny confines of a lab, raising...

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

Big-Bang-Gate Cosmic Titanic: Why Aren't Physics Journal's Editors Bringing It To The Center of Scientific Attention

Science.gov (United States)

Gentry, Robert

2010-02-01

Until now science's greatest debacle occurred when Copernicus exposed Ptolemaic cosmologists' 1300 hundred year-long fraud that it must be true because observations fit theory so well, while they ignored the untested state of its central assumption of Earth centered planetary motion. With much hubris modern physicists are confident this could never happen again, that the integrity of physics journals editors suffices to guarantee that a challenge to the reigning cosmological theory -- big bang cosmology -- would immediately be brought to the center of scientific attention for analysis and discussion. In fact a decade ago it was reported [MPLA 2619 (1997); arXiv:gr-gc/9806061] that, like Ptolemaic cosmology before it, big bang's central assumption that GR expansion effects cause in-flight expansion had never been tested and, further, that experimental testing of it using GR operation of the GPS showed it to be false. This result proves it is impossible for the 2.73 K CBR to be fireball relic radiation. These results were expanded in CERN reports EXT-2003-021;022, but have been uniformly rejected by physics journals, one of which accepted a paper similar to CERN EXT-2003-022, only to reject it a few days later with the admission not to publish it because of fearing reaction of the worldwide physics community. For update on my PRL submission see http://www.alphacosmos.net. )

About Big Data and its Challenges and Benefits in Manufacturing

OpenAIRE

Bogdan NEDELCU

2013-01-01

The aim of this article is to show the importance of Big Data and its growing influence on companies. It also shows what kind of big data is currently generated and how much big data is estimated to be generated. We can also see how much are the companies willing to invest in big data and how much are they currently gaining from their big data. There are also shown some major influences that big data has over one major segment in the industry (manufacturing) and the challenges that appear.

Big Data Management in US Hospitals: Benefits and Barriers.

Science.gov (United States)

Schaeffer, Chad; Booton, Lawrence; Halleck, Jamey; Studeny, Jana; Coustasse, Alberto

Big data has been considered as an effective tool for reducing health care costs by eliminating adverse events and reducing readmissions to hospitals. The purposes of this study were to examine the emergence of big data in the US health care industry, to evaluate a hospital's ability to effectively use complex information, and to predict the potential benefits that hospitals might realize if they are successful in using big data. The findings of the research suggest that there were a number of benefits expected by hospitals when using big data analytics, including cost savings and business intelligence. By using big data, many hospitals have recognized that there have been challenges, including lack of experience and cost of developing the analytics. Many hospitals will need to invest in the acquiring of adequate personnel with experience in big data analytics and data integration. The findings of this study suggest that the adoption, implementation, and utilization of big data technology will have a profound positive effect among health care providers.

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 ...

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...

[Relevance of big data for molecular diagnostics].

Science.gov (United States)

Bonin-Andresen, M; Smiljanovic, B; Stuhlmüller, B; Sörensen, T; Grützkau, A; Häupl, T

2018-04-01

Big data analysis raises the expectation that computerized algorithms may extract new knowledge from otherwise unmanageable vast data sets. What are the algorithms behind the big data discussion? In principle, high throughput technologies in molecular research already introduced big data and the development and application of analysis tools into the field of rheumatology some 15 years ago. This includes especially omics technologies, such as genomics, transcriptomics and cytomics. Some basic methods of data analysis are provided along with the technology, however, functional analysis and interpretation requires adaptation of existing or development of new software tools. For these steps, structuring and evaluating according to the biological context is extremely important and not only a mathematical problem. This aspect has to be considered much more for molecular big data than for those analyzed in health economy or epidemiology. Molecular data are structured in a first order determined by the applied technology and present quantitative characteristics that follow the principles of their biological nature. These biological dependencies have to be integrated into software solutions, which may require networks of molecular big data of the same or even different technologies in order to achieve cross-technology confirmation. More and more extensive recording of molecular processes also in individual patients are generating personal big data and require new strategies for management in order to develop data-driven individualized interpretation concepts. With this perspective in mind, translation of information derived from molecular big data will also require new specifications for education and professional competence.

Big data in psychology: A framework for research advancement.

Science.gov (United States)

Adjerid, Idris; Kelley, Ken

2018-02-22

The potential for big data to provide value for psychology is significant. However, the pursuit of big data remains an uncertain and risky undertaking for the average psychological researcher. In this article, we address some of this uncertainty by discussing the potential impact of big data on the type of data available for psychological research, addressing the benefits and most significant challenges that emerge from these data, and organizing a variety of research opportunities for psychology. Our article yields two central insights. First, we highlight that big data research efforts are more readily accessible than many researchers realize, particularly with the emergence of open-source research tools, digital platforms, and instrumentation. Second, we argue that opportunities for big data research are diverse and differ both in their fit for varying research goals, as well as in the challenges they bring about. Ultimately, our outlook for researchers in psychology using and benefiting from big data is cautiously optimistic. Although not all big data efforts are suited for all researchers or all areas within psychology, big data research prospects are diverse, expanding, and promising for psychology and related disciplines. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

'Big data' in pharmaceutical science: challenges and opportunities.

Science.gov (United States)

Dossetter, Al G; Ecker, Gerhard; Laverty, Hugh; Overington, John

2014-05-01

Future Medicinal Chemistry invited a selection of experts to express their views on the current impact of big data in drug discovery and design, as well as speculate on future developments in the field. The topics discussed include the challenges of implementing big data technologies, maintaining the quality and privacy of data sets, and how the industry will need to adapt to welcome the big data era. Their enlightening responses provide a snapshot of the many and varied contributions being made by big data to the advancement of pharmaceutical science.

Soft computing in big data processing

CERN Document Server

Park, Seung-Jong; Lee, Jee-Hyong

2014-01-01

Big data is an essential key to build a smart world as a meaning of the streaming, continuous integration of large volume and high velocity data covering from all sources to final destinations. The big data range from data mining, data analysis and decision making, by drawing statistical rules and mathematical patterns through systematical or automatically reasoning. The big data helps serve our life better, clarify our future and deliver greater value. We can discover how to capture and analyze data. Readers will be guided to processing system integrity and implementing intelligent systems. With intelligent systems, we deal with the fundamental data management and visualization challenges in effective management of dynamic and large-scale data, and efficient processing of real-time and spatio-temporal data. Advanced intelligent systems have led to managing the data monitoring, data processing and decision-making in realistic and effective way. Considering a big size of data, variety of data and frequent chan...

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

[Big data and their perspectives in radiation therapy].

Science.gov (United States)

Guihard, Sébastien; Thariat, Juliette; Clavier, Jean-Baptiste

2017-02-01

The concept of big data indicates a change of scale in the use of data and data aggregation into large databases through improved computer technology. One of the current challenges in the creation of big data in the context of radiation therapy is the transformation of routine care items into dark data, i.e. data not yet collected, and the fusion of databases collecting different types of information (dose-volume histograms and toxicity data for example). Processes and infrastructures devoted to big data collection should not impact negatively on the doctor-patient relationship, the general process of care or the quality of the data collected. The use of big data requires a collective effort of physicians, physicists, software manufacturers and health authorities to create, organize and exploit big data in radiotherapy and, beyond, oncology. Big data involve a new culture to build an appropriate infrastructure legally and ethically. Processes and issues are discussed in this article. Copyright © 2016 Société Française du Cancer. Published by Elsevier Masson SAS. All rights reserved.

Current applications of big data in obstetric anesthesiology.

Science.gov (United States)

Klumpner, Thomas T; Bauer, Melissa E; Kheterpal, Sachin

2017-06-01

The narrative review aims to highlight several recently published 'big data' studies pertinent to the field of obstetric anesthesiology. Big data has been used to study rare outcomes, to identify trends within the healthcare system, to identify variations in practice patterns, and to highlight potential inequalities in obstetric anesthesia care. Big data studies have helped define the risk of rare complications of obstetric anesthesia, such as the risk of neuraxial hematoma in thrombocytopenic parturients. Also, large national databases have been used to better understand trends in anesthesia-related adverse events during cesarean delivery as well as outline potential racial/ethnic disparities in obstetric anesthesia care. Finally, real-time analysis of patient data across a number of disparate health information systems through the use of sophisticated clinical decision support and surveillance systems is one promising application of big data technology on the labor and delivery unit. 'Big data' research has important implications for obstetric anesthesia care and warrants continued study. Real-time electronic surveillance is a potentially useful application of big data technology on the labor and delivery unit.

Maritime Content in Indonesian History Education: The Development and Alternative Solution

Directory of Open Access Journals (Sweden)

Wasino Wasino

2017-12-01

Full Text Available For a long time ago, Indonesia was identified as maritime country. The collective memory remembered from several islands in Indonesia shows that Indonesia is a large maritime space. The original name of the country was Nusantara, (called archipelago in English. From historical data in some location, there are some evidences about the glorious of the maritime kingdom in the continent. However, maritime perspective is not to be ‘important issue” in the mind of Indonesian people nowadays. History education makes an important rule at the moment. Indonesian independence needs history education based on political perspective, especially to enhance nationalism. The orientation is continued until the New Order, and it is especially focused on the rule of Indonesia military. Reformation since 1998 should make democratization in Indonesian history teaching, but the reality, the tradition of writer in history education, was still stagnant. The content of maritime history in Indonesian History Education still become a big problem. This paper aims to analyze the development of the maritime content in Indonesian History education at school and to give the new alternative in teaching history based on maritime content. The alternative curriculum based on local competitiveness in maritime history related with regional and global region, is the best solution for it.

[The right to know: our bodies, our history].

Science.gov (United States)

Arroba, A

1993-01-01

This work attempts to trace the history of attitudes toward women and their bodies from a feminist perspective, arguing that women in history have always been defined in terms of their sexuality, their sex, and their bodies. Women and nature were defined as inferior to men and the culture created by men. This situation existed throughout history, in one form or another in all countries, and formed a central part of the construction of social, political and cultural significance, especially in western countries. The patriarchal era in which we live has existed for 6000 years. Its institutions, created by men, were ruled by men and described in history by men. But much of the art left behind from the prehistoric era attests to a time when nature and the reproduction of life were venerated. The female body figured in all representations of this era as a powerful and miraculous central subject and not as a controlled and marginalized object. Women's bodies continue to be big business and despite some progress, women are still obliged to struggle against sexual discrimination and increasing day to day violence. It is important for women to know this history for the light it sheds on their present situation.

Volume and Value of Big Healthcare Data.

Science.gov (United States)

Dinov, Ivo D

Modern scientific inquiries require significant data-driven evidence and trans-disciplinary expertise to extract valuable information and gain actionable knowledge about natural processes. Effective evidence-based decisions require collection, processing and interpretation of vast amounts of complex data. The Moore's and Kryder's laws of exponential increase of computational power and information storage, respectively, dictate the need rapid trans-disciplinary advances, technological innovation and effective mechanisms for managing and interrogating Big Healthcare Data. In this article, we review important aspects of Big Data analytics and discuss important questions like: What are the challenges and opportunities associated with this biomedical, social, and healthcare data avalanche? Are there innovative statistical computing strategies to represent, model, analyze and interpret Big heterogeneous data? We present the foundation of a new compressive big data analytics (CBDA) framework for representation, modeling and inference of large, complex and heterogeneous datasets. Finally, we consider specific directions likely to impact the process of extracting information from Big healthcare data, translating that information to knowledge, and deriving appropriate actions.

LLNL's Big Science Capabilities Help Spur Over $796 Billion in U.S. Economic Activity Sequencing the Human Genome

Energy Technology Data Exchange (ETDEWEB)

Stewart, Jeffrey S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2015-07-28

LLNL’s successful history of taking on big science projects spans beyond national security and has helped create billions of dollars per year in new economic activity. One example is LLNL’s role in helping sequence the human genome. Over $796 billion in new economic activity in over half a dozen fields has been documented since LLNL successfully completed this Grand Challenge.

Using Big Book to Teach Things in My House

OpenAIRE

Effrien, Intan; Lailatus, Sa’diyah; Nuruliftitah Maja, Neneng

2017-01-01

The purpose of this study to determine students' interest in learning using the big book media. Big book is a big book from the general book. The big book contains simple words and images that match the content of sentences and spelling. From here researchers can know the interest and development of students' knowledge. As well as train researchers to remain crative in developing learning media for students.

Big Data Analytics Methodology in the Financial Industry

Science.gov (United States)

Lawler, James; Joseph, Anthony

2017-01-01

Firms in industry continue to be attracted by the benefits of Big Data Analytics. The benefits of Big Data Analytics projects may not be as evident as frequently indicated in the literature. The authors of the study evaluate factors in a customized methodology that may increase the benefits of Big Data Analytics projects. Evaluating firms in the…

Big data: survey, technologies, opportunities, and challenges.

Science.gov (United States)

Khan, Nawsher; Yaqoob, Ibrar; Hashem, Ibrahim Abaker Targio; Inayat, Zakira; Ali, Waleed Kamaleldin Mahmoud; Alam, Muhammad; Shiraz, Muhammad; Gani, Abdullah

2014-01-01

Big Data has gained much attention from the academia and the IT industry. In the digital and computing world, information is generated and collected at a rate that rapidly exceeds the boundary range. Currently, over 2 billion people worldwide are connected to the Internet, and over 5 billion individuals own mobile phones. By 2020, 50 billion devices are expected to be connected to the Internet. At this point, predicted data production will be 44 times greater than that in 2009. As information is transferred and shared at light speed on optic fiber and wireless networks, the volume of data and the speed of market growth increase. However, the fast growth rate of such large data generates numerous challenges, such as the rapid growth of data, transfer speed, diverse data, and security. Nonetheless, Big Data is still in its infancy stage, and the domain has not been reviewed in general. Hence, this study comprehensively surveys and classifies the various attributes of Big Data, including its nature, definitions, rapid growth rate, volume, management, analysis, and security. This study also proposes a data life cycle that uses the technologies and terminologies of Big Data. Future research directions in this field are determined based on opportunities and several open issues in Big Data domination. These research directions facilitate the exploration of the domain and the development of optimal techniques to address Big Data.

Big Data: Survey, Technologies, Opportunities, and Challenges

Science.gov (United States)

Khan, Nawsher; Yaqoob, Ibrar; Hashem, Ibrahim Abaker Targio; Inayat, Zakira; Mahmoud Ali, Waleed Kamaleldin; Alam, Muhammad; Shiraz, Muhammad; Gani, Abdullah

2014-01-01

Big Data has gained much attention from the academia and the IT industry. In the digital and computing world, information is generated and collected at a rate that rapidly exceeds the boundary range. Currently, over 2 billion people worldwide are connected to the Internet, and over 5 billion individuals own mobile phones. By 2020, 50 billion devices are expected to be connected to the Internet. At this point, predicted data production will be 44 times greater than that in 2009. As information is transferred and shared at light speed on optic fiber and wireless networks, the volume of data and the speed of market growth increase. However, the fast growth rate of such large data generates numerous challenges, such as the rapid growth of data, transfer speed, diverse data, and security. Nonetheless, Big Data is still in its infancy stage, and the domain has not been reviewed in general. Hence, this study comprehensively surveys and classifies the various attributes of Big Data, including its nature, definitions, rapid growth rate, volume, management, analysis, and security. This study also proposes a data life cycle that uses the technologies and terminologies of Big Data. Future research directions in this field are determined based on opportunities and several open issues in Big Data domination. These research directions facilitate the exploration of the domain and the development of optimal techniques to address Big Data. PMID:25136682

Opportunity and Challenges for Migrating Big Data Analytics in Cloud

Science.gov (United States)

Amitkumar Manekar, S.; Pradeepini, G., Dr.

2017-08-01

Big Data Analytics is a big word now days. As per demanding and more scalable process data generation capabilities, data acquisition and storage become a crucial issue. Cloud storage is a majorly usable platform; the technology will become crucial to executives handling data powered by analytics. Now a day’s trend towards “big data-as-a-service” is talked everywhere. On one hand, cloud-based big data analytics exactly tackle in progress issues of scale, speed, and cost. But researchers working to solve security and other real-time problem of big data migration on cloud based platform. This article specially focused on finding possible ways to migrate big data to cloud. Technology which support coherent data migration and possibility of doing big data analytics on cloud platform is demanding in natute for new era of growth. This article also gives information about available technology and techniques for migration of big data in cloud.

Hot big bang or slow freeze?

Science.gov (United States)

Wetterich, C.

2014-09-01

We confront the big bang for the beginning of the universe with an equivalent picture of a slow freeze - a very cold and slowly evolving universe. In the freeze picture the masses of elementary particles increase and the gravitational constant decreases with cosmic time, while the Newtonian attraction remains unchanged. The freeze and big bang pictures both describe the same observations or physical reality. We present a simple ;crossover model; without a big bang singularity. In the infinite past space-time is flat. Our model is compatible with present observations, describing the generation of primordial density fluctuations during inflation as well as the present transition to a dark energy-dominated universe.

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...

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.

Big data analytics in healthcare: promise and potential.

Science.gov (United States)

Raghupathi, Wullianallur; Raghupathi, Viju

2014-01-01

To describe the promise and potential of big data analytics in healthcare. The paper describes the nascent field of big data analytics in healthcare, discusses the benefits, outlines an architectural framework and methodology, describes examples reported in the literature, briefly discusses the challenges, and offers conclusions. The paper provides a broad overview of big data analytics for healthcare researchers and practitioners. Big data analytics in healthcare is evolving into a promising field for providing insight from very large data sets and improving outcomes while reducing costs. Its potential is great; however there remain challenges to overcome.

Data warehousing in the age of big data

CERN Document Server

Krishnan, Krish

2013-01-01

Data Warehousing in the Age of the Big Data will help you and your organization make the most of unstructured data with your existing data warehouse. As Big Data continues to revolutionize how we use data, it doesn't have to create more confusion. Expert author Krish Krishnan helps you make sense of how Big Data fits into the world of data warehousing in clear and concise detail. The book is presented in three distinct parts. Part 1 discusses Big Data, its technologies and use cases from early adopters. Part 2 addresses data warehousing, its shortcomings, and new architecture

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...

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.

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.

Cross-modal selective attention: on the difficulty of ignoring sounds at the locus of visual attention.

Science.gov (United States)

Spence, C; Ranson, J; Driver, J

2000-02-01

In three experiments, we investigated whether the ease with which distracting sounds can be ignored depends on their distance from fixation and from attended visual events. In the first experiment, participants shadowed an auditory stream of words presented behind their heads, while simultaneously fixating visual lip-read information consistent with the relevant auditory stream, or meaningless "chewing" lip movements. An irrelevant auditory stream of words, which participants had to ignore, was presented either from the same side as the fixated visual stream or from the opposite side. Selective shadowing was less accurate in the former condition, implying that distracting sounds are harder to ignore when fixated. Furthermore, the impairment when fixating toward distractor sounds was greater when speaking lips were fixated than when chewing lips were fixated, suggesting that people find it particularly difficult to ignore sounds at locations that are actively attended for visual lipreading rather than merely passively fixated. Experiments 2 and 3 tested whether these results are specific to cross-modal links in speech perception by replacing the visual lip movements with a rapidly changing stream of meaningless visual shapes. The auditory task was again shadowing, but the active visual task was now monitoring for a specific visual shape at one location. A decrement in shadowing was again observed when participants passively fixated toward the irrelevant auditory stream. This decrement was larger when participants performed a difficult active visual task there versus fixating, but not for a less demanding visual task versus fixation. The implications for cross-modal links in spatial attention are discussed.

BLOTS AND ALL: A HISTORY OF THE RORSCHACH INK BLOT TEST IN BRITAIN.

Science.gov (United States)

Hubbard, Katherine; Hegarty, Peter

2016-01-01

Despite the easily recognizable nature of the Rorschach ink blot test very little is known about the history of the test in Britain. We attend to the oft-ignored history of the Rorschach test in Britain and compare it to its history in the US. Prior to the Second World War, Rorschach testing in Britain had attracted advocates and critiques. Afterward, the British Rorschach Forum, a network with a high proportion of women, developed around the Tavistock Institute in London and The Rorschach Newsletter. In 1968, the International Rorschach Congress was held in London but soon after the group became less exclusive, and fell into decline. A comparative account of the Rorschach in Britain demonstrates how different national institutions invested in the 'projective hypothesis' according to the influence of psychoanalysis, the adoption of a nationalized health system, and the social positioning of 'others' throughout the twentieth century. In comparing and contrasting the history of the Rorschach in Britain and the US, we decentralize and particularize the history of North American Psychology. © 2016 Wiley Periodicals, Inc.

Big Data Analytics, Infectious Diseases and Associated Ethical Impacts

OpenAIRE

Garattini, C.; Raffle, J.; Aisyah, D. N.; Sartain, F.; Kozlakidis, Z.

2017-01-01

The exponential accumulation, processing and accrual of big data in healthcare are only possible through an equally rapidly evolving field of big data analytics. The latter offers the capacity to rationalize, understand and use big data to serve many different purposes, from improved services modelling to prediction of treatment outcomes, to greater patient and disease stratification. In the area of infectious diseases, the application of big data analytics has introduced a number of changes ...

Evaluation of Data Management Systems for Geospatial Big Data

OpenAIRE

Amirian, Pouria; Basiri, Anahid; Winstanley, Adam C.

2014-01-01

Big Data encompasses collection, management, processing and analysis of the huge amount of data that varies in types and changes with high frequency. Often data component of Big Data has a positional component as an important part of it in various forms, such as postal address, Internet Protocol (IP) address and geographical location. If the positional components in Big Data extensively used in storage, retrieval, analysis, processing, visualization and knowledge discovery (geospatial Big Dat...

Value Added: History of Physics in a ``Science, Technology, and Society'' General Education Undergraduate Course

Science.gov (United States)

Neuenschwander, Dwight

2016-03-01

In thirty years of teaching a capstone ``Science, Technology, and Society'' course to undergraduate students of all majors, I have found that, upon entering STS, to most of them the Manhattan Project seems about as remote as the Civil War; few can describe the difference between nuclear and large non-nuclear weapons. With similar lack of awareness, many students seem to think the Big Bang was dreamed up by science sorcerers. One might suppose that a basic mental picture of weapons that held entire populations hostage should be part of informed citizenship. One might also suppose that questions about origins, as they are put to nature through evidence-based reasoning, should be integral to a culture's identity. Over the years I have found the history of physics to be an effective tool for bringing such subjects to life for STS students. Upon hearing some of the history behind (for example) nuclear weapons and big bang cosmology, these students can better imagine themselves called upon to help in a Manhattan Project, or see themselves sleuthing about in a forensic science like cosmology. In this talk I share sample student responses to our class discussions on nuclear weapons, and on cosmology. The history of physics is too engaging to be appreciated only by physicists.

What's a Guy To Do?: Contraceptive Responsibility, Confronting Masculinity, and the History of Vasectomy in Canada.

Science.gov (United States)

Shropshire, Sarah

2014-01-01

Despite the growing popularity of vasectomy in recent years, historians have largely ignored the history of the procedure. The current article provides a preliminary examination of voluntary male sterilization in Canada and, in so doing, challenges the gendered paradigm scholars have often applied to the history of contraception. State-sponsored Medicare and late decriminalization of contraception are discussed as factors that slowed widespread adoption of vasectomy in Canada while evolving surgical techniques are highlighted for their role in increasing acceptability of the procedure. The article explores how evolving definitions of hegemonic masculinity have both hindered and encouraged acceptance of vasectomy over time.

West Virginia's big trees: setting the record straight

Science.gov (United States)

Melissa Thomas-Van Gundy; Robert. Whetsell

2016-01-01

People love big trees, people love to find big trees, and people love to find big trees in the place they call home. Having been suspicious for years, my coauthor and historian Rob Whetsell, approached me with a species identification challenge. There are several photographs of giant trees used by many people to illustrate the past forests of West Virginia,...

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...

D-branes in a big bang/big crunch universe: Misner space

International Nuclear Information System (INIS)

Hikida, Yasuaki; Nayak, Rashmi R.; Panigrahi, Kamal L.

2005-01-01

We study D-branes in a two-dimensional lorentzian orbifold R 1,1 /Γ with a discrete boost Γ. This space is known as Misner or Milne space, and includes big crunch/big bang singularity. In this space, there are D0-branes in spiral orbits and D1-branes with or without flux on them. In particular, we observe imaginary parts of partition functions, and interpret them as the rates of open string pair creation for D0-branes and emission of winding closed strings for D1-branes. These phenomena occur due to the time-dependence of the background. Open string 2→2 scattering amplitude on a D1-brane is also computed and found to be less singular than closed string case

D-branes in a big bang/big crunch universe: Misner space

Energy Technology Data Exchange (ETDEWEB)

Hikida, Yasuaki [Theory Group, High Energy Accelerator Research Organization (KEK), Tukuba, Ibaraki 305-0801 (Japan); Nayak, Rashmi R. [Dipartimento di Fisica and INFN, Sezione di Roma 2, ' Tor Vergata' , Rome 00133 (Italy); Panigrahi, Kamal L. [Dipartimento di Fisica and INFN, Sezione di Roma 2, ' Tor Vergata' , Rome 00133 (Italy)

2005-09-01

We study D-branes in a two-dimensional lorentzian orbifold R{sup 1,1}/{gamma} with a discrete boost {gamma}. This space is known as Misner or Milne space, and includes big crunch/big bang singularity. In this space, there are D0-branes in spiral orbits and D1-branes with or without flux on them. In particular, we observe imaginary parts of partition functions, and interpret them as the rates of open string pair creation for D0-branes and emission of winding closed strings for D1-branes. These phenomena occur due to the time-dependence of the background. Open string 2{yields}2 scattering amplitude on a D1-brane is also computed and found to be less singular than closed string case.

Astroinformatics: the big data of the universe

OpenAIRE

Barmby, Pauline

2016-01-01

In astrophysics we like to think that our field was the originator of big data, back when it had to be carried around in big sky charts and books full of tables. These days, it's easier to move astrophysics data around, but we still have a lot of it, and upcoming telescope  facilities will generate even more. I discuss how astrophysicists approach big data in general, and give examples from some Western Physics & Astronomy research projects.  I also give an overview of ho...

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.)

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

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

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 ...

Emerging technology and architecture for big-data analytics

CERN Document Server

Chang, Chip; Yu, Hao

2017-01-01

This book describes the current state of the art in big-data analytics, from a technology and hardware architecture perspective. The presentation is designed to be accessible to a broad audience, with general knowledge of hardware design and some interest in big-data analytics. Coverage includes emerging technology and devices for data-analytics, circuit design for data-analytics, and architecture and algorithms to support data-analytics. Readers will benefit from the realistic context used by the authors, which demonstrates what works, what doesn’t work, and what are the fundamental problems, solutions, upcoming challenges and opportunities. Provides a single-source reference to hardware architectures for big-data analytics; Covers various levels of big-data analytics hardware design abstraction and flow, from device, to circuits and systems; Demonstrates how non-volatile memory (NVM) based hardware platforms can be a viable solution to existing challenges in hardware architecture for big-data analytics.

Big Data, Algorithmic Regulation, and the History of the Cybersyn Project in Chile, 1971–1973

Directory of Open Access Journals (Sweden)

Katharina Loeber

2018-04-01

Full Text Available We are living in a data-driven society. Big Data and the Internet of Things are popular terms. Governments, universities and the private sector make great investments in collecting and storing data and also extracting new knowledge from these data banks. Technological enthusiasm runs throughout political discourses. “Algorithmic regulation” is defined as a form of data-driven governance. Big Data shall offer brand new opportunities in scientific research. At the same time, political criticism of data storage grows because of a lack of privacy protection and the centralization of data in the hands of governments and corporations. Calls for data-driven dynamic regulation have existed in the past. In Chile, cybernetic development led to the creation of Cybersyn, a computer system that was created to manage the socialist economy under the Allende government 1971–1973. My contribution will present this Cybersyn project created by Stafford Beer. Beer proposed the creation of a “liberty machine” in which expert knowledge would be grounded in data-guided policy. The paper will focus on the human–technological complex in society. The first section of the paper will discuss whether the political and social environment can completely change the attempts of algorithmic regulation. I will deal specifically with the development of technological knowledge in Chile, a postcolonial state, and the relationship between citizens and data storage in a socialist state. In a second section, I will examine the question of which measures can lessen the danger of data storage regarding privacy in a democratic society. Lastly, I will discuss how much data-driven governance is required for democracy and political participation. I will present a second case study: digital participatory budgeting (DPB in Brazil.

Toward a manifesto for the 'public understanding of big data'.

Science.gov (United States)

Michael, Mike; Lupton, Deborah

2016-01-01

In this article, we sketch a 'manifesto' for the 'public understanding of big data'. On the one hand, this entails such public understanding of science and public engagement with science and technology-tinged questions as follows: How, when and where are people exposed to, or do they engage with, big data? Who are regarded as big data's trustworthy sources, or credible commentators and critics? What are the mechanisms by which big data systems are opened to public scrutiny? On the other hand, big data generate many challenges for public understanding of science and public engagement with science and technology: How do we address publics that are simultaneously the informant, the informed and the information of big data? What counts as understanding of, or engagement with, big data, when big data themselves are multiplying, fluid and recursive? As part of our manifesto, we propose a range of empirical, conceptual and methodological exhortations. We also provide Appendix 1 that outlines three novel methods for addressing some of the issues raised in the article. © The Author(s) 2015.

What do Big Data do in Global Governance?

DEFF Research Database (Denmark)

Krause Hansen, Hans; Porter, Tony

2017-01-01

Two paradoxes associated with big data are relevant to global governance. First, while promising to increase the capacities of humans in governance, big data also involve an increasingly independent role for algorithms, technical artifacts, the Internet of things, and other objects, which can...... reduce the control of human actors. Second, big data involve new boundary transgressions as data are brought together from multiple sources while also creating new boundary conflicts as powerful actors seek to gain advantage by controlling big data and excluding competitors. These changes are not just...... about new data sources for global decision-makers, but instead signal more profound changes in the character of global governance....

76 FR 7810 - Big Horn County Resource Advisory Committee

Science.gov (United States)

2011-02-11

..., Wyoming 82801. Comments may also be sent via e-mail to [email protected] , with the words Big... DEPARTMENT OF AGRICULTURE Forest Service Big Horn County Resource Advisory Committee AGENCY: Forest Service, USDA. ACTION: Notice of meeting. SUMMARY: The Big Horn County Resource Advisory Committee...

Hot big bang or slow freeze?

Energy Technology Data Exchange (ETDEWEB)

Wetterich, C.

2014-09-07

We confront the big bang for the beginning of the universe with an equivalent picture of a slow freeze — a very cold and slowly evolving universe. In the freeze picture the masses of elementary particles increase and the gravitational constant decreases with cosmic time, while the Newtonian attraction remains unchanged. The freeze and big bang pictures both describe the same observations or physical reality. We present a simple “crossover model” without a big bang singularity. In the infinite past space–time is flat. Our model is compatible with present observations, describing the generation of primordial density fluctuations during inflation as well as the present transition to a dark energy-dominated universe.

Hot big bang or slow freeze?

International Nuclear Information System (INIS)

Wetterich, C.

2014-01-01

We confront the big bang for the beginning of the universe with an equivalent picture of a slow freeze — a very cold and slowly evolving universe. In the freeze picture the masses of elementary particles increase and the gravitational constant decreases with cosmic time, while the Newtonian attraction remains unchanged. The freeze and big bang pictures both describe the same observations or physical reality. We present a simple “crossover model” without a big bang singularity. In the infinite past space–time is flat. Our model is compatible with present observations, describing the generation of primordial density fluctuations during inflation as well as the present transition to a dark energy-dominated universe

Hot big bang or slow freeze?

Directory of Open Access Journals (Sweden)

C. Wetterich

2014-09-01

Full Text Available We confront the big bang for the beginning of the universe with an equivalent picture of a slow freeze — a very cold and slowly evolving universe. In the freeze picture the masses of elementary particles increase and the gravitational constant decreases with cosmic time, while the Newtonian attraction remains unchanged. The freeze and big bang pictures both describe the same observations or physical reality. We present a simple “crossover model” without a big bang singularity. In the infinite past space–time is flat. Our model is compatible with present observations, describing the generation of primordial density fluctuations during inflation as well as the present transition to a dark energy-dominated universe.

Big Data: Survey, Technologies, Opportunities, and Challenges

Directory of Open Access Journals (Sweden)

Nawsher Khan

2014-01-01

Full Text Available Big Data has gained much attention from the academia and the IT industry. In the digital and computing world, information is generated and collected at a rate that rapidly exceeds the boundary range. Currently, over 2 billion people worldwide are connected to the Internet, and over 5 billion individuals own mobile phones. By 2020, 50 billion devices are expected to be connected to the Internet. At this point, predicted data production will be 44 times greater than that in 2009. As information is transferred and shared at light speed on optic fiber and wireless networks, the volume of data and the speed of market growth increase. However, the fast growth rate of such large data generates numerous challenges, such as the rapid growth of data, transfer speed, diverse data, and security. Nonetheless, Big Data is still in its infancy stage, and the domain has not been reviewed in general. Hence, this study comprehensively surveys and classifies the various attributes of Big Data, including its nature, definitions, rapid growth rate, volume, management, analysis, and security. This study also proposes a data life cycle that uses the technologies and terminologies of Big Data. Future research directions in this field are determined based on opportunities and several open issues in Big Data domination. These research directions facilitate the exploration of the domain and the development of optimal techniques to address Big Data.

Pre-big bang cosmology and quantum fluctuations

International Nuclear Information System (INIS)

Ghosh, A.; Pollifrone, G.; Veneziano, G.

2000-01-01

The quantum fluctuations of a homogeneous, isotropic, open pre-big bang model are discussed. By solving exactly the equations for tensor and scalar perturbations we find that particle production is negligible during the perturbative Pre-Big Bang phase

A large neutral fraction of cosmic hydrogen a billion years after the Big Bang.

Science.gov (United States)

Wyithe, J Stuart B; Loeb, Abraham

2004-02-26

The fraction of ionized hydrogen left over from the Big Bang provides evidence for the time of formation of the first stars and quasar black holes in the early Universe; such objects provide the high-energy photons necessary to ionize hydrogen. Spectra of the two most distant known quasars show nearly complete absorption of photons with wavelengths shorter than the Lyman alpha transition of neutral hydrogen, indicating that hydrogen in the intergalactic medium (IGM) had not been completely ionized at a redshift of z approximately 6.3, about one billion years after the Big Bang. Here we show that the IGM surrounding these quasars had a neutral hydrogen fraction of tens of per cent before the quasar activity started, much higher than the previous lower limits of approximately 0.1 per cent. Our results, when combined with the recent inference of a large cumulative optical depth to electron scattering after cosmological recombination therefore suggest the presence of a second peak in the mean ionization history of the Universe.

Competing with the Big Boys - Strategies for Growth for a Startup Company in the Singapore Food Industry

OpenAIRE

Chew, Kee Heng

2010-01-01

Entrepreneurship provides the basis for satisfying of personal goals and possibly profit maximization; Singapore has a good infrastructure in place to facilitate new business setup and other business functions. Being one of the first few industries that have promoted trade and main revenue drivers, the Singapore Food Industry is in its mature state and entrenched with established big-name global, regional and national players with long histories. But because of its ability to innovate, and wi...

Analysis of Big Data Maturity Stage in Hospitality Industry

OpenAIRE

Shabani, Neda; Munir, Arslan; Bose, Avishek

2017-01-01

Big data analytics has an extremely significant impact on many areas in all businesses and industries including hospitality. This study aims to guide information technology (IT) professionals in hospitality on their big data expedition. In particular, the purpose of this study is to identify the maturity stage of the big data in hospitality industry in an objective way so that hotels be able to understand their progress, and realize what it will take to get to the next stage of big data matur...

A Multidisciplinary Perspective of Big Data in Management Research

OpenAIRE

Sheng, Jie; Amankwah-Amoah, J.; Wang, X.

2017-01-01

In recent years, big data has emerged as one of the prominent buzzwords in business and management. In spite of the mounting body of research on big data across the social science disciplines, scholars have offered little synthesis on the current state of knowledge. To take stock of academic research that contributes to the big data revolution, this paper tracks scholarly work's perspectives on big data in the management domain over the past decade. We identify key themes emerging in manageme...

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.

Big Data as Governmentality in International Development

DEFF Research Database (Denmark)

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

2017-01-01

Statistics have long shaped the field of visibility for the governance of development projects. The introduction of big data has altered the field of visibility. Employing Dean's “analytics of government” framework, we analyze two cases—malaria tracking in Kenya and monitoring of food prices...... in Indonesia. Our analysis shows that big data introduces a bias toward particular types of visualizations. What problems are being made visible through big data depends to some degree on how the underlying data is visualized and who is captured in the visualizations. It is also influenced by technical factors...

"My Grandfather Slammed the Door in Winston Churchill's Face!" Using Family History to Provoke Rigorous Enquiry

Science.gov (United States)

Barrett, Paul

2011-01-01

The idea of using "little stories" to illuminate the "big pictures" of the past was creatively explored in "Teaching History 107," which offered teachers a wealth of detailed vignettes with which to kindle young people's interest and illuminate major historical events. Paul Barrett builds on the ideas explored in that…

A Brief Review on Leading Big Data Models

Directory of Open Access Journals (Sweden)

Sugam Sharma

2014-11-01

Full Text Available Today, science is passing through an era of transformation, where the inundation of data, dubbed data deluge is influencing the decision making process. The science is driven by the data and is being termed as data science. In this internet age, the volume of the data has grown up to petabytes, and this large, complex, structured or unstructured, and heterogeneous data in the form of “Big Data” has gained significant attention. The rapid pace of data growth through various disparate sources, especially social media such as Facebook, has seriously challenged the data analytic capabilities of traditional relational databases. The velocity of the expansion of the amount of data gives rise to a complete paradigm shift in how new age data is processed. Confidence in the data engineering of the existing data processing systems is gradually fading whereas the capabilities of the new techniques for capturing, storing, visualizing, and analyzing data are evolving. In this review paper, we discuss some of the modern Big Data models that are leading contributors in the NoSQL era and claim to address Big Data challenges in reliable and efficient ways. Also, we take the potential of Big Data into consideration and try to reshape the original operationaloriented definition of “Big Science” (Furner, 2003 into a new data-driven definition and rephrase it as “The science that deals with Big Data is Big Science.”

75 FR 71069 - Big Horn County Resource Advisory Committee

Science.gov (United States)

2010-11-22

....us , with the words Big Horn County RAC in the subject line. Facsimilies may be sent to 307-674-2668... DEPARTMENT OF AGRICULTURE Forest Service Big Horn County Resource Advisory Committee AGENCY: Forest Service, USDA. ACTION: Notice of meeting. SUMMARY: The Big Horn County Resource Advisory Committee...

76 FR 26240 - Big Horn County Resource Advisory Committee

Science.gov (United States)

2011-05-06

... words Big Horn County RAC in the subject line. Facsimilies may be sent to 307-674-2668. All comments... DEPARTMENT OF AGRICULTURE Forest Service Big Horn County Resource Advisory Committee AGENCY: Forest Service, USDA. ACTION: Notice of meeting. SUMMARY: The Big Horn County Resource Advisory Committee...

The trust game behind the veil of ignorance: A note on gender differences

NARCIS (Netherlands)

Vyrastekova, J.; Onderstal, S.

2008-01-01

We analyze gender differences in the trust game in a "behind the veil of ignorance" design. This method yields strategies that are consistent with actions observed in the classical trust game experiments. We observe that, on average, men and women do not differ in "trust", and that women are

Market Segmentation in (In)Action: Marketing and 'Yet to Be Installed' Role of Big and Social Media Data

OpenAIRE

Pridmore, Jason; Hämäläinen, Lalu Elias

2017-01-01

textabstract(In)Aktive Marktsegmentierung: Marketing und noch zu installierende Rolle von Big- und Social-Media-Data«. Marketing has always been dependent on the input of new forms of consumer data throughout its history, relying on translations of this data into more and more effective means for targeting and engaging consumers. The focus on the digital segmentation of consumers has been subject to differing marketing orientations, beginning with relationship marketing and moving towards exp...

Ignoring the Obvious: Combined Arms and Fire and Maneuver Tactics Prior to World War I

National Research Council Canada - National Science Library

Bruno, Thomas

2002-01-01

The armies that entered WWI ignored many pre-war lessons though WWI armies later developed revolutionary tactical-level advances, scholars claim that this tactical evolution followed an earlier period...

Accelerating Science Impact through Big Data Workflow Management and Supercomputing

Directory of Open Access Journals (Sweden)

De K.

2016-01-01

Full Text Available The Large Hadron Collider (LHC, operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. ATLAS, one of the largest collaborations ever assembled in the the history of science, is at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, the ATLAS experiment is relying on a heterogeneous distributed computational infrastructure. To manage the workflow for all data processing on hundreds of data centers the PanDA (Production and Distributed AnalysisWorkload Management System is used. An ambitious program to expand PanDA to all available computing resources, including opportunistic use of commercial and academic clouds and Leadership Computing Facilities (LCF, is realizing within BigPanDA and megaPanDA projects. These projects are now exploring how PanDA might be used for managing computing jobs that run on supercomputers including OLCF’s Titan and NRC-KI HPC2. The main idea is to reuse, as much as possible, existing components of the PanDA system that are already deployed on the LHC Grid for analysis of physics data. The next generation of PanDA will allow many data-intensive sciences employing a variety of computing platforms to benefit from ATLAS experience and proven tools in highly scalable processing.

Big is a Thing of the Past: Climate Change and Methodology in the History of Ideas.

Science.gov (United States)

Coen, Deborah R

2016-01-01

The climate crisis has raised questions about the proper scale of historical analysis in the Anthropocene. After explaining how this methodological crisis differs from an earlier stand-off between proponents of microhistory and total history, this paper suggests a role for intellectual history in moving us beyond the current debate. What is needed is a history of "scaling"; that is, we need to historicize the process of mediating between different frameworks of measurement, even those that might at first appear incommensurable. Historical examples are explored in which such a process of commensuration has allowed for a pluralism of perceptions of space and time.

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.

Commentary: Epidemiology in the era of big data.

Science.gov (United States)

Mooney, Stephen J; Westreich, Daniel J; El-Sayed, Abdulrahman M

2015-05-01

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 "three V's": 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.

On the perpetuation of ignorance: system dependence, system justification, and the motivated avoidance of sociopolitical information.

Science.gov (United States)

Shepherd, Steven; Kay, Aaron C

2012-02-01

How do people cope when they feel uninformed or unable to understand important social issues, such as the environment, energy concerns, or the economy? Do they seek out information, or do they simply ignore the threatening issue at hand? One would intuitively expect that a lack of knowledge would motivate an increased, unbiased search for information, thereby facilitating participation and engagement in these issues-especially when they are consequential, pressing, and self-relevant. However, there appears to be a discrepancy between the importance/self-relevance of social issues and people's willingness to engage with and learn about them. Leveraging the literature on system justification theory (Jost & Banaji, 1994), the authors hypothesized that, rather than motivating an increased search for information, a lack of knowledge about a specific sociopolitical issue will (a) foster feelings of dependence on the government, which will (b) increase system justification and government trust, which will (c) increase desires to avoid learning about the relevant issue when information is negative or when information valence is unknown. In other words, the authors suggest that ignorance-as a function of the system justifying tendencies it may activate-may, ironically, breed more ignorance. In the contexts of energy, environmental, and economic issues, the authors present 5 studies that (a) provide evidence for this specific psychological chain (i.e., ignorance about an issue → dependence → government trust → avoidance of information about that issue); (b) shed light on the role of threat and motivation in driving the second and third links in this chain; and (c) illustrate the unfortunate consequences of this process for individual action in those contexts that may need it most.

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

Digital humanitarians how big data is changing the face of humanitarian response

CERN Document Server

Meier, Patrick

2015-01-01

The Rise of Digital HumanitariansMapping Haiti LiveSupporting Search And Rescue EffortsPreparing For The Long Haul Launching An SMS Life Line Sending In The Choppers Openstreetmap To The Rescue Post-Disaster Phase The Human Story Doing Battle With Big Data Rise Of Digital Humanitarians This Book And YouThe Rise of Big (Crisis) DataBig (Size) Data Finding Needles In Big (Size) Data Policy, Not Simply Technology Big (False) Data Unpacking Big (False) Data Calling 991 And 999 Big (

Big Data Provenance: Challenges, State of the Art and Opportunities.

Science.gov (United States)

Wang, Jianwu; Crawl, Daniel; Purawat, Shweta; Nguyen, Mai; Altintas, Ilkay

2015-01-01

Ability to track provenance is a key feature of scientific workflows to support data lineage and reproducibility. The challenges that are introduced by the volume, variety and velocity of Big Data, also pose related challenges for provenance and quality of Big Data, defined as veracity. The increasing size and variety of distributed Big Data provenance information bring new technical challenges and opportunities throughout the provenance lifecycle including recording, querying, sharing and utilization. This paper discusses the challenges and opportunities of Big Data provenance related to the veracity of the datasets themselves and the provenance of the analytical processes that analyze these datasets. It also explains our current efforts towards tracking and utilizing Big Data provenance using workflows as a programming model to analyze Big Data.

[Embracing medical innovation in the era of big data].

Science.gov (United States)

You, Suning

2015-01-01

Along with the advent of big data era worldwide, medical field has to place itself in it inevitably. The current article thoroughly introduces the basic knowledge of big data, and points out the coexistence of its advantages and disadvantages. Although the innovations in medical field are struggling, the current medical pattern will be changed fundamentally by big data. The article also shows quick change of relevant analysis in big data era, depicts a good intention of digital medical, and proposes some wise advices to surgeons.

Big Data and Health Economics: Opportunities, Challenges and Risks

Directory of Open Access Journals (Sweden)

Diego Bodas-Sagi

2018-03-01

Full Text Available Big Data offers opportunities in many fields. Healthcare is not an exception. In this paper we summarize the possibilities of Big Data and Big Data technologies to offer useful information to policy makers. In a world with tight public budgets and ageing populations we feel necessary to save costs in any production process. The use of outcomes from Big Data could be in the future a way to improve decisions at a lower cost than today. In addition to list the advantages of properly using data and technologies from Big Data, we also show some challenges and risks that analysts could face. We also present an hypothetical example of the use of administrative records with health information both for diagnoses and patients.

Speaking sociologically with big data: symphonic social science and the future for big data research

OpenAIRE

Halford, Susan; Savage, Mike

2017-01-01

Recent years have seen persistent tension between proponents of big data analytics, using new forms of digital data to make computational and statistical claims about ‘the social’, and many sociologists sceptical about the value of big data, its associated methods and claims to knowledge. We seek to move beyond this, taking inspiration from a mode of argumentation pursued by Putnam (2000), Wilkinson and Pickett (2009) and Piketty (2014) that we label ‘symphonic social science’. This bears bot...

Application and Exploration of Big Data Mining in Clinical Medicine.

Science.gov (United States)

Zhang, Yue; Guo, Shu-Li; Han, Li-Na; Li, Tie-Ling

2016-03-20

To review theories and technologies of big data mining and their application in clinical medicine. Literatures published in English or Chinese regarding theories and technologies of big data mining and the concrete applications of data mining technology in clinical medicine were obtained from PubMed and Chinese Hospital Knowledge Database from 1975 to 2015. Original articles regarding big data mining theory/technology and big data mining's application in the medical field were selected. This review characterized the basic theories and technologies of big data mining including fuzzy theory, rough set theory, cloud theory, Dempster-Shafer theory, artificial neural network, genetic algorithm, inductive learning theory, Bayesian network, decision tree, pattern recognition, high-performance computing, and statistical analysis. The application of big data mining in clinical medicine was analyzed in the fields of disease risk assessment, clinical decision support, prediction of disease development, guidance of rational use of drugs, medical management, and evidence-based medicine. Big data mining has the potential to play an important role in clinical medicine.

Big Data in Public Health: Terminology, Machine Learning, and Privacy.

Science.gov (United States)

Mooney, Stephen J; Pejaver, Vikas

2018-04-01

The digital world is generating data at a staggering and still increasing rate. While these "big data" have unlocked novel opportunities to understand public health, they hold still greater potential for research and practice. This review explores several key issues that have arisen around big data. First, we propose a taxonomy of sources of big data to clarify terminology and identify threads common across some subtypes of big data. Next, we consider common public health research and practice uses for big data, including surveillance, hypothesis-generating research, and causal inference, while exploring the role that machine learning may play in each use. We then consider the ethical implications of the big data revolution with particular emphasis on maintaining appropriate care for privacy in a world in which technology is rapidly changing social norms regarding the need for (and even the meaning of) privacy. Finally, we make suggestions regarding structuring teams and training to succeed in working with big data in research and practice.

A proposed framework of big data readiness in public sectors

Science.gov (United States)

Ali, Raja Haslinda Raja Mohd; Mohamad, Rosli; Sudin, Suhizaz

2016-08-01

Growing interest over big data mainly linked to its great potential to unveil unforeseen pattern or profiles that support organisation's key business decisions. Following private sector moves to embrace big data, the government sector has now getting into the bandwagon. Big data has been considered as one of the potential tools to enhance service delivery of the public sector within its financial resources constraints. Malaysian government, particularly, has considered big data as one of the main national agenda. Regardless of government commitment to promote big data amongst government agencies, degrees of readiness of the government agencies as well as their employees are crucial in ensuring successful deployment of big data. This paper, therefore, proposes a conceptual framework to investigate perceived readiness of big data potentials amongst Malaysian government agencies. Perceived readiness of 28 ministries and their respective employees will be assessed using both qualitative (interview) and quantitative (survey) approaches. The outcome of the study is expected to offer meaningful insight on factors affecting change readiness among public agencies on big data potentials and the expected outcome from greater/lower change readiness among the public sectors.

Big data analytics to improve cardiovascular care: promise and challenges.

Science.gov (United States)

Rumsfeld, John S; Joynt, Karen E; Maddox, Thomas M

2016-06-01

The potential for big data analytics to improve cardiovascular quality of care and patient outcomes is tremendous. However, the application of big data in health care is at a nascent stage, and the evidence to date demonstrating that big data analytics will improve care and outcomes is scant. This Review provides an overview of the data sources and methods that comprise big data analytics, and describes eight areas of application of big data analytics to improve cardiovascular care, including predictive modelling for risk and resource use, population management, drug and medical device safety surveillance, disease and treatment heterogeneity, precision medicine and clinical decision support, quality of care and performance measurement, and public health and research applications. We also delineate the important challenges for big data applications in cardiovascular care, including the need for evidence of effectiveness and safety, the methodological issues such as data quality and validation, and the critical importance of clinical integration and proof of clinical utility. If big data analytics are shown to improve quality of care and patient outcomes, and can be successfully implemented in cardiovascular practice, big data will fulfil its potential as an important component of a learning health-care system.

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.

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)

The Trust Game Behind the Veil of Ignorance : A Note on Gender Differences

NARCIS (Netherlands)

Vyrastekova, J.; Onderstal, A.M.

2005-01-01

We analyse gender differences in the trust game in a "behind the veil of ignorance" design.This method yields strategies that are consistent with actions observed in the classical trust game experiments.We observe that, on averge, men and women do not differ in "trust", and that women are slightly

BIG´s italesættelse af BIG

DEFF Research Database (Denmark)

Brodersen, Anne Mygind; Sørensen, Britta Vilhelmine; Seiding, Mette

2008-01-01

Since Bjarke Ingels established the BIG (Bjarke Ingels Group) architectural firm in 2006, the company has succeeded in making itself heard and in attracting the attention of politicians and the media. BIG did so first and foremost by means of an overall approach to urban development that is both...... close to the political powers that be, and gain their support, but also to attract attention in the public debate. We present the issues this way: How does BIG speak out for itself? How can we explain the way the company makes itself heard, based on an analysis of the big.dk web site, the Clover Block...... by sidestepping the usual democratic process required for local plans. Politicians declared a positive interest in both the building project and a rapid decision process. However, local interest groups felt they were excluded from any influence regarding the proposal and launched a massive resistance campaign...

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

CERN: A big year for LEP

International Nuclear Information System (INIS)