WorldWideScience

Sample records for reference department collection

  1. Pollen reference collection digitization

    NARCIS (Netherlands)

    Ercan, F.E.Z.|info:eu-repo/dai/nl/41250085X; Donders, T.H.|info:eu-repo/dai/nl/290469872; Bijl, P.K.|info:eu-repo/dai/nl/314028110; Wagner, F.|info:eu-repo/dai/nl/173870783

    2016-01-01

    The extensive Utrecht University pollen reference collection holds thousands of pollen samples of many species and genera from all over the world and has been a basis for the widely-used North West European Pollen Flora. These samples are fixed on glass slides for microscopy use, but the aging

  2. Marine Mammal Food Habits Reference Collections

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The National Marine Mammal Laboratory (NMML) Food Habits Reference Collection, containing over 8000 specimens of cephalopod beaks and fish bones and otoliths, is...

  3. Effects of departing individuals on collective behaviors

    Science.gov (United States)

    Nishiyama, Yuta; Okuda, Shoma; Migita, Masao; Murakami, Hisashi; Tomaru, Takenori

    2017-07-01

    Utilizing living organisms' abilities is an effective approach to realize flexible and unconventional computing. One possible bio-inspired computer might be developed from animal collective research by clarifying collective behaviors. Therefore, it is important to reveal how collective animal behaviors emerge. In many studies, individuals departing from the other individualsare generally ignored. Is it not possible that such departing individuals contribute to the organization of such collectives? To investigate the effects of individuals departing from a collective against collective behaviors, we observed and analyzed the behaviors of 40 soldier crabs in four types of experimental arenas. The recorded behaviors demonstrate a temporally changing pattern and the existence of departing individuals. We analyzed the relationship between global activity and cohesion levels and verified the features of departing individuals. The results imply that departing individuals contribute to collective behaviors.

  4. [Developmental Placement.] Collected Research References.

    Science.gov (United States)

    Bjorklund, Gail

    Drawing on information and references in the ERIC system, this literature review describes research related to a child's developmental placement. The issues examined include school entrance age; predictive validity, reliability, and features of Gesell School Readiness Assessment; retention; and the effectiveness of developmental placement. A…

  5. Collections Care: A Basic Reference Shelflist.

    Science.gov (United States)

    de Torres, Amparo R., Ed.

    This is an extensive bibliography of reference sources--i.e., books and articles--that relate to the care and conservation of library, archival, and museum collections. Bibliographies are presented under the following headings: (1) General Information; (2) Basic Collections Care; (3) Architectural Conservation; (4) Collections Management: Law,…

  6. Department of Energy Construction Safety Reference Guide

    Energy Technology Data Exchange (ETDEWEB)

    1993-09-01

    DOE has adopted the Occupational Safety and Health Administration (OSHA) regulations Title 29 Code of Federal Regulations (CFR) 1926 ``Safety and Health Regulations for Construction,`` and related parts of 29 CFR 1910, ``Occupational Safety and Health Standards.`` This nonmandatory reference guide is based on these OSHA regulations and, where appropriate, incorporates additional standards, codes, directives, and work practices that are recognized and accepted by DOE and the construction industry. It covers excavation, scaffolding, electricity, fire, signs/barricades, cranes/hoists/conveyors, hand and power tools, concrete/masonry, stairways/ladders, welding/cutting, motor vehicles/mechanical equipment, demolition, materials, blasting, steel erection, etc.

  7. Douglas Library Reference Department Policies and Procedure Manual.

    Science.gov (United States)

    Meeker, Robert B.

    This manual presents the policies and procedures of the Reference Department of Chicago State University's Douglas Library. General information about the reference department's staffing, functions, and services is given in the first section. In the next nine sections information is provided about the following areas: scope and circulation period…

  8. The numbering of Sarawak Forest Department collections

    NARCIS (Netherlands)

    Ashton, P.S.

    1966-01-01

    Taxonomists working with material collected by the Sarawak Forest Department have often been hard put to decide how to quote numbers. Is the departmental series number preceeded by a letter S, or an F, or would it be best to quote only the collector and the number? I have tried to unravel the

  9. Reach for Reference: Elementary-Middle School Science Reference Collections

    Science.gov (United States)

    Safford, Barbara Ripp

    2005-01-01

    This article presents a brief review of some new school science reference works. Two of the sources are traditional, while one is considered experimental. The two traditional reference works reviewed are "The American Heritage Children's Science Dictionary" for upper elementary grades, and "The American Heritage Student Science Dictionary" for…

  10. Reference as an Access Service: Collaboration between Reference and Interlibrary Loan Departments

    Science.gov (United States)

    Kern, M. Kathleen; Weible, Cherie L.

    2005-01-01

    Academic libraries increasingly rely on Interlibrary Loan (ILL) departments to obtain research materials. This adds to the workload of ILL at a time when many libraries are experiencing budget cuts and dwindling staff. Collaboration between ILL and Reference can assist ILL by providing searching expertise. Collaboration is facilitated by the…

  11. Reference is Dead, Long Live Reference: Electronic Collections in the Digital Age

    Directory of Open Access Journals (Sweden)

    Heather B. Terrell

    2015-12-01

    Full Text Available In a literature survey on how reference collections have changed to accommodate patrons’ web-based information-seeking behaviors, one notes a marked “us vs. them” mentality — a fear that the Internet might render reference irrelevant. These anxieties are oft-noted in articles urging libraries to embrace digital and online reference sources. Why all the ambivalence? Citing existing research and literature, this essay explores myths about the supposed superiority of physical reference collections and how patrons actually use them, potential challenges associated with electronic reference collections and how providing vital e-reference collections benefits the library as well as its patrons.

  12. Taking the Measure: Applying Reference Outputs to Collection Development.

    Science.gov (United States)

    Moore, Carolyn M.; Mielke, Linda

    1986-01-01

    Presents preliminary results of Clearwater Public Library's study of the usefulness of "Output Measures for Public Libraries" as an indicator of reference performance, and the impact of collection development choices on reference output measures. Data on turnover rate, in-library use, reference fill rate, and reference transactions per…

  13. A digital reference collection for aquatic macroinvertebrates of North America

    Science.gov (United States)

    Walters, David; Ford, Morgan A; Zuellig, Robert E.

    2017-01-01

    Aquatic invertebrates are a key component of freshwater ecosystems, and understanding aquatic invertebrate taxonomy is a cornerstone of freshwater science. Physical reference collections of expertly identified voucher specimens are the ‘gold-standard’ used to confirm specimen identifications. However, most biologists lack access to such collections, which themselves tend to be highly regionalized and somewhat limited in terms of taxonomic scope. The North American Aquatic Macroinvertebrate Digital Reference Collection (NAAMDRC; https://sciencebase.usgs.gov/naamdrc) was developed by the US Geological Survey (USGS) to overcome these limitations of physical collections. NAAMDRC provides users with public-domain, high-quality digital photographs to help verify specimen identifications.

  14. A Reference Bibliography: A Basic Collection for an Elementary School.

    Science.gov (United States)

    San Diego County Office of Education, CA.

    This bibliography provides a selective list of books that could be purchased for a basic reference collection in an elementary (kindergarten through grade 6) library media center. The materials are arranged both by type of reference tool and by subject area. Contents include: (1) Almanacs; (2) Dictionaries; (3) Encyclopedias; (4) Customs,…

  15. Reference Collection Development in Academic Libraries: Report of a Survey.

    Science.gov (United States)

    Biggs, Mary; Biggs, Victor

    1987-01-01

    A survey of heads of academic library reference services gathered information on reference collection development. Findings included: (1) selection and weeding frequently are not guided by written policies; (2) empirical studies of use are almost nonexistent; and (3) online availability of sources is an important factor in selection. (20…

  16. 15 CFR 19.16 - When will Commerce entities refer Commerce debts to the Department of Justice?

    Science.gov (United States)

    2010-01-01

    ... 15 Commerce and Foreign Trade 1 2010-01-01 2010-01-01 false When will Commerce entities refer Commerce debts to the Department of Justice? 19.16 Section 19.16 Commerce and Foreign Trade Office of the Secretary of Commerce COMMERCE DEBT COLLECTION Procedures To Collect Commerce Debts § 19.16 When will...

  17. Description of Specimens in the Marine Mammal Osteology Reference Collection

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NMFS Alaska Fisheries Science Center National Marine Mammal Laboratory (NMML) Marine Mammal Osteology Collection consists of approximately 2500 specimens (skulls...

  18. Reference and access innovative practices for archives and special collections

    CERN Document Server

    Theimer, Kate

    2014-01-01

    Reference and Access: Innovative Practices for Archives and Special Collections explores how archives of different sizes and types are increasing their effectiveness in serving the public and meeting internal needs. The book features twelve case studies that demonstrate new ways to interact with users to answer their questions, provide access to materials, support patrons in the research room, and manage reference and access processes. This volume will be useful to those working in archives and special collections as well as other cultural heritage organizations, and provides ideas ranging fro

  19. Managing the twenty-first century reference department challenges and prospects

    CERN Document Server

    Katz, Linda S

    2014-01-01

    Learn the skills needed to update and manage a reference department that efficiently meets the needs of clients today?and tomorrow! Managing the Twenty-First Century Reference Department: Challenges and Prospects provides librarians with the knowledge and skills they need to manage an effective reference service. Full of useful and practical ideas, this book presents successful methods for recruiting and retaining capable reference department staff and management, training new employees and adapting current services to an evolving field. Expert practitioners address the changing role of the r

  20. Dynamics in natural history collections: Decapod Crustaceans in Biological Reference Collections

    OpenAIRE

    Duró, Alícia; Pérez, Félix; Olivas, Francisco J.; Villanueva, Roger; Lombarte, Antoni; Abelló, Pere

    2013-01-01

    One of the main goals of natural history collections is to preserve for a long term the specimens used for describing and naming new species for science. In this sense, the Biological Reference Collections (CBR) at the Institut de Ciències del Mar of the Consejo Superior de Investigaciones Científicas are a key site for the study and research on marine biodiversity since they act as a scientific marine reference facility. The concept of natural history collections is not dead. On the cont...

  1. U.S. Department of Energy Reference Model Program RM1: Experimental Results.

    Energy Technology Data Exchange (ETDEWEB)

    Hill, Craig [Univ. of Minnesota, Minneapolis, MN (United States); Neary, Vincent Sinclair [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Gunawan, Budi [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Guala, Michele [Univ. of Minnesota, Minneapolis, MN (United States); Sotiropoulos, Fotis [Univ. of Minnesota, Minneapolis, MN (United States)

    2017-08-01

    The Reference Model Project (RMP), sponsored by the U.S. Department of Energy’s (DOE) Wind and Water Power Technologies Program within the Office of Energy Efficiency & Renewable Energy (EERE), aims at expediting industry growth and efficiency by providing nonproprietary Reference Models (RM) of MHK technology designs as study objects for opensource research and development (Neary et al. 2014a,b). As part of this program, MHK turbine models were tested in a large open channel facility at the University of Minnesota’s St. Anthony Falls Laboratory (UMN-SAFL). Reference Model 1 (RM1) is a 1:40 geometric scale dual-rotor axial flow horizontal axis device with counter-rotating rotors, each with a rotor diameter dT = 0.5m. Precise blade angular position and torque measurements were synchronized with three acoustic Doppler velocimeters (ADVs) aligned with each rotor and the midpoint for RM1. Flow conditions for each case were controlled such that depth, h = 1m, and volumetric flow rate, Qw = 2.425m3s-1, resulting in a hub height velocity of approximately Uhub = 1.05ms-1 and blade chord length Reynolds numbers of Rec ≈ 3.0x105. Vertical velocity profiles collected in the wake of each device from 1 to 10 rotor diameters are used to estimate the velocity recovery and turbulent characteristics in the wake, as well as the interaction of the counter-rotating rotor wakes. The development of this high resolution laboratory investigation provides a robust dataset that enables assessing turbulence performance models and their ability to accurately predict device performance metrics, including computational fluid dynamics (CFD) models that can be used to predict turbulent inflow environments, reproduce wake velocity deficit, recovery and higher order turbulent statistics, as well as device performance metrics.

  2. U.S. Department of Energy Reference Model Program RM1: Experimental Results

    Energy Technology Data Exchange (ETDEWEB)

    Hill, Craig [Univ. of Minnesota, Minneapolis, MN (United States); Neary, Vincent Sinclair [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Gunawan, Budi [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Guala, Michele [Univ. of Minnesota, Minneapolis, MN (United States); Sotiropoulos, Fotis [Univ. of Minnesota, Minneapolis, MN (United States)

    2014-10-01

    The Reference Model Project (RMP), sponsored by the U.S. Department of Energy’s (DOE) Wind and Water Power Technologies Program within the Office of Energy Efficiency & Renewable Energy (EERE), aims at expediting industry growth and efficiency by providing non-proprietary Reference Models (RM) of MHK technology designs as study objects for open-source research and development (Neary et al. 2014a,b). As part of this program, MHK turbine models were tested in a large open channel facility at the University of Minnesota’s St. Anthony Falls Laboratory (UMN-SAFL). Reference Model 1 (RM2) is a 1:40 geometric scale dual-rotor axial flow horizontal axis device with counter-rotating rotors, each with a rotor diameter dT = 0.5m. Precise blade angular position and torque measurements were synchronized with three acoustic Doppler velocimeters (ADVs) aligned with each rotor and the midpoint for RM1. Flow conditions for each case were controlled such that depth, h = 1m, and volumetric flow rate, Qw = 2.425m3s-1, resulting in a hub height velocity of approximately Uhub = 1.05ms-1 and blade chord length Reynolds numbers of Rec ≈ 3.0x105. Vertical velocity profiles collected in the wake of each device from 1 to 10 rotor diameters are used to estimate the velocity recovery and turbulent characteristics in the wake, as well as the interaction of the counter-rotating rotor wakes. The development of this high resolution laboratory investigation provides a robust dataset that enables assessing turbulence performance models and their ability to accurately predict device performance metrics, including computational fluid dynamics (CFD) models that can be used to predict turbulent inflow environments, reproduce wake velocity deficit, recovery and higher order turbulent statistics, as well as device performance metrics.

  3. An Experiment: Combining Interlibrary Loan with a Science/Engineering Reference Department.

    Science.gov (United States)

    Paradis, Olga

    1998-01-01

    Describes the inclusion of interlibrary loan services in the reference department of the science and engineering library that accounted for a large percentage of the interlibrary loan activity, based on experiences at Baylor University. Staffing, interlibrary loan statistics, and faculty needs are discussed. (LRW)

  4. U.S. Department of Energy Reference Model Program RM2: Experimental Results

    Energy Technology Data Exchange (ETDEWEB)

    Hill, Craig [Univ. of Minnesota, Minneapolis, MN (United States). St. Anthony Falls Laboratory (UMN-SAFL); Neary, Vincent Sinclair [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Gunawan, Budi [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Guala, Michele [Univ. of Minnesota, Minneapolis, MN (United States). St. Anthony Falls Laboratory (UMN-SAFL); Sotiropoulos, Fotis [Univ. of Minnesota, Minneapolis, MN (United States). St. Anthony Falls Laboratory (UMN-SAFL)

    2014-08-01

    The Reference Model Project (RMP), sponsored by the U.S. Department of Energy’s (DOE) Wind and Water Power Technologies Program within the Office of Energy Efficiency & Renewable Energy (EERE), aims at expediting industry growth and efficiency by providing non-proprietary Reference Models (RM) of MHK technology designs as study objects for open-source research and development (Neary et al. 2014a,b). As part of this program, MHK turbine models were tested in a large open channel facility at the University of Minnesota’s St. Anthony Falls Laboratory (UMN - SAFL) . Reference Model 2 (RM2) is a 1:15 geometric scale dual - rotor cross flow vertical axis device with counter - rotating rotors, each with a rotor diameter dT = 0.43m and rotor height, hT = 0.323 m. RM2 is a river turbine designed for a site modeled after a reach in the lower Mississippi River near Baton Rouge, Louisiana (Barone et al. 2014) . Precise blade angular position and torque measurements were synchronized with three acoustic Doppler velocimeters (ADV) aligned with each rotor and the midpoint for RM2 . Flow conditions for each case were controlled such that depth, h = 1m, and volumetric flow rate, Qw = 2. 35m3s-1 , resulting in a hub height velocity of approximately Uhub = 1. 2 ms-1 and blade chord length Reynolds numbers of Rec = 6 .1x104. Vertical velocity profiles collected in the wake of each device from 1 to 10 rotor diameters are used to estimate the velocity recovery and turbulent characteristics in the wake, as well as the interaction of the counter-rotating rotor wakes. The development of this high resolution laboratory investigation provides a robust dataset that enables assessing computational fluid dynamics (CFD) models and their ability to accurately simulate turbulent inflow environments, device performance metrics, and to reproduce wake velocity deficit, recovery and higher order

  5. Collecting Virtual Reference Statistics with an IM Chat-Bot

    Directory of Open Access Journals (Sweden)

    Mason R.K. Hall

    2008-06-01

    Full Text Available A perennial problem in libraries is capturing accurate statistics. This article addresses this problem with the creative use of Web 2.0 tools: Meebo and AOL Instant Messenger. It describes the development and implementation of an instant messaging "stat-bot" that prompts staff to record virtual reference statistics via IM. Step-by-step guidelines and the perl script are provided.

  6. U.S. Department of Energy Commercial Reference Building Models of the National Building Stock

    Energy Technology Data Exchange (ETDEWEB)

    Deru, M.; Field, K.; Studer, D.; Benne, K.; Griffith, B.; Torcellini, P.; Liu, B.; Halverson, M.; Winiarski, D.; Rosenberg, M.; Yazdanian, M.; Huang, J.; Crawley, D.

    2011-02-01

    The U.S. Department of Energy (DOE) Building Technologies Program has set the aggressive goal of producing marketable net-zero energy buildings by 2025. This goal will require collaboration between the DOE laboratories and the building industry. We developed standard or reference energy models for the most common commercial buildings to serve as starting points for energy efficiency research. These models represent fairly realistic buildings and typical construction practices. Fifteen commercial building types and one multifamily residential building were determined by consensus between DOE, the National Renewable Energy Laboratory, Pacific Northwest National Laboratory, and Lawrence Berkeley National Laboratory, and represent approximately two-thirds of the commercial building stock.

  7. 78 FR 57643 - Agency Information Collection Activities: Department of Homeland Security (DHS) Cybersecurity...

    Science.gov (United States)

    2013-09-19

    ... SECURITY Agency Information Collection Activities: Department of Homeland Security (DHS) Cybersecurity Education Office (CEO) National Initiative for Cybersecurity Careers and Studies (NICCS) Cybersecurity Training and Education Catalog (Training Catalog) Collection AGENCY: Cybersecurity Education Office, DHS...

  8. 78 FR 35295 - Agency Information Collection Activities: Department of Homeland Security (DHS) Cybersecurity...

    Science.gov (United States)

    2013-06-12

    ... SECURITY Agency Information Collection Activities: Department of Homeland Security (DHS) Cybersecurity Education Office (CEO) National Initiative for Cybersecurity Careers and Studies (NICCS) Cybersecurity Training and Education Catalog (Training Catalog) Collection AGENCY: Cybersecurity Education Office, DHS...

  9. Demographic status of married females with suicide attempts referred to the emergency department of Sina Hospital in Tabriz-Iran

    Directory of Open Access Journals (Sweden)

    Shiva Salmasi

    2017-01-01

    Full Text Available Objective: According to the definition of World Health Organization (WHO, attempting suicide is an act that a person intentionally and without others’ interference shows an abnormal behavior (such as harming themselves or eating a drug higher than treatment dose and his objective is realizing his expected changes. The purpose of this study was to investigate the demographic characteristics of married women with suicidal attempt and a variety of methods used to suicide among them who referred to the emergency department of Sina hospital in Tabriz. Methods: In a cross-sectional study 472 married female patients with suicide attempt who referred to the emergency department of Sina hospital in Tabriz in 2014 entered the study and relevant information was collected. Obtained information was analyzed using SPSS version 17.0. Results: Findings showed that the most frequent method of suicide was drug use (99.8%. A significant relationship was found between the type of drug used and seasons of the year. The majority of the population (90.5% lived in urban areas and based on statistical analyses, a significant relationship was found between residency and type of drug used. Conclusion: According to the results of this study it can be concluded that drug use is the most frequent method of suicide that is done with a higher frequency in summer. Thus, rational prescription of drugs by physicians can be considered as one of the factors that can prevent suicide.

  10. 15 CFR 19.15 - How will Commerce entities refer Commerce debts to private collection agencies?

    Science.gov (United States)

    2010-01-01

    ... 15 Commerce and Foreign Trade 1 2010-01-01 2010-01-01 false How will Commerce entities refer Commerce debts to private collection agencies? 19.15 Section 19.15 Commerce and Foreign Trade Office of the Secretary of Commerce COMMERCE DEBT COLLECTION Procedures To Collect Commerce Debts § 19.15 How will...

  11. Report of 121 Cases of Bell's Palsy Referred to the Emergency Department

    Directory of Open Access Journals (Sweden)

    Behzad Zohrevandi

    2014-03-01

    Full Text Available Introduction: According to the high incidence of Bell's palsy (IFP and lack of clinical data regarding different aspects of disease, the present study investigated 121 Iranian patients with peripheral facial paralysis referred to the emergency department. Methods: In this retrospective study, all patients with peripheral facial paralysis, referred to the emergency department of Poursina hospital, Rasht, Iran, from August 2012 to August 2013, were enrolled. For all patients with diagnosis of Bell's palsy variables such as age, sex, occupation, clinical symptoms, comorbid disease, grade of paralysis, and the severity of the facial palsy were reviewed and analyzed using STATA version 11.0. Results: A total of 121 patients with peripheral facial paralysis were assessed with a mean age of 47.14±18.45 years (52.9% male. The majority of patients were observed in the summer (37.2% and autumn (33.1% and the recurrence rate was 22.3%. The most common grades of nerve damage were IV and V based on House- Brackman grading scale (47.1%. Also, the most frequent signs and symptoms were ear pain (43.8%, taste disturbance (38.8%, hyperacusis (15.7% and increased tearing (11.6%. There were not significant correlations between the severity of palsy with age (p= 0.08, recurrence rate (p=0.18, season (p=0.9, and comorbid disease including hypertension (p=0.18, diabetes (p=0.29, and hyperlipidemia (p=0.94. The patients with any of following symptoms such as ear pain (p<0.001, taste disturbance (p<0.001, increased tearing (p=0.03, and Hyperacusis (p<0.001 have more severe palsy. Conclusion: There was equal gender and occupational distribution, higher incidence in fourth decade of life, higher incidence in summer and autumn, higher grade of nerve damage (grade V and VI, and higher incidence of ear pain and taste disturbance in patients suffered from IFP. Also, there was significant association between severity of nerve damage and presence of any simultaneous symptoms. 

  12. Getting Started With Electronic Reference Statistics: Case Studies and Best Practices for Collection and Analysis

    Directory of Open Access Journals (Sweden)

    Elaine H. Dean

    2013-10-01

    Full Text Available Collecting reference statistics is an important facet of academic librarianship. Having accurate, shareable data about the services a library provides is key to understanding the needs of users and highlighting the importance of the library within the overall institution. While many libraries collect reference statistics on paper, gathering this data using an electronic statistics system is an efficient and customizable way to track and analyze reference service trends. By detailing Neumann University Library and Harrell Health Sciences Library’s experiences with two different but equally effective systems, this article will explore the complexities of implementing, customizing, and analyzing the data from an electronic reference statistics system. The authors also discuss challenges encountered and offer recommendations and best practices for others wishing to explore electronic reference statistic collection.

  13. Introducing LIR (Lithotheque Ireland, a reference collection of flaked stone tool raw materials from Ireland

    Directory of Open Access Journals (Sweden)

    Killian Driscoll

    2016-09-01

    Full Text Available The LIR (Lithotheque Ireland reference collection of flaked stone tool raw materials from Ireland began in 2013, and is based on the geological prospection from two projects. The first (2013-2015 focused attention primarily on Carboniferous cherts from the northwest of Ireland, collecting 405 samples. The second (2015-2017 is currently collecting samples of the Cretaceous flint primarily from in situ contexts in the northeast of Ireland, but also includes beach surveys of Cretaceous flint from around the island; the first phase of geological prospection in Autumn 2015 collected 239 samples, with the geological prospection continuing in 2016. Therefore, to date the collection contains over 600 hand samples of chert and flint, along with a small number of other materials (siliceous limestone, tuff, mudstone. The physical reference collection is housed at the UCD School of Archaeology, University College Dublin and contains the geological hand samples along with the various thin sections of the samples that are used for petrographic analysis. The physical collection is complemented by an online database that is to be used alongside the physical collection, or can be used as a stand-alone resource. This paper provides an overview of the database’s metadata and the processes of data entry and editing, to serve as a reference point for the database and the fieldwork undertaken to date, and to serve as a template for other researchers undertaking similar work on lithic reference collections.

  14. 120 Cases of Shoulder Dislocation referred to Emergency Department during One Year; a Case Series Study

    Directory of Open Access Journals (Sweden)

    Payman Asadi

    2015-05-01

    Full Text Available Shoulder dislocation is identified as displacement of humerus head from the glenoid cavity of scapula bone, which makes up about 50% of total joint dislocations. Taking into account the importance of the side effects and disabilities caused by this type of dislocation and that it can be prevented, the present study was designed aiming to evaluate the epidemiologic characteristics of the patients with shoulder dislocation. In this retrospective cross-sectional study, all the patients referred to the emergency department (ED with complaint of shoulder dislocation throughout one year were evaluated. Demographic data and characteristics regarding the type of dislocation, presence of accompanying fractures, mechanism of dislocation, history of dislocation and the method of reduction were extracted from the patients’ profiles and recorded in a checklist designed for this purpose. Data were then statistically analyzed using SPSS version 19. Statistics showed that 120 patients with the mean age of 39.3 ± 21.2 years had been admitted to ED of the studied center in one year (79.2% male. The most common type of dislocation was anterior dislocation (95.8% and in the right shoulder (52.5% and the most common cause was falling on open arm (34.2%. Reduction method was non-operative in 93.3% of the cases and surgery in 6.7%. Based on the results of this study, in the studied population, most patients with shoulder dislocation were young men who had an anterior dislocation in their right shoulder because of falling on out stretched hand and treated with close reduction.

  15. Knowledge and Attitude Regarding Organ Donation among Relatives of Patients Referred to the Emergency Department.

    Science.gov (United States)

    Pouraghaei, Mahboob; Tagizadieh, Mohammad; Tagizadieh, Ali; Moharamzadeh, Payman; Esfahanian, Samaneh; Shahsavari Nia, Kavous

    2015-01-01

    Organ donation is one of the surviving procedures, which can increase the life expectancy of end-stage patients. Inappropriate beliefs and attitude of individuals to organ donation, their poor knowledge, and the socio-economic level are one of the most important barriers for organ donation. Therefore, here knowledge and attitude levels among relatives of trauma patients regarding organ donation were evaluated. This cross-sectional study was done on relatives of trauma patients referred to the emergency department of Sina Hospital, Tabriz, Iran, through 2013 to 2014. The questionnaire included parts of demographic data and socio-economic situations as well as status of knowledge and attitude regarding organ donation. A score between 0-7 was belonged to each person based on his/her level of knowledge. Attitude level had a score between 0-12. Chi- square, Fisher, and Mann-Whitney U test were performed to assess the relation between demographic variables and the level of knowledge and attitude. Porgan transplant. The main causes of disagreement among relatives regarding organ donation were dissatisfaction of the donor's relatives (25%) and religious issues (15%). 49 (62.02%) studied people had inappropriate attitude and 27 (34.2%) ones had good knowledge. male gender (OR=5.87; 95%CI: 3.32-8.42; p=0.001) and self-employed job (OR=7.78; 95%CI: 4.64-10.92; p=0.001) are independent factors associated with poor knowledge about organ donation. Self-employed job (OR=3.86; 95%CI: 1.41-6.11; p=0.009) and poor knowledge (OR=15.3; 95%CI: 9.03-21.57; porgan donation. The present study showed that 73.1% of participants agreed with organ donation. The major causes of disagreements were dissatisfaction of other relatives and religious beliefs. 62.0% of the studied people had positive view regarding organ donation and 34.2% of them well informed about. The most important causative factors for poor knowledge in this context were male gender and self-employed occupation. In addition

  16. Ploidy of USDA (United States Department of Agriculture) world pear germplasm collection determined by flow cytometry

    Science.gov (United States)

    Living germplasm collections representing world diversity of pear (Pyrus L.) are maintained by the U.S. Department of Agriculture at the National Clonal Germplasm Repository (NCGR) in Corvallis, Oregon, USA. Flow cytometry was performed on young leaf tissue from 1,284 genebank accessions to assess p...

  17. 75 FR 4411 - Agency Information Collection Activities: Department of the Interior Regional Climate Science...

    Science.gov (United States)

    2010-01-27

    ... currently valid OMB control number. DATES: You must submit comments on or before February 26, 2010... consideration by the NCCWSC. II. Data OMB Control Number: 1028-NEW. This is a new collection. Title: Department... carrying members of the gun clubs who believe in guns and killing. That kind of closed mind is certainly...

  18. Who Shot Ya? How Emergency Departments Can Collect Reliable Police Shooting Data.

    Science.gov (United States)

    Richardson, Joseph B; St Vil, Christopher; Cooper, Carnell

    2016-04-01

    This paper examines an alternative solution for collecting reliable police shooting data. One alternative is the collection of police shooting data from hospital trauma units, specifically hospital-based violence intervention programs. These programs are situated in Level I trauma units in many major cities in USA. While the intent of these programs is to reduce the risk factors associated with trauma recidivism among victims of violent injury, they also collect reliable data on the number of individuals treated for gunshot wounds. While most trauma units do a great job collecting data on mode of injury, many do not collect data on the circumstances surrounding the injury, particularly police-involved shootings. Research protocol on firearm-related injury conducted in emergency departments typically does not allow researchers to interview victims of violent injury who are under arrest. Most victims of nonfatal police-involved shootings are under arrest at the time they are treated by the ED for their injury. Research protocol on victims of violent injury often excludes individuals under arrest; they fall under the exclusion criteria when recruiting potential participants for research on violence. Researchers working in hospital emergency departments are prohibited from recruited individuals under arrests. The trauma staff, particularly ED physicians and nurses, are in a strategic position to collect this kind of data. Thus, this paper examines how trauma units can serve as an alternative in the reliable collection of police shooting data.

  19. Analysis of Patient Visits and Collections After Opening a Satellite Pediatric Emergency Department.

    Science.gov (United States)

    Nichols, Katherine M; Caperell, Kerry; Cross, Keith; Duncan, Scott; Foster, Ben; Liu, Gil; Pritchard, Hank; Southard, Gary; Shinabery, Ben; Sutton, Brad; Kim, In K

    2017-02-04

    Satellite pediatric emergency departments (PEDs) have emerged as a strategy to increase patient capacity. We sought to determine the impact on patient visits, physician fee collections, and value of emergency department (ED) time at the primary PED after opening a nearby satellite PED. We also illustrate the spatial distribution of patient demographics and overlapping catchment areas for the primary and satellite PEDs using geographical information system. A structured, financial retrospective review was conducted. Aggregate patient demographic data and billing data were collected regarding physician fee charges, collections, and patient visits for both PEDs. All ED visits from January 2009 to December 2013 were analyzed. Geographical information system mapping using ArcGIS mapped ED patient visits. Patient visits at the primary PED were 53,050 in 2009 before the satellite PED opened. The primary PED visits increased after opening the satellite PED to 55,932 in 2013. The satellite PED visits increased to 21,590 in 2013. Collections per visit at the primary PED decreased from $105.13 per visit in 2011 to $86.91 per visit in 2013. Total collections at the satellite PED decreased per visit from $155.41 per visit in 2011 to $128.53 per visit in 2013. After opening a nearby satellite PED, patient visits at the primary PED did not substantially decrease, suggesting that there was a previously unrecognized demand for PED services. The collections per ED visit were greater at the satellite ED, likely due to a higher collection rate.

  20. Depart

    African Journals Online (AJOL)

    USER

    2016-05-06

    May 6, 2016 ... Abstract. This study examines the impact of climate change on water resources in some parts of the. Sudano-Sahelian zone of Nigeria. Climatological data of rainfall amount, temperature and evaporation from rivers and lakes in the zone were collected from Nigeria Meteorological. Agency(NIMET),Lagos ...

  1. Evaluation of the University of Minnesota Libraries Reference Department Telephone Information Service. Pilot Study.

    Science.gov (United States)

    King, Geraldine B.; Berry, Rachel

    This pilot study was conducted to evaluate the telephone reference service of a university library. Questions were called in by volunteers to several different divisions of the library to try to determine: (a) factual accuracy of responses, (b) level of interviewing by the staff person, and (c) attitude of the staff person. Results of the study…

  2. Migration to an electronic journal collection in a hospital library: implications for reference service.

    Science.gov (United States)

    Bardyn, Tania P; Young, Caroline S

    2007-01-01

    This article provides a perspective on the migration to an electronic-only journal collection in a hospital library and its effect on reference services, information-seeking, and library use patterns. Bellevue Hospital Center in New York, NY is one of the first major teaching hospitals in the United States to begin a fundamental shift to a current, electronic-only journal collection. This article describes the process and develops a model for use by other hospital libraries, with commentary on the impact on reference services to library users. Key findings are that physicians, residents, and nurses have come to expect electronic journal collections and use the Internet in the hospital library to access electronic journals. Similar to many academic health sciences libraries, the reference desk in a hospital library has become more like a technical support desk. Users who contact the library have questions about access to the library's electronic resources or about searching techniques. In the future, medical reference librarians will continue to assist searchers who cannot find what they are looking for and will assist those who repeatedly get results that do not match their information needs.

  3. The Efficacy of Mew Score in Renal Transplant Recipients Referred to Emergency Department

    Directory of Open Access Journals (Sweden)

    Egemen Kocabas

    2014-03-01

    Full Text Available Aim: The best treatment option in relation to the advantages in survival in chronic renal disease and in life quality is renal transplantation. During or after the renal transplantation some complications may occur depending on technical reasons. In long term, various infections and metabolic disorders can appear as a result of current immunosuppressive treatments. The present study was conducted in order to determine critical conditions in management of renal transplant cases in Emergency Department and to investigate the efficacy of MODIFIED EARLY WARNING (MEW score in determining the morbidity and acute renal failure (ARF in renal transplant cases. Material and Method: 172 renal transplant recipients presenting to Uludag University Medicine Faculty Emergency Department were investigated prospectively. The patients, whose MEW scores were calculated, were evaluated in terms of the diagnoses, hospitalisation reasons, and presence of (ARF attack and the relationship with MEW score was investigated. Results: 22.8% (n:26 of applications matched with sepsis and significant difference was found out in those patients in terms of ARF (p

  4. Evaluation of a fungal collection as certified reference material producer and as a biological resource center

    Directory of Open Access Journals (Sweden)

    Tatiana Forti

    2016-06-01

    Full Text Available Abstract Considering the absence of standards for culture collections and more specifically for biological resource centers in the world, in addition to the absence of certified biological material in Brazil, this study aimed to evaluate a Fungal Collection from Fiocruz, as a producer of certified reference material and as Biological Resource Center (BRC. For this evaluation, a checklist based on the requirements of ABNT ISO GUIA34:2012 correlated with the ABNT NBR ISO/IEC17025:2005, was designed and applied. Complementing the implementation of the checklist, an internal audit was performed. An evaluation of this Collection as a BRC was also conducted following the requirements of the NIT-DICLA-061, the Brazilian internal standard from Inmetro, based on ABNT NBR ISO/IEC 17025:2005, ABNT ISO GUIA 34:2012 and OECD Best Practice Guidelines for BRCs. This was the first time that the NIT DICLA-061 was applied in a culture collection during an internal audit. The assessments enabled the proposal for the adequacy of this Collection to assure the implementation of the management system for their future accreditation by Inmetro as a certified reference material producer as well as its future accreditation as a Biological Resource Center according to the NIT-DICLA-061.

  5. Evaluation of a fungal collection as certified reference material producer and as a biological resource center.

    Science.gov (United States)

    Forti, Tatiana; Souto, Aline da S S; do Nascimento, Carlos Roberto S; Nishikawa, Marilia M; Hubner, Marise T W; Sabagh, Fernanda P; Temporal, Rosane Maria; Rodrigues, Janaína M; da Silva, Manuela

    2016-01-01

    Considering the absence of standards for culture collections and more specifically for biological resource centers in the world, in addition to the absence of certified biological material in Brazil, this study aimed to evaluate a Fungal Collection from Fiocruz, as a producer of certified reference material and as Biological Resource Center (BRC). For this evaluation, a checklist based on the requirements of ABNT ISO GUIA34:2012 correlated with the ABNT NBR ISO/IEC17025:2005, was designed and applied. Complementing the implementation of the checklist, an internal audit was performed. An evaluation of this Collection as a BRC was also conducted following the requirements of the NIT-DICLA-061, the Brazilian internal standard from Inmetro, based on ABNT NBR ISO/IEC 17025:2005, ABNT ISO GUIA 34:2012 and OECD Best Practice Guidelines for BRCs. This was the first time that the NIT DICLA-061 was applied in a culture collection during an internal audit. The assessments enabled the proposal for the adequacy of this Collection to assure the implementation of the management system for their future accreditation by Inmetro as a certified reference material producer as well as its future accreditation as a Biological Resource Center according to the NIT-DICLA-061. Copyright © 2016 Sociedade Brasileira de Microbiologia. Published by Elsevier Editora Ltda. All rights reserved.

  6. A new reference collection of documented human skeletons from Mérida, Yucatan, Mexico.

    Science.gov (United States)

    Chi-Keb, J R; Albertos-González, V M; Ortega-Muñoz, A; Tiesler, V G

    2013-10-01

    This report documents the history and composition of a new reference collection currently composed of 84 identified human skeletons from the modern cemetery of Xoclán in Mérida, Yucatan, Mexico. The skeletal sample is the first of its kind in the Yucatan peninsula, a region with a population short of two million mostly local and non-local Mexican residents and descendants of the ancient Maya. The growing collection is curated at the Facultad de Ciencias Antropológicas (School of Anthropological Sciences) of the Autonomous University of Yucatan. Here we describe recovery procedures, preservation, background information and validation measures of the individuals who make up the collection. Detailed information on the generational pattern, sex, and age distribution, along with socioeconomic context and provenance of the skeletons are provided. The majority of the skeletal series is represented by males and by older individuals of both sexes. Almost all of these individuals come from Mérida's middle and lower socioeconomic sectors and died within the urban city boundaries. Biographic information was collected on each individual at the municipal civil registry and confronted with information of national and municipal censuses (2000 and 2005), to be validated and to be discussed here in terms of the representativeness of the reference series and its potential uses in forensic, anthropological and medical research. Copyright © 2013 Elsevier GmbH. All rights reserved.

  7. Establishment of a taxonomic and molecular reference collection to support the identification of species regulated by the Western Australian Prevention List for Introduced Marine Pests

    DEFF Research Database (Denmark)

    Dias, Joana P.; Fotedar, Seema; Muenoz, Julieta

    2017-01-01

    and industry stakeholders. Recognising that identification of these species requires very specialist expertise which may be in short supply and not readily accessible in a regulatory environment, and the fact that much publicly available data is not verifiable or suitable for regulatory enforcement, the WA...... government commissioned the current project to collate a reference collection of these marine pest specimens. In this work, we thus established collaboration with researchers worldwide in order to source representative specimens of the species listed. Our main objective was to build a reference collection...... Government Department of Fisheries and, where possible, in accessible museums and institutions in Australasia. The reference collection supports the fast and reliable taxonomic and molecular identification of marine pests in WA and constitutes a valuable resource for training of stakeholders with interest...

  8. [Descriptions of treatment in the Hippocratic Collection with special reference to surgery, particularly for urinary stones].

    Science.gov (United States)

    Saitoh, Hiroshi

    2006-03-01

    I analyzed mentions of treatment in the Hippocratic Collection. I examined quantitatively mentions of treatments in the Hippocratic Collection (Roeb edition, Otsuki edition, and Kon edition) to compare preferences for therapy between the Kos and Knidos schools. Treatments, mentioned in 2,687 passages, were medical in 2,319 (86%), and surgical in 368 (14%). These 2,687 descriptions included 1,023 (38%) from the Kos, 1,261 (47%) from the Knidos school, and 403 (15%) from unspecified schools. Of the 2,319 descriptions of medical treatment, 560 (24%) referred to medicines and 466 (20%) to diet, followed by baths, vapor baths, exercise, running, walking, warm applications, and others. The 368 surgical descriptions involved traction and adjustment for treating fractures of bones or dislocation of joints in 166 (45%) and surgery using knife or fire in 202 (55%). Of the latter 202 mentions, 87 (43%) referred to incision with knife, 74 (37%) to cauterization and 73 (37%) to bloodletting. Diet, exercises, running, walks, traction, adjustment and bloodletting were mentioned more frequently by the Kos school than the Knidos school, while medicines, baths, vapor baths (for gynecological diseases) and incision were mentioned more frequently by the Knidos school (chi-squared test, p Hippocratic Collection, while surgical treatments also were emphasized. Hippocrates warned beginning doctors not to used unproven treatments for urinary stone in the introduction to the "Oath", but did not forbid surgical treatments.

  9. Health sciences librarians' reference services during a disaster: more than collection protection.

    Science.gov (United States)

    McKnight, Michelynn

    2006-01-01

    Reliable and timely professional information services are always important, but even more so during a community-wide disaster, like the aftermath of Hurricane Katrina. There are classes and literature on planning for library collection protection in local emergencies, but little about planning for reference and information services. Four accounts from South Louisiana in September of 2005 demonstrate the value of proactive and innovative services based on professional information needs analysis skills. More study of such cases could lead to the development of best practice guidelines for the planning and provision of disaster information services.

  10. Urine Collection in the Emergency Department: What Really Happens in There?

    Directory of Open Access Journals (Sweden)

    Harrison Alter

    2012-12-01

    Full Text Available Introduction: In women with suspected urinary tract infection (UTI, a non-contaminated voidedspecimen is considered important for valid urinalysis and culture results. We assess whethermidstream parted-labia catch (MSPC instructions were provided by nurses, understood, andperformed correctly, according to the patient.Methods: We conducted a cross-sectional survey of English- and Spanish-speaking female patientssubmitting voided urine samples for urinalysis for suspected UTI. The survey was conducted in apublic teaching hospital emergency department (ED from June to December 2010, beginning 2months after development and dissemination of a nursing MSPC instructions protocol. Researchassistants administered the survey within 2 hours of urine collection. Nurses were unaware of thestudy purpose.Results: Of 129 patients approached, 74 (57% consented and were included in the analysis.Median age was 35; 44% were Latino. Regarding instructions from nurses, patients reported thefollowing: 45 (61%; 95% CI 50-72% received any instructions; of whom 37 (82%; 95% CI 71-93%understood them completely. Sixteen (36%; 95% CI 22-51% were instructed to collect midstream;and 7 (16%; 95% CI 6-29% to part the labia. Regardless of receiving or understanding instructions,33 (45%; 95% CI 33-57% reported actually collecting midstream, and 11 (15%, 95% CI 8-25%parting the labia.Conclusion: In this ED, instructions for MSPC urine collection frequently were not given, despite anursing protocol, and patients rarely performed the essential steps. An evidence-based approachto urine testing in the ED that considers urine collection technique, is needed.

  11. Demographic features of pediatric patients with burn injuries referred to the emergency department of Sina hospital in Tabriz, Iran, in 2014

    Directory of Open Access Journals (Sweden)

    Farzad Rahmani

    2017-03-01

    Full Text Available Introduction: The aim of this study was to evaluate the demographic status of children with burn injuries who were referred to the emergency department of the Sina hospital in Tabriz, Iran, in 2014. Methods: Total of 220 pediatric patients with burn injuries, who referred to the emergency department of Sina hospital, were enrolled in this prospective descriptive study. Data such as age, gender, type of injury, location of injury, and severity of burns was collected, and analyzed using SPSS statistical software. Results: Most patients were the first children of their families (61.8%. Two-year-old children had a higher incidence of burn injuries (33.2%. Most of the burns (94.5% occurred at home. The most common cause of injury was hot liquids (74.5%. The position of the burn injuries in most patients was the upper extremities (47.3% and second-degree burn severity was more frequent (70.5%. There were no significant statistical differences between the two genders regarding cause, severity, percentage, and anatomical area of the burn.Conclusion: It is necessary to design effective strategies to reduce the incidence of burn injuries in pediatric patients, so that steps can be taken to reduce burn injuries and their complications.

  12. Advantage of multiple spot urine collections for estimating daily sodium excretion: comparison with two 24-h urine collections as reference.

    Science.gov (United States)

    Uechi, Ken; Asakura, Keiko; Ri, Yui; Masayasu, Shizuko; Sasaki, Satoshi

    2016-02-01

    Several estimation methods for 24-h sodium excretion using spot urine sample have been reported, but accurate estimation at the individual level remains difficult. We aimed to clarify the most accurate method of estimating 24-h sodium excretion with different numbers of available spot urine samples. A total of 370 participants from throughout Japan collected multiple 24-h urine and spot urine samples independently. Participants were allocated randomly into a development and a validation dataset. Two estimation methods were established in the development dataset using the two 24-h sodium excretion samples as reference: the 'simple mean method' estimated by multiplying the sodium-creatinine ratio by predicted 24-h creatinine excretion, whereas the 'regression method' employed linear regression analysis. The accuracy of the two methods was examined by comparing the estimated means and concordance correlation coefficients (CCC) in the validation dataset. Mean sodium excretion by the simple mean method with three spot urine samples was closest to that by 24-h collection (difference: -1.62  mmol/day). CCC with the simple mean method increased with an increased number of spot urine samples at 0.20, 0.31, and 0.42 using one, two, and three samples, respectively. This method with three spot urine samples yielded higher CCC than the regression method (0.40). When only one spot urine sample was available for each study participant, CCC was higher with the regression method (0.36). The simple mean method with three spot urine samples yielded the most accurate estimates of sodium excretion. When only one spot urine sample was available, the regression method was preferable.

  13. Getting to MARS: Working with an Automated Retrieval System in the Special Collections Department at the University of Nevada, Reno

    Science.gov (United States)

    Sundstrand, Jacquelyn K.

    2011-01-01

    The University of Nevada, Reno's Special Collections and University Archives Department moved into a new facility and had to utilize an automated storage and retrieval systems (ASRS) for storage of manuscript and archival collections. Using ASRS bins presented theoretical challenges in planning for the move. This article highlights how well the…

  14. 75 FR 78807 - Agency Information Collection (Notice to Department of Veterans Affairs of Veteran or Beneficiary...

    Science.gov (United States)

    2010-12-16

    ... Incarcerated in Penal Institution) Activity Under OMB Review AGENCY: Veterans Benefits Administration, Department of Veterans Affairs. ACTION: Notice. SUMMARY: In compliance with the Paperwork Reduction Act (PRA... Veterans Affairs of Veteran or Beneficiary Incarcerated in Penal Institution, VA Form 21-4193. OMB Control...

  15. Managing and Collecting Student Accounts and Loans: A Desk Reference for Educational Receivables Stewardship

    Science.gov (United States)

    Glezerman, David R.; DeSantis, Dennis

    2008-01-01

    This handy desk reference will help readers and their institutions develop and maintain a professional environment that will maximize efficiencies and provide the necessary skills to properly manage operations and portfolios while ensuring that students receive fair and equitable service and opportunities. Written for business officers, financial…

  16. Reference gene selection for gene expression analysis of oocytes collected from dairy cattle and buffaloes during winter and summer.

    Directory of Open Access Journals (Sweden)

    Carolina Habermann Macabelli

    Full Text Available Oocytes from dairy cattle and buffaloes have severely compromised developmental competence during summer. While analysis of gene expression is a powerful technique for understanding the factors affecting developmental hindrance in oocytes, analysis by real-time reverse transcription PCR (RT-PCR relies on the correct normalization by reference genes showing stable expression. Furthermore, several studies have found that genes commonly used as reference standards do not behave as expected depending on cell type and experimental design. Hence, it is recommended to evaluate expression stability of candidate reference genes for a specific experimental condition before employing them as internal controls. In acknowledgment of the importance of seasonal effects on oocyte gene expression, the aim of this study was to evaluate the stability of expression levels of ten well-known reference genes (ACTB, GAPDH, GUSB, HIST1H2AG, HPRT1, PPIA, RPL15, SDHA, TBP and YWHAZ using oocytes collected from different categories of dairy cattle and buffaloes during winter and summer. A normalization factor was provided for cattle (RPL15, PPIA and GUSB and buffaloes (YWHAZ, GUSB and GAPDH based on the expression of the three most stable reference genes in each species. Normalization of non-reference target genes by these reference genes was shown to be considerably different from normalization by less stable reference genes, further highlighting the need for careful selection of internal controls. Therefore, due to the high variability of reference genes among experimental groups, we conclude that data normalized by internal controls can be misleading and should be compared to not normalized data or to data normalized by an external control in order to better interpret the biological relevance of gene expression analysis.

  17. Reference Gene Selection for Gene Expression Analysis of Oocytes Collected from Dairy Cattle and Buffaloes during Winter and Summer

    Science.gov (United States)

    Gimenes, Lindsay Unno; de Carvalho, Nelcio Antonio Tonizza; Soares, Júlia Gleyci; Ayres, Henderson; Ferraz, Márcio Leão; Watanabe, Yeda Fumie; Watanabe, Osnir Yoshime; Sangalli, Juliano Rodrigues; Smith, Lawrence Charles; Baruselli, Pietro Sampaio; Meirelles, Flávio Vieira; Chiaratti, Marcos Roberto

    2014-01-01

    Oocytes from dairy cattle and buffaloes have severely compromised developmental competence during summer. While analysis of gene expression is a powerful technique for understanding the factors affecting developmental hindrance in oocytes, analysis by real-time reverse transcription PCR (RT-PCR) relies on the correct normalization by reference genes showing stable expression. Furthermore, several studies have found that genes commonly used as reference standards do not behave as expected depending on cell type and experimental design. Hence, it is recommended to evaluate expression stability of candidate reference genes for a specific experimental condition before employing them as internal controls. In acknowledgment of the importance of seasonal effects on oocyte gene expression, the aim of this study was to evaluate the stability of expression levels of ten well-known reference genes (ACTB, GAPDH, GUSB, HIST1H2AG, HPRT1, PPIA, RPL15, SDHA, TBP and YWHAZ) using oocytes collected from different categories of dairy cattle and buffaloes during winter and summer. A normalization factor was provided for cattle (RPL15, PPIA and GUSB) and buffaloes (YWHAZ, GUSB and GAPDH) based on the expression of the three most stable reference genes in each species. Normalization of non-reference target genes by these reference genes was shown to be considerably different from normalization by less stable reference genes, further highlighting the need for careful selection of internal controls. Therefore, due to the high variability of reference genes among experimental groups, we conclude that data normalized by internal controls can be misleading and should be compared to not normalized data or to data normalized by an external control in order to better interpret the biological relevance of gene expression analysis. PMID:24676354

  18. [History of the human milk collection bank of the Pediatric Department of the Dresden Medical Academy].

    Science.gov (United States)

    Henker, J; Schmidt, B

    1989-11-01

    The Dresden's milk banking depot was established in 1942. Though there has been a correlation between birth rate and milk quantity collected over the last years, this comparison also points out an unsatisfying willingness of our mothers to nurse their babies. Despite the danger of transferring special infections by raw human milk we will not be able to renounce on this food in special indications in the future.

  19. Hybrid Paper/Electronic Archival Collecting, Processing, and Reference: A View from SLAC

    Energy Technology Data Exchange (ETDEWEB)

    Deken, Jean M.; /SLAC

    2008-05-23

    Real-time archiving of mixed paper and digital collections presents challenges not encountered in the primarily paper environment. A few recent examples from the archives of the Stanford Linear Accelerator Center highlight obstacles encountered, and attempted and contemplated solutions.

  20. Definition of key parameters for constructing an online reference micrographs collection of processed animal particles in feed

    Directory of Open Access Journals (Sweden)

    Belinchon Crespo, C.

    2012-01-01

    Full Text Available The European Union Reference Laboratory for the detection of animal proteins in feedingstuffs (EURL-AP has developed an online micrographs collection supporting its network activities within the European Union for the detection of prohibited animal by-products in feed. So far, the only official method for detecting these by-products is light microscopy, which is highly dependent on the skills of a microscopist because it relies on particle recognition. In order to help the microscopist network to achieve high proficiency levels, it was necessary to create an online reference tool based on micrographs and accessible via an Intranet platform. Members of the National Reference Laboratories for animal proteins in feedingstuffs (NRL-AP and the International Association for Feedingstuff Analysis – Section Feedingstuff Microscopy (IAG have access to this micrographs collection. This paper describes how the online collection was created and what conditions had to be taken into account in creating such a tool. It also describes how information are periodically updated and managed within the context of the large amount of information included in each micrograph. The need for a robust back-office system as the foundation for all the research activities in this project is also covered, and the evaluation of the use of the online collection is discussed.

  1. Corpse dismemberment in the material collected by the Department of Forensic Medicine, Cracow, Poland.

    Science.gov (United States)

    Konopka, Tomasz; Strona, Marcin; Bolechała, Filip; Kunz, Jerzy

    2007-01-01

    In this study, we present 23 cases of dismembered bodies examined by the Cracow Department of Forensic Medicine in 1968-2005 period. Presented material includes 17 instances of defensive mutilation, three instances of offensive mutilation and two cases when dismemberment (decapitation) was a direct cause of death. One case is hard to classified, the perpetrator dissected free skin from the all torso. Analysis of all presented cases and other publications concentrating on the problem of dismemberment gave us the possibility to perform some conclusions. Apart from rare cases of necrophilia, the victim of dismemberment is always a victim of homicide. Homicides ending with corpse dismemberment are most commonly committed by a person close to, or at least acquainted with the victim and they are performed at the site of homicide, generally in the place inhabited by the victim, the perpetrator or shared by both. Such instances are generally not planned by the perpetrator and rarely serial in character.

  2. Cost analysis of strategies to reduce blood culture contamination in the emergency department: sterile collection kits and phlebotomy teams.

    Science.gov (United States)

    Self, Wesley H; Talbot, Thomas R; Paul, Barbara R; Collins, Sean P; Ward, Michael J

    2014-08-01

    Blood culture collection practices that reduce contamination, such as sterile blood culture collection kits and phlebotomy teams, increase up-front costs for collecting cultures but may lead to net savings by eliminating downstream costs associated with contamination. The study objective was to compare overall hospital costs associated with 3 collection strategies: usual care, sterile kits, and phlebotomy teams. Cost analysis. This analysis was conducted from the perspective of a hospital leadership team selecting a blood culture collection strategy for an adult emergency department (ED) with 8,000 cultures drawn annually. Total hospital costs associated with 3 strategies were compared: (1) usual care, with nurses collecting cultures without a standardized protocol; (2) sterile kits, with nurses using a dedicated sterile collection kit; and (3) phlebotomy teams, with cultures collected by laboratory-based phlebotomists. In the base case, contamination rates associated with usual care, sterile kits, and phlebotomy teams were assumed to be 4.34%, 1.68%, and 1.10%, respectively. Total hospital costs included costs of collecting cultures and hospitalization costs according to culture results (negative, true positive, and contaminated). Compared with usual care, annual net savings using the sterile kit and phlebotomy team strategies were $483,219 and $288,980, respectively. Both strategies remained less costly than usual care across a broad range of sensitivity analyses. EDs with high blood culture contamination rates should strongly consider evidence-based strategies to reduce contamination. In addition to improving quality, implementing a sterile collection kit or phlebotomy team strategy is likely to result in net cost savings.

  3. Genetic structure, diversity, and allelic richness in composite collection and reference set in chickpea (Cicer arietinum L.

    Directory of Open Access Journals (Sweden)

    Gowda Cholenahalli LL

    2008-10-01

    Full Text Available Abstract Background Plant genetic resources (PGR are the basic raw materials for future genetic progress and an insurance against unforeseen threats to agricultural production. An extensive characterization of PGR provides an opportunity to dissect structure, mine allelic variations, and identify diverse accessions for crop improvement. The Generation Challenge Program http://www.generationcp.org conceptualized the development of "composite collections" and extraction of "reference sets" from these for more efficient tapping of global crop-related genetic resources. In this study, we report the genetic structure, diversity and allelic richness in a composite collection of chickpea using SSR markers, and formation of a reference set of 300 accessions. Results The 48 SSR markers detected 1683 alleles in 2915 accessions, of which, 935 were considered rare, 720 common and 28 most frequent. The alleles per locus ranged from 14 to 67, averaged 35, and the polymorphic information content was from 0.467 to 0.974, averaged 0.854. Marker polymorphism varied between groups of accessions in the composite collection and reference set. A number of group-specific alleles were detected: 104 in Kabuli, 297 in desi, and 69 in wild Cicer; 114 each in Mediterranean and West Asia (WA, 117 in South and South East Asia (SSEA, and 10 in African region accessions. Desi and kabuli shared 436 alleles, while wild Cicer shared 17 and 16 alleles with desi and kabuli, respectively. The accessions from SSEA and WA shared 74 alleles, while those from Mediterranean 38 and 33 alleles with WA and SSEA, respectively. Desi chickpea contained a higher proportion of rare alleles (53% than kabuli (46%, while wild Cicer accessions were devoid of rare alleles. A genotype-based reference set captured 1315 (78% of the 1683 composite collection alleles of which 463 were rare, 826 common, and 26 the most frequent alleles. The neighbour-joining tree diagram of this reference set represents

  4. Incidence of respiratory syncytial virus infection in infants and young children referred to the emergency departments for lower respiratory tract diseases in Italy.

    Science.gov (United States)

    Medici, Maria Cristina; Arcangeletti, Maria Cristina; Merolla, Rocco; Chezzi, Carlo

    2004-04-01

    Respiratory Syncytial Virus (RSV) is the leading cause of emergency visits and hospitalization for acute lower respiratory tract infections (LRTI) in infants and young children worldwide. To collect specific epidemiological data on the incidence of RSV infection among infants referred to Emergency Departments (ED) for LRTI in a Mediterranean country, an Italian multicenter epidemiological surveillance program was established. Eight pediatric centers throughout Italy participated in this study. The study population included 272 children 2 years of age. Data regarding medical history and physical examination were recorded for each child, whereas an immunoenzymatic RSV test (TestPack RSV, Abbott) was performed on nasal and pharyngeal secretions. Out of 272 tested children, 85 were positive for RSV. The peak of the RSV epidemic occurred in February, with an earlier start and end of the RSV season in the northern and central regions, compared to the southern regions. Major risk factors for RSV infection were younger age (p 2 years of age. RSV positivity was associated with a higher rate of hospitalization in the whole study population (p<0.01) and especially in the children < or =12 months of age (p<0.01). Clinical evidence of lower respiratory tract involvement, was also more frequently observed in RSV positive than in RSV negative children, both in the whole study population (p<0.01) and in the < or =12 months of age subgroup (p<0.01). These data confirm that the patterns of RSV infection in Italy are similar to those reported for other countries in the northern hemisphere: RSV is associated with a higher risk of hospitalization and clinically evident LRTI involvement than respiratory infections of other etiologies, especially in infants.

  5. Current European data collection on emergency department presentations with acute recreational drug toxicity: gaps and national variations.

    Science.gov (United States)

    Heyerdahl, Fridtjof; Hovda, Knut Erik; Giraudon, Isabelle; Yates, Christopher; Dines, Alison M; Sedefov, Roumen; Wood, David M; Dargan, Paul I

    2014-12-01

    The number of new (novel) psychoactive substances (NPS) available in the illegal market is increasing; however, current monitoring of the drug situation in Europe focuses mainly on classical drugs of abuse, with limited emphasis on clinical presentation in the emergency department (ED). The European Drug Emergencies Network (Euro-DEN) is a European Commission-funded project that aims to improve the knowledge of acute drug toxicity of both classical recreational drugs and NPS. As a baseline for this project, we performed a study to establish which data are currently being collected and reported in Europe on ED presentations with acute toxicity related to NPS and classical drugs of abuse. We used a three-pronged approach to identify any systematic collection of data on NPS toxicity in Europe by i) performing a literature search, ii) utilising an online survey of the European Monitoring Centre for Drugs and Drug Addiction Re seau Europe en d'Information sur les Drogues et les Toxicomanies national focal points and iii) exploiting the knowledge and resources of the Euro-DEN network members. The literature search revealed 21 papers appropriate for assessment, but only one described a systematic collection of clinical data on NPS. Twenty-seven of thirty countries responded to the online survey. More than half of all the countries (52%) did not perform any registration at all of such data, 37% collected systematic clinical data on NPS at a national level, while 44% collected data on classical drugs. A few examples for good practice of systematic collection of clinical data on ED presentations due to acute toxicity were identified. The systematic collection of data on ED presentation of toxicity related to NPS and classical drugs in Europe is scarce; the existing collection is limited to single centres, single countries, groups of patients or not focused on novel drugs; the collection of data is highly variable between the different countries. Euro-DEN, a European

  6. Handbook of College Teaching. Theory and Applications. The Greenwood Educators' Reference Collection.

    Science.gov (United States)

    Prichard, Keith W., Ed.; Sawyer, R. McLaran, Ed.

    This collection of 34 essays focuses on the practical application of theory within the domain of college classroom teaching, dealing primarily with undergraduate teaching at two- and four-year institutions. Part 1 examines the psychological foundations of teaching and learning, with chapters on cognition, student motivation, student and faculty…

  7. 12 CFR 233.1 - Authority, purpose, collection of information, and incorporation by reference.

    Science.gov (United States)

    2010-01-01

    ... (CONTINUED) BOARD OF GOVERNORS OF THE FEDERAL RESERVE SYSTEM PROHIBITION ON FUNDING OF UNLAWFUL INTERNET GAMBLING (REGULATION GG) § 233.1 Authority, purpose, collection of information, and incorporation by... Unlawful Internet Gambling Enforcement Act of 2006 (Act) (enacted as Title VIII of the Security and...

  8. Homicides with corpse dismemberment in the material collected by the Department of Forensic Medicine, Krakow, Poland

    Directory of Open Access Journals (Sweden)

    Tomasz Konopka

    2017-06-01

    Full Text Available Aim of the study : To determine the circumstances which can be useful for offenders profiling in homicide cases with victim’s body dismemberment. Material and methods: Study of all homicide cases with victim’s corpse dismemberment examined in Krakow Department of Forensic Medicine over the last 50 years. Results : Within the past 50 years, a total number of 30 cases of homicides with dismembered bodies were examined in Krakow. 22 cases represent defensive mutilations performed by offender, 3 cases can be classified as offensive muti­lations and 3 cases represent aggressive mutilations – decapitation as a method of committing homicide. In this period the only 1 case of necrophilic mutilations was examined, when the body was dismembered without murder. In most cases the background of homicide was the family conflict, 6 was cause of mental illness of perpetrator and in 3 was sexual motive. Only in 3 cases (from 25 when the offender was known perpetrator kill a stranger. In the other the offender belonged to the family or friends of the victim. In all cases where the perpetrator was determined, homicide and dismemberment was performed in his place of residence. The findings of the Police investigations indicate that in most cases homicides were not planned, occurred under the influence of emotion, only two have been previously scheduled. Conclusions : Homicides with corpses dismemberment usually are committed by offenders who is in close relationship with victim (family or friend. Dismemberment is almost always performed in the same place as murder – home of perpetrator. This type of homicide usually is not planned.

  9. Psychiatric Disorders and Personality Profiles of Middle-Aged Suicide Attempters with no Evidence of Specific Psychopathological Profiles Referring to an Emergency Department

    Directory of Open Access Journals (Sweden)

    Serge Brand

    2017-10-01

    Full Text Available Objective: The aim of the present study was to assess socio-demographic and psychiatric characteristics of 40-65 years old suicide attempters referred to an emergency department within four hours of making their attempt.Method: We assessed a total of 93 suicide attempters (Mage=46.59 years referred to an emergency department. Patients completed questionnaires covering socio-demographic data, personality traits, mood, and impulsivity; experts rated patients’ psychiatric status.Results: Experts rated 85 (92.4% of the suicide attempters as having a psychiatric disorder. Based on self-ratings and compared to normative data, 42 (46.6% were psychopathologically ill. Suicide attempts were not related to impulsive personality traits, mood disorders, socio-demographic patterns or gender (gender-ratio: 1:1.58;f:m.Conclusions: The pattern of results suggests that further unknown factors were involved in pushing people to attempt suicide.

  10. A suggested syllabus model for a course in developing reading skills with special reference to the ELT Department at Gazi University

    OpenAIRE

    Tikence, Mevlüt

    1991-01-01

    Ankara : The Institute of Economics and Social Sciences of Bilkent Univ., 1991. Thesis (Master's) -- Bilkent University, 1991. Includes bibliographical references leaves 63-64. The focus of this study is the development of a model syllabus for an English for Specific Purposes (ESP) reading course taught to first year students of the Gazi University ELT Department. First, the general background of ESP, problems of the reading course at Gazi and the limitations of the st...

  11. Virtual Interpretation of Earth Web-Interface Tool (VIEW-IT for Collecting Land-Use/Land-Cover Reference Data

    Directory of Open Access Journals (Sweden)

    Matthew L. Clark

    2011-03-01

    Full Text Available Web-based applications that integrate geospatial information, or the geoweb, offer exciting opportunities for remote sensing science. One such application is a Web‑based system for automating the collection of reference data for producing and verifying the accuracy of land-use/land-cover (LULC maps derived from satellite imagery. Here we describe the capabilities and technical components of the Virtual Interpretation of Earth Web-Interface Tool (VIEW-IT, a collaborative browser-based tool for “crowdsourcing” interpretation of reference data from high resolution imagery. The principal component of VIEW-IT is the Google Earth plug-in, which allows users to visually estimate percent cover of seven basic LULC classes within a sample grid. The current system provides a 250 m square sample to match the resolution of MODIS satellite data, although other scales could be easily accommodated. Using VIEW-IT, a team of 23 student and 7 expert interpreters collected over 46,000 reference samples across Latin America and the Caribbean. Samples covered all biomes, avoided spatial autocorrelation, and spanned years 2000 to 2010. By embedding Google Earth within a Web-based application with an intuitive user interface, basic interpretation criteria, distributed Internet access, server-side storage, and automated error-checking, VIEW-IT provides a time and cost efficient means of collecting a large dataset of samples across space and time. When matched with predictor variables from satellite imagery, these data can provide robust mapping algorithm calibration and accuracy assessment. This development is particularly important for regional to global scale LULC mapping efforts, which have traditionally relied on sparse sampling of medium resolution imagery and products for reference data. Our ultimate goal is to make VIEW-IT available to all users to promote rigorous, global land-change monitoring.

  12. A Case of Plasmodium Falciparum Malaria in a 28-Year-Old Man Referred to the Emergency Department

    Directory of Open Access Journals (Sweden)

    Farhad Heidari

    2015-02-01

    Full Text Available Malaria is a parasite disease associated with fever and about half of the world population is at risk. According to the reports of World Organization Center (WHO, about 207 million cases of clinical manifestation of malaria happened in 2012, which followed with 627,000 deaths. Considering to presence of malaria-endemic areas in Iran, several efforts have been performed recently to control and eradication of malaria in terms of country programs. Despite of reducing the incidence rate, few cases of malaria have been reported yet. Therefore, the present report was done with the aim of remembering the model of referring, clinical signs, as well as diagnostic and therapeutic procedures of patients suffered malaria

  13. Development of a Reference Image Collection Library for Histopathology Image Processing, Analysis and Decision Support Systems Research.

    Science.gov (United States)

    Kostopoulos, Spiros; Ravazoula, Panagiota; Asvestas, Pantelis; Kalatzis, Ioannis; Xenogiannopoulos, George; Cavouras, Dionisis; Glotsos, Dimitris

    2017-06-01

    Histopathology image processing, analysis and computer-aided diagnosis have been shown as effective assisting tools towards reliable and intra-/inter-observer invariant decisions in traditional pathology. Especially for cancer patients, decisions need to be as accurate as possible in order to increase the probability of optimal treatment planning. In this study, we propose a new image collection library (HICL-Histology Image Collection Library) comprising 3831 histological images of three different diseases, for fostering research in histopathology image processing, analysis and computer-aided diagnosis. Raw data comprised 93, 116 and 55 cases of brain, breast and laryngeal cancer respectively collected from the archives of the University Hospital of Patras, Greece. The 3831 images were generated from the most representative regions of the pathology, specified by an experienced histopathologist. The HICL Image Collection is free for access under an academic license at http://medisp.bme.teiath.gr/hicl/ . Potential exploitations of the proposed library may span over a board spectrum, such as in image processing to improve visualization, in segmentation for nuclei detection, in decision support systems for second opinion consultations, in statistical analysis for investigation of potential correlations between clinical annotations and imaging findings and, generally, in fostering research on histopathology image processing and analysis. To the best of our knowledge, the HICL constitutes the first attempt towards creation of a reference image collection library in the field of traditional histopathology, publicly and freely available to the scientific community.

  14. Planning, Coordinating, and Managing Off-Site Storage is an Area of Increasing, Professional Responsibility for Special Collections Departments

    Directory of Open Access Journals (Sweden)

    Melissa Goertzen

    2016-03-01

    Full Text Available Objective – To measure the use of off-site storage for special collections materials and to examine how this use impacts core special collections activities. Design – Survey questionnaire containing both structured and open ended questions. Follow-up interviews were also conducted. Setting – Association of Research Libraries (ARL member institutions in the United States of America. Subjects – 108 directors of special collections. Methods – Participants were recruited via email; contact information was compiled through professional directories, web searches, and referrals from professionals at ARL member libraries. The survey was sent out on October 31, 2013, and two reminder emails were distributed before it closed three weeks later. The survey was created and distributed using Qualtrics, a research software that supports online data collection and analysis. All results were analyzed using Microsoft Excel and Qualtrics. Main Results – The final response rate was 58% (63 out of 108. The majority (51 participants, or 81% reported use of off-site storage for library collections. Of this group, 91% (47 out of 51 house a variety of special collections in off-site storage. The criteria most frequently utilized to designate these materials to off-site storage are use (87%, size (66%, format (60%, and value (57%. The authors found that special collections directors are most likely to send materials to off-site storage facilities that are established and in use by other departments at their home institution; access to established workflows, especially those linked to transit and delivery, and space for expanding collections are benefits. In regard to core special collections activities, results indicated that public service was most impacted by off-site storage. The authors discussed challenges related to patron use and satisfaction. In regard to management and processing, directors faced challenges using the same level of staff to maintain

  15. The private library of Baron F. R. Steinheil in the holdings of the Department of Librarian Gatherings and Historical Collections: composition and significance

    Directory of Open Access Journals (Sweden)

    Hurzhii I.

    2014-01-01

    Full Text Available The object of research in the article is the description of Baron F. R. Steinheil private library, which is deposited in the holdings of the V. Vernadsky National Library of Ukraine Department of Librarian Gatherings and Historical Collections. In the article we have defi ned the degree of the issue study. The biographical data represents F. R. Steinheil as a public person, area studies specialist and ethnologist. In 1896 he founded a Volyn area study museum in the village Horodok, which had a library being its essential part. Thanks to the archival materials and published documents it provided for informational inquiries of the local enthusiasts. The Baron’s private library structure was represented by several thematic sections which were: philology, technology, reference, periodicals, natural sciences, geography, philosophy, art, medicine, pedagogics, history, theology, law, statistics, agriculture. The library ceased to exist as a complex unit after 1918. The issue of the Kyiv part of Baron F. R. Steinheil book heritage transportation was within the responsibility of the first Head of the Temporary Committee of the National Library of Ukraine organization, the academician V. I. Vernadsky. In modern times the Baron collection is dispersed, therefore specific books, periodical editions and scientific complement documents revealing is of vital importance.

  16. Prevalence evaluation of ocular injuries of different kinds as zygomatic fractures consequences in patients referring to department of oral and maxillofacial surgery, Shariati Hospital (Oct 2004-Oct 2

    Directory of Open Access Journals (Sweden)

    Mahmood Hashemi H.

    2008-11-01

    Full Text Available "nBackground and Aim: Zygomatic fractures are common among oral and maxillofacial problems and ocular injuries are of great importance, the prevalence of ocular problems following zygomatic fractures in Iran is not clear so we performed this study to evaluate this problem in patients referring to Shariati Hospital. "nMaterials and Methods: In this descriptive, cross-sectional study, we evaluated the patients who referred to department of oral and maxillofacial surgery of Shariati hospital for ocular complains following zygomatic fractures. The evaluation was performed both clinically and historically. "nResults: 115 patients were examined (87 males and 28 females with the mean age of 26 for males and 32 for females. The prevalence of ocular injuries were as follows: subconjunctival ecchymosis: 23.07% for males and 21.05% for females. Displacement of palpebral fissure: 26.5% for males and 27.6% for females. Unequal papillary levels: 18.37% for males and 15.78% for females. Diplopia: 8.9% for males and 10.5% for females. Enophthalmos: 23.1% for males and 25% for females. "nConclusion: It is strongly recommended to refer patients with zygomatic fracture for an ophthalmologic consultation.

  17. [Web-based collection of educational needs in a medicine department. An intranet survey for planning CME corse.

    Science.gov (United States)

    Morbidoni, Laura; Correani, Massimiliano; Candela, Marco

    2017-01-01

    Few evidences about methods to harvest educational needs by health care professionals in internal medicine have been published. In this project the following objectives have been pursued: to express preferences by each health care worker; to evaluate the efficacy of an intranet-based survey in order to structure continuing medical education (CME) planning. We created a form based on 7 questions, exploring the following areas: knowledge, know-how, communication, transversal competencies. This survey, implemented on a google drive platform, was accessible through the Azienda Sanitaria Unica Regione (ASUR) Marche intranet. Each questionnaire was analyzed with Google drive and the results were discussed within Medicine Department Committee. 103/228 health care workers responded to the survey. On the basis of health care workers preferences, financial resources, relevance, untreated topics in the previous 5 years and congruence with ASUR targets, heart failure, malnutrition and non-invasive mechanical ventilation were chosen as main topics for the year 2017 and practical training, internal courses and focus groups were planned. A relevant percentage of health care workers (45%) responded to our online survey and the analysis of the results has been used for planning users-centered educational courses; this approach represents a sure novelty in failure of published experiences about the relationship between collection of needs and CME planning.

  18. Comparing Usage Patterns Recorded between an Electronic Reference and an Electronic Monograph Collection: The Differences in Searches and Full-Text Content Viewings

    Science.gov (United States)

    Lamothe, Alain R.

    2012-01-01

    This paper presents the results from a quantitative and systematic analysis comparing the online usage of an e-reference and an e-monograph collection. A very strong relationship exists between size and usage: the larger the collection, the greater the usage. An equally strong relationship exists between searches and viewings, meaning that the…

  19. EVALUASI PEMANFAATAN JURNAL DALAM DATABASE "EBSCO BIOMEDICAL REFERENCE COLLECTION" DI UNIT PERPUSTAKAAN DAN INFORMATIKA KEDOKTERAN (UPIK FAKULTAS KEDOKTERAN UGM YOGYAKARTA

    Directory of Open Access Journals (Sweden)

    Eka Wardhani S.

    2015-12-01

    Full Text Available Evaluasi terhadap pemanfaatan koleksi sangat diperlukan untuk mengetahui seberapa besar koleksi tersebut diakses dan dimanfaatkan oleh pengguna. Ebsco Biomedical Reference Collection (Ebsco BRC merupakan salah satu database jurnal yang berparadigma akses. Evaluasi pemanfaatan jurnal dalam database Ebsco BRC merupakan penelitian tentang pemanfaatan koleksi perpustakaan yang dilakukan di UPIK (Unit Perpustakaan dan Informatika Kedokteran Fakultas Kedokteran Universitas Gadjah Mada Yogyakarta. Penelitian ini bertujuan untuk mengetahui tingkat keterpakaian dan pemanfaatan jumal oleh sivitas akademika di FK UGM. Evaluasi dilakukan dengan metode deskriptif dengan pendekatan data kuantitatif dan kualitatif. . Instrumen yang digunakan dalam evaluasi adalah kuesioner dan usage statistics report. Hasil Penelitian ini menunjukkan bahwa tingkat keterpakaian jurnal berdasarkan judul yang ada tinggi (97,96%, akan tetapi tingkat pengaksesannya belum dilakukan secara maksimal. Rata-rata pengaksesan jurnal setiap harinya 25%. Dari data usage statistics report dapat diketahui sebanyak 12 judul jumal yang diakses lebih dari 1000 kali yang dinyatakan sebagai jumal yang paling sering diakses oleh pengguna. Saran peneliti berdasarkan hasil penelitian yang diperoleh adalah bahwa kegiatan melanggan koleksi database Ebsco dapat terus dilakukan , akan tetapi UPIK harus berusaha meningkatkan sosialisasi koleksi, aksesibilitas, fasilitas, dan bimbingan bagi pengguna dalam melakukan penelusuran dalam database tersebut agar dapat dimanfaatkan secara maksimal. Kata Kunci: Evaluasi Koleksi, Ebsco

  20. United States Climate Reference Network (USCRN) Raw Observations from Datalogger

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Datalogger files are raw USCRN data. However, instead of being collected via satellite, the raw data are collected from station dataloggers (also referred to as...

  1. Are patients who call a primary care office referred to the emergency department by non-healthcare personnel without the input of a physician?

    Science.gov (United States)

    Hill, Russell; Gest, Albert; Smith, Cynthia; Guardiola, Jose H; Apolinario, Michael; Ha, Joann; Gonzalez, Jose R; Richman, Peter B

    2016-01-01

    Objective. We hypothesized that a significant percentage of patients who are referred to the Emergency Department (ED) after calling their primary care physician's (PCP) office receive such instructions without the input of a physician. Methods. We enrolled a convenience sample of stable adults at an inner-city ED. Patients provided written answers to structured questions regarding PCP contact prior to the ED visit. Continuous data are presented as means ± standard deviation; categorical data as frequency of occurrence. 95% confidence intervals were calculated. Results. The study group of 660 patients had a mean age of 41.7 ± 14.7 years and 72.6% had income below $20,000/year. 472 patients (71.51%; 67.9%-74.8%) indicated that they had a PCP. A total of 155 patients (23.0%; 19.9%-26.4%) called to contact their PCP prior to ED visit. For patients who called their PCP office and were directed by phone to the ED, the referral pattern was observed as follows: 31/98 (31.63%; 23.2%-41.4%) by a non-health care provider without physician input, 11/98 (11.2%; 6.2%-19.1%) by a non-healthcare provider after consultation with a physician, 12/98 (12.3%; 7.7%-20.3%) by a nurse without physician input, and 14/98 (14.3%; 8.6%-22.7%) by a nurse after consultation with physician. An additional 11/98, 11.2%; 6.2-19.1%) only listened to a recorded message and felt the message was directing them to the ED. Conclusion. A relatively small percentage of patients were referred to the ED without the consultation of a physician in our overall population. However, over half of those that contacted their PCP's office felt directed to the ED by non-health care staff.

  2. Comparison of haloperidol and midazolam in restless management of patients referred to the Emergency Department: A double-blinded, randomized clinical trial

    Directory of Open Access Journals (Sweden)

    Mehrdad Esmailian

    2015-01-01

    Full Text Available Background: Restless and violent behaviors are common in Emergency Departments (EDs, which need therapeutic interventions in most of the times. The first-generation anti-psychotic drugs are one of the most applicable therapeutic agents in the management of such patients, but their use has some limitations. Some studies suggest midazolam as an alternative medicine. Therefore, this study was performed with the aim of comparison of the efficacy and safety of haloperidol and midazolam in the restless management of referring patients to EDs. Materials and Methods: The present double-blinded trial was done on patients needed sedation and referred to the ED of Alzahra Hospital, Isfahan, Iran, in 2014. The patients were categorized into two random groups of haloperidol (5 mg and midazolam receivers (2.5 mg for those weighing 50 kg, as intramuscular administration. The time to achieve sedation, need for rescue dose, need to resedation within the first 60 min, and adverse effects of drugs were compared among the groups. Results: Forty-eight patients were entered to the study. The mean age in the haloperidol and midazolam groups was 44.8 ± 4.1 years and 45.5 ± 4.7 years, respectively (P = 0.91. The mean time of sedation in the haloperidol and midazolam groups was 5.6 ± 0.3 min and 5.2 ± 0.1 min, respectively (P = 0.31. The mean time of full consciousness after sedation was 36.2 ± 4.5 min and 38.2 ± 3.4 min in the haloperidol and midazolam groups, respectively (P = 0.72. On average, time to arousal in the midazolam group was 10.33 min more than the haloperidol group, but it was not statistically significant. Conclusion: The results of the present study show that administration of midazolam and haloperidol have similar efficacy in the treatment of restless symptoms with the same recovery time from drug effects for referring patients to the ED. In addition, none of the adverse effects were observed in this study.

  3. Analysis of latent tuberculosis infection treatment adherence among refugees and other patient groups referred to the Baltimore City Health Department TB clinic, February 2009-March 2011.

    Science.gov (United States)

    Nuzzo, Jennifer B; Golub, Jonathan E; Chaulk, Patrick; Shah, Maunank

    2015-02-01

    We sought to determine the proportion of refugee patients at the Baltimore City Health Department Tuberculosis program (BCHD-TB) successfully completing latent tuberculosis infection (LTBI) treatment, as compared to other referral groups, and to identify factors associated with treatment completion. We completed a retrospective cohort analysis of individuals referred to BCHD-TB program for LTBI care between February 1, 2009 and March 31, 2011. Among 841 patients evaluated by BCHD-TB and diagnosed with LTBI, 81% of refugees, 50% of non-refugee foreign-born, and 35% of US-born patients completed LTBI treatment. In multivariate analysis, refugees had greater odds of LTBI treatment completion (Adjusted Odds Ratio 7.2; 95% CI 4.2-12.4, p < 0.001) compared to US-born individuals adjusting for age, gender, and treatment regimen. Overall, LTBI treatment completion remains suboptimal. At BCHD-TB, LTBI treatment completion was significantly higher among refugees than other referral groups. Additional efforts are needed to optimize LTBI care, and future efforts may need to be tailored for different risk groups.

  4. Everything in its place. Social bookmarking and reference manager tools to collect, manage and cite information sources.

    Science.gov (United States)

    Giglia, E

    2010-06-01

    Aim of this contribution was to present some free reference manager software and social bookmarking tools. They help scholars and authors in recording, managing and re-using Web pages, scientific articles and bibliographic citations. Most of them support integration within the commonly used browsers or word processors, in order to easily create or import a full bibliography or a single reference.

  5. 76 FR 1658 - 60-Day Notice of Proposed Information Collection: DS 4053, Department of State Mentor-Protégé...

    Science.gov (United States)

    2011-01-11

    ... . SUPPLEMENTARY INFORMATION: We are soliciting public comments to permit the Department to: Evaluate whether the proposed information collection is necessary for the proper performance of our functions. Evaluate the...-4053. Respondents: Small and large for-profit companies planning to team together in an official mentor...

  6. Are patients who call a primary care office referred to the emergency department by non-healthcare personnel without the input of a physician?

    Directory of Open Access Journals (Sweden)

    Russell Hill

    2016-03-01

    Full Text Available Objective. We hypothesized that a significant percentage of patients who are referred to the Emergency Department (ED after calling their primary care physician’s (PCP office receive such instructions without the input of a physician. Methods. We enrolled a convenience sample of stable adults at an inner-city ED. Patients provided written answers to structured questions regarding PCP contact prior to the ED visit. Continuous data are presented as means ± standard deviation; categorical data as frequency of occurrence. 95% confidence intervals were calculated. Results. The study group of 660 patients had a mean age of 41.7 ± 14.7 years and 72.6% had income below $20,000/year. 472 patients (71.51%; 67.9%–74.8% indicated that they had a PCP. A total of 155 patients (23.0%; 19.9%–26.4% called to contact their PCP prior to ED visit. For patients who called their PCP office and were directed by phone to the ED, the referral pattern was observed as follows: 31/98 (31.63%; 23.2%–41.4% by a non-health care provider without physician input, 11/98 (11.2%; 6.2%–19.1% by a non-healthcare provider after consultation with a physician, 12/98 (12.3%; 7.7%–20.3% by a nurse without physician input, and 14/98 (14.3%; 8.6%–22.7% by a nurse after consultation with physician. An additional 11/98, 11.2%; 6.2–19.1% only listened to a recorded message and felt the message was directing them to the ED. Conclusion. A relatively small percentage of patients were referred to the ED without the consultation of a physician in our overall population. However, over half of those that contacted their PCP’s office felt directed to the ED by non-health care staff.

  7. Standard Reference Tables -

    Data.gov (United States)

    Department of Transportation — The Standard Reference Tables (SRT) provide consistent reference data for the various applications that support Flight Standards Service (AFS) business processes and...

  8. Comparing Linear Relationships between E-Book Usage and University Student and Faculty Populations: The Differences between E-Reference and E-Monograph Collections

    Science.gov (United States)

    Lamothe, Alain R.

    2013-01-01

    This paper reports the results from a quantitative study examining the strength of linear relationships between Laurentian University students and faculty members and the J. N. Desmarais Library's reference and monograph e-book collections. The number of full-text items accessed, searches performed, and undergraduate, graduate, and faculty…

  9. Quality Assurance Plan for Data Collection: Characterizing and Quantifying Local and Regional Particulate Matter Emissions from Department of Defense Installations

    National Research Council Canada - National Science Library

    Gillies, J

    2000-01-01

    ...-post regional visibility effects. This document has been assembled to describe the quality assurance plan for data collection for the different components of the proposed research. Quality control (QC...

  10. Debt Collection Improvement Act of 1996: Department of Agriculture's Farm Service Agency Has Not Yet Fully Implemented Certain Key Provisions

    National Research Council Canada - National Science Library

    2002-01-01

    The administrator of FSA stated in comments on this report that FSA generally agreed with our findings and recommendations but took issue with our portrayal of FSAs efforts to collect delinquent debts...

  11. 78 FR 69171 - 60-Day Notice of Proposed Information Collection: Department of State Mentor Protégé Program...

    Science.gov (United States)

    2013-11-18

    ... assumptions used. Enhance the quality, utility, and clarity of the information to be collected. ] Minimize the... public record. Before including any detailed personal information, you should be aware that your comments as submitted, including your personal information, will be available for public review. Abstract of...

  12. Descriptive study of symptomatic epilepsy by age of onset in patients with a 3-year follow-up at the Neuropaediatric Department of a reference centre.

    Science.gov (United States)

    Ochoa-Gómez, L; López-Pisón, J; Fuertes-Rodrigo, C; Fernando-Martínez, R; Samper-Villagrasa, P; Monge-Galindo, L; Peña-Segura, J L; García-Jiménez, M C

    2017-09-01

    We conducted a descriptive study of symptomatic epilepsy by age at onset in a cohort of patients who were followed up at a neuropaediatric department of a reference hospital over a 3-year period PATIENTS AND METHODS: We included all children with epilepsy who were followed up from January 1, 2008 to December 31, 2010 RESULTS: Of the 4595 children seen during the study period, 605 (13.17%) were diagnosed with epilepsy; 277 (45.79%) of these had symptomatic epilepsy. Symptomatic epilepsy accounted for 67.72% and 61.39% of all epilepsies starting before one year of age, or between the ages of one and 3, respectively. The aetiologies of symptomatic epilepsy in our sample were: prenatal encephalopathies (24.46% of all epileptic patients), perinatal encephalopathies (9.26%), post-natal encephalopathies (3.14%), metabolic and degenerative encephalopathies (1.98%), mesial temporal sclerosis (1.32%), neurocutaneous syndromes (2.64%), vascular malformations (0.17%), cavernomas (0.17%), and intracranial tumours (2.48%). In some aetiologies, seizures begin before the age of one; these include Down syndrome, genetic lissencephaly, congenital cytomegalovirus infection, hypoxic-ischaemic encephalopathy, metabolic encephalopathies, and tuberous sclerosis. The lack of a universally accepted classification of epileptic syndromes makes it difficult to compare series from different studies. We suggest that all epilepsies are symptomatic because they have a cause, whether genetic or acquired. The age of onset may point to specific aetiologies. Classifying epilepsy by aetiology might be a useful approach. We could establish 2 groups: a large group including epileptic syndromes with known aetiologies or associated with genetic syndromes which are very likely to cause epilepsy, and another group including epileptic syndromes with no known cause. Thanks to the advances in neuroimaging and genetics, the latter group is expected to become increasingly smaller. Copyright © 2016 Sociedad Espa

  13. Blood sample tube transporting system versus point of care technology in an emergency department; effect on time from collection to reporting?

    DEFF Research Database (Denmark)

    Nørgaard, Birgitte; Mogensen, Christian Backer

    2012-01-01

    Time is a crucial factor in an emergency department and the effectiveness of diagnosing depends on, among other things, the accessibility of rapid reported laboratory test results; i.e.: a short turnaround time (TAT). Former studies have shown a reduced time to action when point of care technolog......Time is a crucial factor in an emergency department and the effectiveness of diagnosing depends on, among other things, the accessibility of rapid reported laboratory test results; i.e.: a short turnaround time (TAT). Former studies have shown a reduced time to action when point of care...... technologies (POCT) are used in emergency departments. This study assesses the hypothesis, that using Point of Care Technology in analysing blood samples versus tube transporting blood samples for laboratory analyses results in shorter time from the blood sample is collected to the result is reported...

  14. Effect of salt supplementation on the rate of inadequate sweat collection for infants less than 3 months of age referred for the sweat test.

    Science.gov (United States)

    Guglani, Lokesh; Abdulhamid, Ibrahim

    2015-01-01

    Sweat testing in young infants (≤ 3 months) with a positive newborn screen for Cystic Fibrosis (CF) can yield higher rates of inadequate sweat collection. The role of salt supplements in improving sweat collection has not been studied before. All young infants referred to our CF center for sweat testing were randomized to either receive salt supplements {1/8th teaspoon salt (750 mg)} mixed in formula feeds 1 day prior to sweat testing (study group) or no salt supplement (controls). Of the 151 young infants that underwent sweat testing over 18 months, 75 received salt supplements, while 76 did not. A total of 9 (11.8%) infants in the salt supplement group had inadequate sweat collection, as compared to 4 (5.2%) infants in the control group (p = 0.16, Fisher's Exact Test). Oral salt supplementation for young infants prior to sweat testing does not help to reduce the rates of inadequate sweat collection.

  15. Trace Elements, With Special Reference to Mercury, in Fish Collected Upstream and Downstream of Los Alamos National Laboratory

    Energy Technology Data Exchange (ETDEWEB)

    P. R. Fresquez; J. D. Huchton; M. A. Mullen

    1999-11-01

    Trace elements (Ag, As, Ba, Be, Cr, Cd, Cu, Hg, Ni, Pb, Sb, Se, and Tl) were determined in muscle (fillet) of average sized fish (mostly carp, catfish, and sucker) collected from the confluences of major canyons that cross Los Alamos National Laboratory (LANL) lands with the Rio Grande (RG). Also, trace elements were determined in fish from reservoirs upstream (Abiquiu [AR]) and downstream (Cochiti [CR]) of LANL from 1991 through 1999. In general, all of the (mean) trace elements, including Hg, were either at the limits of detection (LOD) or in low concentrations at all study sites. Of the trace elements (e.g., Ba, Cu, and Hg) that were found to be above the LOD in fish muscle collected from LANL canyons/RG, none were in significantly higher (p < 0.05) concentrations than in muscle of fish collected from background locations. Mercury concentrations (mean of means) in fish from AR (all other trace elements were at LOD) were significantly higher (p < 0.10) than Hg concentrations in fish from CR, and Hg concentrations in fish collected from both reservoirs exhibited significantly (AR = p <0.05 and CR = p < 0.10) decreasing trends over time.

  16. The Effects of Austerity on Collection Development in Nigerian University Libraries with Particular Reference to Usmanu Danfodiyo University Library, Sokoto.

    Science.gov (United States)

    Ekoja, Innocent I.

    1992-01-01

    Describes a study that examined the effects of austerity on collection development at the Usmanu Danfodiyo University (Nigeria) library since its inception in 1977 through 1990. The findings reported indicate that decreased allocations have led to declining book purchases and journal subscriptions and large debts to foreign book dealers. (23…

  17. [Blood cultures in the paediatric emergency department. Guidelines and recommendations on their indications, collection, processing and interpretation].

    Science.gov (United States)

    Hernández-Bou, S; Álvarez Álvarez, C; Campo Fernández, M N; García Herrero, M A; Gené Giralt, A; Giménez Pérez, M; Piñeiro Pérez, R; Gómez Cortés, B; Velasco, R; Menasalvas Ruiz, A I; García García, J J; Rodrigo Gonzalo de Liria, C

    2016-05-01

    Blood culture (BC) is the gold standard when a bacteraemia is suspected, and is one of the most requested microbiological tests in paediatrics. Some changes have occurred in recent years: the introduction of new vaccines, the increasing number of patients with central vascular catheters, as well as the introduction of continuous monitoring BC systems. These changes have led to the review and update of different factors related to this technique in order to optimise its use. A practice guideline is presented with recommendations on BC, established by the Spanish Society of Paediatric Emergency Care and the Spanish Society for Paediatric Infectious Diseases. After reviewing the available scientific evidence, several recommendations for each of the following aspects are presented: BC indications in the Emergency Department, how to obtain, transport and process cultures, special situations (indications and interpretation of results in immunosuppressed patients and/or central vascular catheter carriers, indications for anaerobic BC), differentiation between bacteraemia and contamination when a BC shows bacterial growth and actions to take with a positive BC in patients with fever of unknown origin. Copyright © 2015 Asociación Española de Pediatría. Published by Elsevier España, S.L.U. All rights reserved.

  18. Last drinks: A study of rural emergency department data collection to identify and target community alcohol-related violence.

    Science.gov (United States)

    Miller, Peter; Droste, Nicolas; Baker, Tim; Gervis, Cathreena

    2015-06-01

    The present study summarises the methodology and findings of a pilot project designed to measure the sources and locations of alcohol-related harm by implementing anonymised 'last drinks' questions in the ED of a rural community. 'Last drinks' questions were added to computerised triage systems at South West Healthcare ED in rural Warrnambool, Victoria, from 1 November 2013 to 3 July 2014. For all injury presentations aged 15 years or older, attendees were asked whether alcohol was consumed in the 12 h prior to injury, how many standard drinks were consumed, where they purchased most of the alcohol and where they consumed the last alcoholic drink. From 3692 injury attendances, 10.8% (n = 399) reported consuming alcohol in the 12 h prior to injury. 'Last drinks' data collection was 100% complete for participants who reported alcohol use prior to injury. Approximately two-thirds (60.2%) of all alcohol-related presentations had purchased their alcohol at packaged liquor outlets. During high-alcohol hours, alcohol-related injuries accounted for 36.1% (n = 101) of all ED injury presentations, and in total 41.7% of alcohol-related attendances during these hours reported consuming last drinks at identifiable hotels, bars, nightclubs or restaurants, or identifiable public areas/events. This pilot demonstrates the feasibility and reliability of implementing sustainable 'last drinks' data collection methods in the ED, and the ability to effectively map the source of alcohol-related ED attendances in a rural community. © 2015 Australasian College for Emergency Medicine and Australasian Society for Emergency Medicine.

  19. Satisfaction Data Collected by E-mail and Smartphone for Emergency Department Patients: How Do Responders Compare With Nonresponders?

    Science.gov (United States)

    Strickler, Jeffery C; Lopiano, Kenneth K

    2016-11-01

    This study profiles an innovative approach to capture patient satisfaction data from emergency department (ED) patients by implementing an electronic survey method. This study compares responders to nonresponders. Our hypothesis is that the cohort of survey respondents will be similar to nonresponders in terms of the key characteristics of age, gender, race, ethnicity, ED disposition, and payor status. This study is a cross-sectional design using secondary data from the database and provides an opportunity for univariate analysis of the key characteristics for each group. The data elements will be abstracted from the database and compared with the same key characteristics from a similar sample from the database on nonresponders to the ED satisfaction survey. Age showed a statistically significant difference between responders and nonresponders. Comparison by disposition status showed no substantial difference between responders and nonresponders. Gender distribution showed a greater number of female than male responders. Race distribution showed a greater number and response by white and Asian patients as compared with African Americans. A review of ethnicity showed fewer Hispanics responded. An evaluation by payor classification showed greater number and response rate by those with a commercial or Workers Comp payor source. The response rate by Medicare recipients was stronger than expected; however, the response rate by Medicaid recipients and self-pay could be a concern for underrepresentation by lower socioeconomic groups. Finally, the evaluation of the method of notification showed that notification by both e-mail and text substantially improved response rates. The evaluation of key characteristics showed no difference related to disposition, but differences related to age, gender, race, ethnicity, and payor classification. These results point to a potential concern for underrepresentation by lower socioeconomic groups. The results showed that notification by

  20. 40 CFR Appendix G to Part 50 - Reference Method for the Determination of Lead in Suspended Particulate Matter Collected From...

    Science.gov (United States)

    2010-07-01

    ... the sample as follows: 7.2.1.5.1 Rinse watch glass and sides of beaker with D.I. water. 7.2.1.5.2.... 1.1 Ambient air suspended particulate matter is collected on a glass-fiber filter for 24 hours using... lead content of the sample is analyzed by atomic absorption spectrometry using an air-acetylene flame...

  1. Treatment of self-referred patients with abdominal complaints by emergency physicians. A prospective observational study in an emergency department in The Netherlands

    NARCIS (Netherlands)

    van Geloven, A. A.; de Vries, G. M.; van der Eerden, M. M.; Luitse, J. S.; Hoitsma, H. F.; Obertop, H.

    1999-01-01

    The quality of the treatment by emergency physicians of patients with abdominal complaints, who visited the emergency department (ED) of a city hospital (OLVG), Amsterdam, The Netherlands, was evaluated in a prospective observational study. During 6 months 1853 patients with abdominal complaints

  2. Great Lakes Research Vessel Operations 1958-2016: Reference

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The RVCAT database contains data that have been collected on various vessel operations on the Great Lakes and select connecting waterways. This section of Reference...

  3. Short- and long-term prognosis of critically-ill patients referred to the ICU from the Emergency Department of a tertiary hospital.

    Science.gov (United States)

    García-Gigorro, Renata; Dominguez Aguado, Helena; Barea Mendoza, Jesús Abelardo; Viejo Moreno, Rubén; Sánchez Izquierdo, Jose Angel; Montejo-González, Juan Carlos

    2017-03-03

    A frequent source of critically-ill patients admitted to the ICU is the Emergency Department. It is essential to analyse the short-term prognosis of these patients, but also their evolution after their discharge from the hospital, since this is one of the major concerns of these patients. The aim of this study is to describe the epidemiological characteristics of patients admitted to the ICU from the Emergency Department and to analyse their outcome. This consisted of an observational prospective cohorts study which included 269 Emergency Department patients consecutively admitted to the ICU over an 18-month period. Factors associated with hospital mortality were presented as an odds ratio (OR) and factors associated with long-term mortality were presented as a hazard ratio (HR). A P-value lower than .05 was accepted as significant. The overall survival was analysed on the basis of the Kaplan-Meier curves. Hospital mortality was 15%, ICU complications where the variables with the greatest impact on short-term mortality: acute renal failure (OR 22.7) and respiratory distress syndrome (OR 51.2). After hospital discharge, the cumulative mortality at 12, 24 and 36 months was 6, 11 and 15%, respectively. The degree of functional dependence (HR 3.7), cancer (HR 3.4) and arrhythmias (HR 2.4) were factors related to long-term mortality. The short-term outcome of ICU patients is related to age and comorbidity, but more significantly to the characteristics of the acute illness. However, the long-term outcome is more closely associated with the patients' characteristics. Copyright © 2016 Elsevier España, S.L.U. All rights reserved.

  4. Potential for advice from doctors to reduce the number of patients referred to emergency departments by NHS 111 call handlers: observational study.

    Science.gov (United States)

    Anderson, Andrew; Roland, Martin

    2015-11-27

    To determine the effect of using experienced general practitioners (GPs) to review the advice given by call handlers in NHS 111, a national service giving telephone advice to people seeking medical care. Observational study following the introduction of GPs to review call handlers' decisions which had been made using decision support software. NHS 111 call centre covering Cambridgeshire and Peterborough. When a call handler using standard NHS 111 decision support software would have advised the caller to attend the hospital accident and emergency (A&E) department, the decision was reviewed by an experienced GP. Percentage of calls where an outcome other than A&E attendance was recommended by the GP. Of 1474 cases reviewed, the GP recommended A&E attendance in 400 cases (27.1%). In the remainder of cases, the GP recommended attendance at a primary care out-of-hours centre or minor injury unit in 665 cases (45.2%) and self-management or some alternative strategy in 409 (27.8%). Fewer callers to NHS 111 would be sent to emergency departments if the decision was reviewed by an experienced GP. Telephone triage services need to consider whether using relatively unskilled call handlers supported by computer software is the most cost-effective way to handle requests for medical care. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

  5. Requirements in the Overseas Employment and Domestic Connected Education for Radiological Technologists : Refers to Students Enrolled in the Department of Radiation

    Energy Technology Data Exchange (ETDEWEB)

    Han, Eun Ok; Kim, Boo Soon [Dept. of Radiologic Technology, Daegu Health College, Daegu (Korea, Republic of)

    2008-06-15

    This study investigated the realities of information acquirements and its requirements in the overseas employment and domestic connected education for students at the department of radiation in order to provide basic information for developing the standard educational curriculum for future internationalization in the education of radiation and presenting its direction. The investigation implemented in this study was performed through a questionnaire with 688 students enrolled in the department of radiation. The conclusion of the investigation is summarized as follows : The answers for the question of 'No acquirements in the information of the overseas employment and connected education for radiological technologists' were 487 students (70.8%), and the reason that 'There are no chances in related education' was the highest rate, 424 students (61.6%), of the answers. In the education for the overseas employment, the answers for the question of 'Select a connected education program in school instead of study abroad' were the highest rate, 436 students (63.4%). The most concerned country for the overseas employment was 'Australia', 247 students (35.9%). As a result, answers for the interest, participation, need, and hope for the overseas employment showed high rates even though they demonstrated a low recognition level in the overseas employment. In addition, it is necessary to strategically plan an education program for this issue because all participants agree with the current stream.

  6. CMS Statistics Reference Booklet

    Data.gov (United States)

    U.S. Department of Health & Human Services — The annual CMS Statistics reference booklet provides a quick reference for summary information about health expenditures and the Medicare and Medicaid health...

  7. Fundamentals of Reference

    Science.gov (United States)

    Mulac, Carolyn M.

    2012-01-01

    The all-in-one "Reference reference" you've been waiting for, this invaluable book offers a concise introduction to reference sources and services for a variety of readers, from library staff members who are asked to work in the reference department to managers and others who wish to familiarize themselves with this important area of…

  8. Anatomical variations of the sternal angle and anomalies of adult human sterna from the Galloway osteological collection at Makerere University Anatomy Department.

    Science.gov (United States)

    Kirum, Gonzaga Gonza; Munabi, Ian; Kukiriza, John; Tumusiime, Gerald; Kange, Mesach; Ibingira, Charles; Buwembo, William

    2017-03-29

    Anatomical variations of the sternal angle and anomalies of the sternum are unique happenings of major clinical significance.It is known that misplaced sternal angles may lead to inaccurate counting of ribs and create challenges with intercostal nerve blocks and needle thoracostomies. Sternal foramina may pose a great hazard during sternal puncture, due to inadvertent cardiac or great vessel injury. These sternal variations and anomalies are rarely reported among Africans. The aim of this study was to determine the anatomical variations of the sternal angle and anomalies of the sternum among adult dry human sterna at the Galloway osteological collection, Makerere University, Uganda. This was a descriptive cross sectional study in which quantitative and qualitative data were collected. The study examined 85 adult human sterna at the Department of Anatomy, Makerere University. Univariate and bivariate analyses were done using SPSS 21.0 for windows. Over 40% (36/85) of the specimens had variations in size, location and fusion of the sternal angle. There was no significant difference in the mean size of the sternal angle in males at 163.40 (SD 6.7) compared with 165.00 (SD 6.4) in females (p=0.481). Of the 85 specimens examined, only 21 (24.7%) had a xiphoid process. The most frequent sternal anomalies were bifid xiphoid process 42.9% (9/21) and sternal foramen 12.9% (11/85). Sternal variations and anomalies are prevalent in the Galloway osteological collection and there is need for increased awareness of these findings as they may determine the accuracy of clinical and other procedures in the thoracic region.

  9. Determination of reference intervals and comparison of venous blood gas parameters using standard and non-standard collection methods in 24 cats.

    Science.gov (United States)

    Bachmann, Karin; Kutter, Annette Pn; Schefer, Rahel Jud; Marly-Voquer, Charlotte; Sigrist, Nadja

    2017-08-01

    Objectives The aim of this study was to determine in-house reference intervals (RIs) for venous blood analysis with the RAPIDPoint 500 blood gas analyser using blood gas syringes (BGSs) and to determine whether immediate analysis of venous blood collected into lithium heparin (LH) tubes can replace anaerobic blood sampling into BGSs. Methods Venous blood was collected from 24 healthy cats and directly transferred into a BGS and an LH tube. The BGS was immediately analysed on the RAPIDPoint 500 followed by the LH tube. The BGSs and LH tubes were compared using paired t-test or Wilcoxon matched-pairs signed-rank test, Bland-Altman and Passing-Bablok analysis. To assess clinical relevance, bias or percentage bias between BGSs and LH tubes was compared with the allowable total error (TEa) recommended for the respective parameter. Results Based on the values obtained from the BGSs, RIs were calculated for the evaluated parameters, including blood gases, electrolytes, glucose and lactate. Values derived from LH tubes showed no significant difference for standard bicarbonate, whole blood base excess, haematocrit, total haemoglobin, sodium, potassium, chloride, glucose and lactate, while pH, partial pressure of carbon dioxide and oxygen, actual bicarbonate, extracellular base excess, ionised calcium and anion gap were significantly different to the samples collected in BGSs ( P blood base excess, haematocrit, total haemoglobin, sodium, potassium, chloride, glucose and lactate can be made based on blood collected in LH tubes and analysed within 5 mins. For pH, partial pressure of carbon dioxide and oxygen, extracellular base excess, anion gap and ionised calcium the clinically relevant alterations have to be considered if analysed in LH tubes.

  10. Maui, Lanai, and Hawaii Water Quality Sampling Dataset Collected By Dr. Richard Brock on Behalf of the State of Hawaii Department of Health Mostly During 2001-2005 (NODC Accession 0031350)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Transects were made on three islands in nine areas to collect in situ water quality measurements. Each area has several survey transects from the shallows seaward....

  11. Descriptions of marine mammal specimens in Marine Mammal Osteology Reference Collection, Alaska Fisheries Science Center, National Marine Mammal Laboratory from 1938-01-01 to 2015-12-05 (NCEI Accession 0140937)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NMFS Alaska Fisheries Science Center National Marine Mammal Laboratory (NMML) Marine Mammal Osteology Collection consists of approximately 2500 specimens (skulls...

  12. [Archival materials collected by Prof. Wiktor Dega in the Department of the History of Medical Sciences, Karol Marcinkowski University of Medical Sciences - general characteristics].

    Science.gov (United States)

    Hłyń, M

    2000-01-01

    Interesting archival materials collected by Prof. Wiktor Dega are held in the Department of the History of Medical Sciences belonging to Karol Marcinkowski University. There are mainly personal documents including: a military booklet, passport and different identity cards. They are also the diary from 1913. Noteworthy are the notebooks from his student period and diaries full of reflections from his scientific journeys abroad and chrestomathy from the professional literature. Moreover, the archival material about Prof. Degas' pre-war activity and a organiser of cost-free gymnastic courses for children with posture defects should be mentioned in Poznań. After the Second World War Prof. Dega worked on the Committee of Rehabilitation and Adaptation of Human Beings and organised the Polish Branch of the International College of Surgeons, and materials from that time are also available. Also important are documents associated with Prof. Dega's the Order of Smile from the St. Maria Magdelena secondary school in Poznań. His letters are extremely valuable and the interesting press articles, photos and diplomas are also noteworthy.

  13. The role of ground reference data collection in the prediction of stem volume with LiDAR data in mountain areas

    Science.gov (United States)

    Dalponte, Michele; Martinez, Cristina; Rodeghiero, Mirco; Gianelle, Damiano

    2011-11-01

    Ground reference data collection represents an important element in the prediction of stem volume with LiDAR-derived variables, and at present it is the most expensive part of such analyses. In this paper two aspects of ground reference data collection were analyzed: (1) the positioning error of the ground plots; and (2) the optimal number of training plots. A system for the prediction of stem volume at area-based level was adopted. LiDAR data were preprocessed and 13 variables describing both height and coverage were extracted. Models were defined using a stepwise ordinary least square (OLS) regression. Three experiments were conducted: (i) the role of the plots positioning error on prediction accuracy; (ii) the influence of random downsampling of plot numbers on prediction accuracy; and (iii) the influence of a stratified downsampling of plot numbers on prediction accuracy based on LiDAR-derived variables. A dataset comprising 799 ground plots was used. They were distributed throughout a mountainous area in the Southern Alps, where the presence of a complex landscape increases the uncertainty of the Global Positioning System (GPS) accuracy, and where a large variety of tree forest species and climatic environments make it necessary to have a large number of sample plots for accurate characterization of the study area. All the experiments provided important indications for LiDAR based forest inventories: the GPS error did not significantly influence the prediction accuracy and it was possible to reduce the number of training samples without compromising the generalization ability of the prediction model. Leading on from these findings, a new ground sampling protocol based on genetic algorithms was proposed. The new protocol allowed us to obtain promising results for the considered dataset: using only 53 training plots, instead of 534 in the original dataset, we obtained the same results for the validation set. These results, obtained in a complex mountainous area

  14. Oil Well Bottom Hole Locations, This GIS data set was produced as a general reference for the Department of Natural Resources, the oil and gas industry, environmental and regulatory agencies, landowners, and the public., Published in 2007, 1:24000 (1in=2000ft) scale, Louisiana State University (LSU).

    Data.gov (United States)

    NSGIC Education | GIS Inventory — Oil Well Bottom Hole Locations dataset current as of 2007. This GIS data set was produced as a general reference for the Department of Natural Resources, the oil and...

  15. Summary of residue analysis of biota collected for the Department of the Interior: Reconnaissance investigation of irrigation drainage in the San Juan River area, northwestern New Mexico

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — There were three primary objectives of this reconnaissance study. These objectives were: (1) to determine if DOI-sponsored irrigation projects contribute to...

  16. Introduction to Reference Links

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — Unlike most traditional metadata systems, the power of ServCat comes in relating a Reference to others. This module discusses the different types of links (aka...

  17. Reference Climatological Stations

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Reference Climatological Stations (RCS) network represents the first effort by NOAA to create and maintain a nationwide network of stations located only in areas...

  18. [Development of forensic thanatology through the prism of analysis of postmortem protocols collected at the Department of Forensic Medicine, Jagiellonian University].

    Science.gov (United States)

    Konopka, Tomasz

    2011-01-01

    When assessed based on the analysis of postmortem protocols, the successes of forensic thanatology appear to differ from those that might be assumed using as the foundation a review of publications and textbooks. The greatest achievements date back to as early as the 18th and 19th centuries, when the morphological changes observed in the majority of types of deaths resulting from disease-associated and traumatic causes were described. Within the past 130 years, however, or in other words, in the period when autopsy protocols were written that are today collected in the archives of the Krakow Department of Forensic Medicine, the causes and mechanisms of death became understood even when the said factors were associated with discrete postmortem changes only or no no such changes whatsoever were left. At the end of the 19th century and for a long time afterwards, a difficult problem was posed by sudden deaths, where the postmortem examinations demonstrated solely atherosclerosis and the cause of death was described as "heart palsy". As it turned out, a great portion of such deaths represented individuals with myocardial infarction; in spite of its evident macroscopic presentation, the diagnostic management of the disease was progressing very slowly. Myocardial infarction, known at least since 1912, was associated by forensic medicine with the phenomenon of sudden death only in the forties, and the ability to detect myocardial infarction in practice developed only in the fifties of the last century. The achievement of the present dissertation is the formulation of a theory ascribing such a long delay in macroscopic diagnostics of myocardial infarction to forensic medicine specialists being attached to and fond of employing the "in situ" autopsy technique, which was unfavorable from the viewpoint of heart examination, since the organ was not dissected free and removed from the body in the course of a postmortem examination. When autopsies started to concentrate on

  19. Multibeam collection for NECR04RR: Multibeam data collected aboard Roger Revelle from 2000-10-05 to 2000-11-06, departing from Honolulu, HI and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for NECR05RR: Multibeam data collected aboard Roger Revelle from 2000-11-12 to 2000-12-07, departing from Honolulu, HI and returning to Hilo, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for NECR01RR: Multibeam data collected aboard Roger Revelle from 2000-07-14 to 2000-08-11, departing from San Diego, CA and returning to Astoria, OR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for NECR02RR: Multibeam data collected aboard Roger Revelle from 2000-08-13 to 2000-08-25, departing from Astoria, OR and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for AII8L18: Multibeam data collected aboard Atlantis II from 1987-07-12 to 1987-08-02, departing from Agana, Guam and returning to Yokohama, Japan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for EW9605: Multibeam data collected aboard Maurice Ewing from 1996-06-14 to 1996-07-05, departing from San Juan, Puerto Rico and returning to San Juan, Puerto Rico

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for AMAT05RR: Multibeam data collected aboard Roger Revelle from 2006-05-26 to 2006-05-31, departing from Honolulu, HI and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for EW0501: Multibeam data collected aboard Maurice Ewing from 2005-01-07 to 2005-02-01, departing from Colon, Panama and returning to Progresso, Mexico

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for NT05-13: Multibeam data collected aboard Natsushima from 2005-08-14 to 2005-08-15, departing from Unknown Port and returning to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for AHI-03-07c: Multibeam data collected aboard Ahi from 2003-09-16 to 2003-09-17, departing from Saipan, CNMI and returning to Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for HI-07-01: Multibeam data collected aboard Hi'ialakai from 2007-04-29 to 2007-05-02, departing from Honolulu, HI and returning to Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for B00049: Multibeam data collected aboard Surveyor from 1986-05-01 to 1986-05-06, departing from Seattle, WA and returning to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for MGL0810: Multibeam data collected aboard Marcus G. Langseth from 2008-05-27 to 2008-06-02, departing from San Diego, CA and returning to San Diego, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for TN295: Multibeam data collected aboard Thomas G. Thompson from 2013-04-10 to 2013-04-18, departing from Honolulu, HI and returning to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for KM0809: Multibeam data collected aboard Kilo Moana from 2008-06-12 to 2008-06-15, departing from Honolulu, HI and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for HLY07TG: Multibeam data collected aboard Healy from 2007-08-06 to 2007-08-17, departing from Seattle, WA and returning to Barrow, AK

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for AT26-02: Multibeam data collected aboard Atlantis from 2013-06-25 to 2013-07-09, departing from Astoria, OR and returning to Astoria, OR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for KN199-03: Multibeam data collected aboard Knorr from 2010-10-01 to 2010-10-10, departing from Nuuk (Godthab), Greenland and returning to Lisboa, Portugal

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for B00218: Multibeam data collected aboard Mt. Mitchell from 1990-05-17 to 1990-05-22, departing from Norfolk, VA and returning to Norfolk, VA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for BD07-1: Multibeam data collected aboard Bowditch from 2007-11-16 to 2007-12-17, departing from Garapan, Saipan and returning to Garapan, Saipan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for RR1114: Multibeam data collected aboard Roger Revelle from 2011-08-29 to 2011-09-26, departing from Darwin, Australia and returning to Phuket, Thailand

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for KN195-10: Multibeam data collected aboard Knorr from 2009-06-14 to 2009-07-13, departing from Dutch Harbor, AK and returning to Dutch Harbor, AK

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for EW0103: Multibeam data collected aboard Maurice Ewing from 2001-04-08 to 2001-04-12, departing from San Juan, Puerto Rico and returning to Colon, Panama

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for NBP0801: Multibeam data collected aboard Nathaniel B. Palmer from 2008-01-14 to 2008-01-26, departing from Lyttelton, New Zealand and returning to McMurdo Station, Antarctica

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for TUIM14MV: Multibeam data collected aboard Melville from 2005-09-02 to 2005-09-22, departing from Seattle, WA and returning to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for NBP1310B: Multibeam data collected aboard Nathaniel B. Palmer from 2013-12-03 to 2014-01-23, departing from Rothera Station, Antarctica and returning to Hobart, Tasmania

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for MV1210: Multibeam data collected aboard Melville from 2012-07-28 to 2012-08-26, departing from San Diego, CA and returning to San Diego, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for NF-14-06: Multibeam data collected aboard Nancy Foster from 2014-09-03 to 2014-09-11, departing from Fort Pierce, FL and returning to Cape Canaveral, FL

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for HLY00TC: Multibeam data collected aboard Healy from 2000-03-11 to 2000-03-13, departing from Port Everglades, FL and returning to Norfolk, VA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for KNOX19RR: Multibeam data collected aboard Roger Revelle from 2008-08-21 to 2008-10-03, departing from Miami, FL and returning to Port Everglades, FL

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for AT18-16: Multibeam data collected aboard Atlantis from 2012-01-06 to 2012-01-28, departing from Port Everglades, FL and returning to Port Everglades, FL

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for KNOX20RR: Multibeam data collected aboard Roger Revelle from 2008-10-07 to 2008-10-25, departing from Port Everglades, FL and returning to Tampa, FL

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for EW9003: Multibeam data collected aboard Maurice Ewing from 1990-06-25 to 1990-07-02, departing from Port Everglades, FL and returning to Newark, NJ

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for EW9002: Multibeam data collected aboard Maurice Ewing from 1990-06-20 to 1990-06-24, departing from Miami, FL and returning to Port Everglades, FL

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for KN200-03: Multibeam data collected aboard Knorr from 2011-04-03 to 2011-04-09, departing from Halifax, Canada and returning to Port Everglades, FL

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for KNOX17RR: Multibeam data collected aboard Roger Revelle from 2008-05-02 to 2008-05-31, departing from Port Everglades, FL and returning to Woods Hole, MA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for KN203-04: Multibeam data collected aboard Knorr from 2011-10-02 to 2011-10-21, departing from Nuuk (Godthab), Greenland and returning to Nuuk (Godthab), Greenland

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for EW9202: Multibeam data collected aboard Maurice Ewing from 1992-03-06 to 1992-03-14, departing from Lyttelton, New Zealand and returning to Gladstone, Australia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for TN293: Multibeam data collected aboard Thomas G. Thompson from 2013-03-16 to 2013-04-01, departing from Honolulu, HI and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for KN209-02: Multibeam data collected aboard Knorr from 2012-10-16 to 2012-11-09, departing from Ponta Delgada, Azores and returning to Charleston, SC

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for KN204-01: Multibeam data collected aboard Knorr from 2011-11-06 to 2011-12-11, departing from Woods Hole, MA and returning to Praia, Cape Verde

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for KN156: Multibeam data collected aboard Knorr from 1998-01-31 to 1998-02-14, departing from Woods Hole, MA and returning to Woods Hole, MA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for KN194-02: Multibeam data collected aboard Knorr from 2008-09-01 to 2008-09-23, departing from Nuuk (Godthab), Greenland and returning to Nuuk (Godthab), Greenland

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for KN190: Multibeam data collected aboard Knorr from 2007-07-31 to 2007-08-13, departing from Woods Hole, MA and returning to Woods Hole, MA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for FK008: Multibeam data collected aboard Falkor from 2013-05-30 to 2013-06-30, departing from St. Petersburg, FL and returning to Montego Bay, Jamaica

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for FK008-T: Multibeam data collected aboard Falkor from 2013-07-09 to 2013-07-11, departing from Montego Bay, Jamaica and returning to Victoria, Canada

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for AT18-03: Multibeam data collected aboard Atlantis from 2010-12-06 to 2010-12-15, departing from Gulfport, MS and returning to Gulfport, MS

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for HLY10TD: Multibeam data collected aboard Healy from 2010-07-28 to 2010-07-31, departing from Seward, AK and returning to Dutch Harbor, AK

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for TN303: Multibeam data collected aboard Thomas G. Thompson from 2013-10-25 to 2013-12-20, departing from Manta, Ecuador and returning to Papeete, French Polynesia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for A125L6: Multibeam data collected aboard Atlantis II from 1990-05-02 to 1990-05-14, departing from Punta Arenas, Chile and returning to Guayaquil, Ecuador

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for AT15-42: Multibeam data collected aboard Atlantis from 2009-01-09 to 2009-02-02, departing from Puerto Ayora, Ecuador and returning to Puntarenas, Costa Rica

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for MV1208: Multibeam data collected aboard Melville from 2012-06-05 to 2012-06-21, departing from Puerto Ayora, Ecuador and returning to San Diego, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for AT15-63: Multibeam data collected aboard Atlantis from 2010-03-15 to 2010-04-14, departing from Puerto Ayora, Ecuador and returning to Puerto Ayora, Ecuador

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for MV1207: Multibeam data collected aboard Melville from 2012-05-22 to 2012-06-04, departing from Valparaiso, Chile and returning to Puerto Ayora, Ecuador

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for KN195-05: Multibeam data collected aboard Knorr from 2009-03-24 to 2009-04-05, departing from Puerto Ayora, Ecuador and returning to Puerto Ayora, Ecuador

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for AT11L33: Multibeam data collected aboard Atlantis from 2005-09-21 to 2005-10-13, departing from Seattle, WA and returning to Woods Hole, MA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for KM1125: Multibeam data collected aboard Kilo Moana from 2011-09-06 to 2011-09-21, departing from Honolulu, HI and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for B00295: Multibeam data collected aboard Mt. Mitchell from 1991-08-12 to 1991-08-14, departing from Norfolk, VA and returning to Norfolk, VA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for MV1104: Multibeam data collected aboard Melville from 2011-03-23 to 2011-04-23, departing from Valparaiso, Chile and returning to Arica, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for TN321: Multibeam data collected aboard Thomas G. Thompson from 2015-05-13 to 2015-05-16, departing from San Diego, CA and returning to Portland, OR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for KN193-06: Multibeam data collected aboard Knorr from 2008-06-29 to 2008-07-12, departing from St. George's, Bermuda and returning to Norfolk, VA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for B00245: Multibeam data collected aboard Whiting from 1990-08-27 to 1990-09-11, departing from Norfolk, VA and returning to Norfolk, VA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for FK150324: Multibeam data collected aboard Falkor from 2015-03-24 to 2015-04-06, departing from Broome, Australia and returning to Broome, Australia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for KM1209: Multibeam data collected aboard Kilo Moana from 2012-05-15 to 2012-05-25, departing from Pohnpei, Micronesia and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for HI-06-02: Multibeam data collected aboard Hi'ialakai from 2006-02-10 to 2006-02-13, departing from Unknown Port and returning to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for NBP9501: Multibeam data collected aboard Nathaniel B. Palmer from 1995-02-07 to 1995-03-13, departing from McMurdo Station, Antarctica and returning to Lyttelton, New Zealand

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for COOK11MV: Multibeam data collected aboard Melville from 2001-08-08 to 2001-08-17, departing from Naha, Japan and returning to Lae, Papua New Guinea

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for NBP0305A: Multibeam data collected aboard Nathaniel B. Palmer from 2003-12-20 to 2003-12-30, departing from Lyttelton, New Zealand and returning to McMurdo Station, Antarctica

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for 2009_Amundsen: Multibeam data collected aboard Amundsen from 2009-07-03 to 2009-11-17, departing from Unknown Port and returning to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for MGL1407: Multibeam data collected aboard Marcus G. Langseth from 2014-08-21 to 2014-09-13, departing from Brooklyn, NY and returning to Norfolk, VA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for KM0716: Multibeam data collected aboard Kilo Moana from 2007-08-23 to 2007-08-30, departing from Honolulu, HI and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for AT3L58: Multibeam data collected aboard Atlantis from 2000-10-16 to 2000-10-31, departing from Galveston, TX and returning to Key West, FL

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for B00274: Multibeam data collected aboard Whiting from 1991-05-24 to 1991-05-29, departing from Norfolk, VA and returning to Norfolk, VA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for B00050: Multibeam data collected aboard Surveyor from 1986-05-06 to 1986-05-08, departing from Seattle, WA and returning to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for RR1111: Multibeam data collected aboard Roger Revelle from 2011-07-25 to 2011-08-04, departing from Kao-hsiung, Taiwan and returning to Kao-hsiung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for AT03L29: Multibeam data collected aboard Atlantis from 1998-11-23 to 1998-12-12, departing from Manzanillo, Mexico and returning to Manzanillo, Mexico

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for EW9309: Multibeam data collected aboard Maurice Ewing from 1993-11-20 to 1993-12-26, departing from Unknown Port and returning to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for MGLN10MV: Multibeam data collected aboard Melville from 2006-10-24 to 2006-11-12, departing from Honolulu, HI and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for lophelia2009: Multibeam data collected aboard Ronald Brown from 2009-08-20 to 2009-09-12, departing from Miami, FL and returning to Pensacola, FL

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for KM0315: Multibeam data collected aboard Kilo Moana from 2003-10-13 to 2003-10-17, departing from Honolulu, HI and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for CE05_03: Multibeam data collected aboard Celtic Explorer from 2005-07-26 to 2007-08-24, departing from Killybegs, Ireland and returning to Killybegs, Ireland

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for NF-13-09: Multibeam data collected aboard Nancy Foster from 2013-08-21 to 2013-08-28, departing from Charleston, SC and returning to Charleston, SC

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for AT26-15: Multibeam data collected aboard Atlantis from 2014-05-21 to 2014-06-14, departing from Gulfport, MS and returning to St. Petersburg, FL

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for M31L2: Multibeam data collected aboard Meteor from 1995-02-09 to 1995-02-27, departing from Port Said, Egypt and returning to Djibouti, Djibouti

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for AT26-24: Multibeam data collected aboard Atlantis from 2014-11-30 to 2014-12-12, departing from Puntarenas, Costa Rica and returning to Puntarenas, Costa Rica

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for RR1413: Multibeam data collected aboard Roger Revelle from 2014-11-29 to 2014-12-21, departing from Apra, Guam and returning to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for RR1308: Multibeam data collected aboard Roger Revelle from 2013-06-12 to 2013-06-26, departing from Kao-hsiung, Taiwan and returning to Palau, Palau

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for RR1016: Multibeam data collected aboard Roger Revelle from 2010-11-06 to 2010-11-24, departing from Kao-hsiung, Taiwan and returning to Kao-hsiung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for RR1516: Multibeam data collected aboard Roger Revelle from 2015-11-13 to 2015-11-18, departing from Palau, Palau and returning to Chi-Lung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for MGL0909: Multibeam data collected aboard Marcus G. Langseth from 2009-07-27 to 2009-08-17, departing from Kao-hsiung, Taiwan and returning to Astoria, OR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for RR1205: Multibeam data collected aboard Roger Revelle from 2012-06-03 to 2012-06-16, departing from Kao-hsiung, Taiwan and returning to Kao-hsiung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for RR1105: Multibeam data collected aboard Roger Revelle from 2011-03-24 to 2011-04-16, departing from Kao-hsiung, Taiwan and returning to Kao-hsiung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for RR1010: Multibeam data collected aboard Roger Revelle from 2010-07-31 to 2010-08-12, departing from Kao-hsiung, Taiwan and returning to Kao-hsiung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for MGL0907: Multibeam data collected aboard Marcus G. Langseth from 2009-06-07 to 2009-06-14, departing from Kao-hsiung, Taiwan and returning to Kao-hsiung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for MGLN17MV: Multibeam data collected aboard Melville from 2007-04-23 to 2007-04-28, departing from Kao-hsiung, Taiwan and returning to Yokohama, Japan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for MV0905: Multibeam data collected aboard Melville from 2009-03-31 to 2009-04-09, departing from Kao-hsiung, Taiwan and returning to Kao-hsiung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for RR1403: Multibeam data collected aboard Roger Revelle from 2014-04-14 to 2014-04-19, departing from Palau, Palau and returning to Chi-Lung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for KM0910: Multibeam data collected aboard Kilo Moana from 2009-04-14 to 2009-05-13, departing from Kao-hsiung, Taiwan and returning to Kao-hsiung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for MGLN35MV: Multibeam data collected aboard Melville from 2008-03-23 to 2008-04-02, departing from Kao-hsiung, Taiwan and returning to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for MV0907: Multibeam data collected aboard Melville from 2009-05-06 to 2009-05-15, departing from Kao-hsiung, Taiwan and returning to Kao-hsiung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for RR1005: Multibeam data collected aboard Roger Revelle from 2010-04-06 to 2010-04-28, departing from Kao-hsiung, Taiwan and returning to Kao-hsiung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for RR1307: Multibeam data collected aboard Roger Revelle from 2013-05-30 to 2013-06-09, departing from Kao-hsiung, Taiwan and returning to Kao-hsiung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for RR1004: Multibeam data collected aboard Roger Revelle from 2010-03-21 to 2010-04-01, departing from Kao-hsiung, Taiwan and returning to Kao-hsiung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for ZHNG04RR: Multibeam data collected aboard Roger Revelle from 2005-03-29 to 2005-04-15, departing from Auckland, New Zealand and returning to Kao-hsiung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for RR1006: Multibeam data collected aboard Roger Revelle from 2010-05-06 to 2010-05-29, departing from Kao-hsiung, Taiwan and returning to Kao-hsiung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for RR0907: Multibeam data collected aboard Roger Revelle from 2009-08-03 to 2009-08-09, departing from Chi-Lung, Taiwan and returning to Chi-Lung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for RR1014: Multibeam data collected aboard Roger Revelle from 2010-10-12 to 2010-10-24, departing from Naha, Japan and returning to Kao-hsiung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for EW9508: Multibeam data collected aboard Maurice Ewing from 1995-08-03 to 1995-08-20, departing from Honolulu, HI and returning to Chi-Lung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for EW9510: Multibeam data collected aboard Maurice Ewing from 1995-09-28 to 1995-10-15, departing from Kao-hsiung, Taiwan and returning to Honiara, Solomon Island

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for RR1008: Multibeam data collected aboard Roger Revelle from 2010-06-19 to 2010-07-02, departing from Kao-hsiung, Taiwan and returning to Kao-hsiung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for KM0909: Multibeam data collected aboard Kilo Moana from 2009-03-20 to 2009-04-09, departing from Kao-hsiung, Taiwan and returning to Kao-hsiung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for MGLN37MV: Multibeam data collected aboard Melville from 2008-04-28 to 2008-05-03, departing from Apra, Guam and returning to Kao-hsiung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for EW9509: Multibeam data collected aboard Maurice Ewing from 1995-08-23 to 1995-09-24, departing from Chi-Lung, Taiwan and returning to Kao-hsiung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for RR1109: Multibeam data collected aboard Roger Revelle from 2011-06-21 to 2011-07-07, departing from Kao-hsiung, Taiwan and returning to Kao-hsiung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for HNRO17RR: Multibeam data collected aboard Roger Revelle from 2000-05-08 to 2000-05-20, departing from Kao-hsiung, Taiwan and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for RR1204: Multibeam data collected aboard Roger Revelle from 2012-04-24 to 2012-05-14, departing from Legaspi Port, Philippines and returning to Kao-hsiung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for MGLN39MV: Multibeam data collected aboard Melville from 2008-05-15 to 2008-05-30, departing from Kao-hsiung, Taiwan and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for MGLN27MV: Multibeam data collected aboard Melville from 2007-10-22 to 2007-11-03, departing from Kao-hsiung, Taiwan and returning to Kao-hsiung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for MV0906: Multibeam data collected aboard Melville from 2009-04-14 to 2009-05-03, departing from Kao-hsiung, Taiwan and returning to Kao-hsiung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for RR1103: Multibeam data collected aboard Roger Revelle from 2011-02-26 to 2011-02-28, departing from Chi-Lung, Taiwan and returning to Kao-hsiung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for RR1107: Multibeam data collected aboard Roger Revelle from 2011-05-18 to 2011-06-05, departing from Kao-hsiung, Taiwan and returning to Kao-hsiung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for NBP0103: Multibeam data collected aboard Nathaniel B. Palmer from 2001-04-24 to 2001-06-05, departing from Punta Arenas, Chile and returning to Punta Arenas, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for NBP1202: Multibeam data collected aboard Nathaniel B. Palmer from 2012-02-11 to 2012-02-27, departing from McMurdo Station, Antarctica and returning to Punta Arenas, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for ARIA03WT: Multibeam data collected aboard Thomas Washington from 1982-04-07 to 1982-04-28, departing from Punta Arenas, Chile and returning to San Diego, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for NBP1001: Multibeam data collected aboard Nathaniel B. Palmer from 2010-01-04 to 2010-03-01, departing from Punta Arenas, Chile and returning to Punta Arenas, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for NBP0003: Multibeam data collected aboard Nathaniel B. Palmer from 2000-05-10 to 2000-06-01, departing from Punta Arenas, Chile and returning to Punta Arenas, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for NBP9704B: Multibeam data collected aboard Nathaniel B. Palmer from 1997-07-20 to 1997-07-25, departing from Talcahuano, Chile and returning to Punta Arenas, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for AMLR92: Multibeam data collected aboard Surveyor from 1992-01-16 to 1992-03-15, departing from Punta Arenas, Chile and returning to Punta Arenas, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for TN247: Multibeam data collected aboard Thomas G. Thompson from 2010-03-11 to 2010-04-17, departing from Punta Arenas, Chile and returning to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for RC2901: Multibeam data collected aboard Robert Conrad from 1988-01-06 to 1988-02-10, departing from Valparaiso, Chile and returning to Punta Arenas, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for NBP0106: Multibeam data collected aboard Nathaniel B. Palmer from 2001-11-09 to 2001-11-30, departing from Punta Arenas, Chile and returning to Punta Arenas, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for AMLR94: Multibeam data collected aboard Surveyor from 1994-01-13 to 1994-04-12, departing from Punta Arenas, Chile and returning to Punta Arenas, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for TN245: Multibeam data collected aboard Thomas G. Thompson from 2009-12-14 to 2010-01-09, departing from Seattle, WA and returning to Punta Arenas, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for NBP1302: Multibeam data collected aboard Nathaniel B. Palmer from 2013-02-12 to 2013-04-05, departing from McMurdo Station, Antarctica and returning to Punta Arenas, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for MV1016: Multibeam data collected aboard Melville from 2010-12-15 to 2010-12-28, departing from Isla De Pascua, Chile and returning to Punta Arenas, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for AT26-29: Multibeam data collected aboard Atlantis from 2015-02-12 to 2015-03-05, departing from Punta Arenas, Chile and returning to Punta Arenas, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for MV1101: Multibeam data collected aboard Melville from 2011-01-11 to 2011-02-16, departing from Punta Arenas, Chile and returning to Punta Arenas, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for MV1205: Multibeam data collected aboard Melville from 2012-04-20 to 2012-04-30, departing from Punta Arenas, Chile and returning to Valparaiso, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for RR0901: Multibeam data collected aboard Roger Revelle from 2009-01-12 to 2009-02-22, departing from Punta Arenas, Chile and returning to Punta Arenas, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for NBP0606: Multibeam data collected aboard Nathaniel B. Palmer from 2006-07-04 to 2006-08-13, departing from Punta Arenas, Chile and returning to Punta Arenas, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for NBP0709: Multibeam data collected aboard Nathaniel B. Palmer from 2007-09-28 to 2007-10-29, departing from Punta Arenas, Chile and returning to Punta Arenas, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for NBP0901: Multibeam data collected aboard Nathaniel B. Palmer from 2009-01-07 to 2009-02-25, departing from Punta Arenas, Chile and returning to Punta Arenas, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for NBP0506: Multibeam data collected aboard Nathaniel B. Palmer from 2005-07-24 to 2005-09-15, departing from Punta Arenas, Chile and returning to Punta Arenas, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for NBP9904: Multibeam data collected aboard Nathaniel B. Palmer from 1999-04-15 to 1999-05-10, departing from Punta Arenas, Chile and returning to Punta Arenas, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for KN182L10: Multibeam data collected aboard Knorr from 2006-01-04 to 2006-01-25, departing from Manzanillo, Mexico and returning to Punta Arenas, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for NBP1304: Multibeam data collected aboard Nathaniel B. Palmer from 2013-05-13 to 2013-06-12, departing from Punta Arenas, Chile and returning to Punta Arenas, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for NBP9902: Multibeam data collected aboard Nathaniel B. Palmer from 1999-02-12 to 1999-03-25, departing from McMurdo Station, Antarctica and returning to Punta Arenas, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for NBP1201: Multibeam data collected aboard Nathaniel B. Palmer from 2011-12-24 to 2012-02-11, departing from Punta Arenas, Chile and returning to McMurdo Station, Antarctica

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for NBP9805: Multibeam data collected aboard Nathaniel B. Palmer from 1998-07-25 to 1998-08-19, departing from Punta Arenas, Chile and returning to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for KM0504: Multibeam data collected aboard Kilo Moana from 2005-02-17 to 2005-03-23, departing from Wellington, New Zealand and returning to Brisbane, Australia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for MV0910: Multibeam data collected aboard Melville from 2009-10-29 to 2009-11-12, departing from Chi-Lung, Taiwan and returning to Brisbane, Australia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for GENE03RR: Multibeam data collected aboard Roger Revelle from 1997-02-23 to 1997-04-05, departing from Punta Arenas, Chile and returning to Callao, Peru

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for NF-07-09-GRNMS: Multibeam data collected aboard Nancy Foster from 2007-06-01 to 2007-06-10, departing from Savannah, GA and returning to Savannah, GA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for KM1128: Multibeam data collected aboard Kilo Moana from 2011-10-01 to 2011-10-25, departing from Honolulu, HI and returning to Apia, Samoa

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for MGL1115: Multibeam data collected aboard Marcus G. Langseth from 2011-11-26 to 2011-12-29, departing from Honolulu, HI and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for KN188-01: Multibeam data collected aboard Knorr from 2007-02-07 to 2007-02-27, departing from Woods Hole, MA and returning to St. George's, Bermuda

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for RR1508: Multibeam data collected aboard Roger Revelle from 2015-05-19 to 2015-06-17, departing from Auckland, New Zealand and returning to Napier, New Zealand

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for NBP0306: Multibeam data collected aboard Nathaniel B. Palmer from 2004-01-04 to 2004-01-15, departing from McMurdo Station, Antarctica and returning to McMurdo Station, Antarctica

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for NBP1101: Multibeam data collected aboard Nathaniel B. Palmer from 2011-01-19 to 2011-02-15, departing from McMurdo Station, Antarctica and returning to McMurdo Station, Antarctica

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for NBP9802: Multibeam data collected aboard Nathaniel B. Palmer from 1998-02-25 to 1998-04-03, departing from McMurdo Station, Antarctica and returning to Lyttelton, New Zealand

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for KM0919: Multibeam data collected aboard Kilo Moana from 2009-07-29 to 2009-08-14, departing from Honolulu, HI and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for EW9803: Multibeam data collected aboard Maurice Ewing from 1998-03-15 to 1998-04-06, departing from Bridgetown, Barbados and returning to Norfolk, VA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for EW9908: Multibeam data collected aboard Maurice Ewing from 1999-07-21 to 1999-08-18, departing from Kochi, Japan and returning to Yokohama, Japan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for AT26-20: Multibeam data collected aboard Atlantis from 2014-09-15 to 2014-09-20, departing from Astoria, OR and returning to Astoria, OR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for AT26-04: Multibeam data collected aboard Atlantis from 2013-07-31 to 2013-08-26, departing from Astoria, OR and returning to Astoria, OR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for KM1106: Multibeam data collected aboard Kilo Moana from 2011-02-19 to 2011-02-23, departing from Honolulu, HI and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for KM0326: Multibeam data collected aboard Kilo Moana from 2003-12-26 to 2003-12-31, departing from Honolulu, HI and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for KM0904: Multibeam data collected aboard Kilo Moana from 2009-02-04 to 2009-02-07, departing from Honolulu, HI and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for KM0318: Multibeam data collected aboard Kilo Moana from 2003-10-23 to 2003-10-26, departing from Honolulu, HI and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for KM0903: Multibeam data collected aboard Kilo Moana from 2009-01-30 to 2009-02-04, departing from Honolulu, HI and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for KM0906: Multibeam data collected aboard Kilo Moana from 2009-02-12 to 2009-02-15, departing from Honolulu, HI and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for TN291: Multibeam data collected aboard Thomas G. Thompson from 2013-01-25 to 2013-02-03, departing from Seattle, WA and returning to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for KM0632: Multibeam data collected aboard Kilo Moana from 2006-11-27 to 2006-12-05, departing from Honolulu, HI and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for TN189: Multibeam data collected aboard Thomas G. Thompson from 2006-01-21 to 2006-01-28, departing from Puerto Ayora, Ecuador and returning to Puerto Ayora, Ecuador

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for TN315: Multibeam data collected aboard Thomas G. Thompson from 2014-10-22 to 2014-10-31, departing from Seattle, WA and returning to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for EW9806: Multibeam data collected aboard Maurice Ewing from 1998-07-02 to 1998-08-13, departing from Halifax, Canada and returning to Halifax, Canada

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for EW9805: Multibeam data collected aboard Maurice Ewing from 1998-05-16 to 1998-07-01, departing from Halifax, Canada and returning to Halifax, Canada

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for EW9808: Multibeam data collected aboard Maurice Ewing from 1998-10-05 to 1998-10-09, departing from Halifax, Canada and returning to Norfolk, VA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for NBP9804: Multibeam data collected aboard Nathaniel B. Palmer from 1998-06-27 to 1998-07-15, departing from Unknown Port and returning to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for TN311: Multibeam data collected aboard Thomas G. Thompson from 2014-06-10 to 2014-06-14, departing from Newport, OR and returning to Newport, OR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for FK150117: Multibeam data collected aboard Falkor from 2015-01-17 to 2015-02-13, departing from Hobart, Australia and returning to Hobart, Australia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for AT15-49: Multibeam data collected aboard Atlantis from 2009-07-04 to 2009-08-14, departing from Victoria, Canada and returning to Victoria, Canada

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for MV1401: Multibeam data collected aboard Melville from 2014-02-14 to 2014-02-24, departing from San Diego, CA and returning to San Diego, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for KM1129: Multibeam data collected aboard Kilo Moana from 2011-10-28 to 2011-11-05, departing from Apia, Samoa and returning to Apia, Samoa

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for HE0905: Multibeam data collected aboard Healy from 2009-08-07 to 2009-09-16, departing from Barrow, AK and returning to Barrow, AK

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for NF-09-10-TER: Multibeam data collected aboard Nancy Foster from 2009-09-22 to 2009-09-29, departing from Unknown Port and returning to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for NBP0107: Multibeam data collected aboard Nathaniel B. Palmer from 2001-12-05 to 2002-01-13, departing from Punta Arenas, Chile and returning to Punta Arenas, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for HLY05TH: Multibeam data collected aboard Healy from 2005-11-06 to 2005-11-17, departing from St. Maarten, Netherland Antilles and returning to Cabo San Lucas, Mexico

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for KN177L03: Multibeam data collected aboard Knorr from 2004-05-20 to 2004-06-04, departing from Bergen, Norway and returning to Woods Hole, MA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for RR1110: Multibeam data collected aboard Roger Revelle from 2011-07-11 to 2011-07-22, departing from Kao-hsiung, Taiwan and returning to Kao-hsiung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for KM1310: Multibeam data collected aboard Kilo Moana from 2013-06-11 to 2013-06-21, departing from Honolulu, HI and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for NF-07-02-MPA: Multibeam data collected aboard Nancy Foster from 2006-10-25 to 2006-11-07, departing from Morehead City, NC and returning to Charleston, SC

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for EW0302: Multibeam data collected aboard Maurice Ewing from 2003-05-16 to 2003-05-22, departing from San Juan, Puerto Rico and returning to Gulfport, MS

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for MGL1304: Multibeam data collected aboard Marcus G. Langseth from 2013-03-31 to 2013-04-08, departing from Galveston, TX and returning to St. George's, Bermuda

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for MV1213: Multibeam data collected aboard Melville from 2012-10-13 to 2012-10-21, departing from San Diego, CA and returning to San Diego, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for RR1412: Multibeam data collected aboard Roger Revelle from 2014-10-29 to 2014-11-23, departing from Apra, Guam and returning to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for BMRG01MV: Multibeam data collected aboard Melville from 1995-10-15 to 1995-11-23, departing from San Diego, CA and returning to Papeete, French Polynesia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for TN300: Multibeam data collected aboard Thomas G. Thompson from 2013-09-03 to 2013-09-19, departing from Seattle, WA and returning to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for KN151L4: Multibeam data collected aboard Knorr from 1997-08-15 to 1997-09-02, departing from Port of Spain, Trinidad and Tobago and returning to Woods Hole, MA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for SU10-1: Multibeam data collected aboard Sumner from 2010-08-06 to 2010-09-05, departing from Apra, Guam and returning to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for EW0201: Multibeam data collected aboard Maurice Ewing from 2002-01-31 to 2002-02-14, departing from Hobart, Tasmania and returning to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for SU10-2: Multibeam data collected aboard Sumner from 2010-09-24 to 2010-10-21, departing from Apra, Guam and returning to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for SKQ201501T: Multibeam data collected aboard Sikuliaq from 2015-01-19 to 2015-02-11, departing from Apra, Guam and returning to Ketchikan, AK

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for EX1004: Multibeam data collected aboard Okeanos Explorer from 2010-06-08 to 2010-08-19, departing from Apra, Guam and returning to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for TUNE08WT: Multibeam data collected aboard Thomas Washington from 1992-01-01 to 1992-01-31, departing from Apra, Guam and returning to Majuro, Marshall Islands

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for MV1301: Multibeam data collected aboard Melville from 2013-01-16 to 2013-01-29, departing from Honolulu, HI and returning to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for TN273: Multibeam data collected aboard Thomas G. Thompson from 2011-12-22 to 2012-01-22, departing from Apra, Guam and returning to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for FK141109: Multibeam data collected aboard Falkor from 2014-11-09 to 2014-12-09, departing from Apra, Guam and returning to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for TN275: Multibeam data collected aboard Thomas G. Thompson from 2012-02-11 to 2012-02-21, departing from Apra, Guam and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for MGL1204: Multibeam data collected aboard Marcus G. Langseth from 2012-02-02 to 2012-02-29, departing from Apra, Guam and returning to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for TN233: Multibeam data collected aboard Thomas G. Thompson from 2009-04-20 to 2009-05-01, departing from Apra, Guam and returning to Apia, Samoa

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for KM1004: Multibeam data collected aboard Kilo Moana from 2010-02-26 to 2010-03-11, departing from Honolulu, HI and returning to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for BD0601: Multibeam data collected aboard Bowditch from 2006-10-16 to 2006-11-11, departing from Okinawa, Japan and returning to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for MGLN01MV: Multibeam data collected aboard Melville from 2006-03-22 to 2006-04-11, departing from San Diego, CA and returning to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for MV1302: Multibeam data collected aboard Melville from 2013-02-01 to 2013-02-15, departing from Apra, Guam and returning to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for RR0914: Multibeam data collected aboard Roger Revelle from 2009-11-06 to 2009-11-19, departing from Apra, Guam and returning to Nuku'alofa, Tonga

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for KM1005: Multibeam data collected aboard Kilo Moana from 2010-03-16 to 2010-03-30, departing from Apra, Guam and returning to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for TUNE06WT: Multibeam data collected aboard Thomas Washington from 1991-10-31 to 1991-12-02, departing from Kwajalein, Marshall Islands and returning to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for EX1604: Multibeam data collected aboard Okeanos Explorer from 2016-03-23 to 2016-04-13, departing from Kwajalein, Marshall Islands and returning to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for FK151121: Multibeam data collected aboard Falkor from 2015-11-21 to 2015-12-17, departing from Apra, Guam and returning to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for EX1003: Multibeam data collected aboard Okeanos Explorer from 2010-05-19 to 2010-06-03, departing from Honolulu, HI and returning to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for KM1021: Multibeam data collected aboard Kilo Moana from 2010-10-17 to 2010-11-09, departing from Honolulu, HI and returning to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for EX1005: Multibeam data collected aboard Okeanos Explorer from 2010-08-23 to 2010-09-05, departing from Apra, Guam and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for KM0913: Multibeam data collected aboard Kilo Moana from 2009-06-07 to 2009-06-18, departing from Apra, Guam and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for MGLN36MV: Multibeam data collected aboard Melville from 2008-04-05 to 2008-04-26, departing from Apra, Guam and returning to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for FK151221: Multibeam data collected aboard Falkor from 2015-12-21 to 2016-01-05, departing from Apra, Guam and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for EW0204: Multibeam data collected aboard Maurice Ewing from 2002-04-26 to 2002-05-08, departing from Apra, Guam and returning to Dutch Harbor, AK

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for RC2710: Multibeam data collected aboard Robert Conrad from 1986-11-14 to 1986-11-30, departing from Cape Town, South Africa and returning to Cape Town, South Africa

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for MGL1218: Multibeam data collected aboard Marcus G. Langseth from 2012-11-25 to 2012-11-25, departing from Astoria, OR and returning to Newport, OR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for Tran2new: Multibeam data collected aboard Ocean Alert from 1998-05-16 to 1998-05-17, departing from Unknown Port and returning to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for NBP0702: Multibeam data collected aboard Nathaniel B. Palmer from 2007-02-03 to 2007-03-23, departing from McMurdo Station, Antarctica and returning to Punta Arenas, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for NBP0002: Multibeam data collected aboard Nathaniel B. Palmer from 2000-04-05 to 2000-05-06, departing from Punta Arenas, Chile and returning to Punta Arenas, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for B00082: Multibeam data collected aboard Discoverer from 1986-10-10 to 1986-10-14, departing from Seattle, WA and returning to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for AT26-12: Multibeam data collected aboard Atlantis from 2014-03-14 to 2014-03-26, departing from New Orleans, LA and returning to Gulfport, MS

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for KN207-02: Multibeam data collected aboard Knorr from 2012-05-09 to 2012-06-11, departing from St. George's, Bermuda and returning to Ponta Delgada, Azores

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for PF0502: Multibeam data collected aboard Pathfinder from 2005-06-05 to 2005-06-23, departing from Charleston, SC and returning to Port Canaveral, FL

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for PF0501: Multibeam data collected aboard Pathfinder from 2005-04-30 to 2005-05-30, departing from Norfolk, VA and returning to Charleston, SC

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for NBP1210: Multibeam data collected aboard Nathaniel B. Palmer from 2013-01-06 to 2013-02-09, departing from Punta Arenas, Chile and returning to Punta Arenas, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for FK141215: Multibeam data collected aboard Falkor from 2014-12-15 to 2014-12-21, departing from Apra, Guam and returning to Apra, Guam

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for DANA03RR: Multibeam data collected aboard Roger Revelle from 2003-11-10 to 2003-11-26, departing from Manta, Ecuador and returning to Arica, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for DANA06RR: Multibeam data collected aboard Roger Revelle from 2004-02-09 to 2004-03-09, departing from Puerto Caldera, Costa Rica and returning to Mazatlan, Mexico

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for DANA07RR: Multibeam data collected aboard Roger Revelle from 2004-03-11 to 2004-04-01, departing from Mazatlan, Mexico and returning to San Diego, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for KM0319: Multibeam data collected aboard Kilo Moana from 2003-10-26 to 2003-10-31, departing from Honolulu, HI and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for FK140613: Multibeam data collected aboard Falkor from 2014-06-13 to 2014-06-19, departing from Honolulu, HI and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for KM1116: Multibeam data collected aboard Kilo Moana from 2011-05-20 to 2011-06-07, departing from Honolulu, HI and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for HLY1302: Multibeam data collected aboard Healy from 2013-08-16 to 2013-09-07, departing from Barrow, AK and returning to Barrow, AK

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for MGLN19MV: Multibeam data collected aboard Melville from 2007-05-26 to 2007-06-03, departing from Yokohama, Japan and returning to Manila, Philippines

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for MGLN29MV: Multibeam data collected aboard Melville from 2007-11-27 to 2007-11-29, departing from Kao-hsiung, Taiwan and returning to Manila, Philippines

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for MV0903: Multibeam data collected aboard Melville from 2009-02-27 to 2009-03-21, departing from Manila, Philippines and returning to Manila, Philippines

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for MGLN31MV: Multibeam data collected aboard Melville from 2008-01-09 to 2008-02-01, departing from Manila, Philippines and returning to Manila, Philippines

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for MV0904: Multibeam data collected aboard Melville from 2009-03-23 to 2009-03-28, departing from Manila, Philippines and returning to Kao-hsiung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for MGLN30MV: Multibeam data collected aboard Melville from 2007-11-30 to 2008-01-04, departing from Manila, Philippines and returning to Manila, Philippines

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for KN161L06: Multibeam data collected aboard Knorr from 2000-04-07 to 2000-05-16, departing from Recife, Brazil and returning to Recife, Brazil

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for EW9402: Multibeam data collected aboard Maurice Ewing from 1994-02-17 to 1994-03-21, departing from Salvador de Bahia, Brazil and returning to Cayenne, French Guiana

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for SOJN07MV: Multibeam data collected aboard Melville from 1997-04-10 to 1997-04-16, departing from Hobart, Tasmania and returning to Melbourne, Australia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for BMRG06MV: Multibeam data collected aboard Melville from 1996-02-22 to 1996-04-15, departing from Fremantle, Australia and returning to Port Hedland, Australia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for BMRG05MV: Multibeam data collected aboard Melville from 1996-01-16 to 1996-02-16, departing from Hobart, Tasmania and returning to Fremantle, Australia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for EW9912: Multibeam data collected aboard Maurice Ewing from 1999-10-27 to 1999-11-28, departing from Townsville, Australia and returning to Townsville, Australia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for EW0112: Multibeam data collected aboard Maurice Ewing from 2001-10-06 to 2001-10-23, departing from Seychelles and returning to Fremantle, Australia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for EW9911: Multibeam data collected aboard Maurice Ewing from 1999-10-10 to 1999-10-10, departing from Lae, Papua New Guinea and returning to Townsville, Australia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for MGLN11MV: Multibeam data collected aboard Melville from 2006-11-15 to 2006-12-17, departing from Honolulu, HI and returning to Brisbane, Australia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for VANC30MV: Multibeam data collected aboard Melville from 2004-05-18 to 2004-05-27, departing from Port Moresby, Papua New Guinea and returning to Cairns, Australia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for NF-11-06-FKNMS: Multibeam data collected aboard Nancy Foster from 2011-07-25 to 2011-08-05, departing from Charleston, SC and returning to Pascagoula, MS

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for 09CQ01_Saipan: Multibeam data collected aboard Swamp Fox from 2009-06-12 to 2009-06-22, departing from Unknown Port and returning to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for AT15-24: Multibeam data collected aboard Atlantis from 2007-09-30 to 2007-10-06, departing from Aberdeen, WA and returning to San Diego, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for 09CQ02_Tinian: Multibeam data collected aboard Swamp Fox from 2009-06-18 to 2009-06-18, departing from Unknown Port and returning to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for KM0405: Multibeam data collected aboard Kilo Moana from 2004-02-24 to 2004-03-03, departing from Honolulu, HI and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for RR1202: Multibeam data collected aboard Roger Revelle from 2012-02-18 to 2012-03-03, departing from Durban, South Africa and returning to Fremantle, Australia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for FK140502: Multibeam data collected aboard Falkor from 2014-05-02 to 2014-06-06, departing from Honolulu, HI and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for PASC03WT: Multibeam data collected aboard Thomas Washington from 1983-03-03 to 1983-03-28, departing from Easter Island, Chile and returning to Easter Island, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for RC2508: Multibeam data collected aboard Robert Conrad from 1984-07-08 to 1984-07-20, departing from Piraievs, Greece and returning to L'Orient, France

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for AT21-04: Multibeam data collected aboard Atlantis from 2012-07-13 to 2012-07-29, departing from Bridgetown, Barbados and returning to Bridgetown, Barbados

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for MV1110: Multibeam data collected aboard Melville from 2011-09-03 to 2011-10-08, departing from Bridgetown, Barbados and returning to Bridgetown, Barbados

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for KN197-08: Multibeam data collected aboard Knorr from 2010-05-22 to 2010-06-24, departing from Bridgetown, Barbados and returning to Bridgetown, Barbados

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for HLY0402: Multibeam data collected aboard Healy from 2004-05-15 to 2004-06-23, departing from Nome, AK and returning to Nome, AK

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for HLY0201: Multibeam data collected aboard Healy from 2002-05-06 to 2002-06-14, departing from Nome, AK and returning to Nome, AK

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for HLY07TD: Multibeam data collected aboard Healy from 2007-06-19 to 2007-06-25, departing from Dutch Harbor, AK and returning to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for RR1214: Multibeam data collected aboard Roger Revelle from 2012-11-05 to 2012-11-16, departing from Nuku Hiva, French Polynesia and returning to San Diego, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for TOGA92T: Multibeam data collected aboard Discoverer from 1992-10-16 to 1992-12-04, departing from Manzanillo, Mexico and returning to Port Salinas, Ecuador

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for KN168: Multibeam data collected aboard Knorr from 2002-09-27 to 2002-10-18, departing from Woods Hole, MA and returning to Woods Hole, MA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for B00306: Multibeam data collected aboard Whiting from 1992-05-29 to 1992-07-16, departing from Norfolk, VA and returning to Norfolk, VA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for EW9008: Multibeam data collected aboard Maurice Ewing from 1990-09-29 to 1990-10-26, departing from Bergen, Norway and returning to Newark, NJ

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for NT05-06: Multibeam data collected aboard Natsushima from 2005-05-22 to 2005-05-27, departing from Unknown Port and returning to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for GEO13_01: Multibeam data collected aboard Geo from 2013-05-03 to 2013-05-19, departing from Dun Laoghaire, Ireland and returning to Howth, Ireland

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for TN261: Multibeam data collected aboard Thomas G. Thompson from 2011-01-06 to 2011-01-14, departing from Honolulu, HI and returning to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for B00233: Multibeam data collected aboard Mt. Mitchell from 1990-08-15 to 1990-08-28, departing from Norfolk, VA and returning to Norfolk, VA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for NF-07-04-PMEL: Multibeam data collected aboard Nancy Foster from 2007-03-09 to 2007-03-25, departing from San Juan, Puerto Rico and returning to Mayaguez, Puerto Rico

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for KIWI09RR: Multibeam data collected aboard Roger Revelle from 1998-02-13 to 1998-03-19, departing from Lyttelton, New Zealand and returning to Lyttelton, New Zealand

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for EX1401: Multibeam data collected aboard Okeanos Explorer from 2014-02-06 to 2014-02-09, departing from North Kingstown, RI and returning to North Kingstown, RI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for PPTU02WT: Multibeam data collected aboard Thomas Washington from 1985-10-19 to 1985-11-17, departing from Manzanillo, Mexico and returning to Manzanillo, Mexico

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for NBP0209: Multibeam data collected aboard Nathaniel B. Palmer from 2002-12-11 to 2002-12-29, departing from Lyttelton, New Zealand and returning to McMurdo Station, Antarctica

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for B00276: Multibeam data collected aboard Whiting from 1991-05-29 to 1991-05-30, departing from Norfolk, VA and returning to Norfolk, VA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for EW9407: Multibeam data collected aboard Maurice Ewing from 1994-06-11 to 1994-06-25, departing from San Francisco, CA and returning to Eureka, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for H11324: Multibeam data collected aboard Thomas Jefferson from 2004-04-01 to 2004-04-30, departing from Galveston, TX and returning to Galveston, TX

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for NF-07-11-IL: Multibeam data collected aboard Nancy Foster from 2007-07-30 to 2007-08-10, departing from Unknown Port and returning to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for AMLR90T: Multibeam data collected aboard Surveyor from 1989-12-09 to 1990-04-08, departing from Iquique, Chile and returning to San Diego, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for PAT0903E: Multibeam data collected aboard Pathfinder from 2009-07-07 to 2009-08-06, departing from Unknown Port and returning to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for ZHNG08RR: Multibeam data collected aboard Roger Revelle from 2005-06-17 to 2005-07-17, departing from Yokohama, Japan and returning to Yokohama, Japan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for EW0405: Multibeam data collected aboard Maurice Ewing from 2004-06-06 to 2004-06-11, departing from San Juan, Puerto Rico and returning to Tampa, FL

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for MGL1504: Multibeam data collected aboard Marcus G. Langseth from 2015-04-06 to 2015-04-06, departing from Jacksonville, FL and returning to Charleston, SC

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for HI-05-03: Multibeam data collected aboard Hi'ialakai from 2005-05-14 to 2005-06-07, departing from Unknown Port and returning to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for NF0804_mona: Multibeam data collected aboard Nancy Foster from 2008-02-24 to 2008-03-08, departing from San Juan, Puerto Rico and returning to San Juan, Puerto Rico

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for HLY07TB: Multibeam data collected aboard Healy from 2007-03-09 to 2007-03-16, departing from Seattle, WA and returning to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for B00179: Multibeam data collected aboard Mt. Mitchell from 1989-05-11 to 1989-06-20, departing from Norfolk, VA and returning to Norfolk, VA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for Haleakel: Multibeam data collected aboard Ocean Alert from 1998-02-25 to 1998-02-28, departing from Unknown Port and returning to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for KN173L02: Multibeam data collected aboard Knorr from 2003-10-23 to 2003-11-14, departing from Port of Spain, Trinidad and Tobago and returning to Woods Hole, MA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for AT03L24: Multibeam data collected aboard Atlantis from 1998-07-29 to 1998-08-09, departing from Astoria, OR and returning to Astoria, OR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for AT18-18: Multibeam data collected aboard Atlantis from 2012-02-01 to 2012-02-07, departing from Port Everglades, FL and returning to Woods Hole, MA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for B00075: Multibeam data collected aboard Surveyor from 1986-09-20 to 1986-10-22, departing from Seattle, WA and returning to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for AT07L33: Multibeam data collected aboard Atlantis from 2003-04-17 to 2003-04-18, departing from Bridgetown, Barbados and returning to Bridgetown, Barbados

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for HLY09TB: Multibeam data collected aboard Healy from 2009-03-04 to 2009-03-09, departing from Seattle, WA and returning to Kodiak, AK

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for AT03L35: Multibeam data collected aboard Atlantis from 1999-06-20 to 1999-07-13, departing from San Diego, CA and returning to Astoria, OR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for NF-08-14-OE: Multibeam data collected aboard Nancy Foster from 2008-09-05 to 2008-10-02, departing from Unknown Port and returning to Unknown Port

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for RB0701: Multibeam data collected aboard Ronald Brown from 2007-03-22 to 2007-04-10, departing from Charleston, SC and returning to San Juan, Puerto Rico

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for EX1504L1: Multibeam data collected aboard Okeanos Explorer from 2015-07-10 to 2015-07-24, departing from Honolulu, HI and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for TUNE02WT: Multibeam data collected aboard Thomas Washington from 1991-07-17 to 1991-08-25, departing from Papeete, French Polynesia and returning to Papeete, French Polynesia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for SKQ201510S: Multibeam data collected aboard Sikuliaq from 2015-07-20 to 2015-08-22, departing from Nome, AK and returning to Nome, AK

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for TN243: Multibeam data collected aboard Thomas G. Thompson from 2009-11-07 to 2009-11-09, departing from Seattle, WA and returning to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for B00202: Multibeam data collected aboard Mt. Mitchell from 1989-09-28 to 1989-10-17, departing from Norfolk, VA and returning to Norfolk, VA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for B00012: Multibeam data collected aboard Davidson from 1985-05-02 to 1985-06-01, departing from Seattle, WA and returning to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for KN162L11: Multibeam data collected aboard Knorr from 2001-02-11 to 2001-03-15, departing from Mombassa, Kenya and returning to Seychelles

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for SOJN02MV: Multibeam data collected aboard Melville from 1996-10-28 to 1996-11-21, departing from Papeete, French Polynesia and returning to Valparaiso, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for GLOR04MV: Multibeam data collected aboard Melville from 1993-01-11 to 1993-02-03, departing from Papeete, French Polynesia and returning to Papeete, French Polynesia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for KM0818: Multibeam data collected aboard Kilo Moana from 2008-09-08 to 2008-09-22, departing from Port Hueneme, CA and returning to Port Hueneme, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for KN217: Multibeam data collected aboard Knorr from 2014-04-07 to 2014-04-19, departing from Woods Hole, MA and returning to Woods Hole, MA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for AT12: Multibeam data collected aboard Atlantis from 2005-10-20 to 2005-10-31, departing from Seattle, WA and returning to Woods Hole, MA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for MGL0906: Multibeam data collected aboard Marcus G. Langseth from 2009-05-04 to 2009-06-04, departing from Kao-hsiung, Taiwan and returning to Kao-hsiung, Taiwan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for MV1308: Multibeam data collected aboard Melville from 2013-06-12 to 2013-07-11, departing from San Diego, CA and returning to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for NF-13-01: Multibeam data collected aboard Nancy Foster from 2013-02-25 to 2013-03-01, departing from San Juan, Puerto Rico and returning to San Juan, Puerto Rico

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for MGL1108: Multibeam data collected aboard Marcus G. Langseth from 2011-05-26 to 2011-06-03, departing from San Diego, CA and returning to Kodiak, AK

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for RC2602: Multibeam data collected aboard Robert Conrad from 1985-02-04 to 1985-02-26, departing from Ascension Island and returning to Bridgetown, Barbados

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for KN145L4: Multibeam data collected aboard Knorr from 1994-11-19 to 1994-11-22, departing from Fremantle, Australia and returning to Fremantle, Australia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for AT03L30: Multibeam data collected aboard Atlantis from 1998-12-16 to 1999-01-21, departing from Manzanillo, Mexico and returning to Easter Island, Chile

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for AT11L26: Multibeam data collected aboard Atlantis from 2005-04-23 to 2005-05-15, departing from Manzanillo, Mexico and returning to Puntarenas, Costa Rica

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for EX1402L3: Multibeam data collected aboard Okeanos Explorer from 2014-04-10 to 2014-05-01, departing from Pascagoula, MS and returning to St. Petersburg, FL

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for KM0406: Multibeam data collected aboard Kilo Moana from 2004-03-05 to 2004-03-14, departing from Honolulu, HI and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for AT07L36: Multibeam data collected aboard Atlantis from 2003-06-21 to 2003-07-08, departing from St. George's, Bermuda and returning to Woods Hole, MA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for A125L39: Multibeam data collected aboard Atlantis II from 1992-02-23 to 1992-02-29, departing from Manzanillo, Mexico and returning to Manzanillo, Mexico

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for AT07L04: Multibeam data collected aboard Atlantis from 2001-11-05 to 2001-12-03, departing from Manzanillo, Mexico and returning to Manzanillo, Mexico

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for AT07L20: Multibeam data collected aboard Atlantis from 2002-08-29 to 2002-09-23, departing from Astoria, OR and returning to Newport, OR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for AT11L32: Multibeam data collected aboard Atlantis from 2005-09-08 to 2005-09-19, departing from Seattle, WA and returning to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for AT07L09: Multibeam data collected aboard Atlantis from 2002-04-18 to 2002-04-20, departing from San Diego, CA and returning to San Diego, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for KN151L3: Multibeam data collected aboard Knorr from 1997-07-17 to 1997-08-09, departing from Halifax, Canada and returning to Port of Spain, Trinidad and Tobago

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for AT07L32: Multibeam data collected aboard Atlantis from 2003-03-25 to 2003-04-14, departing from Freeport, Bahamas and returning to Bridgetown, Barbados

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for KN166L02: Multibeam data collected aboard Knorr from 2002-01-05 to 2002-01-25, departing from Fort Lauderdale, FL and returning to Fort Lauderdale, FL

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for KN177L02: Multibeam data collected aboard Knorr from 2004-05-08 to 2004-05-18, departing from Bergen, Norway and returning to Bergen, Norway

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for KN162L15: Multibeam data collected aboard Knorr from 2001-05-07 to 2001-05-20, departing from Seychelles and returning to Istanbul, Turkey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for AT3L53: Multibeam data collected aboard Atlantis from 2000-06-10 to 2000-07-12, departing from Astoria, OR and returning to Astoria, OR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for EX1502L3: Multibeam data collected aboard Okeanos Explorer from 2015-04-09 to 2015-04-30, departing from San Juan, Puerto Rico and returning to San Juan, Puerto Rico

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for AT11L28: Multibeam data collected aboard Atlantis from 2005-06-07 to 2005-06-16, departing from Puntarenas, Costa Rica and returning to Puntarenas, Costa Rica

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for AT11L09: Multibeam data collected aboard Atlantis from 2004-03-15 to 2004-04-01, departing from Puntarenas, Costa Rica and returning to Manzanillo, Mexico

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for AT3L60: Multibeam data collected aboard Atlantis from 2000-11-11 to 2000-12-16, departing from St. George's, Bermuda and returning to Woods Hole, MA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for KN158L5: Multibeam data collected aboard Knorr from 1998-07-18 to 1998-07-27, departing from Reykjavik, Iceland and returning to Woods Hole, MA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for LFEX02MV: Multibeam data collected aboard Melville from 2004-10-16 to 2004-11-08, departing from Honolulu, HI and returning to San Diego, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for KM1123: Multibeam data collected aboard Kilo Moana from 2011-08-19 to 2011-08-25, departing from Honolulu, HI and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for RR0903: Multibeam data collected aboard Roger Revelle from 2009-03-20 to 2009-05-13, departing from Cape Town, South Africa and returning to Fremantle, Australia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for MV0911: Multibeam data collected aboard Melville from 2009-11-21 to 2010-01-02, departing from Brisbane, Australia and returning to Papeete, French Polynesia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for VANC33MV: Multibeam data collected aboard Melville from 2004-07-29 to 2004-08-27, departing from Honolulu, HI and returning to San Diego, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for EW0208: Multibeam data collected aboard Maurice Ewing from 2002-08-12 to 2002-09-06, departing from Newport, OR and returning to Newport, OR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for KM1210: Multibeam data collected aboard Kilo Moana from 2012-05-30 to 2012-06-09, departing from Honolulu, HI and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for KN197-04: Multibeam data collected aboard Knorr from 2010-02-19 to 2010-03-12, departing from Bridgetown, Barbados and returning to Fortaleza, Brazil

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for EW0408: Multibeam data collected aboard Maurice Ewing from 2004-08-22 to 2004-09-23, departing from Newport, OR and returning to Kodiak, AK

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  1. Multibeam collection for RR1208: Multibeam data collected aboard Roger Revelle from 2012-06-28 to 2012-07-17, departing from Danang, Vietnam and returning to Apia, Samoa

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  2. Multibeam collection for B00150: Multibeam data collected aboard Surveyor from 1988-06-30 to 1988-07-12, departing from Seattle, WA and returning to Seattle, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  3. Multibeam collection for KM0921: Multibeam data collected aboard Kilo Moana from 2009-08-23 to 2009-09-16, departing from Honolulu, HI and returning to Honolulu, HI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  4. Multibeam collection for SMNT01WT: Multibeam data collected aboard Thomas Washington from 1983-06-17 to 1983-06-28, departing from San Diego, CA and returning to San Diego, CA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  5. Multibeam collection for EX1301: Multibeam data collected aboard Okeanos Explorer from 2013-03-18 to 2013-04-05, departing from North Kingstown, RI and returning to North Kingstown, RI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  6. Multibeam collection for EX1502L1: Multibeam data collected aboard Okeanos Explorer from 2015-02-23 to 2015-03-11, departing from North Kingstown, RI and returning to San Juan, Puerto Rico

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  7. Multibeam collection for EX1304Leg1: Multibeam data collected aboard Okeanos Explorer from 2013-07-08 to 2013-07-25, departing from North Kingstown, RI and returning to New York, NY

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  8. Multibeam collection for EX1404L3: Multibeam data collected aboard Okeanos Explorer from 2014-09-16 to 2014-10-07, departing from Baltimore, MD and returning to North Kingstown, RI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  9. Multibeam collection for EX1404L1: Multibeam data collected aboard Okeanos Explorer from 2014-08-09 to 2014-08-30, departing from North Kingstown, RI and returning to North Kingstown, RI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  10. Multibeam collection for HEN04-2: Multibeam data collected aboard Henson from 2004-09-25 to 2004-10-21, departing from Newport, RI and returning to Norfolk, VA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  11. Multibeam collection for EX1206: Multibeam data collected aboard Okeanos Explorer from 2012-11-02 to 2012-11-20, departing from North Kingstown, RI and returning to North Kingstown, RI

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  12. Multibeam collection for HNRO06RR: Multibeam data collected aboard Roger Revelle from 1999-06-06 to 1999-06-15, departing from Pusan, South Korea and returning to Pusan, South Korea

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  13. Multibeam collection for HNRO05RR: Multibeam data collected aboard Roger Revelle from 1999-05-19 to 1999-06-03, departing from Pusan, South Korea and returning to Pusan, South Korea

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  14. Multibeam collection for COOK09MV: Multibeam data collected aboard Melville from 2001-06-21 to 2001-07-05, departing from Pusan, South Korea and returning to Pusan, South Korea

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  15. Multibeam collection for HNRO14RR: Multibeam data collected aboard Roger Revelle from 2000-01-16 to 2000-02-05, departing from Pusan, South Korea and returning to Pusan, South Korea

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  16. Multibeam collection for HNRO04RR: Multibeam data collected aboard Roger Revelle from 1999-05-05 to 1999-05-13, departing from Pusan, South Korea and returning to Pusan, South Korea

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  17. Multibeam collection for HNRO07RR: Multibeam data collected aboard Roger Revelle from 1999-06-24 to 1999-07-17, departing from Pusan, South Korea and returning to Pusan, South Korea

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  18. Multibeam collection for HLY09TD: Multibeam data collected aboard Healy from 2009-07-06 to 2009-07-25, departing from Seattle, WA and returning to Barrow, AK

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  19. Multibeam collection for HLY05TD: Multibeam data collected aboard Healy from 2005-07-27 to 2005-07-31, departing from Barrow, AK and returning to Dutch Harbor, AK

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...

  20. Multibeam collection for HLY14TD: Multibeam data collected aboard Healy from 2014-07-31 to 2014-08-03, departing from Dutch Harbor, AK and returning to Seward, AK

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is part of a larger set of data called the Multibeam Bathymetry Database (MBBDB) where other similar data can be found at...