{ "documentation": "https://dmtc-api.edacnm.org/api/resources/documentation.html", "hits-total": 238, "hits-returned": 10, "facets": { "authors.givenName": { "Amber": 9, "David": 9, "Matthew": 9, "Sean": 9, "Sarah": 8, "Angelina": 7, "Erika": 7, "Robert R.": 7, "Jonathan": 6, "Juan": 6, "Katrin": 6, "Martin": 6, "Robert": 5, "Ruth E.": 5, "Amita": 4, "Sergey": 4, "Erin": 3, "Nancy": 3, "Nancy J.": 3, "Sergei": 3, "Abilene Thiele Concepcion": 2, "Amir": 2, "Ana": 2, "Andrew": 2, "Barbara": 2, "Brian": 2, "Curt": 2, "Daniel": 2, "Heather": 2, "James": 2, "Jeff": 2, "Jens": 2, "Karen": 2, "Lola": 2, "Lynn": 2, "Marieke": 2, "Megan Carter": 2, "Melanie": 2, "Nick": 2, "Paul": 2, "Pawan": 2, "Peter": 2, "Suchith": 2, "Suresh K.S.": 2, "Tim": 2, "Tyler": 2, "W. Christopher": 2, "Xianfeng": 2, "Abigail": 1, "Adam": 1, "Adrian": 1, "Alastair": 1, "Alexander": 1, "Alexandre": 1, "Alisa": 1, "Amanda": 1, "Amandine": 1, "Andre": 1, "Andrea": 1, "Andr\u00e9": 1, "Anne": 1, "Anne Sofie Fink": 1, "Anton": 1, "Barry": 1, "Ben": 1, "Bill": 1, "Brock": 1, "Carl": 1, "Carol": 1, "Carol X.": 1, "Cees H. J.": 1, "Christopher": 1, "Cindy": 1, "Conor": 1, "Constance": 1, "Constanze": 1, "Craig": 1, "Danie": 1, "Davor": 1, "Deng": 1, "Derrick": 1, "Diana": 1, "Douglas": 1, "Ellen": 1, "Ellie": 1, "Enrique": 1, "Eric": 1, "Ewa": 1, "Fernando-Ariel": 1, "Filip": 1, "Francesco": 1, "Frank": 1, "Friederike": 1, "Gabriela": 1, "Geoffrey": 1, "Gerben": 1, "Gert Jan": 1, "Graeme": 1, "Gry": 1 }, "authors.familyName": { "Mayernik": 9, "McCartney": 9, "Ball": 7, "Downs": 7, "Kraft": 7, "McCullum": 7, "Jones": 6, "Leinweber": 6, "Podes": 6, "Duerr": 5, "Cook": 4, "Mehta": 4, "Sukhonosov": 4, "Torres-Perez": 4, "Belov": 3, "Donnelly": 3, "Hoebelheinrich": 3, "Smith": 3, "Anand": 2, "Banks": 2, "Behnamian": 2, "Biddle": 2, "Eisen": 2, "Follette-Cook": 2, "Gray": 2, "Gupta": 2, "Guy": 2, "Hammitzsch": 2, "Jiao": 2, "Lenhardt": 2, "Luis Torres Perez": 2, "McNairn": 2, "Michener": 2, "Olsen": 2, "Orlando": 2, "Perez": 2, "Prados": 2, "Shockey": 2, "Stevens": 2, "Tedds": 2, "Tilmes": 2, "Vannan": 2, "A J Wilson": 1, "Ahalt": 1, "Alejandra Galeano": 1, "Andaur": 1, "Arnesen": 1, "Arnfield": 1, "Arrowsmith": 1, "Ayris": 1, "Bagley": 1, "Bangert": 1, "Bartoli": 1, "Beagrie": 1, "Beaulieu": 1, "Benoit": 1, "Benson": 1, "Bishop": 1, "Blanton": 1, "Blevins": 1, "Boettiger": 1, "Boon": 1, "Boulton": 1, "Bowman": 1, "Brophy": 1, "Brullemans-Spansier": 1, "Brvar": 1, "Bryant": 1, "Budden": 1, "Budroni": 1, "Bulley": 1, "Burton": 1, "Carr": 1, "Chodacki": 1, "Chow": 1, "Christiansen": 1, "Christopherson": 1, "Clark": 1, "Clarke": 1, "Copley": 1, "Cousijn": 1, "Coutin": 1, "Crosby": 1, "Cukier": 1, "Curdt": 1, "D Onghia": 1, "Dalmasso": 1, "Davidson": 1, "Davis Pierel": 1, "Deelman": 1, "Demchenko": 1, "Dennis": 1, "Denton": 1, "Dierkes": 1, "Dillo": 1, "Ding": 1, "Doorn": 1, "Duda": 1, "Dumontier": 1 }, "author_org.name": { "NASA Applied Remote Sensing Training Program (ARSET)": 21, "Facilitate Open Science Training for European Research (FOSTER)": 11, "Technische Informationsbibliothek (TIB) AV-Portal": 8, "Digital Curation Centre": 6, "NASA ORNL DAAC (Oak Ridge National Laboratory Distributed Active Archive Center)": 4, "Environmental Data Initiative (EDI)": 3, "Interdisciplinary Earth Data Alliance (IEDA)": 3, "My Geo Hub": 3, "Ocean Teacher Global Academy": 3, "Russian Federation": 3, "Australian National Data Service (ANDS)": 2, "EDINA - University of Edinburgh": 2, "EUDAT": 2, "GODAN Working Group on Capacity Development": 2, "ISRIC World Soil Information": 2, "LEARN Project (Leaders Activating Research Networks)": 2, "LabArchives": 2, "National Network of Libraries of Medicine (NNLM)": 2, "National Oceanic and Atmospheric Administration (NOAA)": 2, "Open Science Framework (OSF)": 2, "University of Antwerp": 2, "University of Glasgow": 2, "University of New Mexico": 2, "sciNote": 2, "Australian Research Data Commons (ARDC)": 1, "BlueSky to BluePrint": 1, "British Library (BL)": 1, "CIO Council (U.S.)": 1, "Cal Poly, San Luis Obispo": 1, "Center for Chemical Process Safety": 1, "Danish National Archives/Danish Data Archive (DDA)": 1, "Dartmouth College Libraries": 1, "DataCamp": 1, "Dauphin Island Sea Lab": 1, "Delft University of Technology": 1, "Department of Scientific Publication, University of Texas MD Anderson Cancer Center": 1, "ESRI": 1, "Elsevier": 1, "European Commission": 1, "General Assembly": 1, "GeoBeyond": 1, "Global Open Data for Agriculture and Nutrition (GODAN)": 1, "Harvard Medical School": 1, "Incorporated Research Institutions for Seismology (IRIS)": 1, "Information Sciences Institute (ISI), University of Southern California": 1, "Inter-University Consortium for Political and Social Research (ICPSR)": 1, "International DOI Foundation (IDF)": 1, "Journal of Open Research Software": 1, "Lab Folder": 1, "Lamont-Doherty Earth Observatory at Columbia University": 1, "Library Carpentry": 1, "Massachusetts Institute of Technology (MIT) Libraries": 1, "Mazama Science": 1, "Mozilla Science Lab": 1, "NYU Health Sciences Library": 1, "National Agriculture Library, United States Department of Agriculture (USDA)": 1, "National Centre for the Replacement, Refinement, and Reduction of Animals for Research (NC3Rs)": 1, "National Library of Finland": 1, "Netherlands Biodiversity Information Facility (NLBIF)": 1, "Netherlands Coalition for Digital Preservation": 1, "Network of Data and Information Curation Communities (NeDICC)": 1, "Norwegian Centre for Research Data (NSD)": 1, "Nottingham University": 1, "OCLC Research": 1, "ORCID, Inc.": 1, "Oak Ridge National Laboratory": 1, "OntoSoft Team": 1, "Open Data Institute": 1, "Piled Higher and Deeper Publishing, LLC": 1, "Portage Network": 1, "Purdue University": 1, "RStudio": 1, "ResearchSpace": 1, "SNSB IT Center": 1, "San Diego Supercomputer Center": 1, "Smithsonian Libraries": 1, "Stanford University Libraries": 1, "Swedish National Data Service (SND)": 1, "System for Earth Sample Registration (SESAR)": 1, "Technical University of Denmark": 1, "The National Center for Ecological Analysis and Synthesis (NCEAS)": 1, "The Paleobiology Database": 1, "U.K. Data Services (UKDS)": 1, "U.S. Bureau of Reclamation": 1, "U.S. Fish and Wildlife Service": 1, "U.S. Geological Survey": 1, "University of Arizona Libraries": 1, "University of California Curation Center (UC3)": 1, "University of California, Berkeley": 1, "University of California, Davis": 1, "University of California, Los Angeles Library": 1, "University of Cambridge": 1, "University of Central Florida Libraries": 1, "University of Cologne": 1, "University of Florida Research Computing": 1, "University of Iowa Libraries": 1, "University of North Carolina at Chapel Hill": 1, "University of Pretoria": 1, "University of Sheffield": 1, "Vanderbilt University": 1 }, "subject": { "Physical Sciences and Mathematics: Earth Sciences": 63, "Education: Science and Mathematics Education": 21, "Medicine and Health Sciences": 10, "Physical Sciences and Mathematics: Environmental Sciences": 5, "Engineering": 4, "Arts and Humanities": 3, "Engineering: Aerospace Engineering": 3, "Engineering: Chemical Engineering": 3, "Social and Behavioral Sciences": 3, "Arts and Humanities: History of Art, Architecture, and Archaeology": 2, "Life Sciences: Agriculture": 2, "Life Sciences: Microbiology": 2, "Life Sciences: Nutrition": 2, "Physical Sciences and Mathematics: Oceanography and Atmospheric Sciences and Meteorology": 2, "Engineering: Biomedical Engineering and Bioengineering": 1, "Engineering: Electrical and Computer Engineering": 1, "Life Sciences": 1, "Life Sciences: Genetics and Genomics": 1, "Physical Sciences and Mathematics: Computer Sciences": 1, "Physical Sciences and Mathematics: Mathematics": 1, "Arts and Humanities: Digital Humanities": 0, "Arts and Humanities: History": 0, "Arts and Humanities: Other Languages, Societies, and Cultures": 0, "Engineering: Bioresource and Agricultural Engineering": 0, "Engineering: Computer Engineering": 0, "Medicine and Health Sciences: Biomedical Science": 0, "Physical Sciences and Mathematics": 0, "Physical Sciences and Mathematics: Astrophysics and Astronomy": 0, "Physical Sciences and Mathematics: Statistics and Probability": 0, "Social and Behavioral Sciences: Linguistics": 0, "Social and Behavioral Sciences: Agricultural and Resource Economics": 0, "Social and Behavioral Sciences: Library and Information Science": 0 }, "keywords": { "Data management": 95, "Data access": 66, "Data management planning": 62, "Data sharing": 62, "Data reuse - Core Trustworthy Data Repositories Requirements": 43, "Accessible data - FAIR Data Principle": 34, "Data publication": 32, "Open data": 31, "Data collection": 27, "Metadata": 26, "Re-usable data - FAIR Data Principle": 25, "Data archiving": 24, "Data citation": 24, "Data management planning tools": 24, "Data storage": 24, "Data discovery and identification - Core Trustworthy Data Repositories Requirements": 22, "Data lifecycle": 22, "Data access methods": 21, "Remote sensing": 21, "Satellite imagery": 21, "Data handling": 19, "Data preservation": 19, "Environmental management": 19, "Persistent Identifiers (PID)": 19, "Data analysis": 18, "Workflows - Core Trustworthy Data Repositories Requirements": 18, "Capacity building": 17, "Data portals": 17, "Data usage": 17, "Findable data - FAIR Data Principle": 17, "Data formats": 16, "Land management": 16, "Open access": 16, "Cyberinfrastructure to enable FAIR data principles": 14, "Data quality - Core Trustworthy Data Repositories Requirements": 14, "Organizing data": 14, "Continuity of access - - Core Trustworthy Data Repositories Requirements": 13, "Interoperable data - FAIR Data Principle": 13, "Licenses - Core Trustworthy Data Repositories Requirements": 13, "Agriculture data": 12, "Collaborative workflow": 11, "Conservation": 11, "Data policy": 11, "Discovery metadata": 11, "Environmental change records": 11, "Software management": 11, "Sustainable Development Goals (SDGs)": 11, "Biodiversity data": 10, "Data integrity and authenticity - Core Trustworthy Data Repositories Requirements": 10, "Digital preservation workflow": 10, "Expert guidance - Core Trustworthy Data Repositories Requirements": 10, "Confidentiality/Ethics - - Core Trustworthy Data Repositories Requirements": 9, "Data backup": 9, "Electronic lab notebook (ELN)": 9, "Metadata standards": 9, "Preservation plan - Core Trustworthy Data Repositories Requirements": 9, "R software": 8, "Community standards": 7, "Copyright of data": 7, "Data literacy": 7, "Data use restrictions": 7, "Landcover applications": 7, "Scientific publications": 7, "Scientific reproducibility": 7, "Security - Core Trustworthy Data Repositories Requirements": 7, "User guides for Earth science data": 7, "Workflow": 7, "Appraisal - Core Trustworthy Data Repositories Requirements": 6, "Data visualization tools": 6, "Federal agency data management requirements (U.S.)": 6, "Marine data": 6, "Metadata registries": 6, "Scientific record preservation": 6, "Soils data assessment systems": 6, "Soils software and data management applications": 6, "Big data": 5, "Climate data": 5, "Data curation": 5, "File naming": 5, "Flood mapping applications": 5, "Geographic Information System (GIS)": 5, "Scientific record archives": 5, "Technical infrastructure - Core Trustworthy Data Repositories Requirements": 5, "Access rights": 4, "Coastal data": 4, "Data loss": 4, "Data skills education": 4, "Data user community": 4, "Digital scholarship": 4, "Documented storage procedures - Core Trustworthy Data Repositories Requirements": 4, "Earthquake data": 4, "Food security data": 4, "Geoscience data": 4, "Nutrition data": 4, "Ocean data": 4, "Organizational infrastructure - - Core Trustworthy Data Repositories Requirements": 4, "PID data architecture": 4, "Python": 4, "Synthetic aperture radar data (SAR)": 4, "Aichi Biodiversity Targets (ABTs)": 3 }, "license": { "Creative Commons Attribution 4.0 International - CC BY 4.0": 40, "Creative Commons Attribution 3.0 United States - CC BY 3.0 US": 34, "Creative Commons Attribution 2.0 Generic - CC BY 2.0": 29, "Standard YouTube License": 27, "Creative Commons Attribution 3.0 Germany - CC BY 3.0 DE": 9, "Creative Commons Attribution-NonCommercial 4.0 International - CC BY-NC 4.0": 9, "Creative Commons Attribution-ShareAlike 4.0 International License - CC BY-SA 4.0": 9, "Creative Commons Attribution 3.0 Unported - CC BY 3.0": 8, "Creative Commons 1.0 Universal (Public Domain Dedication)": 3, "Creative Commons 0 - CC0 \"No Rights Reserved\" (Public Domain)": 2, "Creative Commons Attribution 2.5 UK:Scotland": 2, "Creative Commons Attribution-NonCommercial 4.0 International - CC BY-NC-SA 4.0": 1, "GNU Affero General Public License (AGPL)": 1, "Apache-2.0": 0, "BSD-3-Clause": 0, "Creative Commons Attribution-NoDerivatives 4.0 - CC BY-ND 4.0": 0, "Creative Commons Attribution-NonCommercial-ShareAlike 2.0 Unported - CC BY-NC-SA 2.0": 0, "Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported - CC BY-NC-SA 3.0": 0, "MIT License": 0 }, "usage_info": { "USGS Disclaimer - approved data released to public": 1, "Khan Academy Terms of Service": 0 }, "publisher": { "Federation of Earth Science Information Partners (ESIP Federation)": 34, "Facilitate Open Science Training for European Research (FOSTER)": 23, "NASA Applied Remote Sensing Training Program (ARSET)": 21, "Australian Research Data Commons (ARDC)": 10, "Digital Curation Centre": 9, "Technische Informationsbibliothek (TIB) AV-Portal": 9, "Gurdon Institute": 6, "Global Open Data for Agriculture and Nutrition (GODAN)": 4, "International Oceanographic Data and Information Exchange (IODE)": 4, "My Geo Hub": 4, "NASA ORNL DAAC (Oak Ridge National Laboratory Distributed Active Archive Center)": 4, "Science Gateway Community Institute (SGCI)": 4, "EUDAT": 3, "Environmental Data Initiative (EDI)": 3, "ISRIC World Soil Information": 3, "Interdisciplinary Earth Data Alliance (IEDA)": 3, "Open Topography": 3, "Project THOR": 3, "Zenodo": 3, "American Institute of Chemical Engineers (AIChE)": 2, "Coursera": 2, "DataONE": 2, "EDINA - University of Edinburgh": 2, "LEARN Project (Leaders Activating Research Networks)": 2, "National Network of Libraries of Medicine (NNLM)": 2, "Network of Data and Information Curation Communities (NeDICC)": 2, "Ocean Teacher Global Academy": 2, "AGACAD": 1, "ALCTS the Association for Library Collections and Technical Services": 1, "Association for Learning Technology": 1, "Association for Library Collections and Technical Services (ALCTS)": 1, "Belmont Forum": 1, "Center for Open Science (COS)": 1, "Consortium of European Social Science Data Archives European Infrastructure Consortium (CESSDA ERIC)": 1, "Dartmouth College Libraries": 1, "DataCamp": 1, "Dataverse": 1, "Digital Preservation Coalition": 1, "Dutch Techcentre for Life Sciences (DTL)": 1, "ESRI": 1, "Earth Science Information Partners (ESIP)": 1, "Elsevier": 1, "General Assembly": 1, "Harvard Medical School": 1, "Incorporated Research Institutions for Seismology (IRIS)": 1, "Institute for Social Research University of Michigan": 1, "International Association for Social Science Information Services and Technology (IASSIST)": 1, "Journal of Open Research Software": 1, "Lab Folder": 1, "Lamont-Doherty Earth Observatory at Columbia University": 1, "Library Carpentry": 1, "London School of Economics and Political Science": 1, "Mazama Science": 1, "Microsol Resources": 1, "Mozilla Science Lab": 1, "NYU Health Sciences Library": 1, "National Agriculture Library, United States Department of Agriculture (USDA)": 1, "National Oceanic and Atmospheric Administration (NOAA)": 1, "National Science Foundation (NSF)": 1, "OCLC Research": 1, "ORCID, Inc.": 1, "Open Science Framework (OSF)": 1, "Open Source Geospatial Foundation (OSGeo)": 1, "PLoS Computational Biology": 1, "Piled Higher and Deeper Publishing, LLC": 1, "Portage Network": 1, "Prezi": 1, "Regents of the University of California": 1, "Smithsonian Libraries": 1, "The Paleobiology Database": 1, "U.S. Bureau of Reclamation": 1, "U.S. Fish and Wildlife Service": 1, "U.S. Geological Survey": 1, "United States Government": 1, "University of Arizona Libraries": 1, "University of California Board of Regents": 1, "University of California, Davis": 1, "University of Central Florida Libraries": 1, "University of Florida Research Computing": 1, "University of Glasgow": 1, "University of Iowa Libraries": 1, "University of Sheffield": 1, "University of Texas": 1, "Woods Hole Scientific Community (WHOS)": 1, "2018 IEEE international conference on BIG DATA, Seattle WA": 0, "ACTION": 0, "Adastra Academy": 0, "Agriculture Information Management Standards (AIMS)": 0, "Analytics Vidhya": 0, "Archaeology Data Service": 0, "Archive of the Indigenous Languages of Latin America (AILLA)": 0, "Arizona State University": 0, "Association of Research Managers and Administrators(ARMA)": 0, "Australian National Data Service (ANDS)": 0, "Bioconductor": 0, "Blue-Cloud": 0, "Brazilian National Institute of Space Research (INPE)": 0, "British Geological Survey": 0, "CEOS": 0, "CIMdata": 0 }, "accessibility_features.name": { "Structure and Navigation - aids to structure and navigation of the learning resource content, e.g., by including an index or table of contents.": 5, "Augmentation - provision of content in learning resource by alternate means, e.g., by alternative text for a graphic image.": 0, "Control - features that allow the user to control access to the learning resource, e.g., by pausing a timed interface when needed.": 0, "Transformation - features that allow the content to be changed for ease of access, e.g., by using large print fonts.": 0 }, "language_primary": { "en": 232, "es": 5, "fr": 1, "af": 0, "de": 0 }, "languages_secondary": { "es": 14, "fr": 7, "en": 6, "pt": 3, "de": 2, "it": 1, "ar": 0, "nl": 0 }, "ed_frameworks.name": { "ICSU - World Data System Training Resources Guide": 58, "FAIR Data Principles": 45, "ESIP Data Management for Scientists Short Course": 34, "USGS Science Support Framework": 2, "DataONE Education Modules": 0, "The Digital Preservation Network": 0 }, "author_names": { "Matthew Mayernik": 9, "Sean McCartney": 9, "Amber McCullum": 7, "Angelina Kraft": 7, "David Ball": 7, "Robert R. Downs": 7, "Erika Podes": 6, "Katrin Leinweber": 6, "Ruth E. Duerr": 5, "Sarah Jones": 5, "Amita Mehta": 4, "Juan Torres-Perez": 4, "Robert Cook": 4, "Sergey Sukhonosov": 4, "Martin Donnelly": 3, "Nancy J. Hoebelheinrich": 3, "Sergei Belov": 3, "Abilene Thiele Concepcion Perez": 2, "Amir Behnamian": 2, "Ana Prados": 2, "Curt Tilmes": 2, "Heather McNairn": 2, "Jonathan Eisen": 2, "Jonathan Tedds": 2, "Juan Luis Torres Perez": 2, "Lola Olsen": 2, "Marieke Guy": 2, "Martin Hammitzsch": 2, "Megan Carter Orlando": 2, "Melanie Follette-Cook": 2, "Nick Shockey": 2, "Pawan Gupta": 2, "Sarah Banks": 2, "Suchith Anand": 2, "Suresh K.S. Vannan": 2, "Tyler Stevens": 2, "W. Christopher Lenhardt": 2, "Xianfeng Jiao": 2, "Abigail Benson": 1, "Adam Shepherd": 1, "Adrian Burton": 1, "Alastair Dunning": 1, "Alexander Louis Handwerger": 1, "Alexandre Faria De Oliveria": 1, "Alisa Surkis": 1, "Amanda Whitmire": 1, "Amandine Philippart De Foy": 1, "Amber Budden": 1, "Amber York": 1, "Andre Jellema": 1, "Andrea Denton": 1, "Andrew Gray": 1, "Andrew Janke": 1, "Andr\u00e9 Laperri\u00e8re": 1, "Anne McKenzie": 1, "Anne Sofie Fink Kjeldgaard": 1, "Anton Van de Putte": 1, "Barbara Simpson": 1, "Barbara S\u00e1nchez Sol\u00eds": 1, "Barry Smith": 1, "Ben Roberts-Pierel": 1, "Bill LeFurgy": 1, "Brian Blanton": 1, "Brian Lavoie": 1, "Brock Blevins": 1, "Carl Boettiger": 1, "Carol Willing": 1, "Carol X. Song": 1, "Cees H. J. Hof": 1, "Christopher Crosby": 1, "Cindy Schmidt": 1, "Conor Brophy": 1, "Constance Malpas": 1, "Constanze Curdt": 1, "Craig Willis": 1, "Danie Kinkade": 1, "Daniel Bangert": 1, "Daniel Garijo": 1, "David Carr": 1, "David Fergusson": 1, "David Tarrant": 1, "Davor Orlic": 1, "Deng Ding": 1, "Derrick Kearney": 1, "Diana LaScala-Gruenewald": 1, "Douglas R. Clark": 1, "Ellen Verbakel": 1, "Ellie Davis Pierel": 1, "Enrique Montes": 1, "Eric Jameson Fielding": 1, "Erika Podest": 1, "Erin McLean": 1, "Erin Robinson": 1, "Erin Satterthwaite": 1, "Ewa Deelman": 1, "Fernando-Ariel L\u00f3pez": 1, "Filip Schouwenaars": 1, "Francesco Bartoli": 1, "Frank Muller-Karger": 1, "Friederike Ehrhart": 1 }, "target_audience": { "Research scientist": 168, "Early-career research scientist": 148, "Mid-career research scientist": 123, "Graduate student": 122, "Research faculty": 100, "Data professional": 95, "Data manager": 94, "Librarian": 91, "Undergraduate student": 71, "Data policymaker": 46, "Data supporter": 37, "Repository manager": 35, "Citizen scientist": 34, "Educator": 33, "Technology expert group": 25, "Software engineer": 20, "Funding organization": 19, "Publisher": 12, "High school student": 3, "Middle school student": 1 }, "lr_type": { "Unit - long-range plan of instruction on a particular concept containing multiple, related lessons.": 0 }, "purpose": { "Professional Development - increasing knowledge and capabilities related to managing the data produced, used or re-used, curated and/or archived.": 238, "Assessment - the evaluation, measurement and documentation of the skills or knowledge about data management.": 0, "Instruction - detailed information about aspects or processes related to data management or data skills.": 0 }, "media_type": { "Presentation - representation of the particular way in which an author shows, describes or explains one or more concepts, e.g., a set of Powerpoint slides.": 130, "Text - an explanation of a concept or a story using human readable characters formed into words, usually distinguished from graphical images.": 25, "Event - time-based happening that is portrayed or covered by the learning resource, e.g., a webinar.": 21, "Collection - a group or set of items that comprise a single learning resource, e.g., a PDF version of a slide presentation, an audio file of the presentation and a textual representation of the oral transcription of the presentation.": 20, "Interactive Resource - requires a user to take action or make a request in order for the content to be understood, executed or experienced.": 19, "Moving Image - explains a concept or tells a story by using sound plus a sequence of visual images that give the illusion of continuous movement, e.g., movie.": 12, "Animation - a method of making a series of drawings, computer graphics or photographs appear to move.": 5, "Service - self-contained unit of functionality that enables operations or capabilities, e.g., searching for instruction or training resources on data management.": 2, "Dataset - collection of information organized in logical record and block structures for use by a computer.": 1, "Software - programs used to direct the operation of a computer and related devices.": 1, "Sound - an explanation of a concept or a story using audio means within the acoustic range available to humans, and differentiated from audio visual resources (i.e.,moving image).": 1, "Static Image - a single visual representation that does not change. Example: a poster explicating a concept.": 1, "Physical Object - entity that has a physical presence in the present, as opposed to an artifact (a physical object) of the past.": 0 }, "access_cost": { "false": 237, "true": 1 }, "status": { "true": 238, "false": 0 }, "pub_status": { "published": 238, "in-process": 0 } }, "results": [ { "title": "Biological Observation Data Standardization - A Primer for Data Managers", "status": 1, "pub_status": "published", "modification_date": "2022-06-21T10:59:03Z", "resource_modification_date": "1900-01-01T00:00:00Z", "url": "https://doi.org/10.6084/m9.figshare.16806712.v1", "access_cost": 0, "submitter_name": "Stace Beaulieu", "submitter_email": "stace@whoi.edu", "authors": [ { "givenName": "Abigail", "familyName": "Benson", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Diana", "familyName": "LaScala-Gruenewald", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Robert", "familyName": "McGuinn", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Erin", "familyName": "Satterthwaite", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Stace", "familyName": "Beaulieu", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Mathew", "familyName": "Biddle", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Lynn", "familyName": "deWitt", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Megan", "familyName": "McKinzie", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Enrique", "familyName": "Montes", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Hassan", "familyName": "Moustahfid", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Frank", "familyName": "Muller-Karger", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Tylar", "familyName": "Murray", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Anton", "familyName": "Van de Putte", "name_identifier": "", "name_identifier_type": "" } ], "author_names": [ "Abigail Benson", "Diana LaScala-Gruenewald", "Robert McGuinn", "Erin Satterthwaite", "Stace Beaulieu", "Mathew Biddle", "Lynn deWitt", "Megan McKinzie", "Enrique Montes", "Hassan Moustahfid", "Frank Muller-Karger", "Tylar Murray", "Anton Van de Putte" ], "author_org": { "name": "", "name_identifier": "", "name_identifier_type": "" }, "contact": { "name": "", "org": "esip-biodatastandards@lists.esipfed.org", "email": "" }, "abstract_data": "Lots of standards exist for use with biological data but navigating them can be difficult for data managers who are new to them. The Earth Science Information Partners (ESIP) Biological Data Standards Cluster developed this primer for managers of biological data to provide a quick, easy resource for navigating a selection of the standards that exist. The goal of the primer is to spread awareness about existing standards and is intended to be shared online and at conferences to increase the adoption of standards for biological data and make them FAIR.", "abstract_format": "filtered_html", "subject": "Life Sciences", "keywords": [ "Agriculture applications", "Biodiversity data", "Biological data", "Community standards", "Data formats", "Data sharing", "Data stewardship", "Earth observation data", "FAIR metrics" ], "license": "Creative Commons 0 - CC0 \"No Rights Reserved\" (Public Domain)", "usage_info": "", "citation": "Benson, Abigail; LaScala-Gruenewald, Diana; McGuinn, Robert; Satterthwaite, Erin; Beaulieu, Stace; Biddle, Mathew; et al. (2021): Biological Observation Data Standardization - A Primer for Data Managers. ESIP. Online resource. https://doi.org/10.6084/m9.figshare.16806712.v1", "locator_data": "10.6084/m9.figshare.16806712.v1", "locator_type": "DOI", "publisher": "", "version": "", "created": "2021-11-08T10:11:26", "published": "2021-10-19T00:00:00Z", "accessibility_features": [], "accessibility_summary": "", "language_primary": "en", "languages_secondary": [], "ed_frameworks": [ { "name": "FAIR Data Principles", "nodes": [ { "description": "", "name": "Accessible" }, { "description": "", "name": "Findable" }, { "description": "", "name": "Interoperable" }, { "description": "", "name": "Re-usable" } ], "type": "framework" } ], "target_audience": [ "Data manager", "High school student" ], "purpose": "Professional Development - increasing knowledge and capabilities related to managing the data produced, used or re-used, curated and/or archived.", "completion_time": "Up to 1 hour", "media_type": "Static Image - a single visual representation that does not change. Example: a poster explicating a concept.", "lr_type": "Lesson - detailed description of an element of instruction in a course, [could be] contained in a unit of one or more lessons, and used by a teacher to guide class instruction. Example: presentation slides on a topic.", "creator": "sbeaulieu", "md_record_id": "", "ratings": [], "rating": 0.0, "id": "05e285b9-4266-3842-8bc3-2e7739203f4e", "contributors": [], "contributor_orgs": [ { "name": "ESIP Biological Data Standards Cluster", "name_identifier": "N.A.", "name_identifier_type": "N.A.", "type": "Conceptualization" } ], "score": 1.9005997, "accesibility_summary": [], "country_of_origin": null, "credential_status": null, "notes": [] }, { "title": "Supporting Researchers in Discovering Data Repositories", "status": 1, "pub_status": "published", "modification_date": "2022-06-21T10:59:00Z", "resource_modification_date": "1900-01-01T00:00:00Z", "url": "https://www.dataone.org/webinars/repo-discovery/", "access_cost": 0, "submitter_name": "Zohreh Mehrabi", "submitter_email": "zmehrabi@unm.edu", "authors": [ { "givenName": "Amber", "familyName": "Budden", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Erin", "familyName": "McLean", "name_identifier": "", "name_identifier_type": "" } ], "author_names": [ "Amber Budden", "Erin McLean" ], "author_org": { "name": "", "name_identifier": "", "name_identifier_type": "" }, "contact": { "name": "", "org": "", "email": "" }, "abstract_data": "How do researchers go about identifying a repository to preserve their data? Do they have all the information they need to make an informed decision? Are there resources available to help?
\r\nThere is a myriad of repositories available to support data preservation and they differ across multiple axes. So which one is right for your data? The answer is large, ‘it depends’. But this can be frustrating to a new researcher looking to publish data for the first time. What questions need to be asked to detangle these dependencies and where can a researcher go for answers?
\r\nConversations and sessions at domain conferences have consistently suggested that researchers need more support in navigating the landscape of data repositories and with support from ESIP Funding Friday, we sought to do that. In this webinar, we will introduce a resource under development that aims to serve as a gateway for information about repository selection. With links to existing resources, games, and outreach materials, we aim to facilitate the discovery of data repositories and we welcome contributions to increase the value of this resource.", "abstract_format": "filtered_html", "subject": "", "keywords": [ "Data discovery and identification - Core Trustworthy Data Repositories Requirements", "Data management", "Data preservation", "Data reuse - Core Trustworthy Data Repositories Requirements", "Data storage" ], "license": "Creative Commons Attribution 4.0 International - CC BY 4.0", "usage_info": "", "citation": "", "locator_data": "", "locator_type": "", "publisher": "DataONE", "version": "", "created": "2021-02-22T11:35:35", "published": "2021-01-12T00:00:00Z", "accessibility_features": [], "accessibility_summary": "", "language_primary": "en", "languages_secondary": [], "ed_frameworks": [], "target_audience": [ "Citizen scientist", "Early-career research scientist", "Graduate student", "Librarian", "Publisher", "Repository manager", "Research scientist", "Undergraduate student" ], "purpose": "Professional Development - increasing knowledge and capabilities related to managing the data produced, used or re-used, curated and/or archived.", "completion_time": "Up to 1 hour", "media_type": "Event - time-based happening that is portrayed or covered by the learning resource, e.g., a webinar.", "lr_type": "Lesson - detailed description of an element of instruction in a course, [could be] contained in a unit of one or more lessons, and used by a teacher to guide class instruction. Example: presentation slides on a topic.", "creator": "zmehrabi", "md_record_id": "", "ratings": [], "rating": 0.0, "id": "ca9d6303-95de-3c60-a19d-66b607844873", "contributors": [], "contributor_orgs": [], "score": 1.9005997, "accesibility_summary": [], "country_of_origin": null, "credential_status": null, "notes": [] }, { "title": "RDM Onboarding Checklist", "status": 1, "pub_status": "published", "modification_date": "2022-06-21T10:58:59Z", "resource_modification_date": "1900-01-01T00:00:00Z", "url": "https://datamanagement.hms.harvard.edu/plan/rdm-onboarding-checklist", "access_cost": 0, "submitter_name": "Zohreh Mehrabi", "submitter_email": "zmehrabi@unm.edu", "authors": [ { "givenName": "Julie", "familyName": "Goldman", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Sarah", "familyName": "Hauserman", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Meghan", "familyName": "Kerr", "name_identifier": "", "name_identifier_type": "" } ], "author_names": [ "Julie Goldman", "Sarah Hauserman", "Meghan Kerr" ], "author_org": { "name": "Harvard Medical School", "name_identifier": "", "name_identifier_type": "" }, "contact": { "name": "", "org": "", "email": "" }, "abstract_data": "Research Data Management is essential for responsible research and should be introduced when starting a new project or joining a new lab. Managing data across a project and/ or a team allows for accurate communication about that project. This session will review the important steps for onboarding new employees/trainees to a lab or new projects. The key takeaway from this session will be how to incorporate these steps within your individual project or lab environment. While the principles are general, these documents focus on Harvard policies and resources. Internal and external links have been provided throughout the document as supplementary resources, including a glossary of terms. 
\r\n
\r\nThere are 2 checklists as follow: 
\r\nThe RDM Onboarding Checklist: Abridged Version serves as a condensed version of the comprehensive checklist described above. This version is intended to be used as an actionable checklist, employed after reviewing the onboarding processes and resources provided in the comprehensive checklist.
\r\nThe RDM Onboarding Checklist: Comprehensive Version serves as a general, research data management-focused guide to employee/trainee onboarding as they join a new lab or begin new projects (follow one or both of these as they apply to your situation). This comprehensive version is provided as an initial introduction to the onboarding process and to the breadth of available resources; this version is intended to be reviewed first, prior to utilizing the abridged version.
\r\n
\r\n Learning Objectives:\r\n\r\n", "abstract_format": "filtered_html", "subject": "", "keywords": [ "Data backup", "Data communication", "Data management", "Data management planning", "Data policy", "Data publication", "Data research", "Data sharing", "Data storage", "File naming", "Metadata standards", "Research lifecycle", "Researcher engagement", "Version control" ], "license": "Standard YouTube License", "usage_info": "", "citation": "", "locator_data": "", "locator_type": "", "publisher": "Harvard Medical School", "version": "", "created": "2021-02-08T15:28:31", "published": "2020-09-14T00:00:00Z", "accessibility_features": [], "accessibility_summary": "", "language_primary": "en", "languages_secondary": [], "ed_frameworks": [], "target_audience": [ "Citizen scientist", "Data manager", "Data professional", "Early-career research scientist", "Funding organization", "Librarian", "Mid-career research scientist", "Repository manager", "Research faculty", "Research scientist" ], "purpose": "Professional Development - increasing knowledge and capabilities related to managing the data produced, used or re-used, curated and/or archived.", "completion_time": "Up to 1 hour", "media_type": "Collection - a group or set of items that comprise a single learning resource, e.g., a PDF version of a slide presentation, an audio file of the presentation and a textual representation of the oral transcription of the presentation.", "lr_type": "Lesson - detailed description of an element of instruction in a course, [could be] contained in a unit of one or more lessons, and used by a teacher to guide class instruction. Example: presentation slides on a topic.", "creator": "zmehrabi", "md_record_id": "", "ratings": [], "rating": 0.0, "id": "ea45507f-2c11-3f2d-b800-74d3f9bdd89a", "contributors": [], "contributor_orgs": [], "score": 1.9005997, "accesibility_summary": [], "country_of_origin": null, "credential_status": null, "notes": [] }, { "title": "What we wish we had learned in Graduate School - a data management training roadmap for graduate students", "status": 1, "pub_status": "published", "modification_date": "2022-06-21T10:58:56Z", "resource_modification_date": "1900-01-01T00:00:00Z", "url": "https://doi.org/10.6084/m9.figshare.14384456.v1", "access_cost": 0, "submitter_name": "zohreh mehrabi", "submitter_email": "zmehrabi@unm.edu", "authors": [ { "givenName": "Ellie", "familyName": "Davis Pierel", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Ben", "familyName": "Roberts-Pierel", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Yuhan", "familyName": "Rao", "name_identifier": "", "name_identifier_type": "" } ], "author_names": [ "Ellie Davis Pierel", "Ben Roberts-Pierel", "Yuhan Rao" ], "author_org": { "name": "", "name_identifier": "", "name_identifier_type": "" }, "contact": { "name": "", "org": "", "email": "" }, "abstract_data": "
This Road Map is a dynamic guide to help graduate students wade through the ocean of data resources. This guide will help identify what data management practices graduate students should be considering at different graduate school milestones.
\r\n
\r\nData management training for graduate students is a very important but often undervalued area of graduate school education. Many graduate students will go on and become professionals who are using, producing, and/or managing data that have tremendous benefits for both the research community and society. However, our personal experiences as graduate students show that data lifecycle and data management training are not part of the core curriculum in graduate school. As Earth Science Information Partners (ESIP) Community Fellows, we understand that data management is a critical skill in earth science and we all wished we had an opportunity to integrate it from the beginning in our graduate school experience. To the issue of lack of formal data management training in graduate education, we convened a working session during the 2020 ESIP Summer Meeting called “What we wish we had learned in Graduate School?” The session was initially planned as a working session for early career professionals to share resources and lessons learned during our own graduate school experiences. The session has sparked broad interests from the Earth science data community and attracted participants across different career stages and with different levels of expertise. The outcome of the session has been summarized as a roadmap that follows the DataONE Data Lifecycle. This roadmap projects the data lifecycle into the traditional graduate school timeline and highlights the benefits and resources of data management training for each component in the data lifecycle. This roadmap for graduate data management training will be distributed via ESIP and be continued as part of the ESIP Community Program in the future to promote data management training for graduate students in Earth sciences and beyond.
\r\n
\r\nAlso available as a webinar from DataONE:  https://vimeo.com/481534921 
\r\n", "abstract_format": "filtered_html", "subject": "", "keywords": [ "Data collection", "Data lifecycle", "Data management" ], "license": "Creative Commons Attribution 4.0 International - CC BY 4.0", "usage_info": "", "citation": "Roberts-Pierel, Ben; Davis, Eleanor; Rao, Yuhan (2021): A Graduate Student's Road Map to Data Management Training. ESIP. Educational resource. https://doi.org/10.6084/m9.figshare.14384456.v1 ", "locator_data": "10.6084/m9.figshare.14384456.v1", "locator_type": "DOI", "publisher": "Earth Science Information Partners (ESIP)", "version": "", "created": "2020-11-25T10:13:03", "published": "2021-07-04T00:00:00Z", "accessibility_features": [], "accessibility_summary": "", "language_primary": "en", "languages_secondary": [], "ed_frameworks": [], "target_audience": [ "Data manager", "Educator", "Graduate student", "Librarian" ], "purpose": "Professional Development - increasing knowledge and capabilities related to managing the data produced, used or re-used, curated and/or archived.", "completion_time": "Up to 1 hour", "media_type": "Presentation - representation of the particular way in which an author shows, describes or explains one or more concepts, e.g., a set of Powerpoint slides.", "lr_type": "Lesson - detailed description of an element of instruction in a course, [could be] contained in a unit of one or more lessons, and used by a teacher to guide class instruction. Example: presentation slides on a topic.", "creator": "zmehrabi", "md_record_id": "", "ratings": [], "rating": 0.0, "id": "dd70d3a6-8313-3fab-87cd-4131fa7b2da0", "contributors": [], "contributor_orgs": [ { "name": "DataONE", "name_identifier": "N.A.", "name_identifier_type": "N.A.", "type": "Collaborator" } ], "score": 1.9005997, "accesibility_summary": [], "country_of_origin": null, "credential_status": null, "notes": [] }, { "title": "Content-based Identifiers for Iterative Forecasts: A Proposal", "status": 1, "pub_status": "published", "modification_date": "2022-06-21T10:58:55Z", "resource_modification_date": "1900-01-01T00:00:00Z", "url": "https://www.dataone.org/webinars/iterative-forecasts/", "access_cost": 0, "submitter_name": "zohreh Mehrabi", "submitter_email": "zmehrabi@unm.edu", "authors": [ { "givenName": "Carl", "familyName": "Boettiger", "name_identifier": "", "name_identifier_type": "" } ], "author_names": [ "Carl Boettiger" ], "author_org": { "name": "University of California, Berkeley", "name_identifier": "", "name_identifier_type": "" }, "contact": { "name": "", "org": "", "email": "" }, "abstract_data": "Iterative forecasts pose particular challenges for archival data storage and retrieval. In an iterative forecast, data about the past and present must be downloaded and fed into an algorithm that will output a forecast data product. Previous forecasts must also be scored against the realized values in the latest observations. Content-based identifiers provide a convenient way to consistently identify input and outputs and associated scripts. These identifiers are:
\r\n(1) location-agnostic – they don’t depend on a URL or other location-based authority (like DOI)
\r\n(2) reproducible – the same data file always has the same identifier
\r\n(3) frictionless – cheap and easy to generate with widely available software, no authentication or network connection
\r\n(4) sticky – the identifier cannot become unstuck or separated from the content
\r\n(5) compatible – most existing infrastructure, including DataONE, can quite readily use these identifiers.
\r\n
\r\nIn this webinar, the speaker will illustrate an example iterative forecasting workflow. In the process, he will highlight some newly developed R packages for making this easier.", "abstract_format": "filtered_html", "subject": "Physical Sciences and Mathematics: Environmental Sciences", "keywords": [ "Data archiving", "Data skills education", "Data storage", "Persistent Identifiers (PID)", "Programming", "R software" ], "license": "Creative Commons Attribution 4.0 International - CC BY 4.0", "usage_info": "", "citation": "", "locator_data": "", "locator_type": "", "publisher": "DataONE", "version": "", "created": "2020-11-12T10:35:13", "published": "2020-10-13T00:00:00Z", "accessibility_features": [], "accessibility_summary": "", "language_primary": "en", "languages_secondary": [], "ed_frameworks": [], "target_audience": [ "Citizen scientist", "Data manager", "Data professional", "Data supporter", "Early-career research scientist", "Graduate student", "Librarian", "Mid-career research scientist", "Repository manager", "Research scientist", "Undergraduate student" ], "purpose": "Professional Development - increasing knowledge and capabilities related to managing the data produced, used or re-used, curated and/or archived.", "completion_time": "Up to 1 hour", "media_type": "Interactive Resource - requires a user to take action or make a request in order for the content to be understood, executed or experienced.", "lr_type": "Learning Activity - guided or unguided activity engaged in by a learner to acquire skills, concepts, or knowledge that may or may not be defined by a lesson. Examples: data exercises, data recipes.", "creator": "zmehrabi", "md_record_id": "", "ratings": [], "rating": 0.0, "id": "38de3dde-104f-3cff-a0a9-7036e7c53cb9", "contributors": [], "contributor_orgs": [], "score": 1.9005997, "accesibility_summary": [], "country_of_origin": null, "credential_status": null, "notes": [] }, { "title": "Remote Sensing for Conservation & Biodiversity [Introductory]", "status": 1, "pub_status": "published", "modification_date": "2022-06-21T10:58:50Z", "resource_modification_date": "1900-01-01T00:00:00Z", "url": "https://appliedsciences.nasa.gov/what-we-do/capacity-building/arset", "access_cost": 0, "submitter_name": "zohreh mehrabi", "submitter_email": "zmehrabi@unm.edu", "authors": [ { "givenName": "Cindy", "familyName": "Schmidt", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Amber", "familyName": "McCullum", "name_identifier": "", "name_identifier_type": "" } ], "author_names": [ "Cindy Schmidt", "Amber McCullum" ], "author_org": { "name": "NASA Applied Remote Sensing Training Program (ARSET)", "name_identifier": "", "name_identifier_type": "" }, "contact": { "name": "Brock Blevins", "org": "NASA Applied Remote Sensing Training Program (ARSET)", "email": "" }, "abstract_data": "The United Nations Millennium Ecosystem Assessment states: \u0093ecosystems are critical to human well-being - to our health, our prosperity, our security, and to our social and cultural identity.\u0094 Conservation and biodiversity management play important roles in maintaining healthy ecosystems. Earth observations can help with these efforts. This online webinar series introduces participants to the\u00a0use of satellite data for\u00a0conservation\u00a0and biodiversity\u00a0applications. The series will\u00a0highlight\u00a0specific projects that\u00a0have successfully used\u00a0satellite data. Examples include: \n \nLearning Objectives:\u00a0By the end of this training, attendees will:\u00a0 \n \n \nCourse Format:\u00a0 \n \n \nPrerequisites:\u00a0Fundamentals of\u00a0Remote Sensing\u00a0or equivalent knowledge
\nIf you do\u00a0not complete the prerequisite, you may not be adequately prepared for the pace of the training.
\n
\nSession One: Remote Sensing for Conservation\u00a0
\nThis session will focus on remote sensing for habitat suitability, species population dynamics, and monitoring wildfires.
\n
\nSession Two: Remote Sensing for Biodiversity\u00a0
\nThis session will focus on the Group on Earth Observations Biodiversity Observation Network (GEOBON), Marine Biodiversity Observation Network (MBON), and essential biodiversity variables.
\n
\nEach part of 2 includes links to the recordings, presentation slides, exercises, and Question & Answer Transcripts, in English and in Spanish.\u00a0 There is no link to a landing page in Spanish for this resource.\u00a0 \u00a0", "abstract_format": "filtered_html", "subject": "Education: Science and Mathematics Education", "keywords": [ "Biodiversity data", "Climate data", "Conservation", "Environmental change records", "Environmental management", "Land management", "Landcover applications", "Remote sensing", "Satellite imagery" ], "license": "Creative Commons Attribution 2.0 Generic - CC BY 2.0", "usage_info": "", "citation": "", "locator_data": "", "locator_type": "", "publisher": "NASA Applied Remote Sensing Training Program (ARSET)", "version": "", "created": "2020-10-15T13:19:06", "published": "2019-01-24T00:00:00Z", "accessibility_features": [], "accessibility_summary": "", "language_primary": "en", "languages_secondary": [ "es" ], "ed_frameworks": [], "target_audience": [ "Citizen scientist", "Data policymaker", "Data professional", "Early-career research scientist", "Educator", "Graduate student", "Mid-career research scientist", "Research scientist", "Technology expert group", "Undergraduate student" ], "purpose": "Professional Development - increasing knowledge and capabilities related to managing the data produced, used or re-used, curated and/or archived.", "completion_time": "More than 1 hour (but less than 1 day)", "media_type": "Presentation - representation of the particular way in which an author shows, describes or explains one or more concepts, e.g., a set of Powerpoint slides.", "lr_type": "Lesson - detailed description of an element of instruction in a course, [could be] contained in a unit of one or more lessons, and used by a teacher to guide class instruction. Example: presentation slides on a topic.", "creator": "zmehrabi", "md_record_id": "", "ratings": [], "rating": 0.0, "id": "91c0cd7b-33bb-34b6-8483-354ff82ff872", "contributors": [], "contributor_orgs": [], "score": 1.9005997, "accesibility_summary": [], "country_of_origin": null, "credential_status": null, "notes": [] }, { "title": "An Inside Look at how NASA Measures Air Pollution [Introductory]", "status": 1, "pub_status": "published", "modification_date": "2022-06-21T10:58:48Z", "resource_modification_date": "1900-01-01T00:00:00Z", "url": "https://appliedsciences.nasa.gov/what-we-do/capacity-building/arset", "access_cost": 0, "submitter_name": "zohreh mehrabi", "submitter_email": "zmehrabi@unm.edu", "authors": [ { "givenName": "Melanie", "familyName": "Follette-Cook", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Ana", "familyName": "Prados", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Pawan", "familyName": "Gupta", "name_identifier": "", "name_identifier_type": "" } ], "author_names": [ "Melanie Follette-Cook", "Ana Prados", "Pawan Gupta" ], "author_org": { "name": "NASA Applied Remote Sensing Training Program (ARSET)", "name_identifier": "", "name_identifier_type": "" }, "contact": { "name": "Brock Blevins", "org": "NASA Applied Remote Sensing Training Program (ARSET)", "email": "" }, "abstract_data": "Would you like to learn how to access and visualize NASA satellite imagery? With the world\u0092s eyes and media coverage turned to recent global changes in air pollution from the economic downturn, this two-part webinar series provides a primer for the novice and a good refresher course for all others. You will learn which pollutants can be measured from space, how satellites make these measurements, the do\u0092s and don\u0092ts in interpreting satellite data, and how to download and create your own visualizations.
\n
\nLearning Objectives:\u00a0By the end of this training, attendees will be able to: \n \n
\nPrerequisites:\u00a0Fundamentals of Remote Sensing\u00a0(recommended but not required)
\n
\nPart One: Nitrogen Dioxide (NO2)
\n\u0095 What is NO2?
\n\u0095 NASA Remote Sensing Basics
\n\u0095 Interpreting NO2 Imagery: Dos and Don\u0092ts
\n\u0095 Downloading Data and Creating Imagery
\n
\nPart Two: Particulate Matter (Aerosols)
\n\u0095 What are Aerosols?
\n\u0095 Interpreting Aerosol Imagery: Dos and Don\u0092ts
\n\u0095 A Tour of NASA Resources for Generating Your Own Visualizations
\n
\nEach part of 2 includes links to the recordings, presentation slides,\u00a0 and Question & Answer Transcripts.", "abstract_format": "filtered_html", "subject": "Education: Science and Mathematics Education", "keywords": [ "Air quality data", "Climate data", "Data analysis", "Environmental change records", "Environmental management", "Geospatial data", "Remote sensing", "Satellite imagery", "User guides for Earth science data" ], "license": "Creative Commons Attribution 2.0 Generic - CC BY 2.0", "usage_info": "", "citation": "", "locator_data": "", "locator_type": "", "publisher": "NASA Applied Remote Sensing Training Program (ARSET)", "version": "", "created": "2020-10-08T10:46:51", "published": "2020-05-26T00:00:00Z", "accessibility_features": [], "accessibility_summary": "", "language_primary": "en", "languages_secondary": [ "es" ], "ed_frameworks": [], "target_audience": [ "Citizen scientist", "Data policymaker", "Data professional", "Early-career research scientist", "Educator", "Graduate student", "Mid-career research scientist", "Research scientist", "Technology expert group", "Undergraduate student" ], "purpose": "Professional Development - increasing knowledge and capabilities related to managing the data produced, used or re-used, curated and/or archived.", "completion_time": "More than 1 hour (but less than 1 day)", "media_type": "Presentation - representation of the particular way in which an author shows, describes or explains one or more concepts, e.g., a set of Powerpoint slides.", "lr_type": "Lesson - detailed description of an element of instruction in a course, [could be] contained in a unit of one or more lessons, and used by a teacher to guide class instruction. Example: presentation slides on a topic.", "creator": "zmehrabi", "md_record_id": "", "ratings": [], "rating": 0.0, "id": "db85a104-81cd-3ad3-880c-07650aec6fc1", "contributors": [], "contributor_orgs": [], "score": 1.9005997, "accesibility_summary": [], "country_of_origin": null, "credential_status": null, "notes": [] }, { "title": "Un Vistazo a C\u00f3mo la NASA Mide la Contaminaci\u00f3n del Aire [Introductorio]", "status": 1, "pub_status": "published", "modification_date": "2022-06-21T10:58:48Z", "resource_modification_date": "1900-01-01T00:00:00Z", "url": "https://appliedsciences.nasa.gov/what-we-do/capacity-building/arset", "access_cost": 0, "submitter_name": "zohreh mehrabi", "submitter_email": "zmehrabi@unm.edu", "authors": [ { "givenName": "Melanie", "familyName": "Follette-Cook", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Ana", "familyName": "Prados", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Pawan", "familyName": "Gupta", "name_identifier": "", "name_identifier_type": "" } ], "author_names": [ "Melanie Follette-Cook", "Ana Prados", "Pawan Gupta" ], "author_org": { "name": "NASA Applied Remote Sensing Training Program (ARSET)", "name_identifier": "", "name_identifier_type": "" }, "contact": { "name": "Brock Blevins", "org": "NASA Applied Remote Sensing Training Program (ARSET)", "email": "" }, "abstract_data": "\u00bfLe gustar\u00eda saber c\u00f3mo acceder y visualizar im\u00e1genes satelitales de la NASA? La reciente disminuci\u00f3n de la contaminaci\u00f3n atmosf\u00e9rica a nivel mundial debido al baj\u00f3n econ\u00f3mico ha capturado la atenci\u00f3n del mundo entero y recibido mucha cobertura medi\u00e1tica. Inspir\u00e1ndose en ello, esta serie de dos webinars imparte conocimiento fundamental para novatos y sirve de curso de repaso para los dem\u00e1s. Ud. aprender\u00e1 cu\u00e1les son los contaminantes que se pueden medir desde el espacio, c\u00f3mo los sat\u00e9lites hacen estas mediciones, lo que se debe hacer y no se debe hacer al momento de interpretar datos satelitales y c\u00f3mo descargar y crear sus propias visualizaciones.\u00a0
\n
\nObjetivos de Aprendizaje:Al finalizar esta capacitaci\u00f3n, los/las participantes podr\u00e1n: \n \n
\nPrerrequisitos:\u00a0Fundamentos de la Teledetecci\u00f3n (Percepci\u00f3n Remota)\u00a0-\u00a0 recomendado pero no obligatorio
\n
\nParte 1: Di\u00f3xido de Nitr\u00f3geno (NO2) \n \nParte 2: Part\u00edculas (Aerosoles) \n \n \n", "abstract_format": "filtered_html", "subject": "Education: Science and Mathematics Education", "keywords": [ "Air quality data", "Environmental change records", "Environmental management", "Geospatial data", "Remote sensing", "Satellite imagery", "User guides for Earth science data" ], "license": "Creative Commons Attribution 2.0 Generic - CC BY 2.0", "usage_info": "", "citation": "", "locator_data": "", "locator_type": "", "publisher": "NASA Applied Remote Sensing Training Program (ARSET)", "version": "", "created": "2020-10-08T11:14:16", "published": "2020-05-26T00:00:00Z", "accessibility_features": [], "accessibility_summary": "", "language_primary": "es", "languages_secondary": [ "en" ], "ed_frameworks": [], "target_audience": [ "Citizen scientist", "Data policymaker", "Data professional", "Early-career research scientist", "Educator", "Graduate student", "Mid-career research scientist", "Research scientist", "Technology expert group", "Undergraduate student" ], "purpose": "Professional Development - increasing knowledge and capabilities related to managing the data produced, used or re-used, curated and/or archived.", "completion_time": "More than 1 hour (but less than 1 day)", "media_type": "Presentation - representation of the particular way in which an author shows, describes or explains one or more concepts, e.g., a set of Powerpoint slides.", "lr_type": "Lesson - detailed description of an element of instruction in a course, [could be] contained in a unit of one or more lessons, and used by a teacher to guide class instruction. Example: presentation slides on a topic.", "creator": "zmehrabi", "md_record_id": "", "ratings": [], "rating": 0.0, "id": "67c4bfcd-a957-3489-b355-8b9661a04e16", "contributors": [], "contributor_orgs": [], "score": 1.9005997, "accesibility_summary": [], "country_of_origin": null, "credential_status": null, "notes": [] }, { "title": "Earth Observations for Disaster Risk Assessment & Resilience [Introductory]", "status": 1, "pub_status": "published", "modification_date": "2022-06-21T10:58:48Z", "resource_modification_date": "1900-01-01T00:00:00Z", "url": "https://appliedsciences.nasa.gov/what-we-do/capacity-building/arset", "access_cost": 0, "submitter_name": "zohreh mehrabi", "submitter_email": "zmehrabi@unm.edu", "authors": [ { "givenName": "Amita", "familyName": "Mehta", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Sean", "familyName": "McCartney", "name_identifier": "", "name_identifier_type": "" } ], "author_names": [ "Amita Mehta", "Sean McCartney" ], "author_org": { "name": "NASA Applied Remote Sensing Training Program (ARSET)", "name_identifier": "", "name_identifier_type": "" }, "contact": { "name": "Brock Blevins", "org": "NASA Applied Remote Sensing Training Program (ARSET)", "email": "" }, "abstract_data": "
According to a UN report, between 1998 and 2017, the U.S. alone lost $944.8 billion USD from disasters. Between 1878 and 2017, losses from extreme weather events rose by 251 percent. It is critical to developing disaster management strategies to reduce and mitigate disaster risks. A major factor in regional risk assessment is evaluating the vulnerability of lives and property to disasters. Environmental information about disasters, their spatial impact, and their temporal evolution can plan an important role as well.
\nThis webinar series will focus on Earth observation (EO) data useful for disaster risk assessment. The series will cover disasters including tropical cyclones, flooding, wildfires, and heat stress. The training will also include access to socioeconomic and disaster damage data. Sessions 3 & 4 will cover case studies and operational applications of EO for disaster risk assessment.
\n
\nLearning Objectives:\u00a0By the end of this training, attendees will:\u00a0
\n \n \n \n

\nCourse Format:
\n \n \n \n

\nPrerequisites:\u00a0
\n \n \n \n
Part One: NASA Remote Sensing and Socioeconomic Data for Disaster Risk Assessment Attendees will learn basic concepts and definitions in disaster risk management. Attendees will also learn about the types of satellites and socioeconomic data available through NASA for disaster risk management.
\n
\n
\nPart Two: Assessing the Risk of Floods and Cyclones Using NASA Data Attendees will learn a methodology for analyzing remote sensing and socioeconomic data to assess flood and cyclone risk. Examples will be shown for an urban area (Houston, TX, USA) and a country (Mozambique). These case studies will use both historical and forecast data.
\n
\nPart Three: Disaster Risk Assessment Case Studies Using Remote Sensing Data This will cover two case studies for using remote sensing data. One on how New York state is using NASA data for heatwave risk assessment, another on the freely available online tools from the World Resources Institute for visualizing NASA remote sensing and socioeconomic data.
\n
\nPart Four: Operational Application of Remote Sensing for Disaster Management The Pacific Disaster Center will describe the data, applications, and strategies they use for disaster risk reduction, response, and relief operations.
\n
\n
\nEach part of 4 includes links to the recordings, presentation slides,\u00a0 and Question & Answer Transcripts.", "abstract_format": "filtered_html", "subject": "Education: Science and Mathematics Education", "keywords": [ "Climate data", "Climate resilience", "Climate risk assessment applications", "Data analysis", "Disaster applications", "Earth observation data", "Environmental change records", "Environmental management", "Remote sensing", "Satellite imagery", "Sustainable Development Goals (SDGs)", "User guides for Earth science data" ], "license": "Creative Commons Attribution 2.0 Generic - CC BY 2.0", "usage_info": "", "citation": "", "locator_data": "", "locator_type": "", "publisher": "NASA Applied Remote Sensing Training Program (ARSET)", "version": "", "created": "2020-10-14T10:51:53", "published": "2019-08-15T00:00:00Z", "accessibility_features": [], "accessibility_summary": "", "language_primary": "en", "languages_secondary": [], "ed_frameworks": [], "target_audience": [ "Citizen scientist", "Data policymaker", "Data professional", "Early-career research scientist", "Educator", "Graduate student", "Mid-career research scientist", "Research scientist", "Technology expert group", "Undergraduate student" ], "purpose": "Professional Development - increasing knowledge and capabilities related to managing the data produced, used or re-used, curated and/or archived.", "completion_time": "More than 1 hour (but less than 1 day)", "media_type": "Presentation - representation of the particular way in which an author shows, describes or explains one or more concepts, e.g., a set of Powerpoint slides.", "lr_type": "Lesson - detailed description of an element of instruction in a course, [could be] contained in a unit of one or more lessons, and used by a teacher to guide class instruction. Example: presentation slides on a topic.", "creator": "zmehrabi", "md_record_id": "", "ratings": [], "rating": 0.0, "id": "7d09a16e-a46b-3c32-a375-4a26e15e8337", "contributors": [], "contributor_orgs": [], "score": 1.9005997, "accesibility_summary": [], "country_of_origin": null, "credential_status": null, "notes": [] }, { "title": "Data Management and Reporting: BCO-DMO Data Management Services and Best Practices", "status": 1, "pub_status": "published", "modification_date": "2022-06-21T10:58:47Z", "resource_modification_date": "1900-01-01T00:00:00Z", "url": "https://darchive.mblwhoilibrary.org/handle/1912/24614", "access_cost": 0, "submitter_name": "zohreh mehrabi", "submitter_email": "zmehrabi@unm.edu", "authors": [ { "givenName": "Shannon", "familyName": "Rauch", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Danie", "familyName": "Kinkade", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Matt", "familyName": "Biddle", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Nancy", "familyName": "Copley", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Amber", "familyName": "York", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Karen", "familyName": "Soenen", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Adam", "familyName": "Shepherd", "name_identifier": "", "name_identifier_type": "" } ], "author_names": [ "Shannon Rauch", "Danie Kinkade", "Matt Biddle", "Nancy Copley", "Amber York", "Karen Soenen", "Adam Shepherd" ], "author_org": { "name": "", "name_identifier": "", "name_identifier_type": "" }, "contact": { "name": "", "org": "", "email": "" }, "abstract_data": "The University-National Oceanographic Laboratory System (UNOLS) hosted an Early Career Chief Scientist Training Workshop in June 2019. The goal of this workshop was to help early-career marine scientists plan and write effective cruise proposals, develop collaborative sampling strategies and plans, become familiar with shipboard equipment and sampling at sea, and communicate major findings through the writing of manuscripts and cruise reports. This presentation provides information on data management and reporting best practices for chief scientists. It includes information on the National Science Foundation (NSF) data policy requirements, writing a Data Management Plan (DMP), the data lifecycle, data publication, and shipboard data management recommendations.", "abstract_format": "filtered_html", "subject": "Physical Sciences and Mathematics: Environmental Sciences", "keywords": [ "Data access", "Data discovery and identification - Core Trustworthy Data Repositories Requirements", "Data lifecycle", "Data management examples", "Data management stories", "Data policy", "Data preservation", "Data publication", "Data storage", "Marine data" ], "license": "Creative Commons Attribution 4.0 International - CC BY 4.0", "usage_info": "", "citation": "Presentation: Rauch, Shannon, Kinkade, Danie, Biddle, Matt, Copley, Nancy, York, Amber, Soenen, Karen, Shepherd, Adam, \"Data Management and Reporting: BCO-DMO Data Management Services and Best Practices\", Presented at Early Career Chief Scientist Training Workshop, Honolulu, HI, 13 June - 14 June 2019, DOI:10.1575/1912/24614, https://hdl.handle.net/1912/24614", "locator_data": "10.1575/1912/24614", "locator_type": "DOI", "publisher": "Woods Hole Scientific Community (WHOS)", "version": "", "created": "2020-10-01T10:41:32", "published": "2019-06-14T00:00:00Z", "accessibility_features": [], "accessibility_summary": "", "language_primary": "en", "languages_secondary": [], "ed_frameworks": [], "target_audience": [ "Citizen scientist", "Data manager", "Early-career research scientist", "Graduate student", "Mid-career research scientist", "Research faculty", "Research scientist" ], "purpose": "Professional Development - increasing knowledge and capabilities related to managing the data produced, used or re-used, curated and/or archived.", "completion_time": "Up to 1 hour", "media_type": "Presentation - representation of the particular way in which an author shows, describes or explains one or more concepts, e.g., a set of Powerpoint slides.", "lr_type": "Lesson - detailed description of an element of instruction in a course, [could be] contained in a unit of one or more lessons, and used by a teacher to guide class instruction. Example: presentation slides on a topic.", "creator": "zmehrabi", "md_record_id": "", "ratings": [], "rating": 0.0, "id": "44cdf712-4366-3a5f-a7a3-75640639acee", "contributors": [], "contributor_orgs": [ { "name": "University-National Oceanographic Laboratory System (UNOLS)", "name_identifier": "N.A.", "name_identifier_type": "N.A.", "type": "Organizer" }, { "name": "National Science Foundation (NSF)", "name_identifier": "N.A.", "name_identifier_type": "N.A.", "type": "Funding and sponsorship" } ], "score": 1.9005997, "accesibility_summary": [], "country_of_origin": null, "credential_status": null, "notes": [] } ] }