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Example: a poster explicating a concept.": 2, "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, "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": 274, "true": 2 }, "status": { "true": 275, "false": 1 }, "pub_status": { "published": 276, "in-process": 0 } }, "results": [ { "id": "93a7b9ae-659d-46bd-acfa-86c79a968868", "pub_status": "published", "status": 0, "rating": 0.0, "ratings": [], "creator": "Nhoebelheinrich", "created": "2024-01-25T09:12:50Z", "submitter_email": "nhoebel@kmotifs.com", "submitter_name": "Nhoebelheinrich", "title": "Databases and Data Management", "url": "https://ucsb-library-research-data-services.github.io/bren-meds213-spring-2023/", "access_cost": "false", "authors": [ { "givenName": "Greg", "familyName": "Jan\u00e9e", "name_identifier": "", "name_identifier_type": "n/a" }, { "givenName": "Renata", "familyName": "Curty", "name_identifier": "", "name_identifier_type": "n/a" } ], "author_org": { "name": "University of California,Santa Barbara", "name_identifier": "https://ror.org/02t274463", "name_identifier_type": "ROR" }, "contact": { "name": "Greg Janee", "org": "University of California, Santa Barbara", "email": "gjanee@ucsb.edu" }, "abstract_data": "This is an archive of the materials used for a 4-unit, letter-grade course delivered in Spring 2023 as part of the Master of Environmental Data Science (MEDS) program in the Bren School of Environmental Science & Management. It includes PowerPoint presentations, instructor notes, live coding transcripts, supplemental materials and readings, and homework assignments. The goals of the course were to give MEDS students the skills they need to practically, successfully, and ethically manage their data, and to create, manage, and use relational databases where appropriate. Relational database topics went farther than just SQL queries and included a significant unit on data modeling and database constraints and integrity, in addition to advanced database topics such as triggers and indexes and accessing databases from programming environments. The data management portion tied into the students\u2019 capstone projects in a couple places, and included analyzing data from an ethical perspective, creating standards-compliant metadata, and employing data de-identification techniques. The course also included a unit on the Unix command line, with an emphasis on creating reusable Bash scripts, given in the spirit that Bash is a generally useful tool that all data scientists should have at least some familiarity with.", "subject": [ "Physical Sciences and Mathematics: Environmental Sciences" ], "keywords": [ "Accessible data - FAIR Data Principle", "Data documentation", "Data ethics", "Data management", "Data modeling", "Data privacy", "Data publication", "Database design", "Database management", "Metadata", "Metadata editors", "Metadata standards", "Open data", "Programming", "Python", "R software", "Relational database", "Restricted data", "Structured Query Language (SQL)", "Unix" ], "license": "Creative Commons Attribution-NonCommercial 4.0 International - CC BY-NC 4.0", "usage_info": "", "citation": "", "locator_data": "", "locator_type": "", "publisher": "University of California,Santa Barbara", "accesibility_features": [], "accesibility_summary": "", "language_primary": "en", "languages_secondary": [], "ed_frameworks": [], "target_audience": [ "Graduate student" ], "purpose": "Instruction - detailed information about aspects or processes related to data management or data skills.", "completion_time": "More than 1 Week", "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": "Unit - long-range plan of instruction on a particular concept containing multiple, related lessons.", "country_of_origin": "US", "resource_modification_date": "2023-12-21", "contributors": [], "contributor_orgs": [], "modification_date": "2024-01-25T09:14:59Z", "published": "2024-01-25T09:12:50Z", "score": 1.4812363, "abstract_format": null, "accessibility_features": {}, "accessibility_summary": null, "author_names": [], "credential_status": null, "md_record_id": null, "notes": [], "version": null }, { "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": 1.5405371, "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": 1.601245, "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": 1.6514012, "accesibility_summary": [], "country_of_origin": null, "credential_status": null, "notes": [] }, { "title": "Train-the-Trainer Concept on Research Data Management", "status": 1, "pub_status": "published", "modification_date": "2022-06-21T10:58:55Z", "resource_modification_date": "1900-01-01T00:00:00Z", "url": "https://doi.org/10.5281/zenodo.4071471", "access_cost": 0, "submitter_name": "Katarzyna Biernacka", "submitter_email": "biernack@hu-berlin.de", "authors": [ { "givenName": "Katarzyn", "familyName": "Biernacka", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Maik", "familyName": "Bierwirth (Dr.)", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Petra", "familyName": "Buchholz", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Dominika", "familyName": "Dolzycka", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Kerstin", "familyName": "Helbig", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Janna", "familyName": "Neumann (Dr.)", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Carolin", "familyName": "Odebrecht (Dr.)", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Cord", "familyName": "Wiljes", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Ulrike", "familyName": "Wuttke (Dr.)", "name_identifier": "", "name_identifier_type": "" } ], "author_names": [ "Katarzyn Biernacka", "Maik Bierwirth (Dr.)", "Petra Buchholz", "Dominika Dolzycka", "Kerstin Helbig", "Janna Neumann (Dr.)", "Carolin Odebrecht (Dr.)", "Cord Wiljes", "Ulrike Wuttke (Dr.)" ], "author_org": { "name": "", "name_identifier": "", "name_identifier_type": "" }, "contact": { "name": "", "org": "", "email": "" }, "abstract_data": "
Within the project\u00a0FDMentor, a German Train-the-Trainer Programme on Research Data Management (RDM) was developed and piloted in a series of workshops. The topics cover many aspects of research data management, such as data management plans and the publication of research data, as well as didactic units on learning concepts, workshop design, and a range of didactic methods.
\nAfter the end of the project, the concept was supplemented and updated by members of the Sub-Working Group Training/Further Education (UAG Schulungen/Fortbildungen) of the DINI/Nestor Working Group Research Data (DINI/Nestor-AG Forschungsdaten). The newly published English version of the Train-the-Trainer Concept contains the translated concept, the materials, and all methods of the Train-the-Trainer Programme. Furthermore, additional English references and materials complement this version.
\nThis document is primarily intended for trainers who want to conduct a Train-the-Trainer workshop on research data management. It contains background knowledge on the PowerPoint slides and teaching scripts as well as further information on the individual subject areas required for reuse and implementation of a two-day workshop of seven and a half hours a day.
\n
\nEach unit of this guide contains information about how to teach the unit including\u00a0the unit's learning objectives, key aspects, contents, didactic methods and exercises, training materials, addiitional sources, template, and teaching scripts.
\n
\nTopics of the units inlclude orientation, didactic approach, digital research data, research data policies, data management plans, order and structure, documentation and metadata, storage and backup, long term archiving, access control, formal framework, data publication, re-use of research data, legal aspects, institutional infrastructure, training exercises, concept development and didactic methods.\u00a0\u00a0
\n\u00a0
\n", "abstract_format": "filtered_html", "subject": "", "keywords": [ "Access rights", "Data analysis", "Data archiving", "Data documentation", "Data management", "Data management planning", "Data policy", "Data preservation", "Data publication", "Data reuse - Core Trustworthy Data Repositories Requirements", "Data storage", "Metadata" ], "license": "Creative Commons Attribution 4.0 International - CC BY 4.0", "usage_info": "", "citation": "Biernacka, Katarzyna, Bierwirth, Maik, Buchholz, Petra, Dolzycka, Dominika, Helbig, Kerstin, Neumann, Janna, \u0085 Wuttke, Ulrike. (2020). Train-the-Trainer Concept on Research Data Management (Version 3.0). Zenodo. https://doi.org/10.5281/zenodo.4071471", "locator_data": "10.5281/zenodo.4071471", "locator_type": "DOI", "publisher": "Zenodo", "version": "3.0", "created": "2020-11-09T10:58:54", "published": "2020-11-04T00:00:00Z", "accessibility_features": [], "accessibility_summary": "", "language_primary": "de", "languages_secondary": [ "en" ], "ed_frameworks": [], "target_audience": [ "Data manager", "Data professional", "Educator", "Graduate student", "Librarian", "Publisher", "Repository manager" ], "purpose": "Instruction - detailed information about aspects or processes related to data management or data skills.", "completion_time": "More than 1 Week", "media_type": "Text - an explanation of a concept or a story using human readable characters formed into words, usually distinguished from graphical images.", "lr_type": "Educator Curriculum Guide - document that defines what concepts should be taught and/or how a concept should be taught effectively.", "creator": "", "md_record_id": "", "ratings": [], "rating": 0.0, "id": "dd15cd74-3413-3827-a0f9-d96e03960c2f", "contributors": [ { "familyName": "Bierwirth (Dr.)", "givenName": "Maik", "type": "Translation" } ], "contributor_orgs": [ { "name": "Federal Ministry of Education and Research (BMBF)", "name_identifier": "N.A.", "name_identifier_type": "N.A.", "type": "Funding and sponsorship" } ], "score": 1.601245, "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": 1.601245, "accesibility_summary": [], "country_of_origin": null, "credential_status": null, "notes": [] }, { "title": "Satellite Remote Sensing for Agricultural Applications[Introductory]", "status": 1, "pub_status": "published", "modification_date": "2022-06-21T10:58:45Z", "resource_modification_date": "1900-01-01T00:00:00Z", "url": "https://arset.gsfc.nasa.gov/water/webinars/remote-sensing-for-agriculture-20?utm_source=social&utm_medium=ext&utm_campaign=AG-RS-2020", "access_cost": 0, "submitter_name": "zohreh Mehrabi", "submitter_email": "zmehrabi@unm.edu", "authors": [ { "givenName": "Sean", "familyName": "McCartney", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Amita", "familyName": "Mehta", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Erika", "familyName": "Podes", "name_identifier": "", "name_identifier_type": "" } ], "author_names": [ "Sean McCartney", "Amita Mehta", "Erika Podes" ], "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": "
Since the launch of NASA\u0092s first Landsat mission in 1972, satellite imagery has been used for global agricultural monitoring, providing one of the longest operational applications for the Landsat program. Although satellite observations of land began with agricultural monitoring, only in recent years has agricultural remote sensing seen reinvigoration among space agencies, national ministries of agriculture, and global initiatives. To monitor agricultural systems, NASA utilizes satellite observations to assess a wide variety of geophysical and biophysical parameters, including precipitation, temperature, evapotranspiration, soil moisture, and vegetation health.
\n
\nPast ARSET webinars on land and water resources covered remote sensing-derived parameters relevant to agriculture within a broader scope. This 4-part introductory webinar will focus on data products, data access, and case-studies demonstrating how remote sensing data can be used for decision-making among the agriculture and food security communities.
\n
\nThis training will address how to use remote sensing data for agriculture monitoring, specifically drought and crop monitoring. The webinar will also provide end-users the ability to evaluate which regions of the world agricultural productivity are above or below long-term trends. This informs decisions pertaining to market stability and humanitarian relief.
\n
\nLearning Objectives:\u00a0By the end of this training, attendees will be able to: \n \n \ncourse Format:\u00a0 \n \n \n\u00a0Prerequisites:
\n\u00a0Attendees who have not completed the following may not be prepared for the pace of the training:
\nFundamentals of Remote Sensing\u00a0\u00a0
\n
\nPart 1: Overview of Agricultural Remote Sensing
\nThis section will cover the ARSET\u00a0Program and give a general overview of remote sensing as it pertains to agriculture. This part will include the history of Earth observations (EO)\u00a0for agriculture, satellites and sensors that can be used, the limitations of satellite data, an introduction of\u00a0NASA HARVEST, examples of current EO applications in agriculture, and a Q&A\u00a0session.
\n
\nSupplementary Materials:
\nNASA Satellites and Sensors Relevant for Agriculture\u00a0\u00bb
\n
\nFact Sheets: \n \nPart 2: Soil Moisture for Agricultural Applications
\nThis part of the training provides an overview of SMAP and case studies for agricultural applications and an overview of soil moisture and shallow groundwater from the Land Data Assimilation System (LDAS), as well as a Q&A session.
\n
\nPart 3: Earth Observations for Agricultural Monitoring
\nThis section will cover previous ARSET training that relates to agricultural monitoring and present case studies of EO being used for agricultural monitoring. There will also be a Q&A session.
\n
\nPart 4: Evapotranspiration (ET) & Evaporative Stress Index (ESI) for Agricultural Applications
\nThis section includes a presentation from guest speaker Dr. Christopher Hain, along with an overview and case studies of ET and ESI in agricultural applications. This section will conclude\u00a0with a Q&A session.
\n
\nEach part of 4 includes links to the recordings, presentation slides,\u00a0 and Question & Answer Transcripts.
\n\u00a0", "abstract_format": "filtered_html", "subject": "Education: Science and Mathematics Education", "keywords": [ "Agriculture applications", "Agriculture data", "Conservation", "Crop monitoring", "Data access", "Drought monitoring", "Environmental management", "Land management", "Remote sensing", "Satellite imagery", "Soil moisture analysis", "Soils data assessment systems", "Soils software and data management applications" ], "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": "2020-09-17T15:47:40", "published": "2020-04-14T00:00:00Z", "accessibility_features": [], "accessibility_summary": "", "language_primary": "en", "languages_secondary": [ "es" ], "ed_frameworks": [], "target_audience": [ "Citizen scientist", "Data manager", "Data policymaker", "Early-career research scientist", "Mid-career research scientist", "Research scientist", "Technology expert group" ], "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": "d7ba8c7d-3c15-391c-add8-7fc7567345d1", "contributors": [], "contributor_orgs": [], "score": 1.5029536, "accesibility_summary": [], "country_of_origin": null, "credential_status": null, "notes": [] }, { "title": "SAR for Landcover Applications [Advanced] ", "status": 1, "pub_status": "published", "modification_date": "2022-06-21T10:58:44Z", "resource_modification_date": "1900-01-01T00:00:00Z", "url": "https://arset.gsfc.nasa.gov/disasters/webinars/2019-SAR?utm_source=social&utm_medium=ext&utm_campaign=SAR-LC", "access_cost": 0, "submitter_name": "zohreh Mehrabi", "submitter_email": "zmehrabi@unm.edu", "authors": [ { "givenName": "Erika", "familyName": "Podest", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Sean", "familyName": "McCartney", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Heather", "familyName": "McNairn", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Xianfeng", "familyName": "Jiao", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Sarah", "familyName": "Banks", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Amir", "familyName": "Behnamian", "name_identifier": "", "name_identifier_type": "" } ], "author_names": [ "Erika Podest", "Sean McCartney", "Heather McNairn", "Xianfeng Jiao", "Sarah Banks", "Amir Behnamian" ], "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": "This webinar series will build on the knowledge and skills previously developed in ARSET SAR training. Presentations and demonstrations will focus on agriculture and flood\u00a0applications. Participants will learn to characterize floods with Google Earth Engine. Participants will also learn to analyze synthetic aperture radar (SAR) for agricultural applications, including retrieving soil moisture and identifying crop types.
\n
\nLearning Objectives:\u00a0By the end of this training, attendees will be able to:\u00a0 \n
    \n\t
  1. analyze SAR data in Google Earth Engine
    2. \n\t
  2. generate soil moisture analyses
    3. \n\t
  3. identify different types of crops\u00a0 \u00a0
    4. \n
\nCourse\u00a0Format:\u00a0 \n \n \nPrerequisites:\u00a0
\nPrerequisites are not required for this training, but attendees that do not complete them may not be adequately prepared for the pace of the training.\u00a0 \n \n
\nPart One: Monitoring Flood Extent with Google Earth Engine
\nThis session will focus on the use of Google Earth Engine (GEE) to generate flood extent products using SAR images from Sentinel-1. The first third of the session will cover the basic\u00a0principles of radar remote sensing related to flooded vegetation. The remaining time in the session will be dedicated to a demonstration on how to use GEE to generate flood extent products with Sentinel-1.
\nPart Two: Exploiting SAR to Monitor Agriculture
\nFeaturing guest speaker Dr. Heather McNairn, from Agriculture and Agri-Food Canada,\u00a0this session will focus on using SAR to monitor different agriculture-related topics, building on the skills learned in the SAR agriculture session from 2018. The first part of the session will cover the basics of radar remote sensing as related to agriculture. The remainder of the session will focus on the use of SAR to retrieve soil moisture, identify crop types, and map land cover.
\n
\nEach part of 2 includes links to the recordings, presentation slides, and Question & Answer Transcripts.
\n\u00a0", "abstract_format": "filtered_html", "subject": "Education: Science and Mathematics Education", "keywords": [ "Agriculture data", "Capacity building", "Data access", "Data analysis", "Environmental management", "Flood mapping applications", "Land management", "Landcover applications", "Remote sensing", "Satellite imagery", "Soil moisture analysis", "Soils data assessment systems", "Soils software and data management applications", "Synthetic aperture radar data (SAR)" ], "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": "2020-09-16T14:48:21", "published": "2019-08-28T00:00:00Z", "accessibility_features": [], "accessibility_summary": "", "language_primary": "en", "languages_secondary": [ "es" ], "ed_frameworks": [], "target_audience": [ "Citizen scientist", "Data manager", "Data policymaker", "Early-career research scientist", "Mid-career research scientist", "Research scientist", "Technology expert group" ], "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": "cec11be7-067c-3555-9995-8b5a5a6d9229", "contributors": [], "contributor_orgs": [], "score": 1.4836532, "accesibility_summary": [], "country_of_origin": null, "credential_status": null, "notes": [] }, { "title": "SAR y sus Aplicaciones para la Cobertura Terrestre [Avanzado]", "status": 1, "pub_status": "published", "modification_date": "2022-06-21T10:58:44Z", "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": "Erika", "familyName": "Podes", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Sean", "familyName": "McCartney", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Heather", "familyName": "McNairn", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Xianfeng", "familyName": "Jiao", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Sarah", "familyName": "Banks", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Amir", "familyName": "Behnamian", "name_identifier": "", "name_identifier_type": "" } ], "author_names": [ "Erika Podes", "Sean McCartney", "Heather McNairn", "Xianfeng Jiao", "Sarah Banks", "Amir Behnamian" ], "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": "Esta capacitaci\u00f3n se basar\u00e1 en los conocimientos y las habilidades adquiridas en capacitaciones anteriores de ARSET sobre radar de apertura sint\u00e9tica (synthetic aperture radar o SAR). Las presentaciones y demostraciones se enfocar\u00e1n en aplicaciones para la agricultura y para desastres. Los participantes aprender\u00e1n a utilizar im\u00e1genes SAR 1) para caracterizar inundaciones con Google Earth Engine 2) y para aplicaciones en la agricultura incluyendo estimaci\u00f3n de la humedad del suelo e identificaci\u00f3n de cultivos.
\n
\nObjetivos de Aprendizaje:\u00a0Para la conclusi\u00f3n de esta capacitaci\u00f3n, los participantes podr\u00e1n: \n
    \n\t
  1. analizar datos SAR en Google Earth Engine para el mapeo de inundaciones
    2. \n\t
  2. generar an\u00e1lisis de la humedad del suelo
    3. \n\t
  3. identificar diferentes tipos de cultivos
    4. \n
\nFormato del Curso:\u00a0Dos\u00a0partes de dos horas cada una \n \n \n
\nPrerequisites:
\n
\nLos prerrequisitos no son obligatorios para esta capacitaci\u00f3n, pero quienes no los completen podr\u00edan no estar lo\u00a0suficientemente preparados para esta capacitaci\u00f3n \n \nInscripciones:
\nDebido a la demanda anticipada, por favor inscr\u00edbase solo para la sesi\u00f3n en espa\u00f1ol o la sesi\u00f3n en ingl\u00e9s.
\n
\nParte Uno: SAR para el Mapeo de Inundaciones Utilizando Google Earth Engine
\nEsta parte\u00a0estar\u00e1 enfocada en el uso de Google Earth Engine (GEE) para mapear inundaciones utilizando im\u00e1genes SAR de Sentinel-1. La primera parte de la sesi\u00f3n cubrir\u00e1 los principios b\u00e1sicos de SAR relacionados a las inundaciones. El resto de la sesi\u00f3n estar\u00e1 enfocada en una demostraci\u00f3n de c\u00f3mo utilizar\u00a0GEE para generar mapas de inundaci\u00f3n con Sentinel-1.
\nParte Dos: SAR para el Monitoreo Agr\u00edcola
\nEsta\u00a0parte\u00a0estar\u00e1 enfocada en el uso de SAR para monitorear diferentes aspectos relacionados con la agricultura, extendiendo los conocimientos adquiridos en la sesi\u00f3n de SAR para la agricultura del 2018. El resto de la sesi\u00f3n estar\u00e1 enfocada en el uso de SAR para estimar la humedad del suelo e identificar diferentes tipos de cultivos. La Dra. Heather McNairn, de Agriculture and Agri-Food Canad\u00e1, ser\u00e1 la presentadora de esta sesi\u00f3n.
\n\u00a0", "abstract_format": "filtered_html", "subject": "Education: Science and Mathematics Education", "keywords": [ "Agriculture data", "Capacity building", "Data access", "Data analysis", "Environmental management", "Flood mapping applications", "Land management", "Landcover applications", "Lidar technology", "Remote sensing", "Satellite imagery", "Soil moisture analysis", "Soils software and data management applications", "Synthetic aperture radar data (SAR)" ], "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": "2020-09-16T16:03:26", "published": "2019-08-28T00:00:00Z", "accessibility_features": [], "accessibility_summary": "", "language_primary": "es", "languages_secondary": [ "en" ], "ed_frameworks": [], "target_audience": [ "Citizen scientist", "Data manager", "Data policymaker", "Early-career research scientist", "Mid-career research scientist", "Research scientist", "Technology expert group" ], "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": "fb4fb416-2f18-320a-b0c4-2b495fdd6a08", "contributors": [], "contributor_orgs": [], "score": 1.4887216, "accesibility_summary": [], "country_of_origin": null, "credential_status": null, "notes": [] }, { "title": "Data Science Training Camp at Woods Hole Oceanographic Institution: Syllabus and slide presentations in 2020", "status": 1, "pub_status": "published", "modification_date": "2022-06-21T10:58:43Z", "resource_modification_date": "1900-01-01T00:00:00Z", "url": "https://hdl.handle.net/1912/26103", "access_cost": 0, "submitter_name": "Stace Beaulieu", "submitter_email": "sbeaulieu@whoi.edu", "authors": [ { "givenName": "Stace E.", "familyName": "Beaulieu", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Lisa", "familyName": "Raymond", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Audrey", "familyName": "Mickle", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Joe", "familyName": "Futrelle", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Nick", "familyName": "Symmonds", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Roberta", "familyName": "Mazzoli", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Rich", "familyName": "Brey", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Danie", "familyName": "Kinkade", "name_identifier": "", "name_identifier_type": "" }, { "givenName": "Shannon", "familyName": "Rauch", "name_identifier": "", "name_identifier_type": "" } ], "author_names": [ "Stace E. Beaulieu", "Lisa Raymond", "Audrey Mickle", "Joe Futrelle", "Nick Symmonds", "Roberta Mazzoli", "Rich Brey", "Danie Kinkade", "Shannon Rauch" ], "author_org": { "name": "", "name_identifier": "", "name_identifier_type": "" }, "contact": { "name": "", "org": "", "email": "" }, "abstract_data": "With data and software increasingly recognized as scholarly research products, and aiming towards open science and reproducibility, it is imperative for today's oceanographers to learn foundational practices and skills for data management and research computing, as well as practices specific to the ocean sciences. This educational package was developed as a data science training camp for graduate students and professionals in the ocean sciences and implemented at the Woods Hole Oceanographic Institution (WHOI) in 2019 and 2020. Here we provide materials for the 2020 camp.  Contents of this package include the syllabus and slide presentations for each of the four modules:
\r\n1 "Good enough practices in scientific computing,"
\r\n2 Data management,
\r\n3 Software development and research computing,
\r\nand 4 Best practices in the ocean sciences.
\r\nThe 3rd module is split into two parts. We also include a poster presented at the 2020 Ocean Science Meeting, which has some results from pre- and post-surveys.
\r\n ", "abstract_format": "filtered_html", "subject": "Physical Sciences and Mathematics: Earth Sciences", "keywords": [ "Big data", "Coastal data", "Data citation", "Data management", "Data sharing", "Ocean data", "Open science", "Programming", "Scientific reproducibility", "Software management" ], "license": "Creative Commons Attribution 4.0 International - CC BY 4.0", "usage_info": "", "citation": "Beaulieu, Stace E., Raymond, Lisa, Mickle, Audrey, Futrelle, Joe, Symmonds, Nick, Mazzoli, Roberta, Brey, Rich, Kinkade, Danie, Rauch, Shannon, \"Data Science Training Camp at Woods Hole Oceanographic Institution: Syllabus and slide presentations in 2020\", Presented at Data Science Training Camp, Woods Hole, MA, January, 22 - 23, 2020., DOI:10.1575/1912/26103, https://hdl.handle.net/1912/26103", "locator_data": "10.1575/1912/26103", "locator_type": "DOI", "publisher": "Woods Hole Scientific Community (WHOS)", "version": "", "created": "2020-09-09T15:20:28", "published": "2020-08-21T00:00:00Z", "accessibility_features": [], "accessibility_summary": "", "language_primary": "en", "languages_secondary": [], "ed_frameworks": [], "target_audience": [ "Data professional", "Early-career research scientist", "Graduate student", "Librarian", "Mid-career research scientist" ], "purpose": "Instruction - detailed information about aspects or processes related to data management or data skills.", "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": "Nhoebelheinrich", "md_record_id": "", "ratings": [], "rating": 0.0, "id": "f1a11daf-e19a-3854-9517-e6540a3b5cda", "contributors": [], "contributor_orgs": [ { "name": "Woods Hole Oceanographic Institution (WHOI)", "name_identifier": "N.A.", "name_identifier_type": "N.A.", "type": "Funding and sponsorship" }, { "name": "National Science Foundation (NSF)", "name_identifier": "N.A.", "name_identifier_type": "N.A.", "type": "Funding and sponsorship" } ], "score": 1.5551572, "accesibility_summary": [], "country_of_origin": null, "credential_status": null, "notes": [] } ] }