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<resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4/metadata.xsd">     <identifier identifierType="DOI">10.48321/D17598</identifier>     <creators>       <creator>         <creatorName nameType="Personal">Maria Praetzellis</creatorName>         <nameIdentifier schemeURI="https://orcid.org/" nameIdentifierScheme="ORCID">           https://orcid.org/0000-0001-5047-3090         </nameIdentifier>         <affiliation affiliationIdentifier="https://ror.org/01cwqze88" affiliationIdentifierScheme="ROR">           National Institutes of Health         </affiliation>       </creator>     </creators>     <titles>       <title xml:lang="en-US">EAGER: The FAIR Island Project for Open Science</title>     </titles>     <publisher xml:lang="en-US">DMPTool</publisher>     <publicationYear>2024</publicationYear>     <language>en</language>     <resourceType resourceTypeGeneral="OutputManagementPlan">Data Management Plan</resourceType>     <descriptions>       <description xml:lang="en" descriptionType="Abstract">         In response to the need for Findable, Accessible, Interoperable, and Reusable (FAIR) data for Open Science (Wilkinson et al. 2016), the FAIR Island Project is a multi-institutional initiative to deploy, test and iterate on optimal data policies and technical infrastructure. Our immediate goal is to build and showcase exemplar policies and technical infrastructure utilizing Digital Object Identifiers (DOI) for place-based research data that will allow all data, samples, and knowledge generated at field stations, marine laboratories, long-term ecological research (LTER) sites (and other networks spanning physical, biological and social sciences) to be made openly available as quickly as possible. The FAIR Island Project is coordinated through the University of California Gump South Pacific Research Station (host of NSF’s Moorea Coral Reef LTER site) and the California Digital Library. Use cases include research programs addressing ocean acidification, ecosystem restoration, infectious disease, archeology, and community resilience, among others. Our initial focus is a new research station on the atoll of Tetiaroa in French Polynesia, where we can implement best practices in research data management from the ground up. In the next phase, we aim to include established research facilities across California (41 field sites in the University of California Natural Reserve System) and across the Pacific Islands through the ‘4Site Collaborative’, a transect from Hawaii to French Polynesia involving University of Hawaii (HIMB marine lab; Oahu), The Nature Conservancy (Palmyra atoll research station; Palmyra), France’s CNRS (CRIOBE marine station; Moorea), University of California (Gump Station; Moorea), and Tetiaroa Society (Tetiaroa atoll research station; Tetiaroa). Informed by on-the-ground implementations of data management policies and requirements at working field stations, the project will make federally funded research more accessible and usable, improving reproducibility and validation to enhance scientific rigor and maximize impact. Data management plans will be utilized as key documents for tracking provenance, attribution, compliance, deposit, and publication of all data collected at the research sites. The FAIR Island project will (i) build templated implementations and generalize the findings and outcomes from tracked, monitored implementation of FAIR principles utilizing machine-actionable data management plans (maDMP) and Digital Object Identifiers (DOI) for research data in a working environment, (ii) translate broader data management principles into a set of specific requirements and implementable activities for field stations, and (iii) demonstrate how best practices and policies accelerate research for the benefit of all stakeholders, and how they can be implemented at place-based research facilities across the United States and worldwide.       </description>     </descriptions>     <contributors>       <contributor contributorType="Producer">         <contributorName nameType="Organizational">National Institutes of Health</contributorName>         <nameIdentifier schemeURI="https://ror.org/" nameIdentifierScheme="ROR">           https://ror.org/01cwqze88         </nameIdentifier>       </contributor>       <contributor contributorType="ProjectLeader">         <contributorName nameType="Personal">John Chodacki</contributorName>         <nameIdentifier schemeURI="https://orcid.org/" nameIdentifierScheme="ORCID">           https://orcid.org/0000-0002-7378-2408         </nameIdentifier>         <affiliation affiliationIdentifier="https://ror.org/00dmfq477" affiliationIdentifierScheme="ROR">           University of California, Office of the President         </affiliation>       </contributor>       <contributor contributorType="ProjectLeader">         <contributorName nameType="Personal">Neil Davies</contributorName>         <nameIdentifier schemeURI="https://orcid.org/" nameIdentifierScheme="ORCID">           https://orcid.org/0000-0001-8085-5014         </nameIdentifier>         <affiliation affiliationIdentifier="https://ror.org/01an7q238" affiliationIdentifierScheme="ROR">           University of California, Berkeley         </affiliation>       </contributor>       <contributor contributorType="ProjectLeader">         <contributorName nameType="Personal">Erin Robinson</contributorName>         <nameIdentifier schemeURI="https://orcid.org/" nameIdentifierScheme="ORCID">           https://orcid.org/0000-0001-9998-0114         </nameIdentifier>         <affiliation affiliationIdentifier="https://ror.org/05bp8ka05" affiliationIdentifierScheme="ROR">           Metadata Game Changers         </affiliation>       </contributor>       <contributor contributorType="ProjectLeader">         <contributorName nameType="Personal">Catherine Nancarrow</contributorName>         <nameIdentifier schemeURI="https://orcid.org/" nameIdentifierScheme="ORCID">           https://orcid.org/0000-0001-8659-3115         </nameIdentifier>         <affiliation affiliationIdentifier="https://ror.org/00dmfq477" affiliationIdentifierScheme="ROR">           University of California, Office of the President         </affiliation>       </contributor>       <contributor contributorType="ProjectLeader">         <contributorName nameType="Personal">Maria Praetzellis</contributorName>         <nameIdentifier schemeURI="https://orcid.org/" nameIdentifierScheme="ORCID">           https://orcid.org/0000-0001-5047-3090         </nameIdentifier>         <affiliation affiliationIdentifier="https://ror.org/00dmfq477" affiliationIdentifierScheme="ROR">           University of California, Office of the President         </affiliation>       </contributor>       <contributor contributorType="ProjectLeader">         <contributorName nameType="Personal">Brian Riley</contributorName>         <nameIdentifier schemeURI="https://orcid.org/" nameIdentifierScheme="ORCID">           https://orcid.org/0000-0001-9870-5882         </nameIdentifier>         <affiliation affiliationIdentifier="https://ror.org/00dmfq477" affiliationIdentifierScheme="ROR">           University of California, Office of the President         </affiliation>       </contributor>     </contributors>     <fundingReferences>       <fundingReference>         <funderName>National Science Foundation (nsf.gov)</funderName>         <funderIdentifier funderIdentifierType="ROR">https://ror.org/021nxhr62</funderIdentifier>       </fundingReference>     </fundingReferences>     <relatedIdentifiers>       <relatedIdentifier relationType="Cites" relatedIdentifierType="DOI">         https://doi.org/10.29242/rli.302.2       </relatedIdentifier>       <relatedIdentifier relationType="Cites" relatedIdentifierType="DOI">         https://doi.org/10.5281/ZENODO.8183685       </relatedIdentifier>       <relatedIdentifier relationType="Cites" relatedIdentifierType="DOI">         https://doi.org/10.5281/ZENODO.6536701       </relatedIdentifier>       <relatedIdentifier relationType="Cites" relatedIdentifierType="DOI">         https://doi.org/10.5281/ZENODO.7308803       </relatedIdentifier>       <relatedIdentifier relationType="Cites" relatedIdentifierType="DOI">         https://doi.org/10.5281/ZENODO.7384146       </relatedIdentifier>       <relatedIdentifier relationType="Cites" relatedIdentifierType="DOI">         https://doi.org/10.1093/gigascience/giad004       </relatedIdentifier>       <relatedIdentifier relationType="Cites" relatedIdentifierType="DOI">         https://datascience.codata.org/articles/10.5334/dsj-2023-026       </relatedIdentifier>       <relatedIdentifier relationType="Cites" relatedIdentifierType="DOI">         https://doi.org/10.5438/3qxz-sx64       </relatedIdentifier>     </relatedIdentifiers>   </resource>