maDMPs shiyan baogao

A collaboration between the Association of Research Librariesand California Digital Library. Funded by the Institute ofMuseum and Library Services. Prepared by Clare Dean, Becky Grady, Cynthia Hudson Vitale, Marcel LaFlamme,Maria Praetzellis, and Judy Ruttenberg August, 2025 Contents Introduction03 Background04Pilot project overview06 Pilot partner integrations and developments 09 DMP Tool technical developments10 Pilot Observations15 Key Recommendations19 Final Thoughts23 Appendix25 Introduction Introduction Background Project Origins Academic institutions are being asked tosupport increasingly complex researchdata requirements, yet often lack insightinto what researchers need and when. Datamanagement plans (DMPs) are capableof capturing researchers’ needs and therequirements of funded research; however, intheir current static format, their institutionalvalue is limited. Machine-actionable DMPs(maDMPs) offer a potential vehicle for changeby transforming DMPs into living, structureddocuments that serve as bridges betweenresearchers and services. The Machine-Actionable Plans (MAP) project explored what itwould take to move from this vision of maDMPto implementation. for needed planning and development,complex, collaborative workflow mapping,and the cultural changes required broader forresearcher adoption. The technical component involved theDMP Tool, a free, open-source, web-basedapplication for creating funder-compliantDMPs managed by CDL. This applicationemerged in response to U.S. federal agencies’2011 requirement for the creation andsubmission of DMPs with funding applicationsand is now widely adopted across the U.S.and internationally, with more than 400participating institutions and hundreds ofthousands of plans created to date. Prior tothe MAP pilot project’s inception, the DMP Toolsupported the creation of basic maDMPs;however, the use of maDMPs was in a veryearly stage with minimal adoption, and theapplication did not support all the machine-actionability desired by potential partners. This project addressed that gap by pilotingmaDMP technical integrations, surfacing keychallenges and use cases, and providingconcrete examples to inform broader adoptionacross the research data managementcommunity. In 2023, the California Digital Library (CDL)and the Association of Research Libraries(ARL) partnered to enhance digital researchmanagement infrastructures and services.The ‘Building a Scalable Data-ManagementInfrastructure for Strategic InstitutionalCoordination’ project, funded by the Instituteof Museum and Library Services (IMLS), wasdesigned to address the urgent needs ofacademic and research libraries of varyingsizes and budgets to respond to increasingrequirements to make data managementplans machine-actionable and share federallyfunded research data. The MAP pilot Project,as it became known, included both a technicalcomponent and a community-developmentinitiative. The MAP pilot was established to examinethe potential of machine-actionable datamanagement plans to connect with existinguniversity infrastructure and people. Whilemany within the library community arefamiliar with existing tools, guidance, andbest practices for developing DMPs, maDMPsoffer new opportunities for creating moreefficiencies in the provisioning of Universityresources and coordinating services to supportthe critical research underway by researcherson University campuses. Given the complexityof this coordination, few institutions havebeen able to advance these integrations,restricted by resource and time limitations What is an maDMP? A machine actionable data managementand sharing plan is a structured, machine-readable version of the traditional datamanagement and sharing plan. Machine-actionability enables automation andintegration with administrative andresearch workflows and enables the DMPto be a living, versioned document that isupdatable over time. Background of machine-actionable Data ManagementPlans (maDMPs) “The pilot program was very useful inidentifying interest and use cases (bothcurrent and potential) in maDMPs andrelated efforts across campus. The sitevisit was especially informative in gettingto hear various campus stakeholders’in-depth perspectives on maDMPs, publicaccess to research data, and other relatedtopics.” Five institutions received IMLS funding fortheir projects to facilitate developments. Asso many strong applications were received,an additional five were also invited toparticipate in development and meetings,but without funding or site visits as thoughtpartners. IMLS-funded partners included: Machine-actionable DMPs support theFAIRprinciples (Findable, Accessible, Interoperable,Reusable) by enabling research data andrelated information to be shared seamlesslyacross stakeholder groups. They reducethe administrative burden on researchers,staff, and grant managers; allow dynamicintegrations with other research infrastructures;and make research outputs easier to discoverwhile st