A Programmatic and Scalable Approach to making Data Management Machine-Actionable
The data management plan (DMP), while seen by many as an ancillary document during a grant application, is a rich source of contextual information that is key to ensuring researchers, funders, and institutions follow the best possible and most appropriate research data management (RDM) practices. Un...
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Ubiquity Press
2023-08-01
|
| Series: | Data Science Journal |
| Subjects: | |
| Online Access: | https://account.datascience.codata.org/index.php/up-j-dsj/article/view/1526 |
| _version_ | 1797672628033421312 |
|---|---|
| author | Maria Praetzellis Matthew Buys Xiaoli Chen John Chodacki Neil Davies Kristian Garza Catherine Nancarrow Brian Riley Erin Robinson |
| author_facet | Maria Praetzellis Matthew Buys Xiaoli Chen John Chodacki Neil Davies Kristian Garza Catherine Nancarrow Brian Riley Erin Robinson |
| author_sort | Maria Praetzellis |
| collection | DOAJ |
| description | The data management plan (DMP), while seen by many as an ancillary document during a grant application, is a rich source of contextual information that is key to ensuring researchers, funders, and institutions follow the best possible and most appropriate research data management (RDM) practices. Unfortunately, the current practice is to transmit this information to the funder as a PDF or Word file through their web portals. As optimizing internal workflows and information sharing is a priority across the research space, retooling DMPs as machine-readable and machine-actionable will enable leveraging of key information to build RDM strategies collectively. Similarly, there is a growing need to streamline workflows, reuse information and reduce the burden on researchers. |
| first_indexed | 2024-03-11T21:32:55Z |
| format | Article |
| id | doaj.art-84ed63a763fa455189aa440d5aef85b8 |
| institution | Directory Open Access Journal |
| issn | 1683-1470 |
| language | English |
| last_indexed | 2024-03-11T21:32:55Z |
| publishDate | 2023-08-01 |
| publisher | Ubiquity Press |
| record_format | Article |
| series | Data Science Journal |
| spelling | doaj.art-84ed63a763fa455189aa440d5aef85b82023-09-27T07:53:25ZengUbiquity PressData Science Journal1683-14702023-08-0122262610.5334/dsj-2023-026981A Programmatic and Scalable Approach to making Data Management Machine-ActionableMaria Praetzellis0https://orcid.org/0000-0001-5047-3090Matthew Buys1https://orcid.org/0000-0001-7234-3684Xiaoli Chen2https://orcid.org/0000-0003-0207-2705John Chodacki3https://orcid.org/0000-0002-7378-2408Neil Davies4https://orcid.org/0000-0001-8085-5014Kristian Garza5https://orcid.org/0000-0003-3484-6875Catherine Nancarrow6https://orcid.org/0000-0001-8659-3115Brian Riley7https://orcid.org/0000-0001-9870-5882Erin Robinson8https://orcid.org/0000-0001-9998-0114California Digital Library, University of California Office of the PresidentDataCiteDataCiteCalifornia Digital Library, University of California Office of the PresidentGump South Pacific Research Station, University of California Berkeley, MooreaDataCiteCalifornia Digital Library, University of California Office of the PresidentCalifornia Digital LibraryMetadata Game ChangersThe data management plan (DMP), while seen by many as an ancillary document during a grant application, is a rich source of contextual information that is key to ensuring researchers, funders, and institutions follow the best possible and most appropriate research data management (RDM) practices. Unfortunately, the current practice is to transmit this information to the funder as a PDF or Word file through their web portals. As optimizing internal workflows and information sharing is a priority across the research space, retooling DMPs as machine-readable and machine-actionable will enable leveraging of key information to build RDM strategies collectively. Similarly, there is a growing need to streamline workflows, reuse information and reduce the burden on researchers.https://account.datascience.codata.org/index.php/up-j-dsj/article/view/1526data management planpersistent identifierdoiresearch data managementopen infrastructure |
| spellingShingle | Maria Praetzellis Matthew Buys Xiaoli Chen John Chodacki Neil Davies Kristian Garza Catherine Nancarrow Brian Riley Erin Robinson A Programmatic and Scalable Approach to making Data Management Machine-Actionable Data Science Journal data management plan persistent identifier doi research data management open infrastructure |
| title | A Programmatic and Scalable Approach to making Data Management Machine-Actionable |
| title_full | A Programmatic and Scalable Approach to making Data Management Machine-Actionable |
| title_fullStr | A Programmatic and Scalable Approach to making Data Management Machine-Actionable |
| title_full_unstemmed | A Programmatic and Scalable Approach to making Data Management Machine-Actionable |
| title_short | A Programmatic and Scalable Approach to making Data Management Machine-Actionable |
| title_sort | programmatic and scalable approach to making data management machine actionable |
| topic | data management plan persistent identifier doi research data management open infrastructure |
| url | https://account.datascience.codata.org/index.php/up-j-dsj/article/view/1526 |
| work_keys_str_mv | AT mariapraetzellis aprogrammaticandscalableapproachtomakingdatamanagementmachineactionable AT matthewbuys aprogrammaticandscalableapproachtomakingdatamanagementmachineactionable AT xiaolichen aprogrammaticandscalableapproachtomakingdatamanagementmachineactionable AT johnchodacki aprogrammaticandscalableapproachtomakingdatamanagementmachineactionable AT neildavies aprogrammaticandscalableapproachtomakingdatamanagementmachineactionable AT kristiangarza aprogrammaticandscalableapproachtomakingdatamanagementmachineactionable AT catherinenancarrow aprogrammaticandscalableapproachtomakingdatamanagementmachineactionable AT brianriley aprogrammaticandscalableapproachtomakingdatamanagementmachineactionable AT erinrobinson aprogrammaticandscalableapproachtomakingdatamanagementmachineactionable AT mariapraetzellis programmaticandscalableapproachtomakingdatamanagementmachineactionable AT matthewbuys programmaticandscalableapproachtomakingdatamanagementmachineactionable AT xiaolichen programmaticandscalableapproachtomakingdatamanagementmachineactionable AT johnchodacki programmaticandscalableapproachtomakingdatamanagementmachineactionable AT neildavies programmaticandscalableapproachtomakingdatamanagementmachineactionable AT kristiangarza programmaticandscalableapproachtomakingdatamanagementmachineactionable AT catherinenancarrow programmaticandscalableapproachtomakingdatamanagementmachineactionable AT brianriley programmaticandscalableapproachtomakingdatamanagementmachineactionable AT erinrobinson programmaticandscalableapproachtomakingdatamanagementmachineactionable |