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- Philipson, Joakim, 1958-, et al.
(författare)
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Making Data Management Plans Machine Actionable: Templates and Tools
- 2023
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Ingår i: Data Science Journal. - 1683-1470. ; 22
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Tidskriftsartikel (refereegranskat)abstract
- Since September of 2019, a task group within the European Open Science Cloud - EOSC Nordic Project, work-package 5 (T5.3.2), has focused its attention on machine-actionable Data Management Plans (maDMPs). A delivery working-paper from the group (Hasan et al. 2021) concluded in summary that extracting useful information from traditional free-text based DMPs is problematic. While maDMPs are generally more FAIR compliant, and as such accessible to both humans and machines, more interoperable with other systems, and serving different stakeholders for processing, sharing, evaluation and reuse. Different DMP tools and templates have developed independently, to a varying degree, allowing for the creation of genuinely machine actionable DMPs. Here we will describe the first three tools or projects for creating maDMPs that were central parts of the original task group mission. We will get into a more detailed account of one of these, specifically the Stockholm University – EOSC Nordic maDMP project using the DMP Online tool, as described by Philipson (2021). We will also briefly touch upon some other current tools and projects for creating maDMPs that are compliant with the RDA DMP Common Standard (RDCS), aiming for integration with other research information systems or research data repositories. A possible conclusion from this overview is that the development of tools for maDMPs is progressing fast and seems to converge towards a common standard. Nonetheless, there remains an immense amount of work to get there.
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| 2. |
- Philipson, Joakim, 1958-
(författare)
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The Red Queen in the Repository
- 2020
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Ingår i: International Journal of Digital Curation. - Edinburgh : Edinburgh University Library. - 1746-8256. ; 15:1, s. 16-16
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Tidskriftsartikel (refereegranskat)abstract
- One of the grand curation challenges is to secure metadata quality in the ever-changing environment of metadata standards and file formats. As the Red Queen tells Alice in Through the Looking-Glass: “Now, here, you see, it takes all the running you can do, to keep in the same place.” That is, there is some “running” needed to keep metadata records in a research data repository fit for long-term use and put in place. One of the main tools of adaptation and keeping pace with the evolution of new standards, formats – and versions of standards in this ever-changing environment are validation schemas. Validation schemas are mainly seen as methods of checking data quality and fitness for use, but are also important for long-term preservation. We might like to think that our present (meta)data standards and formats are made for eternity, but in reality we know that standards evolve, formats change (some even become obsolete with time), and so do our needs for storage, searching and future dissemination for re-use. Eventually, we come to a point where transformation of our archival records and migration to other formats will be necessary. This could also mean that even if the AIPs, the Archival Information Packages stay the same in storage, the DIPs, the Dissemination Information Packages that we want to extract from the archive are subject to change of format. Further, in order for archival information packages to be self-sustainable, as required in the OAIS model, it is important to take interdependencies between individual files in the information packages into account. This should be done already by the time of ingest and validation of the SIPs, the Submission Information Packages, and along the line at different points of necessary transformation/migration (from SIP to AIP, from AIP to DIP etc.), in order to counter obsolescence.This paper investigates possible validation errors and missing elements in metadata records from three general purpose, multidisciplinary research data repositories – Figshare, Harvard’s Dataverse and Zenodo, and explores the potential effects of these errors on future transformation to AIPs and migration to other formats within a digital archive.
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