Mindestangaben in einem Datenmanagementplan

Beispiel 1 für DMP-Kriterien

Da die Praktiken in Bezug auf das Managen, Speichern und Teilen von Daten in den einzelnen Disziplinen sehr unterschiedlich sind, verwenden manche Forschungsförderer keine spezifischen DMP-Vorlagen. Für solche Fälle liefert Science Europe mit den Core Requirements for Data Management Plans Anhaltspunkte, welche Mindestanforderungen ein DMP erfüllen sollte.

  • How will new data be collected or produced and/or how will existing data be re-used?
  • What data (for example the kinds, formats, and volumes) will be collected or produced?
  • What metadata and documentation (for example the methodology of data collection and way of organising data) will accompany data?
  • What data quality control measures will be used?
  • How will data and metadata be stored and backed up during the research process?
  • How will data security and protection of sensitive data be taken care of during the research?
  • If personal data are processed, how will compliance with legislation on personal data and on data security be ensured?
  • How will other legal issues, such as intellectual property rights and ownership, be managed? What legislation is applicable?
  • How will possible ethical issues be taken into account, and codes of conduct followed?
  • How and when will data be shared? Are there possible restrictions to data sharing or embargo reasons?
  • How will data for preservation be selected, and where will data be preserved long-term (for example a data repository or archive)?
  • What methods or software tools will be needed to access and use the data?
  • How will the application of a unique and persistent identifier (such as a Digital Object Identifier (DOI)) to each data set be ensured?
  • Who (for example role, position, and institution) will be responsible for data management (i.e. the data steward)?
  • What resources (for example financial and time) will be dedicated to data management and ensuring that data will be FAIR (Findable, Accessible, Interoperable, Re-usable)?

Beispiel 2 für DMP-Kriterien

Auch die Europäische Kommission schreibt derzeit aufgrund unterschiedlicher Praktiken und Standards in den einzelnen Disziplinen kein spezifisches Template vor. Für das European Research Council (ERC) ist es wichtig, dass ein DMP die FAIR-Prinzipien erfüllt. Folgende fünf Informationen sollten demnach in einem DMP enthalten sein. Siehe auch: ERC Data Management Plan Template zum Download.

Grantees to provide a sufficiently detailed description, including the scientific focus and technical approach, to allow association of their data sets with specific research themes.

Grantees to describe the protocols and standards used to structure their data (i.e. fully reference the metadata) so that other scientists can make an assessment and reproduce the dataset. If available, to provide a reference to the community data standards that their data conform to and that make them interoperable with other data sets of similar type.

Grantees should plan to use depositories that will provide a unique and persistent identification (an identifier) of for their data sets and a stable resolvable link to where their datasets can be directly accessed. Submission to a public depository normally provides this; many institutional depositories provide similar services.

Grantees to provide information on the standards that will be used to ensure the integrity of their data sets and the period during which they will be maintained, as well as how they will be preserved and kept accessible in the longer term. If available, to provide a reference to the public data depository in which their data will reside.

Grantees to provide information on how their data sets can be accessed, including the type of license under which they can be accessed and re-used, and information on any restrictions that may apply. It is also important to specify and justify the timing of data sharing. This could be, for example, as soon as possible after the data collection, or at the end of the project. For data underlying publications it could be, for example, at the time of publication or pre-publication.