Research Data Management (RDM)

RDM describes the process that includes all methods and procedures used to ensure the long-term usability of Research Data:

  • Generation
  • Processing
  • Enrichment
  • Archiving
  • Publication

(Handling of data over the entire data lifecycle)

Research Data Management methods and procedures can be described in a Data Management Plan.

"Research data are (...) data that arise in the course of a scientific project, for example through research on sources, experiments, measurements, surveys or consultations." (DFG 2009)

Short introduction: Research Data Management. A Guide for Researchers [Research Data Working Group in the Priority Initiative “Digital Information” of the Alliance of German Science Organisations] Link >>> 

Why should I deal with Research Data Management?

  • Funding organizations such as the DFG (German Research Foundation) expect a statement on the handling of your Research Data when submitting the application.
    Leaflet Information Infrastructures for Research Data (as of September 2019): Link >>>
    Guide for submitting applications, project applications (as of April 2020): Link >>>
  • Publishers and journals often require the availability of the Research Data on which your publication is based on.

Publishers increasingly demand the open accessibility of scientific data in the course of a publication. Many of these journals, in particular open access journals, often encourage the possible reuse of the data. Information on copyright and archiving guidelines for scientific journals and publishers can be found by using the SHERPA / RoMEO search engine at the University of Nottingham.

Data Management Plan

A Data Management Plan (DMP) is a document describing the lifecycle of Research Data, from collection to archiving, including all measures that ensure that the data remains available, usable and traceable (database, data origin, workflow, consolidation, dissemination). It is primarily useful to support one's own good scientific work and to apply for funding for a project. More and more research funding agencies demand a data management plan.

The University of Hildesheim uses the RDMO tool.

RDMO

RDMO is a tool, for example, in order to plan, implement and to manage Research Data Management: https://dmp.uni-hildesheim.de/

FAIR Data Principles

The FAIR Data Principles (Findable, Accessible, Interoperable, Re-usable) help with the processing of Research Data: https://www.ands.org.au/working-with-data/fairdata

Blog about Research Data Management at the University of Hildesheim

Regularly, the Research Data Management blog at the University of Hildesheim provides information about all the developments relating to Research Data Management:
https://www.uni-hildesheim.de/forschungsdaten/
Response and feedback is always very welcome.

Links

A collection of links relating to Research Data Management can be found here:

Online bibliography on Research Data Management

An extensive online bibliography on Research Data Management is maintained in the Zotero group "Research Data":
https://www.zotero.org/groups/439756/forschungsdaten?

Guide book for Research Data Managemen
The guide book for Research Data Management deals with central aspects of Research Data Management from an information science and application-related perspective (in German):
http://opus.kobv.de/fhpotsdam/volltexte/2011/241/pdf/HandbuchForschungsdatenmanagement.pdf

Search engine for specialist subject repositories

Search engine for specialist subject repositories: https://www.re3data.org/

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