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A data management plan will help you in the management of research data generated in your project. Put simply, a data management plan describes the data that is collected or generated in the course of your work and what happens to this data during its life-cycle (storage, publication, citation, long-term availability, anonymity, deletion, etc.). The goal of a data management plan is to meet the requirements of good scientific practice and to allow for reproducibility of research results.

It is recommended to start early with the preparations for the handling of research data and to update the procedures during the project. The following specifications guide you in this process.

In the Guidelines for Research Integrity at the ETH Zurich1, some data management guidelines are specified (see Article 11 "Collection documentation and storage of primary data" and Article 12 "Rights to the primary data and materials"):

  • The project management is responsible for proper storage of the data after project completion.
  • Primary data must be securely stored. The results must be completely reproducible from the primary data.
  • Confidential information must be clearly labelled and stored appropriately.
  • Arrangements for further use of the data by the parties have to be recorded in writing.
  • The necessary information for later reproduction of the experiments will, as a rule, be provided to third parties.

 

Funding organisations often state additional requirements. The SNSF funding regulations2 (Art. 44) require that research data is made available to other researchers for secondary research and is integrated in recognised scientific data pools. Researchers who are applying for funding with the Swiss National Science Foundation (SNSF) will be required to submit a data management plan (DMP) with their funding application as of October 2017. SNSF is currently working out DMP guidelines. Further information will be provided continuously from Spring 2017 onwards on the SNSF website (external link).

The Digital Curation Office is offering guidance on how to develop data management plans in their trainings on research data management. It also provides a checklist with further information on what needs to be considered regarding data management.

 

The following checklists and guidelines help you write a data management plan:

 

Data management plans vary greatly depending on the research project or discipline. The Digital Curation Office can assist you in your work on a data management plan6.

 

Resources were retrieved on 3 April 2017
1 https://www.ethz.ch/content/dam/ethz/main/research/pdf/forschungsethik/Broschure.pdf (Version December 2011)
2 http://www.snf.ch/sitecollectiondocuments/allg_reglement_e.pdf (Version 1 July 2012)
3 http://www.dcc.ac.uk/resources/data-management-plans/guidance-examples
4 http://www.dcc.ac.uk/resources/data-management-plans/checklist
5 http://www.wissgrid.de/publikationen/Leitfaden_Data-Management-WissGrid.pdf (ISBN: 978-3-86488-032-2, 2013)
6 http://www.library.ethz.ch/en/Media/Files/Data-management-checklist
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