Research Data Management
Why Manage Research Data?
Research Data Management addresses the organization, capture, storage, preservation, and sharing of research data created during a research project. It comprises researcher's strategies for caring for their data and decisions concerning what to do with the data upon completion of a project. This results in depositing data in a data repository for long-term access and archiving.
For a researcher, having an effective plan and approach for the management of their data is important for several reasons, including:
- Digital data are fragile and can easily get lost
- Good data management can save researcher teams time and resources in the long-run, by making it easier to find and re-use data files
- There are growing research data requirements imposed by funders and publishers concerning the publication of data
- Research data management helps preventing errors and increases the quality of data analysis
- Well-documented data make it easier to write up research results for publications
- Well-managed and accessible data permits others validating and replicating findings
- Data is a scholarly product and, when shared, well-managed data can lead to valuable discoveries by others outside of the original intent.
This guide is intended to provide Empa researchers with a guideline on how to organize, capture, store, preserve and share research data. As it is stated in the title, this guide provides the "best practice" concerning research data management compiled from various sources. It is not a binding document for Empa employees and every researcher has to take care that he/she complies with the legal requirements – especially from funding agencies such as SNSF but also with the Empa Management Handbook (MHB).
This document should be a living document that is actually used in practice and helpful to our researchers. Any feedback on this best practice guide is therefore welcome and could be included in future versions.
Best Practice Guide
Important Links and Documents:
Template Data Management Plan für SNF-Projekte (Empa, ongoing work, 25.09.2017)
Seit 1. Januar 2017 gelten analoge Anforderungen an Data Management Plans bei Horizon 2020-Projekten!
- Starting 1.10.2017 one has to submit a Daten Management Plan (DMP) together with the proposal.
- The submitted DMP can still be a draft version, but it has to be finalised before the end of the project.
- SNFS will make all DMP publicly available at the end of the project.
- SNFS supports the sharing of research data in a data repositories with up to CHF 10‘000.-. Please request the full amount.
- For further information please consult the best practice guide
- SNFS requires the sharing of all the research data of this publication in a data repository prior to the submission of the publication.
Info vom SNF (13.09.2017)