Why is planning of research data management useful?
Data management planning is not only for meeting expectations and policies of institutions and funding agencies. You should consider the Data Management Plan as a help to plan things, that will come up later in the research process and as a checklist, that helps you not to forget something concerning research data. While planning, keep the whole Research Data Lifecycle in mind.
If you start in the beginning of your project with data management planning,
- you can assign responsabilities and roles for data management in your team
- you can budget needed infrastructure, services, legal issues, and costs (sometimes reimbursable by your funder)
- you save time and resources in the long run and increase research efficiency.
- you prevent loss of data by enhancing data security.
- you avoid unnecessary data dublication through well-arranged data organisation.
- with a good data organisation and communication you enable continuity if things change and new employees need to find quickly what they are looking for.
- you can define the visibility and the outreach of your research data through data publication.
- you enable reproducibility and verifiability of your research.
More information about ...
- Guides and cases for research data management: Digital Curation Center
- Informations, tools and tutorials for research data management: forschungsdaten.info
- Data management plans for other national and international funders, f.e. the National Health Institute: use DMPonline or DMPTool
Informations regarding different steps of your data management planning
- Organizing data: Recommendations by the University of Cambridge regarding the organisation of research data
- Using controlled vocabulary: Basel Register of Thesauri, Ontologies & Classifications (BARTOC) is a comprehensive terminology registry for knowledge organization systems (KOS) like categorization schemes, classification schemes, ontologies, subject heading schemes, taxonomies, thesauri etc..
- Metadata standards by disciplines: see the suggestions by the Digital Curation Center or the Research Data Metadata Directory of the Research Data Alliance.
- Metadata standards by resource type: see the suggestions by the Digital Curation Center
- Data repositories: see the recommendations of the SNSF and the Registry of Research Data Repositories re3data.org. Further recommendations are added on this webpage under "Publishing"
- Finding data: Multidisciplinary and disciplinary data archives can be found with the help of re3data.org, some data sets are findable via Google, Google scholar or customized search engines for data, such as b2find.eudat.eu, datacite.org
- Common guidelines for managing research data - all steps of the data management life cycle, UC San Diego