A recent editorial of the Nature journal had it as prime topic: "Everyone needs a data-management plan". They sound dull, but data-management plans are essential. Funders must explain why, and the ones who want to get funded, need to explain how:
https://www.nature.com/articles/d41586-018-03065-z
Keeping your research data freely available is crucial for open science — and your funding could depend on it. A related companion article describes simple steps, "Data management made simple":
https://www.nature.com/articles/d41586-018-03071-1
Robert-Jan Smits, the EU's outgoing director-general for research, science and innovation, recently been appointed the EU's special envoy on open access, tasked with helping make all publicly funded research in Europe freely available by 2020, says that this should consequently also include the data.
https://horizon-magazine.eu/article/open-access-scientific-publications-must-become-reality-2020-robert-jan-smits_en.html
Imagine if all the billions we are now putting into these expensive subscription journals could be put into research. There are already a good variety of open access repositories like Zenodo, OpenAire etc.
How to make research data publicly available and how to plan for and address it in your Data Management Plan:
EU FAIR DATA PRINCIPLES
https://eudat.eu/events/webinar/joint-eudat-openaire-webinar-%E2%80%9Chow-to-write-a-data-management-plan%E2%80%9D
1. Making data findable
Several datasets may be included. This should consider the dataset reference and name; origin and expected size of the data generated/collected; data types and formats, metadata, persistent and unique identifiers e.g., DOI
- catalogues, data citing etc
2. Making data openly accessible
This should consider which data will be made openly available and if some datasets remain closed, the reasons for not giving access; where the data and associated metadata, documentation and code are deposited (repository?); how the data can be accessed (are relevant software tools/methods provided?)
- https://www.re3data.org/
- https://www.openaire.eu/opendatapilot-repository
The Registry of Research Data Repositories provides a useful listing of repositories that you can search to find a place of deposit.
3. Making data interoperable
The Research Data Alliance provides a Metadata Standards Directory that can be searched for disciplinespecific
standards and associated tools.
- http://rd-alliance.github.io/metadata-directory/standards/
Which standard or field-specific data and metadata vocabularies and methods will be used
4. Increase data reuse
Consider what data will remain re-usable and for how long, is embargo foreseen; how the data is licensed; data quality assurance procedures
- http://www.dcc.ac.uk/resources/how-guides/five-steps-decide-what-data-keep
More aspects:
- Allocation of resources and data security
- Note that costs related to open access to research data are eligible as part of the Horizon 2020 grant (if compliant with the Grant Agreement conditions).
Ethical aspects
Consider whether there are any ethical or legal issues than can have an impact on data sharing. For
example, is informed consent for data sharing and long term preservation included in questionnaires
dealing with personal data?
Last but not least, don't forget to refer to other national/funder/sectorial/departmental procedures for data management that you are using / supposed to be using (if any)
DMPOnline is an online tool that can help you building your Data Management Plan. DMPonline is based on the open source DMPRoadmap codebase, which is jointly developed by the Digital Curation Centre (DCC) and the University of California Curation Center (UC3). The DCC & UC3 work closely with research funders and universities to produce a tool that generates active DMPs and caters for the whole lifecycle of a project, from bid-preparation stage through to completion.
https://dmponline.dcc.ac.uk
