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Research data


Research data may be numerical, textual, images, video or sound recordings. Software code may also count as research data. In the context of open access the term refers to digital data that has been collected or produced for scientific purposes.

Share your data

Why is it important to share research data?
• To enable others to validate and test your results and build on your work
• For new collaborations between research groups, nationally and internationally
• So that research data is saved on secure servers, providing backup for your own storage

Because of the many advantages of making data openly accessible, increasingly, funding agencies require a data management plan (DMP) as part of the project application. Also, some scientific journals require datasets to be deposited along with the article (e.g. Nature) or ask for a statement on the authors’ willingness to data.

Write a Data management plan

A DMP is a formal document that defines what will happen to your research data during and after your research project. Writing a DMP is a good idea even when it is not required. Well organized, structured and documented data makes it easier to validate, reuse, share and preserve.  In addition, it is important that all juridical implications of sharing data are made clear – preferably at the start of a project. Here are some useful links to guides to and templates for DMPs:

Check funders’ requirements

Carefully note what requirements your funder has regarding research data within your project as many ask for DMPs and some demand that both publications and data are published open access. To increase access to publicly funded research, the EU has launched an Open Research Data Pilot[1] as part of the Horizon 2020 program. NB! As from spring 2019, if you are awarded a grant from the Swedish Research Council you must have a plan for how research data collected and produced within your project shall be managed. For more information on funders’ requirements, SHERPA/JULIET[2] lists research funders data archiving policies.

[1] http://ec.europa.eu/research/participants/data/ref/h2020/grants_manual/hi/oa_pilot/h2020-hi-oa-pilot-guide_en.pdf

[2] http://v2.sherpa.ac.uk/

 

Find your repository

  • The online repository Zenodo (European Commission’s OpenAIREplus project), welcomes all researchers to preserve their research data regardless of size and format.
  • Swedish National Data Service (SND) can help Swedish researchers make their data available.
  • re3data.org is a global registry of research data repositories that covers repositories from different academic disciplines.

Cite data

Always cite datasets used in your research. The praxis of publishing and citing datasets creates a formalized system of recognition and reward to data producers. There are many more reasons for citing data; just by being formally published a citation creates accountability for creators of the dataset and reduces the risk of plagiarism. It allows others to locate and access the data for replicating or verifying results. It also increases the transparency of the method and data production. It makes it possible to track the impact of the dataset and encourages reuse of the data. Use a persistent identifier (PID) when publishing your data. The advantage is that a PID always points to the data, even if the data itself has changed web address. There are many types of PIDs, but Digital Object Identifier (DOI) is the most widely used.

Data is cited the same way as other information sources and a citation should include; author, title, year of publication, version, data archive and DOI, e.g.:

Barber, L.B., Weber, A.K., LeBlanc, D.R., Hull, R.B., Sunderland, E.M., and Vecitis, C.D., 2017, Poly- and perfluoroalkyl substances in contaminated groundwater, Cape Cod, Massachusetts, 2014-2015 (ver. 1.1, March 24, 2017): U.S. Geological Survey data release, https://doi.org/10.5066/F7Z899KT.

 

Be FAIR!

The FAIR principles were created to ensure that research data can be discovered, accessed, integrated and reused by humans and machines. They are widely adopted by publishers, data repositories and funding agencies, including the European Commission.

The FAIR acronym stands for Findable, Accessible, Interoperable och Reusable.

 

 FAIR_data_principles-700x238.jpg

 Bild: Sangya Pundir, Wikimedia Commons CC BY-SA 4.0

 

Chalmers