Sharing research data

The Open Science movement encourages researchers to share research output beyond the contents of a published academic article (and possibly supplementary information).

Arguments in favor (from Wikipedia):

• Open access publication of research reports and data allows for rigorous peer-review
• Science is publicly funded so all results of the research should be publicly available
• Open Science will make science more reproducible and transparent
• Open Science has more impact
• Open Science will help answer uniquely complex questions

Arguments against (from Wikipedia):

• Too much unsorted information overwhelms scientists
• Potential misuse
• The public will misunderstand science data
• Increasing the scale of science will make verification of any discovery more difficult
• Low-quality science

(This image was created by Scriberia for The Turing Way community and is used under a CC-BY licence. The image was obtained from https://zenodo.org/record/3332808.)

FAIR principles

(This image was created by Scriberia for The Turing Way community and is used under a CC-BY licence. The image was obtained from https://zenodo.org/record/3332808.)

“FAIR” is the current buzzword for data management. You may be asked about it in, for example, making data management plans for grants:

• Findable
  • Will anyone else know that your data exists?
  • Solutions: put it in a standard repository, or at least a description of the data. Get a digital object identifier (DOI).
• Accessible
  • Once someone knows that the data exists, can they get it?
  • Usually solved by being in a repository, but for non-open data, may require more procedures.
• Interoperable
  • Is your data in a format that can be used by others, like csv instead of PDF?
  • Or better than csv. Example: 5-star open data
• Reusable
  • Is there a license allowing others to re-use?

Even though this is usually referred to as “open data”, it means considering and making good decisions, even if non-open.

FAIR principles are usually discussed in the context of data, but they apply also for research software.

Note that FAIR principles do not require data/software to be open.

Discussion: Discuss open science

• Do you share any other research outputs besides published articles and possibly source code?
• Discuss pros and cons of sharing research data.

Exercise: Get a DOI by connecting your repository to Zenodo

Digital object identifiers (DOI) are the backbone of the academic reference and metrics system. In this exercise we will see how to make a GitHub repository citable by archiving it on the Zenodo archiving service. Zenodo is a general-purpose open access repository created by OpenAIRE and CERN.

1. Sign in to Zenodo using your GitHub account. For this exercise, use the sandbox service: https://sandbox.zenodo.org/login/. This is a test version of the real Zenodo platform.
2. Go to https://sandbox.zenodo.org/account/settings/github/.
3. Find the repository you wish to publish (e.g. the word-count project that you imported or another test repo), and flip the switch to ON.
4. Go to GitHub and create a release by clicking the release tab and Create a new release (a release is based on a Git tag, but is a higher-level GitHub feature),
5. Creating a new release will trigger Zenodo into archiving your repository, and a DOI badge will be displayed next to your repository after a minute or two. You can include it in your GitHub README file: click the DOI badge and copy the relevant format (Markdown, RST, HTML).

Services for sharing and collaborating on research data

To find a research data repository for your data, you can search on the Registry of Research Data Repositories (re3data) platform and filter by country, content type, discipline, etc.

International:

• Zenodo: A general-purpose open access repository created by OpenAIRE and CERN. Integration with GitHub, allows researchers to upload files up to 50 GB.
• Figshare: Online digital repository where researchers can preserve and share their research outputs (figures, datasets, images and videos). Users can make all of their research outputs available in a citable, shareable and discoverable manner.
• EUDAT: European platform for researchers and practitioners from any research discipline to preserve, find, access, and process data in a trusted environment.
• Dryad: A general-purpose home for a wide diversity of datatypes, governed by a nonprofit membership organization. A curated resource that makes the data underlying scientific publications discoverable, freely reusable, and citable.
• The Open Science Framework: Gives free accounts for collaboration around files and other research artifacts. Each account can have up to 5 GB of files without any problem, and it remains private until you make it public.

Sweden:

• ICOS for climate data
• Bolin center climate / geodata
• NBIS for life science, sequence –omics data

Norway:

• NIRD archive is widely used by some communities
• NSD - Norwegian Center for Research Data, for any kind of data
• TSD - Norwegian Service for Sensitive Data
• Dataverse.no - Dataverse network, based at University of Tromsø but open for other institutions

Denmark:

• opendata.dk nationwide portal
• Danish portal for sharing geographical data

Finland:

• IDA, for general data
• FSD for social data
• more information on Finnish resources for open data

Further reading on reproducibility and open science

• The Turing way
• Illustrations from the Turing Way book dashes
• Reproduciblity syllabus
• The reproducible research data analysis platform
• Good talks on open reproducible research can be found here.
• “FAIR is not fair enough”
• “A FAIRer future”
• “Top 10 FAIR Data & Software Things” are brief guides that can be used by the research community to understand how they can make their research (data and software) more FAIR.