Research Data Guide

Youtube video by CSC about FAIR-principle (1,44 min)

A guide for making your data FAIR (2023) Anneli Lehtisalo et al. (2023). Improve the quality and impact of your research through data management - A guide for making your data FAIR. Zenodo. https://doi.org/10.5281/zenodo.8012377

FAIR by design: Plan your research process so that metadata & documentation with permanent identifiers increase automatically along the process

To be Findable:

F1. (meta)data are assigned a globally unique and eternally persistent identifier.
F2. data are described with rich metadata.
F3. (meta)data are registered or indexed in a searchable resource.
F4. metadata specify the data identifier.

To be Accessible:

A1  (meta)data are retrievable by their identifier using a standardized communications protocol.
A1.1 the protocol is open, free, and universally implementable.
A1.2 the protocol allows for an authentication and authorization procedure, where necessary.
A2 metadata are accessible, even when the data are no longer available.

To be Interoperable:

I1. (meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation.
I2. (meta)data use vocabularies that follow FAIR principles.
I3. (meta)data include qualified references to other (meta)data.

To be Re-usable:

R1. meta(data) have a plurality of accurate and relevant attributes.
R1.1. (meta)data are released with a clear and accessible data usage license.
R1.2. (meta)data are associated with their provenance.
R1.3. (meta)data meet domain-relevant community standards.

• Go FAIR initiative
• GoFAIR.org FAIRification process
• FAIR-Aware online tool. Developed by the FAIRsFAIR project. 
• FAIR Data Maturity Model. Specification and Guidelines 2020. Proposed RDA recommendation, FAIR Data Maturity Model WG, 2019-2020
• FAIRsFAIR  - Fostering FAIR data practices in Europe
• 6 Interoperability layers. Joinup, European Commission
• OpenAIRE Research Data Management Handbook

Helpdesk: researchdata@oulu.fi

Data Stewards at UOulu

1. Create a DMP
2. Create metadata, save and publish it
3. Licence your data
4. Get a permanent identifier to your data
5. Document your data
6. Cite your data in your publications
7. Evaluate your data from the point of view of long term preservation
8. Ask for support if needed

Data ONE´s Data Management Skillbuilding Hub. Best practices of data management: plan, collect, assure, describe, preserve, discover, integrate, analyze

Test how FAIR is your data: FAIR data assessment tool by ANDS

Explore Finnish Fairdata services are offered by the Ministry of Education and Culture and produced by CSC – IT Center for Science Ltd.

• QVain Research data metadata tool – saving metadata
• ETSIN Research data finder – browsing metadata
• IDA Research data storage: ​​UOulu contact person Ari-Pekka Kvist
• FAIRDATA-PAS Service for long-term preservation of data
• DMPTuuli  Tool for creating a data management plan

Webinars & tutorials (in Finnish) https://www.fairdata.fi/koulutus/koulutuksen-tallenteet/