Research output per year
Research output per year
Abstract
Do you work with data? Are you looking to make it future-proof? The FAIR Principles can help you.
These principles stand for the Findability, Accessibility, Interoperability and Reusability of data(sets). Applying these principles to your data(set) will help others to find, cite and reuse your data more easily.
FAIR-Aware helps you assess your knowledge of the FAIR Principles, and better understand how making your data(set) FAIR can increase the potential value and impact of your data.
The tool is discipline-agnostic, making it relevant to any scientific field. You can use this tool at any point during your research before depositing your data(set) in a data repository. It is also good to keep in mind that many FAIR-related decisions can already be made in the research planning phase, so you may want to use FAIR-Aware early on to help you make those decisions. Also, if you are a trainer, you can use FAIR-Aware to assess the knowledge of FAIR of your course participants.
The self-assessment consists of 10 questions with additional guidance texts to help you become more aware of what you can do to make your data(set) as FAIR as possible. The assessment will take between 10-30 minutes, after which you will receive an overview of your awareness level and additional tips on how you can further improve your FAIR skills.
These principles stand for the Findability, Accessibility, Interoperability and Reusability of data(sets). Applying these principles to your data(set) will help others to find, cite and reuse your data more easily.
FAIR-Aware helps you assess your knowledge of the FAIR Principles, and better understand how making your data(set) FAIR can increase the potential value and impact of your data.
The tool is discipline-agnostic, making it relevant to any scientific field. You can use this tool at any point during your research before depositing your data(set) in a data repository. It is also good to keep in mind that many FAIR-related decisions can already be made in the research planning phase, so you may want to use FAIR-Aware early on to help you make those decisions. Also, if you are a trainer, you can use FAIR-Aware to assess the knowledge of FAIR of your course participants.
The self-assessment consists of 10 questions with additional guidance texts to help you become more aware of what you can do to make your data(set) as FAIR as possible. The assessment will take between 10-30 minutes, after which you will receive an overview of your awareness level and additional tips on how you can further improve your FAIR skills.
| Original language | English |
|---|---|
| Media of output | Online |
| Publication status | Published - 2020 |
Fingerprint
Dive into the research topics of 'FAIR-Aware'. Together they form a unique fingerprint.Research output
- 1 Article
-
From Conceptualization to Implementation: FAIR Assessment of Research Data Objects
Devaraju, A., Mokrane, M., Cepinskas, L., Huber, R., Herterich, P., de Vries, J., Åkerman, V., L'Hours, H., Davidson, J. & Diepenbroek, M., 03 Feb 2021, In: Data Science Journal. 20, 1Research output: Contribution to journal/periodical › Article › Scientific › peer-review
Open Access26 Citations (Scopus)
Projects
- 1 Finished
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FAIRsFAIR
Dillo, I., Grootveld, M. J., von Stein, I., de Vries, J., Coen, G., Leenarts, E., Mokrane, M., van Horik, R., Kalaitzi, V. & Saldner, S.
01/03/2019 → 28/02/2022
Project: Research