If you are a researcher in the biological sciences, chemistry, digital humanities and sociology the UK Data Service and Jisc would like to invite you to participate in one of several focus groups exploring the use of FAIR data principles within UK academic research.
Two free to attend workshops will be held in September, one in London and the other in Newcastle.
What is meant by the FAIR Data Principles?
FAIR refers to a set of guiding principles developed by a group of international stakeholders which proposes that scholarly outputs should be:
This article published in Scientific Data is the first 'formal' publication of the FAIR principles and it outlines the importance of good research data management practices in a "data-rich research environment".
The European Commission aims to make FAIR data sharing the default for scientific research by 2020. They are currently gathering views from a diverse set of stakeholders through their Expert Group on turning FAIR data into reality, which aims to facilitate this goal.
I really like the Dutch Techcentre for Life Sciences FAIR Data website, which provides a significant amount of information and resources on this topic, including how to comply with the 15 FAIR Data principles
Two free to attend workshops will be held in September, one in London and the other in Newcastle.
What is meant by the FAIR Data Principles?
FAIR refers to a set of guiding principles developed by a group of international stakeholders which proposes that scholarly outputs should be:
- Findable: easy to find for both humans and computers, with metadata that facilitate searching for specific datasets
- Accessible: stored for long term so that they can easily be accessed and/or downloaded with well-defined license and access conditions (open access when possible), whether at the level of metadata, or at the level of the actual data
- Interoperable: ready to be combined with other datasets by humans or computers
- Reusable: ready to be used for future research and to be further processed using computational methods
This article published in Scientific Data is the first 'formal' publication of the FAIR principles and it outlines the importance of good research data management practices in a "data-rich research environment".
The European Commission aims to make FAIR data sharing the default for scientific research by 2020. They are currently gathering views from a diverse set of stakeholders through their Expert Group on turning FAIR data into reality, which aims to facilitate this goal.
I really like the Dutch Techcentre for Life Sciences FAIR Data website, which provides a significant amount of information and resources on this topic, including how to comply with the 15 FAIR Data principles