By Julien Colomb | November 2, 2018
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Open FAIR data is the new standard
(actual srt file available on github)
Research data shall be free, digital, shared and re-usable. Only while open it will reach its true potential.
Fostering collaboration, open data accelerates research, and even years after its production, by allowing easy preliminary and meta-analyses, open data can bring research on the right track.
Open data provides a bulletproof defense against accusation of misconduct or bad scientific practices.
It increases research visibility and paper citations, and well organised open data does also fasten the research process.
Trustworthy results are efficiently and safely delivered, and the research gets more chances to be published and funded.
Governments, Funding agencies, universities, and publishers have recognized the importance of opening research data, and now, they request it, rightfully.
But producing open data does not come without difficulties, it indeed requires to modify the research workflow, a process that does not go without pain and efforts.
But once data management has been implemented, data opening happens in a swing.
Indeed the data is then already FAIR: difficulties are then blocked by open, findable, accessible, interoperable and re-usable data. In the end, good research always wins!
For society as well as for their career, research have to gear their data they need to make it open and FAIR, such that their data may fly away and save the day.
not used for the video and old script versions:
Research data is highly valuable, but only data that is shared, free, and re-usable can achieve its true potential:
Even years after its production, open data is indeed used in preliminary and meta-analyses, it fosters collaboration and accelerate research findings. Open data is saving lives.
On the other hand, the quality and reliability of the research is best controlled by assessing the underlying data.
Governments, Funding agencies, universities, and publishers have recognized the importance of opening research data. Making the data open is moving from being a noble things to do, to being a prerequisite to get funding and publish papers.
The most efficient and effective way to assures not only openeness, but also findability, accessibility, interoperability and re-usability of the data is to get an accurate data management. As often, this new paradigm will be faster and cheaper on the long term, and open FAIR data is an evolving standard.
35sec crash course on open FAIR data
Too fast, get help to design your data flow for sharing and computer readability online or at your RDM helpdesk and make your data easier to find, analyse, deliver and open.
That’s a common process: As researchers encounter the limits of their methods, they are asked to learn new skills and use different paradigms to collect their evidences. The new paradigms are often faster and cheaper to use such that research standards do evolve. The open data standard is no exception.
(Similarly to performing statisitical analyses)
The competitive researchers are being pro-active and are catching the train of open data. They do not stop there. the data should not only be shared, but also understandable first by men then by machines. They are implementing research data management early in the research process, because they know this is a good investment: it can save them time, while producing open FAIR data.
Researchers and especially project leaders shall recognize the advantages of producing FAIR data: - It fosters collaboration inside and outside of your group, making early mistakes recognition possible. - When the team changes, Knowledge transfer is greatly facilitated. - It is a huge time saver
See our next episodes on how to use RDM to make your data findable.