“Academics want to be famous!”
Not in the traditional sense perhaps—academia has more than its fair share of introverts—but to progress their career or win Nobel Prizes, an academic’s name and work need to be well-known in the community. This is traditionally achieved by publishing novel research in high-impact journals. However, evidence in “The State of Open Data 2017” continues to suggest that academics are happy to get their credit wherever they can.
For the second year running, more than 75% of researchers surveyed stated that they value a citation to their nontraditional research outputs (NTROs) as much as, if not more than, to a traditional output. This is consistent with indications that outputs other than publications and their impact will be rewarded at an equal level in funding decisions.
This year, figshare added citation information for every digital object identifier (DOI) that is minted across the system, whether it’s on an institutionally branded repository we support, or on figshare.com. What we are finding is that citations to these outputs are growing year on year. We’re also seeing a disproportionate amount of citations for code or software, an area that the traditional academic publishing systems have struggled to provide a solution for that adequately distributes that much sought-after credit. Being the first system to do this means that we are just scratching the surface on citation trends around NTROs.
This growth in the incentivization of researchers through credit is the first of three big trends that sum up the landscape around NTROs globally. The number of funder policies grows, along with suggestions about how to enforce compliance—yet the majority of researchers still don’t think they have a publisher, funder, or institutional mandate to share data.
Lack of researcher knowledge is the second trend. Institutions continue to hire research data librarians, and big publishers are employing data curators, and yet the majority of researchers still are unclear about licensing requirements. If we’re looking for an acceleration in open research globally, and what will drive it, it seems like there is still a lot of potential in the stick-led compliance approach, as policies and mandates proliferate and grow in precision across the world.
The third big trend in the space has been the buzz around preprints. With arXiv.org’s Physics database, ChemRxiv, and bioRxiv all having strong community-driven solutions, the concept of open access to all research outputs looks ever more likely. A rebrand of the institutional repository to the institutional preprint server may encourage compliance with open access mandates in a way that incentivizes the researchers. This all then becomes an infrastructure issue, one that is at least technically resolvable.
The State of Open Data is really The State of Open Academic Research Outputs, but that isn’t quite as catchy. Herein lies opportunities. The FAIR principles that have been lauded as the Shangri-la for all academic infrastructure can also be applied to open papers. All digital files, including preprints, or papers, should be thought of as “data” in this respect.
Our internal discussions put the general state of affairs to be consistent with:
- Data that is FAIR for humans
- Data that is FA for machines
With all of the above considered, the figshare team has come up with a set of guiding principles that can be adopted by publishers, funders, and institutions as we work toward a FAIR-er future:
- Academic research outputs should be as open as possible, and as closed as necessary.
- Academic research outputs should never be behind a paywall.
- Academic research outputs should be human and machine readable/query-able.
- Academic infrastructure should be interchangeable.
- Academic researchers should never have to put the same information into multiple systems at the same institution.
- There should be identifiers for everything.
- The impact of research is independent of the type of output and where it is published.
So Where Will the Next 12 Months Take Us?
It seems that a “happy” mixture of carrots, sticks, and education is needed to move academia forward, faster. All stakeholders have their own responsibilities. Carrots provided by funders and infrastructure providers, sticks evolving with the growing number of mandates. Perhaps most critical is education, both getting the message to academics and providing curation expertise. Here is the biggest unknown—where will the education come from? I believe we’ll see moves from universities and publishers. The balance of how content is disseminated and who ultimately gets credit for all these new citations, be it academics, publishers, or institutions, will be decided by how much resource and effort can be thrown into the education vertical.
2017 has been good for bringing open data into the mainstream. Infrastructure and credit problems are on their way to being solved. I, for one, hope that in 2018 we can say the same about education at every level of the academic pyramid, with a global focus on making things FAIR becoming our moon landing—a noble, ambitious target to aim for.