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“Myriad worries remain. Top of the pile is the potential for data misuse”


gScience recently released a new data platform, ‘Dimensions’. Designed to improve scholarly search, the platform links different data sources from publications with citations, grants, altmetric data, clinical trials and patents. As Hook emphasises: ‘Dimensions is


tracking citations and mining citations from papers, and can provide citation information, which means researchers can much more easily see the citations they are getting from their data.’ Professor Brian Nosek, social


psychologist from the University of Virginia, US, is equally enthusiastic about data citations, and highlights the significance of these to research communities. ‘Data should be cited as a scholarly contribution in the same way that papers should be cited, and this is beginning to be addressed in the community,’ he says. ‘You’re identifying the source, you’re providing credit and you’re showing that researchers are building on other researchers’ work, which also induces accountability for misuse.’ Nosek, a key figure in the open


science movement, co-founded the Center for Open Science in 2013, with the aim of increasing the openness and


FAIR principles


It’s no secret that existing digital infrastructure surrounding scholarly data publication prevents users from extracting maximum benefit from research investments. What’s more, as researchers increasingly look to reuse data, ways to ease this process are becoming more and more important. One route to best reuse


is to make data ‘FAIR’, that is, Findable, Accessible, Interoperable and Reusable. Conceived in 2014 and first published in 2016, the FAIR guiding principles aim to improve the infrastructure that supports the discovery and reuse of scholarly data, and comprise 14 metrics that


prescribe a continuum of increasing reusability. Two years on, the FAIR principles are being rapidly adopted by publishers, funders and institutions, yet in the world of scholarly research, the guidelines remain relatively unknown. When asked about the FAIR principles, only 15 per cent of the State of Open Data respondents reported being familiar with the guidelines, while 60 per cent sauid they have never heard of these. Digital Science’s Daniel


Hook is not surprised by the results. As he puts it: ‘Academics are busy doing research and given the first time that I heard the term was probably no more than


6 Research Information December 2018/January 2019


15 months ago, this isn’t a surprise to me.’ Still, the lack of awareness signals a clear need for education, and as is highlighted in the survey report, confirms the need for open data initiatives such as GO FAIR, which provides researchers with clear instructions on how to comply with FAIR. ‘Experimental science is


quite often very messy and trying to enshrine guidelines on how to work with the open data that comes out of that is very challenging,’ adds Hook. ‘Open data is a relatively new field, and I do think what we’re seeing here is a representation of this fuzziness.’


reproducibility of scientific research. Five years on, the not-for-profit centre is widely known for a range of mechanisms and tools to promote openness, including the Transparency and Openness Promotion (TOP) guidelines for data citation, data materials, code transparency and more. Crucially, these standards have been


embraced in more than 1,000 journals, with publishing heavyweights, such as Springer Nature, Wiley, Elsevier and more adopting TOP policies. And now the funders are following. ‘The TOP guideline signatories really


show that the journals are aligning on promoting data sharing, either incentivising or requiring it,’ says Nosek. ‘The next frontier is funders, and some have already started to make more assertive requirements. I think that over the next year or two, funders will really start to increase their policy alignment with the TOP guidelines, and promote more transparency for the research that they fund,’ he adds. Funders aside, Nosek is also seeing


more and more research fields sharing data. While the likes of macroeconomics, which hinges on economists sharing government data, and astronomy, with its shared instrumentation, are attuned to the concept, the researcher reckons other disciplines are jumping on board. Psychology is just one example. In 2015, Nosek and colleagues published The Reproducibility Project, which set out to replicate the findings from 100 past psychology studies, and ultimately g


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