By Irene Pasquetto

As we all know too well, making all scientific data technically and legally accessible to all researchers is an ambitious task complicated by constantly evolving social and technical barriers. It is fair to say that we are making progresses in this direction. At Scidatacon 2016, we examined several concrete solutions that can facilitate openness of scientific data or, if you prefer, make sure data are FAIR (findable, accessible, interoperable and reusable).

However, it seems that the more we learn about how to make data open, the least we know about how exactly data will be reused by the scientific community, which means by the researchers who generated the data and should have a primary interest in accessing it. Very few empirical studies exist on the extent to which open data are used and reused once deposited in open repositories.

The fulcrum of the problem is that data take many forms, and are produced, managed and used by diverse communities for different purposes. Nevertheless, different stakeholders (publishers, data curators, digital librarians, funders, scientists etc.) bear competing points of view on the kind of policies, values, and infrastructural solutions necessary to make data open. During a session moderated by Christine Borgman (UCLA) and titled “How, When, and Why are Data Open? Competing Perspectives on Open Data in Science”, Matthew Mayernik (National Center for Atmospheric Research), Parsons Mark (National Snow and Ice Data Center) and Irene Pasquetto (UCLA – Center for Knowledge Infrastructures) presented on some of those challenges that make the use and reuse of “open data” such a complicated and heterogeneous process.

Mayernik argued that the integration of the Internet into research institutions has changed the kinds of accountabilities that apply to research data. On one hand, open data policies expect researchers to be accountable for creating data and metadata that support data sharing and reuse in a broad sense, in many cases, to any possible digital user in the world. On the other hand, providing accounts of data practices that satisfy every possible user is in most cases impossible.

In his talk, Parsons effectively showed that data access is an ongoing process, not a one-time event. Parsons and his team examined how the data repositories products and their curation have evolved over time in response to environmental events and increasing scientific and public demand over several decades. The products have evolved in conjunction with the needs of a changing and expanding designated user community. In other words, Parsons’ case study shows that it is difficult to predict the users of a data service because new and unexpected audiences (with specific needs) could emerge at any time. Parsons also argued that, for this reason, “data generators” may not be the best individuals to predict future uses of their own data.

Because open data users change over time, it is also necessary to built open repositories that provide data in formats flexible enough to allow different approaches to data analysis and integration, for different audiences. This was the point made by Pasquetto, whose case study is a consortium for data sharing in craniofacial research, with a focus on the subfield of developmental/evolutionary biology that recently adopted genomics approaches to knowledge discovery. Pasquetto found flexible data integration to be a necessary precursor to using and reusing data. “Data integration work” is the most contested and problematic task faced by the community, where data need to be integrated at two or more levels and these levels require extensive collaboration between engineers, biologists, and bioinformaticians.

Borgman also presented a paper on the beneath of Ashley Sands, who recently graduated from the department of Information Studies at UCLA and is now senior program officer at the Institute of Museum and Library Services in Washington DC. This talk examined characteristics of openness in the collection, dissemination, and reuse of data in two astronomy sky survey case studies: the Sloan Digital Sky Survey (SDSS) and the Large Synoptic Survey Telescope (LSST). Discussion included how the SDSS and LSST data, and datasets derived from the projects by end users, become available for reuse. Sands found that the rate at which data are released, the populations to which the data are made open, the length of time data creators plan to make the data available, the scale at which these endeavors take place, and the stages of these two projects all have great impact to the extent in which data and then reused.

Moral of the story: open data is a fast moving target. In order to enable reuse, data repositories better start to run.

It was a pleasure to start off the first full day of SciDataCon with a keynote from Elaine M Faustman, Professor and Director at the Institute for Risk Analysis and Risk Communication, University of Washington and member of the ICSU World Data System Scientific Committee.  Professor Faustman’s keynote talk, ‘Challenges and Opportunities with Citizen Science:  How a decade of experiences have shaped our forward paths’, introduced a welcome early focus on the importance of rigorous ethical approaches to ‘citizen science’ research projects. Looking back to the early roots of the knowledge practices we now call ‘science’, Faustman reminded us that of course the roots of these practices can be found in the work of European gentleman scientists and their cabinets of curiosities.   She also situated contemporary citizen science practice in the US legislatory framework of the US citizen’s right to know, work which has been underpinned by standards and acts since the 1940s onwards.

Reflecting over a decade of citizen science practice in the environment and public health domains, Faustman provided examples of projects where citizens are not only research subjects but are centrally influential in the work, to the point where they express ownership of the project alongside the university team.  Discussion focused on the importance of the abilty of research participants to influence the direction and scope of the research project, to provide feedback on its progress, and to have access to the data accrued in order to be able – in case of public health projects at least – to use it to guide their own decision-making.  The message of deep ethical engagement and building respectful relationships with participants set the scene for a day in which ethical issues reverberated.

The second keynote was by Simon Cox, Research Scientist, Environmental Informatics, CSIRO Land and Water, Clayton, Melbourne, Australia.  In his talk, ‘What does that symbol mean? – controlled vocabularies and vocabulary services’, Cox raised a very pragmatic point about the widespread problem of non-systematic use of symbols – and keywords – in data.  He demonstrated that we assume symbols and keywords have some sort of shared meaning, at least in a given community, but that the reality is much less systematic. Symbols and abbreviations with no widely used consistent meaning are often used by researchers when creating data. Popular terms describing volume can mean entirely different things in different countries.  And even symbols of terms describing a widely understood measurement, such as the metre, can be problematic link to a common source: the International Bureau of Weights and Measures provides a definition, which can be found via a given URI. But the fact that this URI has changed regularly from year to year disrupts any expectation of a stable, enduring location for this definition.

Cox suggested a couple of actions to mitigate this situation. Firstly, a new CODATA task group on coordinating data standards will take this work forward. Secondly, the Global Agricultural Concept Scheme – GACS – is the result of three defining sources from agricultural research banding together to deduplicate their respective vocabularies and make them interoperable for agricultural researchers. Cox noted that the technical job is not large but that – in confluence with Faustman’s earlier message – the really big job is achieving the buy-in from the community in question.

So the pesky human dimension appears right at the start of International Data Week!  More information on the keynotes is at http://www.scidatacon.org/site/opening-keynote/

Laura Molloy is a doctoral researcher at the Oxford Internet Institute and the Ruskin School of Art, University of Oxford. She is on Twitter at @LM_HATII.