Data Communities A New Model for Supporting STEM Data Sharing (2019) by Danielle Cooper (@dm_cooper) and Rebecca Springer (@Rsspringer1). @IthakaSR. COVID-19 Professional ReadingAdministrators, funders, librarians, publishers, and even the researchers themselves, have been struggling with what it means to “share data.” In an environment where “open” is officially revered, what it means to be open, to share, and to appropriately document this -- as well as making the data findable, accessible, interoperable, and reusable (FAIR) -- can be challenging, and at best confusing.
This issue brief, from Ithaka S+R tackles the issue from the STEM standpoint (set of disciplines that is at the same time easier and harder than tackling the humanities) and creates the term “Data Community” to define a group that could facilitate data sharing:
“We contend that stakeholders who wish to promote data sharing – librarians, information technologists, scholarly communications professionals, and research funders, to name a few – should work to identify and support emergent data communities. These are groups of scholars for whom a relatively straightforward technological intervention, usually the establishment of a data repository, could kickstart the growth of a more active data sharing culture.”
The authors are careful to note that a "Data Community" is not a discipline, but rather:
“A data community is a fluid and informal network of researchers who share and use a certain type of data, such as crystallographic structures, DNA sequences, or measurements relating to natural disasters.”
The characteristics of successful Data Communities include:
As libraries, publishers, and funders have built systems, services and platforms for a range research information management (RIM) activities, the overall uptake by scholars and researchers has been spotty. Here, in the context of the data communities, the researchers suggest:
“Instead of pouring resources into “build it and they will come” strategies, information professionals, publishers and policy makers should take a ground-up approach to data sharing support.”
They continue:
“Over the past two decades, many academic libraries have invested considerable staff and financial resources into developing and utilizing institutional repositories. Most of these repositories were initially built to store and make available academic gray literature, such as unpublished reports, dissertations, and preprints of articles destined for publication. However, in recent years, librarians have begun exploring ways to repurpose institutional repositories as platforms to enable data sharing; an extensive literature details the successes and challenges of these efforts.”
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“While institutional repositories serve other useful purposes, we believe that they are a vehicle ill-suited to the support of data communities that cross institutional boundaries. By its nature, the institutional repository segregates information according to the college or university at which it was created, while at the same time bringing together the vast array of different types of data created within and across the institution’s departments. While this may fulfill an institution’s preservation mandate, such repositories are not conducive to supporting the way scientific research is conducted, with researchers from different institutions working together on focused projects.”
Academic libraries, generally, have not worked within the larger ecosystems of formal or informal data communities to support and advance their activities or ability to share data.
“It is also worth reflecting on the need to rethink the role of academic libraries specifically in supporting data sharing. The academic institution – and, by extension, its library – is not always the appropriate scale on which to address the challenges that scientists face. Librarians who want to effectively support scientists must find creative ways to contribute their expertise within the broader, cross-institutional, interdisciplinary ecosystem of scientific research. Awareness is the first step: librarians should understand to which data communities scientists at their institutions belong.”
The growing evidence that the authors cite of the formation of data communities as extra mural activities of researchers, leads to the radical thought that: “The best opportunities for librarians to leverage their unique expertise in designing information systems to support science research may lie outside the university altogether.”
In a time of constrained budgets, the ability of university and library administrators to realize the seemingly altruistic activity of devoting resources to activities with no direct connection to the organization (unlike, say, an institutional repository), will involve an important leap of faith.
An excellent and thought provoking report.
