Science friction: Data, metadata, and collaboration

Edwards, Paul N.; Mayernik, Matthew S.; Batcheller, Archer L.; Bowker, Geoffrey C.; Borgman, Christine L.

doi:10.1177/0306312711413314

Cited by 367 publications

(326 citation statements)

References 40 publications

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“…In further work, Edwards et al (2011) focus on how non-standardised metadata generation in a scientific collaboration resulted in science studies has tended to focus on a variety of data problems within particular scientific disciplines; researchers have rarely examined how data travel between diverse disciplines (Edwards et al, 2011;Taylor et al, 2014 She further observes that efforts to overcome friction at one site may simply displace frictions to another site, extending the circulation of data rather than removing friction altogether.…”

Section: Ementioning

confidence: 99%

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The politics of data friction

Bates

2017

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Structured Abstract PurposeThe aim of the paper is to further develop Paul Edwards' concept of "data friction" by examining the socio-material forces that are shaping data movements in the cases of research data and online communications data. The paper aims to articulate a politics of data friction, identifying the interrelated infrastructural, socio-cultural and regulatory dynamics of data friction, and how these are contributing to the constitution of social relations. Design/methodology/approachThe article develops a hermeneutic review of the literature on socio-material factors influencing the movement of digital data between social actors in the cases of research data sharing and online communications data. Parallels between the two cases are identified and used to further develop understanding of the politics of "data friction" beyond the concept's current usage within the Science Studies literature. FindingsA number of overarching parallels are identified relating to (1) the ways in which new data flows and the frictions that shape them bring social actors into new forms of relation with one another, (2) the platformisation of infrastructures for data circulation, and (3) state action to influence the dynamics of d M resulting from the collective decisions of human actors who experience significantly different levels of empowerment with regard to shaping the overall outcome. Research implicationsThe paper further develops Paul Edwards' concept of "data friction" beyond its current application in Science Studies. Analysis of the broader dynamics of data friction across different cases identifies a number of parallels that require further empirical examination and theorisation. Practical implicationsThe observation that sites of data friction are deeply political has significant implications for all engaged in the practice and management of digital data production, circulation and use. Social implicationsI some of the complex socio-material dynamics shaping emergent data movements across a variety of domains, and inform deliberation at all levels -from everyday practice to international regulationabout how such frictions can be collectively shaped towards the creation of more equitable and just societies. Originality/valueThe paper makes an original contribution to the literature on friction in the dynamics of digital data movement, arguing that in many cases data friction may be something to enable and foster, rather than overcome. It also brings together literature from diverse disciplinary fields to examine these frictional dynamics within two cases that have not previously been examined in relation to one another.

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Section: Ementioning

confidence: 99%

“…This emphasis reflects Edwards et al 2011) framing of the concept and 669). However, data friction is clearly a concept that translates beyond study of scientific data infrastructures.…”

Section: Ementioning

confidence: 99%

The politics of data friction

Bates

2017

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“…Current pressures to standardize methods reveal the significant challenges in ensuring that this community can act as a single, strong, and united entity in negotiating access to shared infrastructure (Darch, 2016). Relationships between shared and domain-specific infrastructures should be studied across a wider range of scientific endeavors, as points of friction often reveal deeper truths about scientific practice (Borgman et al, 2015;Edwards et al, 2011).…”

Section: Discussionmentioning

confidence: 99%

Ship space to database: emerging infrastructures for studies of the deep subseafloor biosphere

Darch

Borgman

2016

PeerJ Computer Science

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Background. An increasing array of scientific fields face a ''data deluge.'' However, in many fields data are scarce, with implications for their epistemic status and ability to command funding. Consequently, they often attempt to develop infrastructure for data production, management, curation, and circulation. A component of a knowledge infrastructure may serve one or more scientific domains. Further, a single domain may rely upon multiple infrastructures simultaneously. Studying how domains negotiate building and accessing scarce infrastructural resources that they share with other domains will shed light on how knowledge infrastructures shape science. Methods. We conducted an eighteen-month, qualitative study of scientists studying the deep subseafloor biosphere, focusing on the Center for Dark Energy Biosphere Investigations (C-DEBI) and the Integrated Ocean Drilling Program (IODP) and its successor, the International Ocean Discovery Program (IODP2). Our methods comprised ethnographic observation, including eight months embedded in a laboratory, interviews (n = 49), and document analysis. Results. Deep subseafloor biosphere research is an emergent domain. We identified two reasons for the domain's concern with data scarcity: limited ability to pursue their research objectives, and the epistemic status of their research. Domain researchers adopted complementary strategies to acquire more data. One was to establish C-DEBI as an infrastructure solely for their domain. The second was to use C-DEBI as a means to gain greater access to, and reconfigure, IODP/IODP2 to their advantage. IODP/IODP2 functions as infrastructure for multiple scientific domains, which creates competition for resources. C-DEBI is building its own data management infrastructure, both to acquire more data from IODP and to make better use of data, once acquired. Discussion. Two themes emerge. One is data scarcity, which can be understood only in relation to a domain's objectives. To justify support for public funding, domains must demonstrate their utility to questions of societal concern or existential questions about humanity. The deep subseafloor biosphere domain aspires to address these questions in a more statistically intensive manner than is afforded by the data to which it currently has access. The second theme is the politics of knowledge infrastructures. A single scientific domain may build infrastructure for itself and negotiate access to multi-domain infrastructure simultaneously. C-DEBI infrastructure was designed both as a response to scarce IODP/IODP2 resources, and to configure the data allocation processes of IODP/IODP2 in their favor.

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“…Although scientists' reasoning for making their data available to peers and using others' data has been the topic of some social research (e.g., Edwards et al 2011;Whyte et al 2011;Acord and Harley 2012), much of this work has been confined to high-income settings. In contrast, through a Leverhulme Trust funded project, we set out to investigate the day-to-day experiences of those undertaking research in low-resourced environments.…”

Section: Data Sharing In Africa: Empirical Findingsmentioning

confidence: 99%

Fostering Data Openness by Enabling Science: A Proposal for Micro-Funding

Rappert

2017

Data Science Journal

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In recent years, the promotion of data sharing has come with the recognition that not all scientists around the world are equally placed to partake in such activities. Notably, those within developing countries are sometimes regarded as experiencing hardware infrastructure challenges and data management skill shortages. Proposed remedies often focus on the provision of information and communication technology as well as enhanced data management training. Building on prior empirical social research undertaken in sub-Sahara Africa, this article provides a complementary but alternative proposal; namely, fostering data openness by enabling research. Towards this end, the underlying rationale is outlined for a 'bottom-up' system of research support that addresses the day-to-day demands in low-resourced environments. This approach draws on lessons from development financial assistance programs in recent decades. In doing so, this article provides an initial framework for science funding that call for holding together concerns for ensuring research can be undertaken in low-resourced laboratory environments with concerns about the data generated in such settings can be shared.Keywords: Open Data; micro-funding; cash transfers; micro-credit; AfricaThe 2015 publication Open Data in a Big World: An International Accord produced by the International Council for Science (ICSU), the InterAcademy Partnership (IAP), the World Academy of Sciences (TWAS) and the International Social Science Council (ISSC) offers a recent high level statement on the potential of making research data widely available. Against claims of a revolution in memory storage capacity and connectivity, the report sets out to identify the benefits of promoting data openness; this including facilitating the correction of results, enabling the replication of findings, detecting fraud, promoting international collaborations, and supporting evidence-based decision making.And yet, Open Data in a Big World recognized that achieving openness was not straightforward. Merely making data accessible by putting it online, for instance, would not be sufficient. Other requirements included the need for data to be: readily discoverable; complemented with background information necessary to make it intelligible; combined with sufficient computational metadata; and supplemented with enough information to reveal the competences and financial interests of data producers. Further still, ethical, safety, security and other concerns were recognized in Open Data in a Big World as limiting what data should be shared. Despite the demands of and cautions with open data, when the revolutionizing benefits were considered against potential downsides, the conclusion reached by ICSU, IAP, TWAS and ISSC was clear: openness should be the default position for publicly funded research.And yet, echoing conclusions reached elsewhere, Open Data in a Big World noted that researchers in least developed countries would struggle to partake in collecting, analysing, reusing, and sharing data (see as w...

show abstract

Science friction: Data, metadata, and collaboration

Cited by 367 publications

References 40 publications

The politics of data friction

The politics of data friction

Ship space to database: emerging infrastructures for studies of the deep subseafloor biosphere

Fostering Data Openness by Enabling Science: A Proposal for Micro-Funding

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