Relational data paradigms: What do we learn by taking the materiality of databases seriously?

Big Data and Society 7 (1) (2020)
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Abstract

Although databases have been well-defined and thoroughly discussed in the computer science literature, the actual users of databases often have varying definitions and expectations of this essential computational infrastructure. Systems administrators and computer science textbooks may expect databases to be instantiated in a small number of technologies, but there are numerous examples of databases in non-conventional or unexpected technologies, such as spreadsheets or other assemblages of files linked through code. Consequently, we ask: How do the materialities of non-conventional databases differ from or align with the materialities of conventional relational systems? What properties of the database do the creators of these artifacts invoke in their rhetoric describing these systems—or in the data models underlying these digital objects? To answer these questions, we conducted a close analysis of four non-conventional scientific databases. By examining the materialities of information representation in each case, we show how scholarly communication regimes shape database materialities—and how information organization paradigms shape scholarly communication. These cases show abandonment of certain constraints of relational database construction alongside maintenance of some key relational data organization strategies. We discuss the implications that these relational data paradigms have for data use, preservation, and sharing, and discuss the need to support a plurality of data practices and paradigms.

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References found in this work

The Structure of Scientific Revolutions.Thomas S. Kuhn - 1962 - Chicago, IL: University of Chicago Press. Edited by Ian Hacking.
The Structure of Scientific Revolutions.Thomas Samuel Kuhn - 1962 - Chicago: University of Chicago Press. Edited by Otto Neurath.
Data feminism.Catherine D'Ignazio - 2020 - Cambridge, Massachusetts: The MIT Press. Edited by Lauren F. Klein.
A theory of data.C. H. Coombs - 1960 - Psychological Review 67 (3):143-159.

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