Accepted Paper:

Large scale data assessments through digital platforms in science- the coproduction of significance  

Authors:

Clemens Bluemel (DZHW)
Stephan Gauch (DZHW / Humboldt University Berlin)

Paper Short Abstract:

In this paper, we aim to explore how these data are collected, what drives their collection (e.g., their technical accessibility), how they are ordered and how these orderings resonate within existing frameworks and semantics of science such as open science or societal impact of science.

Paper long abstract:

Large scale data practices have not only become established within specific specialties of science but also in current approaches to evaluate and monitor scientific output .One of the major expressions of this transformation towards digital, large scale data practices in scholarly evaluation are so called alternative metrics which collect and harvest digital traces of reception for scholarly output, taking stock of almost every form of communication in the digital universe. In this paper, we aim to explore how these data are collected, what drives their collection (e.g., their technical accessibility), how they are ordered and how these orderings resonate within existing frameworks and semantics of science such as open science or societal impact of science. We argue that the classification of metrics from novel forms of scholarly output have not only been driven by specific technical or infrastructural conditions that prefigure specific categories of valuation but also by specific regimes of legitimation in the socio-political governance of science. Our material consists of almost 400 scholarly articles, position papers as well as more than 20 interviews of digital platform providers, publishers and scholars in the realm of digital science evaluation.

Panel G03
Technologies that count: big data and social order