Figshare: a universal repository for academic resource sharing?
| Date | 13 June 2016 |
| Published date | 13 June 2016 |
| DOI | https://doi.org/10.1108/OIR-06-2015-0190 |
| Pages | 333-346 |
| Author | Mike Thelwall,Kayvan Kousha |
| Subject Matter | Library & information science,Information behaviour & retrieval |
Figshare: a universal repository
for academic resource sharing?
Mike Thelwall and Kayvan Kousha
School of Mathematics and Computer Science,
University of Wolverhampton, Wolverhampton, UK
Abstract
Purpose –A number of subject-orientated and general websites have emerged to host academic
resources. The purpose of this paper is to evaluate the uptake of such services in order to decide which
depositing strategies are effective and should be encouraged.
Design/methodology/approach –This paper evaluates the views and shares of resources in the
generic repository Figshare by subject category and resource type.
Findings –Figshare use and common resource types vary substantially by subject category but
resources can be highly viewed even in subjects with few members. More active subject areas do not
tend to have more viewed or shared resources.
Research limitations/implications –The view counts and share counts analysed may reflect
author accesses or may be spammed.
Practical implications –Limited uptake of Figshare within a subject area should not be a barrier to
its use. Several highly successful innovative uses for Figshare show that it can reach beyond a purely
academic audience.
Originality/value –This is the first analysis of the uptake and use of a generic academic resource
sharing repository.
Keywords Data sharing, Digitization, Repository, Figshare
Paper type Research paper
Introduction
Scientific resource sharing is important in research for reasons of efficiency, power and
rigour. At the most basic level, making experimental data available allows others to
check calculations or to replicate a study, which is central to rigorous science
(Nature, 2015; Sieber, 1991). Moreover, some studies need data on a scale that requires
sharing. For example, identifying diseases from brain scans requires access to large
numbers of healthy and diseased examples obtained from organised data sharing
(Poline et al., 2012) using common standards (e.g. Demir et al., 2010). More generally,
sharing any kind of academic resource can aid efficiency by ensuring that scholars do
not have to needlessly repeat prior work. An important example of this is the
software R, which contains many statistical procedures written by academics
(e.g. Rosseel, 2012) and freely shared for others to use.
Scholars can use the web to disseminate electronic resources, including software,
datasets, internal reports, and digitised art and cultural artefacts (Schubert et al., 2013;
Schopfel et al., 2014). In genetics and environmental science, for example, datasets are
significant research outputs and are often shared (Anagnostou et al., 2013). Data
sharing can have practical challenges (Borgman, 2012) and researchers may be
cautious (Huang et al., 2012; Vogeli et al. 2006; Walport and Brest, 2011), but there is a
strong tradition of sharing resources in some fields (e.g. software in computer science),
for some types of general data (e.g. surveys: UKDA, 2007) and for specialist
information, such as species records in biodiversity research (Faith et al., 2013; Moritz
et al., 2011; see also: Barve, 2014) and human biological samples (Chen, 2013).
Online Information Review
Vol. 40 No. 3, 2016
pp. 333-346
©Emerald Group Publis hing Limited
1468-4527
DOI 10.1108/OIR-06-2015-0190
Received 9 June 2015
Revised 18 November 2015
Accepted 18 December 2015
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/1468-4527.htm
333
Academic
resource
sharing
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