Library capacity for data curation services: a US national survey
| Published date | 18 November 2019 |
| Pages | 811-828 |
| Date | 18 November 2019 |
| DOI | https://doi.org/10.1108/LHT-12-2018-0209 |
| Author | Ayoung Yoon,Devan Ray Donaldson |
| Subject Matter | Library & information science |
Library capacity for data curation
services: a US national survey
Ayoung Yoon
Department of Library and Information Science,
Indiana University –Purdue University at Indianapolis, Indianapolis,
Indiana, USA, and
Devan Ray Donaldson
Department of Information and Library Science,
Indiana University at Bloomington, Bloomington, Indiana, USA
Abstract
Purpose –The purpose of this paper is to understand the landscape of data curation services among public
and academic libraries in the USA, with a focus on library capacity for providing data curation services.
Design/methodology/approach –The authors conducted an online survey by employing stratified
sampling from the American Library Directory. A total of 198 responses were analyzed.
Findings –The authors’findings provideinsight into the current landscapeof libraries’data curationservices.
The survey participants evaluated six capacity dimensions for both public and academic libraries –value,
financial, administrative, technicalinfrastructure, human resourcesand network. The ratings the participants
gave to these capacitydimensions were significantly different between academic and public libraries.
Practical implications –This study suggests several areas in which libraries will benefit from further
developing their capacity to successfully run data curation services.
Originality/value –This is among the first research study to address the concept of capacity in the context
of libraries’data curation services.
Keywords Library services, Organizational capacity, Data curation, Data services, Library capacity,
National survey
Paper type Research paper
Introduction
The interest in, and need for, data services in libraries is increasing rapidly. Consequently,
libraries –mostly academic, but also a few public –are attempting to establish these
services. Motivations behind the services vary due to the different missions of each type of
library: academic libraries tend to serve faculty and students, and are significantly
influenced by the funding agencies’mandate for research data sharing; while public
libraries are engaged with open data initiatives to serve their community and citizens, and
are mostly influenced by the open government movement. Several recent studies have
identified an increase in academic libraries launching data services or extending existing
services (Cox and Pinfield, 2014; Yoon and Schultz, 2017; Xia and Wang, 2014), which are (or
should be) accompanied by proper data curation programs. Although it is relatively new in
the public library domain, recent studies have argued the need for public libraries’active
engagement in providing data services to communities (Bertot et al., 2014; Gibson et al.,
2009; Robinson and Mather, 2017). These studies also demonstrate a significant level of
variation in these services and programs, perhaps due to the libraries’differing
organizational capacities (Yoon and Schultz, 2017).
To successfully and sustainably launch and maintain data services in libraries, data
curation programsmust be tailored to a library’s existingcapacity. Noah and Brickman (2004)
Library Hi Tech
Vol. 37 No. 4, 2019
pp. 811-828
© Emerald PublishingLimited
0737-8831
DOI 10.1108/LHT-12-2018-0209
Received 31 December 2018
Revised 20 March 2019
Accepted 21 March 2019
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0737-8831.htm
This project was funded by Institute of Museum and Library Services (No. #LG-72-17-0139-17). The
authors would also like to thank Annise Blanchard, Samuel Russell, Mandeep Dhillon and Shen Zhang
for their assistance with the project.
811
Library
capacity for
data curation
services
argue that capacity building is necessary to strengthen or support a library’sabilityto
provide high-quality, accessible and sustainable services to its community –a point that is
also applicable to data curation services. Eventually, libraries must appropriately build or
grow their capacities to sustain or extendtheir data curation programs in thelong-term. Doing
so will ensure effectiveness and help libraries avoid unintended consequences.
Despite the importance of capacity to libraries, few scholars have discussed what the
concept of capacity actually means in the library context, why it is important, and how
capacity assessment and building can be accomplished (Carrigan, 2015). Further, no study
has analyzed how capacity relates to data curation services in libraries. Therefore, the aim
of this study is to understand the landscape of data curation services among public and
academic libraries in the USA, focusing on library capacity for providing data curation
services. While previous literature has discussed organizational capacity as critical to
fulfilling organizational purpose, this concept has not been extensively employed when
studying libraries (Noah and Brickman, 2004).
In this study, we broadly define data curation as the active and ongoing management of
data through its lifecycle to best serve the needs of current and future users. Based on our
review of the literature on capacity and libraries, we define capacity as a library’s ability to
implement or perform internally –or externally-generated expectations and outcomes
(Barman and MacIndoe, 2012; European Commission, 2005; Horton et al., 2003; Sharpe,
2006). As understanding capacity is a fundamental prerequisite for effectively realizing
expected outcomes, this study’s findings help build a foundation to expand libraries’
capacity for data curation services.
As noted, our study included both academic and public libraries. Because we understand
the differences between academic and public libraries in terms of workforce, priorities and
funding, one of our goals is to use this study to examine these differences. This will guide
our next study in developing a capacity assessment framework for libraries, that is whether
one framework is applicable to both types of libraries, or two separate frameworks are
necessary for academic and public libraries.
Literature review
Academic libraries have been traditionally responsible for curating data to address their
mission of protecting and disseminating data, particularly with recent mandates from
funding agencies’data sharing policies. Recent research suggests the way to implement
data services to meet the new demand is assess researchers’needs, select a repository
environment, prepare training materials both for librarians and researchers, build
expertise among library staff and establish metadata guidelines (Erway et al., 2016). The
need to provide data services, however, is not only for academic and research libraries that
provide data management services for faculty. Given the rise in publicly available data
resources, many open government data initiatives at the federal, state, and city levels
currently exist or are in the process of being created, which involve partnerships with
public libraries. For example, the Boston Public Library has a recent initiative to develop
an open data collection for the City of Boston (City of Boston, 2017). Although the
involvement of public libraries in community data services is in its infancy, more public
libraries are developing their interests in data service models. Further, several studies
underscore the significance of public libraries to be Open Data Hubs. Publiclibraries have
the potential to open doors to marginalized populations and encourage citizen to
contribute to existing data sets, improving the quality of life for everyone (Greenwalt,
2014; Sey et al., 2013). Despite the continuous efforts and new demands in academic and
public libraries, previous studies also point out the gaps and opportunities for libraries to
hone their data curation services to more effectively meet users’needs ( Johnston et al.,
2018). Further, existing efforts to understand libraries’data curation practices focus on
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