An assessment of whether educated non-researcher audiences understand how to reuse research data
| Date | 16 October 2024 |
| Pages | 949-969 |
| DOI | https://doi.org/10.1108/EL-10-2023-0241 |
| Published date | 16 October 2024 |
| Author | Yejun Wu,Rujiang Bai,Fang Wang |
An assessment of whether educated
non-researcher audiences understand
how to reuse research data
Yejun Wu
School of Information Studies, Louisiana State University and A&M College,
Baton Rouge, Louisiana, USA
Rujiang Bai
Institute of Information Management, Shandong University of Technology,
Zibo, China, and
Fang Wang
Department of Information Resources Management, Nankai University,
Tianjin, China
Abstract
Purpose –The purpose of thisstudy is to assess whether educated non-researcher audiencesunderstand how
to reuse researchdata stored in a data repository.
Design/methodology/approach –A total of 44 participants in two user studieswere asked to study a data
set accessed from re3data.org. The participants were non-researcher audiences of the disciplines of the
selected data sets. They wereasked to figure out whether they understood how to reuse a data set after reading
all the metadataorcontextualinformation about the data set.
Findings –Most participants reportedthat they figured out how to reuse the data, although their self-reports
can be an overestimated assessment. However, the participants understand how to reuse a data set either
numerically or statisticallysignificantly worse than what the data set is, howit was collected or created and its
purpose. Data settype tends to play a role in understanding how to reuse datasets and the purpose of data sets.
Participants reportedthat unless a data set is self-explanatory,instructions on data set reuse and the purpose of
data set were necessary forunderstanding how to reuse data set. However, because data reuse requiresdomain
knowledge and data processingskills, some non-researcher audiences who lack domain knowledgeand data
processingskills may not understand how to reuse the data setin any way.
Research limitations/implications –This study’sfindingsenrich the theoretical framework of data sharing
and reuse by expanding the necessary information to be included in data documentation to support non-
researchers’datareuse. The findings of the study complement previous literature.
Practical implications –This study extended previous literature by suggesting detailed data reuse
instructions be included in data documentation if data producers and data curators wish to supporteducated
non-researchers’data reuse.This study’sfindings enable policymakers of research data management(RDM)
to formulate guidelines for supporting non-researchers’data reuse. If data curators need to work with data
producers to prepare the instructions on data reuse for non-researcher audiences, they probably need
computing and data processing skills. This has implications for Library and Information Science schools to
educate datalibrarians.
We wish to acknowledge graduate students AAA at ABC and BBBat XYZ who assisted in coding the
data for this study.
Funding: This research did not receive any specific grant from funding agencies in the public,
commercial or not-for-profit sectors.
The Electronic
Library
949
Received7 October 2023
Revised5 January 2024
31Ma rch 2024
31 May 2024
Accepted17June2024
TheElectronic Library
Vol.42 No. 6, 2024
pp. 949-969
© Emerald Publishing Limited
0264-0473
DOI 10.1108/EL-10-2023-0241
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/0264-0473.htm
Originality/value –The research question is original because non-researcher audiences in the context of
RDM have not been studied before.This study extended previous literature by suggesting detailed datareuse
instructions be included in data documentationif data curators and data producers and data curators wish to
support educatednon-researchers’data reuse. This study’sfindingsenable policymakers of RDM to formulate
guidelinesfor supporting non-researchers’data reuse.
Keywords Research data, Data management, User studies
Paper type Research paper
Introduction
In 1999, US federal funding agencies added data management and sha ring requirements to their
grant applications and required all data produced under a federally funded award be made
available to the public. The data management and sharing requirements have promoted the
formulation of policies on data sharing and reuse worldwide. By 2019, the USA, Australia,
Canada, China and 16 European countries had adopted national policies on scientificdata
sharing, with an aim to enhance data reuse (SPARC Europe and Digital Curation Centre, 2019).
The policies and investment in institutional infrastructure and research data management
(RDM) services have encouraged the practice of data sharing and reuse in academia.
The purpose of sharing data is to reuse data. However, there is no common definition of
“reuse”proposed across disciplines (van de Sandt et al., 2019). It can have two meanings.
One is the practice of using data by the same people as the original collectors in data
recycling, data repurposing and data recontextualization. The other meaning is the practice
of using data by people other than the originalcollectors (Wang et al.,2021). The definition
of “reuse”in this paper is limited to the second meaning.
The audience of data reuse is not specifically defined. From the above description of
requirements, the audienceof data reuse is the general public, not only the scientificresearch
community.Borgman et al. (2019) studied who consumed data from the Data Archiving and
Networked Services InstituteofThe Netherlands and found that the consumers were diverse
in terms of discipline and occupation, which included academic researchers, practitioners
and lay persons. They reused data for learning, research and other purposes. Bishop and
Kuula-Luumi (2017) investigated7,155 unique data reuse downloads of 267 data collections
for the UK Data Service and found that 64% of downloaded data sets wereused for learning,
15% for research, 13% for teaching and eight percent for miscellaneous uses. Therefore, the
audiences of data reuse are not only academic researchers but also educated non-researcher
audiences. Non-researcher audiences are important to the RDM services because they are
downloading and using research data, and so are users of RDM services. Non-researcher
audiences can improve education and bring about professional and social developments
through data reuse. Previous studieshave focused on data sharing and reuse by researchers.
Ideally, data service providers should support both researchers and non-researchers for their
various purposes.
The goal of this exploratory research is to assess whether educated non-researcher
audiences understand how to reuse data sets in the domain of their undergraduate majors.
Two user studies were designed to investigate this issue. In each study, a group of educated
non-researcher audienceswere invited to study a data set they selected and were instructedto
figure out how to reuse the data set for teaching or learning purposes. The qualitative data
collected from the two studies were merged for analysis. The findingshave implications for
RDM services to support datareuse by non-researcher audiences.
The paper is organized as follows.The literature review section summarizes the literature
of RDM research that is closely relatedto this study. After presenting research questionsand
EL
42,6
950
Get this document and AI-powered insights with a free trial of vLex and Vincent AI
Get Started for FreeStart Your Free Trial of vLex and Vincent AI, Your Precision-Engineered Legal Assistant
-
Access comprehensive legal content with no limitations across vLex's unparalleled global legal database
-
Build stronger arguments with verified citations and CERT citator that tracks case history and precedential strength
-
Transform your legal research from hours to minutes with Vincent AI's intelligent search and analysis capabilities
-
Elevate your practice by focusing your expertise where it matters most while Vincent handles the heavy lifting
Start Your Free Trial of vLex and Vincent AI, Your Precision-Engineered Legal Assistant
-
Access comprehensive legal content with no limitations across vLex's unparalleled global legal database
-
Build stronger arguments with verified citations and CERT citator that tracks case history and precedential strength
-
Transform your legal research from hours to minutes with Vincent AI's intelligent search and analysis capabilities
-
Elevate your practice by focusing your expertise where it matters most while Vincent handles the heavy lifting
Start Your Free Trial of vLex and Vincent AI, Your Precision-Engineered Legal Assistant
-
Access comprehensive legal content with no limitations across vLex's unparalleled global legal database
-
Build stronger arguments with verified citations and CERT citator that tracks case history and precedential strength
-
Transform your legal research from hours to minutes with Vincent AI's intelligent search and analysis capabilities
-
Elevate your practice by focusing your expertise where it matters most while Vincent handles the heavy lifting
Start Your Free Trial of vLex and Vincent AI, Your Precision-Engineered Legal Assistant
-
Access comprehensive legal content with no limitations across vLex's unparalleled global legal database
-
Build stronger arguments with verified citations and CERT citator that tracks case history and precedential strength
-
Transform your legal research from hours to minutes with Vincent AI's intelligent search and analysis capabilities
-
Elevate your practice by focusing your expertise where it matters most while Vincent handles the heavy lifting
Start Your Free Trial of vLex and Vincent AI, Your Precision-Engineered Legal Assistant
-
Access comprehensive legal content with no limitations across vLex's unparalleled global legal database
-
Build stronger arguments with verified citations and CERT citator that tracks case history and precedential strength
-
Transform your legal research from hours to minutes with Vincent AI's intelligent search and analysis capabilities
-
Elevate your practice by focusing your expertise where it matters most while Vincent handles the heavy lifting