Making Data Count: A Practical Framework for Engaging Researchers in Open Science
Pearce, Alaina
- Publisher
- Zenodo
- Language
- en
Abstract
While sharing research data openly benefits the broader scientific community, it requires significant time and effort and is often perceived to have little benefit to the individual researcher. Contributing to this perception is the fact that data sharing is not formally recognized in tenure or career advancement decisions at most academic institutions. To make open science more appealing and sustainable, it is important to address both the perceived benefit of and effort required for data sharing. Therefore, this framework incorporates data sharing outputs like publications and citations, which ‘count’ in academic structures, in addition to focusing on practical research data management (RDM) skills. This session presents a framework for engaging researchers in open science and data sharing by showing them how to get credit for sharing their data. Central to this approach is the focus on practical research outputs that help to build a researcher’s CV or citation count. One example of this is data papers, which are peer-review publications that accompany open data. Data papers provide an additional peer-reviewed publication and a direct way to cite the use of shared data in the future. To prepare data for publication, researchers also need training in practical, ‘good enough’ RDM practices. These ‘good enough’ practices are relatively low effort, have a shallow learning curve, and increase data reusability. This framework will help librarians develop programing that improves RDM, encourages data sharing, and helps research see strategic benefits of data sharing Learning Objectives: · Identify ‘good enough’ data practices that can support data sharing · Understand how data papers can incentivize researchers to engage in RDM training and data sharing
Full text
Making Data Count: A Practice Framework for Engaging Researchers in Open Science Alaina Pearce, PhD Penn State University [email protected] MDLS - 10/20/25 1
Meeting Researchers Where they Are •Limited time, resources, funding •Prioritize research activities that contribute to: •Competitiveness in the tenuretrack job market •Promotion/tenure •What currently counts? •Publications •Citations 2 MDLS - 10/20/25
3 Data Sharing for Funder Compliance MDLS - 10/20/25
4 Re-Frame: Data as Scholarship MDLS - 10/20/25 •Data sharing as a means to increase visibility and professional recognition •Leverage existing systems so data sharing results in scholarly outputs currently valued: Publications and Citations •Meet researchers where they are with ‘Good Enough’ RDM practice
5 MDLS - 10/20/25 Data Papers: Getting Credit for Sharing Data
6 Data & Research Paper Ecosystem Research Paper •Cites data paper in data availability statement •Points to project directory to support open methods Dataset •All raw data files in open formats •Associated metadata •Often in a data repository separate from the project repository Project Repository •Open protocol and documentation •Version control/change log to maintain record of changes •Provides necessary context for data Data Paper •Provides full documentation of dataset •Project repository and dataset subject to peer review to ensure usability MDLS - 10/20/25
7 Data Papers MDLS - 10/20/25 Re-Frame: Data as Scholarship
8 “Good Enough” Research Data Management Data Papers MDLS - 10/20/25 Re-Frame: Data as Scholarship
“Good Enough” Research Data Management 9 MDLS - 10/20/25
Acknowledgments Open Scholarship Initiative https://penn-state-open-science.github.io/ Ana Enriquez [email protected] Nicole Lazar [email protected] Rick Gilmore r[email protected] Briana Wham [email protected] 16 MDLS - 10/20/25 Briana Wham [email protected] Research Data Stewardship Program
