Incentivising research data sharing: a scoping review

Abstract

Background: Numerous mechanisms exist to incentivise researchers to share their data. This scoping review aims to identify and summarise evidence of the efficacy of different interventions to promote open data practices and provide an overview of current research. Methods: This scoping review is based on data identified from Web of Science and LISTA, limited from 2016 to 2021. A total of 1128 papers were screened, with 38 items being included. Items were selected if they focused on designing or evaluating an intervention or presenting an initiative to incentivise sharing. Items comprised a mixture of research papers, opinion pieces and descriptive articles. Results: Seven major themes in the literature were identified: publisher/journal data sharing policies, metrics, software solutions, research data sharing agreements in general, open science ‘badges’, funder mandates, and initiatives. Conclusions: A number of key messages for data sharing include: the need to build on existing cultures and practices, meeting people where they are and tailoring interventions to support them; the importance of publicising and explaining the policy/service widely; the need to have disciplinary data champions to model good practice and drive cultural change; the requirement to resource interventions properly; and the imperative to provide robust technical infrastructure and protocols, such as labelling of data sets, use of DOIs, data standards and use of data repositories.

Changing patterns in reporting and sharing of review data in systematic reviews with meta-analysis of the effects of interventions: a meta-research study

“…Data sharing via supplementary files or public repositories is an effective tool to improve reproducibility of systematic reviews and should be made a standard practice. Concerted efforts around data infrastructures, fair use guidelines and a supportive environment are required to make data sharing a standard practice [51–53].…”

Identifying and addressing data asymmetries so as to enable (better) science

“…Establishing this human infrastructure lies “at the very basis of the needed revolution in scientific methods” as the move toward more open and effective science in the data era faces “many more socio-cultural hurdles… than technical ones (Mons et al, 2020 ).” A landscape analysis of open science studies performed by Woods and Pinfield ( 2022 ) found that “disciplinary data champions [need] to model good practice and drive cultural change (Woods and Pinfield, 2021 ).”…”

“…There exists an increasing recognition that for data stewardship and sharing to create public and scientific value to achieve success, "it must be a truly multi-professional endeavor, " equipped with a human infrastructure that possesses the mandate and capacity to "create spaces for different types of data to be curated, shared, discoverable, and reusable in an ethical and timely way (Woods and Pinfield, 2021). "…”

“…than technical ones (Mons et al, 2020)." A landscape analysis of open science studies performed by Woods and Pinfield (2022) found that "disciplinary data champions [need] to model good practice and drive cultural change (Woods and Pinfield, 2021). "…”

“…In addition to these questions of relationships and connections, researchers seeking to use private sector data may face legal obstacles. Data-sharing agreements, licenses and other legal frameworks are often necessary for unlocking access to private sector data for research, potentially creating barriers to entry for some (Woods and Pinfield, 2021).…”