Academic Credit for Data Sharing
Focus Area: Transparency
The current system for recognizing academic advancement is predicated on a track record of peer-reviewed publications. Individuals who share data are rarely rewarded academically for making data available to others for secondary analysis, nor are they formally recognized for data preparation and curation. Because the current system of academic recognition is not aligned with the goals of data sharing, investigators may feel reticent about sharing data.
In response to these structural barriers, the MRCT Center, in collaboration with the New England Journal of Medicine and the Association of American Medical Colleges, formed a working group of key stakeholders from academia, journals, and funding organizations. The group worked to advance a system of recognition and academic credit for data generators who opt to share their data. Five focus areas, each of which has its own specific objective, were developed:
- Criteria: create guidelines and criteria for establishing which researchers are given credit for their work in generating, curating, and making available original datasets
- Technical Requirements and Integration with Current Efforts: harmonize and supplement existing principles and strategies for good data management (e.g. data curation, citation, and archiving) and move towards a unified technical solution
- Academic Institutions: obtain consensus from diverse stakeholders to ensure that academic institutions have a standardized process for documenting, incorporating, and assessing credit for data sharing efforts
- Journals and Publishers: obtain agreement from diverse stakeholders to ensure that journals will—and will be able to—adopt a single system for acknowledging the work of data authors in publications in a manner that allows for tracking of the use of datasets and of secondary publications based on the work of data authors
- Funders: obtain consensus and agreement from diverse stakeholders to ensure that funders are able to assess the impact of an applicant’s previously shared data and the validity or robustness of a proposal to use an existing dataset
Current Status: Dissemination
Impact: A systematized, consistent, and universal method for recognizing and crediting researchers who generate, manage, and/or share data to create legitimate and lasting incentives for data sharing.
- To generate practical, comprehensive recommendations on how data generators should be credited and recognized for the design, curation, completion, and communication of quality data sets.
- To harmonize and supplement existing principles and strategies for good data management and citation.
- To unify a technical architecture and end-to-end solution by which a data generator may receive credit for sharing data.
- To obtain support from diverse stakeholders in order to launch, implement, and sustain a system for establishing credit for data sharing.
- Credit for Data Sharing workshop materials
- Article “Credit data generators for data reuse” published in Nature
- March/April 2017: Published “Data Authorship as an Incentive to Data Sharing” in New England Journal of Medicine
- May 2017: Workgroup launched on credit for data sharing
- July 2017: In-person meeting at the New England Journal of Medicine
- September 2017: Technical considerations developed for establishing a system of credit for data sharing
- April 2018: “Implementing a System to Enable Credit for Data Sharing” Workshop at the Association of American Medical Colleges (AAMC)
- June 2019: Published “Credit data generators for data reuse” in Nature
- Barbara E. Bierer, MD. Faculty Director, MRCT Center
- Jeffrey Drazen, MD.New England Journal of Medicine
- Heather Pierce, MPH, JD. Senior Director, Association of American Medical Colleges
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