[Limor Peer]

We hope you are enjoying P22 and have had a chance to attend a few of the sessions so far!

We are continuing our asynchronous discussion, which you can join here in the mailing list or through our slack in the #rda-plenary-22 channel. We invite you to share your thoughts, comments, ideas, and questions!

Our next featured group is the RDA SHARC IG.

The Sharing Rewards and Credit IG

The RDA Sharing Rewards and Credit (SHARC) IG is an interdisciplinary group with the aim of advancing the inclusion of Open Science in research evaluation to ensure it is rewarding for researchers to practice. The group is in the process of publishing two papers that detail their findings and recommendations and would value discussions on the role relationship between rewards and credit and computational reproducibility.

The Sharing Rewards and Credit IG has provided additional information on their vision for reproducibility and its challenges in the thread below. Please feel free to continue the conversation within the thread!

Briefly, tell us about your work/organization and how it’s related to computational reproducibility; What are you trying to address and how?

The RDA Sharing Rewards and Credit (SHARC) IG is an interdisciplinary group with the aim of fostering the implementation of rewarding paths and encouraging the adoption of data sharing/ Open Science (OS) activities-related criteria in the research evaluation process at the institutional, national and European / international levels, and also the goal of providing guidance for researchers and recommendations to critical actors in the academic rewarding scheme.

The IG’s focus is not directly related to computational reproducibility but a number of the findings and recommendations from the IG support the advancement of computational reproducibility in research.

What is your/your organization’s vision when it comes to computational reproducibility (e.g., all scholarship is computationally reproducible by default)?

That our findings/recommendations will drive further adoption of open science and FAIR practices.

What are some of the challenges you see to achieving this vision?

While our survey findings and recommendations are a resource for the range of stakeholders we address, from funders to publishers and institutions, still, these stakeholders face challenges ranging from resource dependent to cultural to sociotechnical to achieve the recommendations presented.

What would you like to ask the members of our Interest Group?

What relationship do you see between sharing rewards and credit with computational reproducibility?

Note: The RDA SHARC IG is in the process of publishing two papers that will detail our findings and recommendations. For a recent presentation of our work to the Evaluation of Research IG, see https://drive.google.com/file/d/1Py2iVLE8rr-ZskzjDO6qzcZ8g67Hx7VP/view.

Discussion