Making data, resources & commons fully available and reusable implies to align with FAIR / CARE (& beyond FAIR) principles. This activity takes time, efforts and expertise that should be recognised and rewarded.

The meeting objective is to address at least the following reward related topics: 

1. Acknowledgement mechanisms along the scientist’s career (in papers, in communication supports, by mapping the re-use of data with relevant standards and metrics…)

2. Valuing the work and skills required: allocating resources (financial, material, human), more specific initiatives…

3. Considering data & resources sharing activities in the research evaluation scheme

How? By stimulating discussion with the audience on the current state of rewarding mechanisms & needs through short presentations (Part 1) and an interactive discussion (Part 2).

Collaborative session notes: https://docs.google.com/document/d/1tOKuc0WBwgVqzTUGffGY9pNIOLJGHmn-udhpmxqIKAs/edit

Part 1: Presentations

Topic 1: acknowledgement mechanisms along career

Some thoughts from the RDA Covid-19 set of recommendations, A. Cambon-Thomsen, Inserm-University of Toulouse.

Topic 2: data & resources sharing activities and evaluation scheme

First steps towards the inclusion of data sharing in the researchers’ evaluation scheme at the Italian Institute of Technology (IIT). Ugo Moschini, Valentina Pasquale, IIT

Knowledge Exchange Openness Profile: A reference model for the evaluation of open scholarship. Fiona murphy, MoreBrains Cooperative, UK.

Part 2: Interactive discussion

1. To get proposals from audience by way of interactive poll of ways / paths or rules to be efficient in implementing the 2 topics of the session, e.g.,    

– awards that could be created or shifted from “best paper” to “best dataset” where dataset is FAIR/CARE

– awareness of any open science practices being rewarded, f.ex. in job ads, tenure decisions?  

– introducing FAIRification /sharing activities in science training

– …

2. To prioritise these proposals with the audience

3. To start define recommandations targets and interactions

Conclusion:

Wrap-up and next actions

Researchers; Data service providers; Data stewards: support staff from research communities and research libraries, and those managing data repositories; Standards bodies governing procedures relevant to FAIR; Policymakers, Research funders, Institutions, Publishers and others defining data policy…