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This seminar is part of a series to provide societies and their journals with information and resources to help their communities be more knowledgeable and prepared to share data (and software) in a way that is relevant and meaningful for each discipline. This is a 12-month series. Democratization of Data 1 October 2021, 10am ET (1400 UTC) Speakers: Sabina Leonelli, Department of Sociology, Philosophy and Anthropology, University of Exeter (bio) Louise Bezuidenhout, Institute for Science, Innovation, and Society, University of Oxford (bio) Moderator: Doug Schuster, NCAR - US National Center for Atmospheric Research Description: Research is dependent on findable, accessible, and well-documented data. And yet there continue to be fundamental challenges in data access equity across disciplines, borders, and even teams. Research data needed for local and regional decision-making can be difficult to find, understand, or lacking altogether. Dr. Sabina Leonelli and Dr. Louise Bezuidenhout will share an overview of their around these challenges and recommend areas where societies can bring awareness and support improvements. Seminar Recording: https://youtu.be/OTNEQudyZuc, Special thank you to Laura Lyon of AGU and her support organizing and managing this seminar.

SHARC (SHAring Reward & Credit) est un groupe d'intérêt scientifique interdisciplinaire créé dans le cadre de RDA (Research Data Alliance) dans le but de faciliter le partage des données de recherche (et des ressources) par la valorisation de l'ensemble des activités pré-requises à ce partage, tout au long du cycle de vie des données. Dans ce cadre, un sous-groupe de travail SHARC élabore des grilles d'évaluation des chercheurs afin de mesurer leur niveau de prise en compte des principes FAIR dans la gestion de leurs données. La grille d'évaluation présentée dans ce poster est destinée à être complétée par tout scientifique produisant et / ou utilisant des données. Il s'agit d'un résumé d'une grille d'évaluation plus étendue conçue pour un partage optimal des données (non encore mise en œuvre pour le moment par la plupart des scientifiques). L'évaluation est basée sur les critères de conformité FAIR. Pour remplir cet objectif, la grille affiche le minimum de critères qui doivent absolument être appliqués par les chercheurs pour attester de leur pratique FAIR. Ces critères sont organisés en 5 groupes: «Motivations de partage»; "Trouvable", "Accessible", "Interopérable" et "Réutilisable". Pour chaque critère, 4 degrés d'évaluation sont proposés ("Jamais / Non évaluable"; "Si obligatoire"; "Parfois"; "Toujours"). Au moins un degré mais un seul doit être sélectionné par critère. L'évaluation doit être effectuée pour chaque catégorie F / A / I / R; L'évaluation finale est la somme de chaque degré coché rapportée au nombre total de critères dans chaque catégorie F / A / I / R. Des règles d'interprétation prenant en compte les «motivations du partage» sont proposées.

The RDA-SHARC (SHAring Reward & Credit) interest group is an interdisciplinary volunteer member-based group set up as part of RDA (Research Data Alliance) to unpack and improve crediting and rewarding mechanisms in the sharing process throughout the data life cycle. Background and objectives of this group are reported here. Notably, one of the objectives is to promote the inclusion of data sharing activities in the research (& researchers) assessment scheme at national and European levels. To this aim, the RDA-SHARC-IG is developing two assessment grids using criteria to establish if data are compliant to the F.A.I.R principles (findable /accessible / interoperable / reusable) based on previous works on FAIR data management (Reymonet et al., 2018; Wilkinson et al., 2018; and E.U.Guidelines*): 1/ The self-assessment grid to be used by a scientist as a ‘checklist’ to identify her/his own activities and to pinpoint the hurdles that hinder efficient sharing and reuse of his/her data by all potential users. 2/ The two-level grid (quick/extensive) to be used by the evaluator to assess the quality of the researcher/scientist sharing practice, over a given period, taking into account the means & support available over that period. Assessment criteria are classified according their importance with regards to FAIRness (essential / recommended / desirable) meanwhile good practices are recommended for critical steps. To implement a highly fair assessment of the sharing process, appropriate criteria must be selected in order to design optimal generic assessment grids. This process requires participation, time and input from volunteer scientists data producers/users from various fields.

Towards recommendations for crediting the sharing in Research: addressing challenges within African academic infrastructures. Despite numerous statements and an active promotion in some countries or institutions, data & materials sharing according to the FAIR principles is still not the practice in most communities. This is even more the case for the sharing of materials such as physical samples. Various obstacles have been identified and discussed in the literature. Some of them are cross-scientific communities over countries, some are more specific. Our group focuses on a major obstacle, the lack of recognition for the efforts required, to make the resources available and reusable, and works to provide recommendations that would take into account as much as possible challenges within existing academic infrastructures to resolve these difficulties. The group’s activity has moved forward on two fronts to date. 1/ Describing the landscape of the crediting and rewarding processes regarding the sharing activity in different scientific communities (biomedical and life sciences, biodiversity, geospatial domains mainly so far) to identify gaps, both domain-specific and transversal. 2/ Drafting recommendations accordingly that will be elaborated, disseminated and presented to relevant stakeholders at national and international levels, to establish improved guidance for resource sharing and its recognition in research practices. Meeting objectives 1) To focus on sharing related concerns specific to African scientific communities; 2) To gain specific insights into the challenges facing Academic scientists interested in sharing research resources 3) To get feedback and input from scientists from those communities and networks interested in the SHARC objectives of regarding actionable interventions to enhance the recognition of sharing activities as important research ouputs 4) To come up with concrete actions to support resource sharing that could be implemented within African research contexts Further questions: How do we incentivise data sharing in situations where individuals have invested their own money into their research? What is the empirical evidence around the benefits that accrue to researchers when they share their data? Will research partnerships and co-authorship be acceptable conditions for obtaining access to secondary data? Recognizing the marked differences in the research settings in Africa (political, legal and ethical, physical, social and economic etc.) which all have a bearing on incentivizing data sharing, to what level can the research community harmonize policies that govern fair data sharing and incentivizing / rewarding in Africa? How best can the research community with a longer experience in the area of data sharing help to develop training programmes to educate research stakeholders in Africa about fair data sharing and incentivizing data sharing practices, at all levels (individual, institutional, continental)?What knowledge, insights, and practices around sharing/re-use are already in place in Africa that could be usefully amplified to other research communities?

The RDA-SHARC (SHAring Reward & Credit) interest group is an interdisciplinary volunteer member-based group set up as part of RDA (Research Data Alliance) to unpack and improve crediting and rewarding mechanisms in the sharing process throughout the data life cycle. Background and objectives of this group are reported here. Notably, one of the objectives is to promote the inclusion of data sharing activities in the research (& researchers) assessment scheme at national and European levels. To this aim, the RDA-SHARC-IG is developing two assessment grids using criteria to establish if data are compliant to the F.A.I.R principles (findable /accessible / interoperable / reusable) based on previous works on FAIR data management (Reymonet et al., 2018; Wilkinson et al., 2018; and E.U.Guidelines*): 1/ The self-assessment grid to be used by a scientist as a ‘checklist’ to identify her/his own activities and to pinpoint the hurdles that hinder efficient sharing and reuse of his/her data by all potential users. 2/ The two-level grid (quick/extensive) to be used by the evaluator to assess the quality of the researcher/scientist sharing practice, over a given period, taking into account the means & support available over that period. Assessment criteria are classified according their importance with regards to FAIRness (essential / recommended / desirable) meanwhile good practices are recommended for critical steps. To implement a highly fair assessment of the sharing process, appropriate criteria must be selected in order to design optimal generic assessment grids. This process requires participation, time and input from volunteer scientists data producers/users from various fields.