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However, their study moves forward through separate lines of research, between information literacy studies and professional learning in networked and online spaces ( Raffaghelli et al., 2016). Overall, new forms of scholarship aligning with open science ideals have been characterised as open, networked and social ( Goodfellow, 2014 Veletsianos, 2013). This is particularly true of increased activity by scholars on academic social networks (ASNs) and ResearchGate ( Manca, 2018). The literature suggests that scholars have moved to social media from traditional repositories and publication in search of strengthening mutual relationships, facilitating peer collaboration, publishing and sharing research products and discussing research topics in open and public formats ( Greenhow et al., 2019 Hildebrandt and Couros, 2016). Moving beyond open data repositories to other types of digital environments promoting scholars' networking and professional learning, research on the researchers' professional practices on social media and the related digital skills must not be left out ( Manca and Ranieri, 2017 Raffaghelli, 2017). Third, the methodological difficulties in capturing the social life of open research data (ORD), with some platforms providing more features to study sharing and reusing approaches than others ( Quarati and Raffaghelli, 2020). In this regard, the FAIR movement has set an agenda pushing the application of quality standard ( Association of European Research Libraries, 2017). Second, any open data quality standard parameters embedded into the digital infrastructures to share data would determine usage and sharing ( Berends et al., 2020). First, data cultures connected to disciplinary issues, research funding and value given to specific research practices address researchers' attention and practices ( Borgman, 2015 Koltay, 2017). Research on open data placed in open data repositories has considered several hypotheses in this regard. The most enthusiastic discussions on the availability of data and the feasibility of appropriation by civil society and researchers immediately encountered other factors blocking advanced data practices, crowd science, quality in research and second-hand data usage for industry or research purposes ( Molloy, 2011).

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