The last few years have seen considerable progress in terms of integrating individual elements of the research ecosystem with the so-called FAIR Principles (Wilkinson et al. 2016), a set of guidelines to make research-related resources more findable, accessible, interoperable and reusable (FAIR). This integration process has lots of technical as well as social components and ramifications, some of which resulted in dedicated terms like that of a FAIR Digital Object (FDO) which stands for research objects (e.g. datasets, software, specimens, publications) having at least a minimum level of compliance with the FAIR Principles.

As the volume, breadth and depth of FAIR data and the variety of FAIR Digital Objects as well as their use and reuse continue to grow, there is ample opportunity for multi-dimensional interactions between generators, managers, curators, users and reusers of data, and the scope of data quality issues is diversifying accordingly.

This poster looks at two ways in which individual collections of FAIR Digital Objects interact with the wider FAIR research landscape. First, it considers communities that curate, generate or use data, metadata or other resources pertaining to individual collections of FAIR Digital Objects. Specifically, which of these community activities are affected by higher or lower compliance of a collection's FDOs with the FAIR Principles? Second, we will consider the case of communities that overlap across FAIR collections - i.e. when some community members are engaged with several collections, possibly through multiple platforms - and what this means in terms of challenges and opportunities for enhancing findability, accessibility, interoperability and reusability between and across FAIR silos.

community curation, data curation, digital curation, collaborative curation, systemic curation, citizen science, participatory science, metadata, multilinguality, data quality, data reuse, data silos, FAIR processes

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This abstract was not presented at the FDO2022 Conference.