Hochstenbach, PatrickPatrickHochstenbachVan De Sompel HerbertVerborgh, RubenRubenVerborgh2026-05-062026-05-062026978-3-032-05408-10302-9743https://imec-publications.be/handle/20.500.12860/59347Common research assessment approaches rely heavily on data pertaining to traditional contributions to the research endeavor (R), including the number of journal articles published, the journals in which those articles are published, and the citations the articles or journals receive. Dissatisfaction with these approaches has led to a global call for alternatives that take a much wider range of contributions into account, including those in areas such as Education (E), societal impact (I), and academic leadership (L). While traditional research outputs are relatively easy to track, thanks to their publication in a finite set of dedicated scholarly venues, non-traditional REIL contributions are typically disseminated across the broader web. This includes outputs such as research data, software, reports, courses, live performances, interviews, and committee leadership, making their discovery and collection far from straightforward. In an attempt to devise a scalable, automated approach to tackle this “find the REIL needles in the web haystack” problem, we introduce the Claims Network approach, which collects information about REIL contributions by inviting researchers to post about them on the distributed Mastodon social media environment. Through a prototype developed around the academic Mastodon instance operated by SURF in the Netherlands, we demonstrate that the approach is feasible and can be extended to include other Mastodon instances, both academic and general-purpose.engProceedings paper10.1007/978-3-032-05409-8_11WOS:001677701100011