The Comparative Anatomy of Nanopublications and FAIR Digital Objects

Beginning in 1995, early Internet pioneers proposed Digital Objects as encapsulations of data and metadata made accessible through persistent identifier resolution services (Kahn Wilensky 2006). In recent years, this Object Architecture has been extended to include the FAIR Guiding Principles (Wilkinson et al. 2016), resulting concept a (FDO), minimal, uniform container making any digital resource machine-actionable. Intense effort is currently underway by global community experts clarify definitions around an FDO Framework (FDOF) provide technical specifications (FAIR DO group 2020, Forum 2020 , Bonino da Silva Santos (2021)) regarding their potential implementation. 2009, nanopublications were independently conceived (Groth 2010) individual semantic assertions associated provenance metadata, They represent minimal units structured citable entities (Mons Velterop 2009). A nanopublication consists assertion assertion, ( publication info ). Nanopublications are implemented aligned with Semantic Web technologies such RDF, OWL, SPARQL (World Wide Consortium (W3C) 2015) can be permanently uniquely identified using resolvable Trusty URIs 2021). The existing Nanopublication Server Network provides vital orchestrating (Kuhn 2021) including resolution, storage, search access. used expose quantitative qualitative data, well hypotheses, claims, negative results, opinions that typically unavailable or go unpublished altogether. first practical application occurred 2014, millions part FANTOM5 Project (The FANTOM RIKEN PMI CLST (DGT) Lizio 2015). Since then, real-world examples spanning diverse knowledge domains now available on server network. Like nanopublication, FDOF also posits ultra-minimal approach structured, self-contained, machine-readable metadata. An of: object itself (subsequently referred here avoid confusion other meanings term “object”); describing resource; globally unique predictable behaviors. These two share same vision infrastructure, act instances Machine-Actionable Containers (MACs) make use standards enable operations. Here, we compare structure computational behaviors those Framework. Although developed there clear parallels between FDOF. Each aspires for encapsulation information into free-standing, publishable (citable, referenceable) entities. involve identifiers resolve standardized semantically enabled descriptions machine actionable paths itself. At time, differences. scope limited assertional type and, name suggests, should remain small size (limited single triples RDF graphs). contrast FDOs unlimited scope, accommodating resources arbitrarily large size, complexity, so long ontologically described. Furthermore, whereas moderately mature technology, specification still under development. If it possible formally draw points contact approaches, then would leverage vast experience gained nanopublishing community. inspired applications FIP Wizard tool (Schultes 2020), extension research claims 2022, McNamara 2022) Schultes (2022a), (2022b), attempt point-by-point comparison FDOs. We find remarkable congruence requirements several FDO-like qualities already embodied ecosystem.