Towards A More Reasonable Semantic Web

TL;DR

This work argues that the original semantic web vision can be accelerated by shifting from Description Logic to existential Horn clauses within $FOL$, reframing ontology as a data-migration and integration problem at scale. It connects the semantic web to the broader automated-theorem-proving and database-theory communities, proposing a $RL$-driven foundation that remains backward compatible with existing RDF/OWL while enabling large-scale interoperability, particularly in geospatial domains. The paper provides formal treatments of relational, graph, and RDF-like models under $FOL$, demonstrates case studies translating geospatial representations (e.g., GML) into $RL$ with chase-based normal forms, and presents concrete proposal formats (JSON-LD-Logic, $TPTP$ multi-sorted) to bridge RDF/OWL with first-order reasoning. The result is a framework that leverages mature reasoning and data-migration tools to achieve scalable, interoperable semantic data integration, with a concrete action plan for adoption in geo-spatial information management.

Abstract

We aim to accelerate the original vision of the semantic web by revisiting design decisions that have defined the semantic web up until now. We propose a shift in direction that more broadly embraces existing data infrastructure by reconsidering the semantic web's logical foundations. We argue to shift attention away from description logic, which has so far underpinned the semantic web, to a different fragment of first-order logic. We argue, using examples from the (geo)spatial domain, that by doing so, the semantic web can be approached as a traditional data migration and integration problem at a massive scale. That way, a huge amount of existing tools and theories can be deployed to the semantic web's benefit, and the original vision of ontology as shared abstraction be reinvigorated.