🧑‍🔬 Aidan Hogan

Aidan Hogan works on knowledge graphs and the Semantic Web, with a focus on how graph-structured data about real-world entities can be represented, published and queried. Their papers here deal with RDF, SPARQL querying and Wikidata. A recurring question is how rich, annotated statements can be expressed within standard graph data models without losing the ability to query them with existing tools. The work falls under the topic of Knowledge graphs & ontologies.

The most cited of these papers is Knowledge Graphs (2020). It is a broad, tutorial-style survey written by a large international team. It sets out what knowledge graphs are, which techniques they draw on and how they connect to earlier data management research. It takes an inclusive view of a knowledge graph as a graph of entities linked by relations, assembled to capture and convey knowledge about the world. An earlier and more technical study, Reifying RDF: What Works Well With Wikidata? (2015), asks how Wikidata should be converted to RDF so that ordinary SPARQL engines can query it. Wikidata statements carry qualifiers and source references, so the triples themselves need to be described. The paper models this as statement-identified quads plus auxiliary triples, and then compares ways of encoding those quads in RDF. Read together, the two papers move from a concrete reification problem in 2015 to a general overview of the field in 2020.

Hogan's current institution is the University of Chile, where bylines run from 2014 onward. Earlier papers, from 2005 to 2018, were written at Ollscoil na Gaillimhe – University of Galway, with some also listing the National University of Ireland. Co-authors in the library include Gerard de Melo and Roberto Navigli.

Aidan Hogan has 2 papers in our library, in 2015–2020, most of them on Knowledge graphs & ontologies; often with Gerard de Melo, Roberto Navigli.