EDBT 2026 Demo / reviewers in the wild / expert
James O'Donnell
dblp:02/9466
· DBLP profile ↗
5ranked-venue papers in the field
0as first author
3since 2021 · last 2026
0000-0002-5881-9989ORCID · reported
Domains — venue-derived; a paper can count in several
Other / Interdisciplinary · 5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Artificial intelligence to enhance BIM-BEPS integration via IFC: Challenges, solutions, and future directions
Liége Garlet, Matheus Körbes Bracht, Roberto Lamberts, Ana Paula Melo, James O'Donnell |
Adv. Eng. Informatics | 5 |
| 2025 | A semantics-driven framework to enable demand flexibility control applications in real buildingsabstractDecarbonising and digitalising the energy sector requires scalable and interoperable Demand Flexibility (DF) applications. Semantic models are promising technologies for achieving these goals, but existing studies focused on DF applications exhibit limitations. These include dependence on bespoke ontologies, lack of computational methods to generate semantic models, ineffective temporal data management and absence of platforms that use these models to easily develop, configure and deploy controls in real buildings. This paper introduces a semantics-driven framework to enable DF control applications in real buildings. The framework supports the generation of semantic models that adhere to Brick and SAREF while using metadata from Building Information Models (BIM) and Building Automation Systems (BAS). The work also introduces a web platform that leverages these models and an actor and microservices architecture to streamline the development, configuration and deployment of DF controls. The paper demonstrates the framework through a case study, illustrating its ability to integrate diverse data sources, execute DF actuation in a real building, and promote modularity for easy reuse, extension, and customisation of applications. The paper also discusses the alignment between Brick and SAREF, the value of leveraging BIM data sources, and the framework's benefits over existing approaches, demonstrating a 75% reduction in effort for developing, configuring, and deploying building controls. Flavia de Andrade Pereira, Kyriakos Katsigarakis, Dimitrios Rovas, Marco Pritoni, Conor Shaw, Lazlo Paul, Anand Prakash, Susana Martin-Toral, Donal Finn, James O'Donnell |
Adv. Eng. Informatics | 10 |
| 2022 | A linked data approach to multi-scale energy modelling
Cathal Hoare, Reihaneh Aghamolaei, Muireann Lynch, Ankita Gaur, James O'Donnell |
Adv. Eng. Informatics | 5 |
| 2014 | Using semantic web technologies to access soft AEC data
Edward Corry, James O'Donnell, Edward Curry, Daniel Coakley, Pieter Pauwels, Marcus M. Keane |
Adv. Eng. Informatics | 2 |
| 2013 | Linking building data in the cloud: Integrating cross-domain building data using linked data
Edward Curry, James O'Donnell, Edward Corry, Souleiman Hasan, Marcus M. Keane, Seán O'Riain |
Adv. Eng. Informatics | 2 |