Knowledge graph for policy- and practice-aligned life cycle analysis and reporting
The built environment is a key leverage point for policy intervention to combat climate change and the statutory reporting of financial and non-financial indicators over the asset lifecycle is increasingly required. This poses significant information management challenges in a sector characterised by complexity. Contributions to-date which address Life Cycle Asset Information Management (LCAIM) remain siloed and difficult to generalise, resulting in limited in-practice uptake, but domain literature identifies graph databases and ontologies as suitable strategies for addressing this information-intensive challenge. This paper provides a LCAIM ontology, co-developed with stakeholders, and verified technically through implementation in a case study by responding to end-user-defined storage, retrieval, and enrichment functions using a knowledge graph. The prototype is then validated qualitatively with experts who perceive it as addressing collective governance-practice requirements. Overall, the study suggests that addressing technical LCAIM challenges may be feasible using available technologies and recommends prioritising research towards socio-economic issues. • Harmonises governance-practice Life Cycle Asset Information Management requirements. • Develops a stakeholder co-created LCAIM ontology based on these requirements. • Verifies ontology functionality via end-user-generated queries in a knowledge graph. • Validates that collective requirements are met via qualitative stakeholder engagement. • Solves LCAIM challenges using available technology, suggesting a renewed research focus.
Authors
- Cathal Hoare (ORCID: https://orcid.org/0000-0002-4507-7269)
- Flávia de Andrade Pereira (ORCID: https://orcid.org/0000-0002-2019-7571)
- James O’Donnell (ORCID: https://orcid.org/0000-0002-5881-9989)
- Karim Farghaly (ORCID: https://orcid.org/0000-0003-0717-7434)
- Conor Shaw (ORCID: https://orcid.org/0000-0003-4642-5533)
- Martijn de Riet
Institutions
- University College Dublin (IE)
- Centerforce (US)
- University College London (GB)
Publication Details
- Journal
- Automation in Construction
- Published
- 2025-05-28
- DOI
- https://doi.org/10.1016/j.autcon.2025.106282
- Citations
- 3
- Primary Topic
- Data Quality and Management
- Type
- article
- Field-Weighted Citation Impact
- 6.32
Funders
- Horizon 2020 Framework Programme
- H2020 Marie Skłodowska-Curie Actions