IEEE Access (Jan 2023)

Semi-Automatic Ontology Development Framework for Building Energy Data Management

  • Zhiyu Pan,
  • Yuting Gao,
  • Ferdinanda Ponci,
  • Antonello Monti

DOI
https://doi.org/10.1109/ACCESS.2023.3323335
Journal volume & issue
Vol. 11
pp. 111991 – 112003

Abstract

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With the ongoing digital transformation and multi-domain interaction occurring in the buildings, a huge amount of heterogeneous data is generated and stored on a daily basis. To take advantage of the gathered data and help better decision makings, suitable methods are needed to meet the demand for building operations and reinvestment planning. Ontology, which provides not only the vocabulary of a certain domain but also the relationship between each other has been used in multiple engineering fields to manage heterogeneous data. A plethora of ontology development methodologies have been developed in the last decade, whereas those methods are still really time-consuming and in a low degree of automation. In this paper, we approach the problem by first presenting a semi-automatic ontology development framework that integrates existing automatic ontology tools and reuses existing ontology and data model. Based on this framework, we create a building energy management ontology and evaluate the data coverage of several real-life data sets.

Keywords