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Data analysts could benefit from an application assistant that supports them throughout the KDD process and aids them to discover which are the relevant variables for the matter at hand, or informing about relationships among relevant data. In this article, the EEPSA (Energy Efficiency Prediction Semantic Assistant) ontology which supports such an assistant is presented. The ontology is developed on the basis that a proper axiomatization shapes the set of admitted models better, and therefore, establishes the ground for a better interoperability. On the contrary, underspecification facilitates the admission of non-isomorphic models to represent the same state which hampers interoperability. This ontology is developed on top of three ODPs (Ontology Design Patterns) which include proper axioms in order to improve precedent proposals to represent features of interest and their respective qualities, as well as observations and actuations, the sensors and actuators that generate them, and the procedures used. Moreover, the ontology introduces six domain ontology modules integrated with the ODPs in such a manner that a methodical customization is facilitated.<\/jats:p>","DOI":"10.3233\/ao-210245","type":"journal-article","created":{"date-parts":[[2021,3,2]],"date-time":"2021-03-02T12:59:31Z","timestamp":1614689971000},"page":"193-228","source":"Crossref","is-referenced-by-count":9,"title":["EEPSA as a core ontology for energy efficiency and thermal comfort in buildings"],"prefix":"10.1177","volume":"16","author":[{"given":"Iker","family":"Esnaola-Gonzalez","sequence":"first","affiliation":[{"name":"TEKNIKER, Basque Research and Technology Alliance (BRTA), I\u00f1aki Goenaga 5, 20600 Eibar, Spain. 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