Metadata Schemas and Ontologies for Building Energy Applications: A Critical Review and Use Case Analysis

Marco Pritoni, Drew Paine, Gabriel Fierro, Cory Mosiman, Michael Poplawski, Avijit Saha, Joel Bender and Jessica Granderson
Additional contact information
Marco Pritoni: Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
Drew Paine: Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
Gabriel Fierro: Electrical Engineering & Computer Sciences Department, University of California, Berkeley, CA 94720, USA
Cory Mosiman: National Renewable Energy Laboratory, Golden, CO 80401, USA
Michael Poplawski: Pacific Northwest National Laboratory, Richland, WA 99354, USA
Avijit Saha: National Renewable Energy Laboratory, Golden, CO 80401, USA
Joel Bender: Building Automation and Control Systems Integration Group, Cornell University, Ithaca, NY 14850, USA
Jessica Granderson: Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA

Energies, 2021, vol. 14, issue 7, 1-37

Abstract: Digital and intelligent buildings are critical to realizing efficient building energy operations and a smart grid. With the increasing digitalization of processes throughout the life cycle of buildings, data exchanged between stakeholders and between building systems have grown significantly. However, a lack of semantic interoperability between data in different systems is still prevalent and hinders the development of energy-oriented applications that can be reused across buildings, limiting the scalability of innovative solutions. Addressing this challenge, our review paper systematically reviews metadata schemas and ontologies that are at the foundation of semantic interoperability necessary to move toward improved building energy operations. The review finds 40 schemas that span different phases of the building life cycle, most of which cover commercial building operations and, in particular, control and monitoring systems. The paper’s deeper review and analysis of five popular schemas identify several gaps in their ability to fully facilitate the work of a building modeler attempting to support three use cases: energy audits, automated fault detection and diagnosis, and optimal control. Our findings demonstrate that building modelers focused on energy use cases will find it difficult, labor intensive, and costly to create, sustain, and use semantic models with existing ontologies. This underscores the significant work still to be done to enable interoperable, usable, and maintainable building models. We make three recommendations for future work by the building modeling and energy communities: a centralized repository with a search engine for relevant schemas, the development of more use cases, and better harmonization and standardization of schemas in collaboration with industry to facilitate their adoption by stakeholders addressing varied energy-focused use cases.

Keywords: smart building; semantic model; ontology; metadata; energy audit; fault detection and diagnostics; optimal control (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

Downloads: (external link)
https://www.mdpi.com/1996-1073/14/7/2024/pdf (application/pdf)
https://www.mdpi.com/1996-1073/14/7/2024/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:14:y:2021:i:7:p:2024-:d:531075

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().