A survey on information modeling and ontologies in building automation

Butzin, Björn; Golatowski, Frank; Timmermann, Dirk

doi:10.1109/iecon.2017.8217514

Cited by 27 publications

(10 citation statements)

References 21 publications

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“…Bhattacharya et al [53] compare the ability of three ontologies to describe concepts necessary to run a set of applications described in the academic literature. Butzin et al [54] present a survey on information modeling and ontologies in building automation to provide contextual information to the applications. While being valuable contributions, these papers do not conduct a systematic survey of existing metadata schemas.…”

Section: Contribution Of This Reviewmentioning

confidence: 99%

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

et al. 2021

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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.

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Section: Contribution Of This Reviewmentioning

confidence: 99%

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

et al. 2021

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“…Other studies comparing ontologies considered qualities not covered in the above assessment, further qualities could therefore be added in the qualitative assessment. Qualities could include depth [75], which described the vagueness of ontology concepts, and data modalities [22] including more qualitative semantic representations such as comfort measures and maintenance. A number of studies have also focused on expanding expressiveness assessment beyond relationship representation to involve quantitative querability [69,13].…”

Section: Future Research Needsmentioning

confidence: 99%

Data Ontology Assessment To Support Smart And Ongoing Commissioning Of Buildings

Quinn¹

2021

Preprint

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To achieve Canada’s GHG reduction targets, building performance must be improved. Enabling buildings with Smart and Ongoing Commissioning (SOCx) applications will help to achieve peak performance in energy use and improved occupant health and comfort, at minimum cost. A comprehensive literature review highlighted the viability of Brick and Project Haystack ontologies, prompting a quantitative comparison of completeness and expressiveness using a case study with an industry ontology as the baseline for comparison. Additionally, a qualitative comparison was completed using key ontology qualities outlined in literature. A recommendation of Brick is made based on results. Brick achieved higher assessment values in completeness and expressiveness achieving 59% and 100% respectively, as compared to Haystacks 43% and 96%. Additionally, Brick exhibited five of six desirable qualities, where Haystack exhibited only three. If used by SOCx applications, the appropriate ontology permits the optimization of building performance. The recommendation of the appropriate ontology forms the basis for longer- term SOCx prototype development, which will support innovative approaches to sustainability in building operations across scale, as well as next- generation building controls and automation strategies.

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“…As advanced analytics and controls applications become more prevalent, the need for a cross-cutting industry standard for organizing point metadata is becoming increasingly important. BAS schemas are constantly being developed or reconfigured [31]. Because any automated approach to generating BAS metadata will be schema-specific, it is important to understand the key features of the available schema.…”

Section: Bas Tagging Schemesan Overviewmentioning

confidence: 99%

Unified architecture for data-driven metadata tagging of building automation systems

Mishra

Glaws

Cutler

et al. 2020

Automation in Construction

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A survey on information modeling and ontologies in building automation

Cited by 27 publications

References 21 publications

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

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

Data Ontology Assessment To Support Smart And Ongoing Commissioning Of Buildings

Unified architecture for data-driven metadata tagging of building automation systems

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