{"id":23403,"date":"2023-11-22T13:33:39","date_gmt":"2023-11-22T21:33:39","guid":{"rendered":"https:\/\/essential.construction\/news\/a-networked-world-of-buildings\/"},"modified":"2023-11-22T13:33:42","modified_gmt":"2023-11-22T21:33:42","slug":"a-networked-world-of-buildings","status":"publish","type":"post","link":"https:\/\/essential.construction\/news\/a-networked-world-of-buildings\/","title":{"rendered":"A Networked World of Buildings"},"content":{"rendered":"

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Buildings are living things. Buildings change shape every day and every minute. They are used by plenty of people, endlessly. Buildings shape our context and environment, and they impact our well-being to a large extent. Buildings constantly change their behavior under the influence of external conditions and occupants. We have an interest in engineering these buildings and making them as comfortable and pleasant as possible. Instead of treating buildings as static monuments that happen to be in our environment, it makes sense to treat them as living things that change incessantly, with streams of people, streams of materials and goods, and as ever-changing ecosystems of living beings.\u00a0<\/p>\n

And so, we must engineer the knowledge and information of our buildings! We need to provide our buildings with a set of brains, brains that evolve and continuously track the state of the facility and all of its internals: systems, materials, demountable elements, furniture, and people. The brains hold a snapshot of the building at any moment and allow us to ensure that this living building responds in a useful and likable manner (comfort). And this needs efforts from us human beings, and not only from \u2018the AI.\u2019<\/p>\n

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To learn more about\u00a0knowledge graphs for buildings, please refer to the chapter\u00a0\u201cKnowledge Graphs and Linked Data for the Built Environment\u201d<\/em>\u00a0by the author\u00a0and co-authors Aaron Costin and Mads Holten Rasmussen\u00a0as part of a Springer book\u00a0Industry 4.0 for the Built Environment<\/a>, edited by Marzia Bolpagni, Rui Gavina, and Diogo Rodrigo Ribeiro.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

What knowledge is in a knowledge graph for buildings<\/h2>\n

Knowledge graphs are networks of data that capture the \u2018knowledge\u2019 of any object or concept at any particular moment in time \u2013 and so it becomes a snapshot representation or \u2018semi-brain\u2019 of that object. So what if we engineer our buildings, and a \u2018knowledge graph\u2019 or \u2018semi-brain\u2019 would be available for each and every building? The technology is ready. Knowledge graphs are webs of data that represent the tangible and intangible elements in a building. They are structured representations of buildings that capture the state of the facility at any moment in time. This knowledge graph evolves, grows, and shrinks with the building life cycle. And so, it is possible to engineer each of our buildings as a cyber-physical system with the knowledge graph functioning as its brain.<\/p>\n

The knowledge graph originates from 2001 and Sir Tim Berners-Lee, the inventor of the World Wide Web [1]. It allows us to describe information and data on an international world wide web-scale, yet interpretable by machines. The denominated standardized language for creating such knowledge graphs is the Resource Description Framework (RDF), supported by the Web Ontology Language (OWL) that can be used to describe vocabularies.<\/p>\n