OfficeGraph

OfficeGraph is a large, real world knowledge graph containing measurements taken by 444 IoT devices, over 11 months, in a seven story office building. The devices are made up of 17 different sensor models, which make measurements of many different properties. The devices in room enrichment adds more information about which devices are located in which rooms, and on which floor those rooms are.The Wikidata days enrichment provides a link to Wikidata, by matching the dates of the measurements to those dates' entities in Wikidata.The graph learning enrichment provides additional properties that have beneficial effects on the learning process when using graph embedding models. The enrichments are located in separate files, with the graph learning enrichment folder only containing the enrichments for the devices on the 7th floor, which were used in the machine learning experiment (the code of this experiment is available on GitHub. This is a zipped version of OfficeGraph. Instead of one file containing the entire knowledge graph the device folders contains a separate file for each individual device. Each file contains all the measurements made by the device. The enrichments are included in separate files. The resource paper describing this dataset was published at ESWC 2024: van der Weerdt, R., de Boer, V., Siebes, R., Groenewold, R., van Harmelen, F. (2024). OfficeGraph: A Knowledge Graph of Office Building IoT Measurements. In: Meroño Peñuela, A., et al. The Semantic Web. ESWC 2024. Lecture Notes in Computer Science, vol 14665. Springer, Cham. https://doi.org/10.1007/978-3-031-60635-9_6