{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,25]],"date-time":"2026-01-25T05:51:44Z","timestamp":1769320304826,"version":"3.49.0"},"publisher-location":"Cham","reference-count":27,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031819735","type":"print"},{"value":"9783031819742","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-81974-2_4","type":"book-chapter","created":{"date-parts":[[2025,2,25]],"date-time":"2025-02-25T00:13:48Z","timestamp":1740442428000},"page":"44-57","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Representation Learning on\u00a0IoT Knowledge Graphs"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1125-1126","authenticated-orcid":false,"given":"Roderick","family":"van der Weerdt","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9079-039X","authenticated-orcid":false,"given":"Victor","family":"de Boer","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9267-7160","authenticated-orcid":false,"given":"Laura","family":"Daniele","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8772-7904","authenticated-orcid":false,"given":"Ronald","family":"Siebes","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7913-0048","authenticated-orcid":false,"given":"Frank","family":"van Harmelen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,2,26]]},"reference":[{"issue":"19","key":"4_CR1","doi-asserted-by":"publisher","first-page":"4217","DOI":"10.3390\/s19194217","volume":"19","author":"C Akasiadis","year":"2019","unstructured":"Akasiadis, C., Pitsilis, V., Spyropoulos, C.D.: A multi-protocol IoT platform based on open-source frameworks. Sensors 19(19), 4217 (2019)","journal-title":"Sensors"},{"issue":"4","key":"4_CR2","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1089\/big.2020.0274","volume":"9","author":"YJ Choi","year":"2021","unstructured":"Choi, Y.J., Lee, Y.W., Kim, B.G.: Residual-based graph convolutional network for emotion recognition in conversation for smart internet of things. Big Data 9(4), 279\u2013288 (2021)","journal-title":"Big Data"},{"key":"4_CR3","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1016\/j.websem.2012.05.003","volume":"17","author":"M Compton","year":"2012","unstructured":"Compton, M., Barnaghi, P., Bermudez, L., et al.: The SSN ontology of the W3C semantic sensor network incubator group. J. Web Semant. 17, 25\u201332 (2012)","journal-title":"J. Web Semant."},{"key":"4_CR4","series-title":"Lecture Notes in Business Information Processing","doi-asserted-by":"publisher","first-page":"100","DOI":"10.1007\/978-3-319-21545-7_9","volume-title":"Formal Ontologies Meet Industry","author":"L Daniele","year":"2015","unstructured":"Daniele, L., den Hartog, F., Roes, J.: Created in close interaction with the industry: the smart appliances REFerence (SAREF) ontology. In: Cuel, R., Young, R. (eds.) FOMI 2015. LNBIP, vol. 225, pp. 100\u2013112. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-21545-7_9"},{"key":"4_CR5","unstructured":"Fey, M., Lenssen, J.E.: Fast graph representation learning with PyTorch Geometric. In: ICLR Workshop on Representation Learning on Graphs and Manifolds (2019)"},{"key":"4_CR6","doi-asserted-by":"crossref","unstructured":"Garc\u00eda-Castro, R., Lefran\u00e7ois, M., Poveda-Villal\u00f3n, M., Daniele, L.: The ETSI SAREF ontology for smart applications: a long path of development and evolution. ESAAMC (2023)","DOI":"10.1002\/9781119899457.ch7"},{"key":"4_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.autcon.2020.103209","volume":"116","author":"A Gouda Mohamed","year":"2020","unstructured":"Gouda Mohamed, A., Abdallah, M.R., Marzouk, M.: BIM and semantic web-based maintenance information for existing buildings. Autom. Constr. 116, 103209 (2020)","journal-title":"Autom. Constr."},{"key":"4_CR8","unstructured":"Iana, A., Paulheim, H.: More is not always better: the negative impact of a-box materialization on RDF2Vec knowledge graph embeddings. In: CEUR WP, vol.\u00a02699, pp. Paper\u20135 (2020)"},{"key":"4_CR9","unstructured":"Kipf, T.N., Welling, M.: Semi-supervised classification with graph convolutional networks. In: International Conference on Learning Representations (2016)"},{"key":"4_CR10","volume":"11","author":"Y Li","year":"2023","unstructured":"Li, Y., Xie, S., Wan, Z., Lv, H., Song, H., Lv, Z.: Graph-powered learning methods in the internet of things: a survey. Mach. Learn. Appl. 11, 100441 (2023)","journal-title":"Mach. Learn. Appl."},{"key":"4_CR11","unstructured":"Mikolov, T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space (2013). arXiv"},{"key":"4_CR12","unstructured":"Moreira, J., Daniele, L., Pires, L.F., et\u00a0al.: Towards IoT platforms\u2019 integration semantic translations between W3C SSN and ETSI SAREF. In: SEMANTICS workshops (2017)"},{"key":"4_CR13","unstructured":"Open power system data: data package household data. Version 2020-04-15. (2020) https:\/\/data.open-power-system-data.org\/household_data\/2020-04-15\/"},{"key":"4_CR14","doi-asserted-by":"crossref","unstructured":"Ouyang, X., Yang, Y., Zhang, Y., Zhou, W.: Spatial-temporal dynamic graph convolution neural network for air quality prediction. In: IJCNN, pp.\u00a01\u20138 (2021)","DOI":"10.1109\/IJCNN52387.2021.9534167"},{"key":"4_CR15","doi-asserted-by":"crossref","unstructured":"\u00d6zcan, F., Lei, C., Quamar, A., Efthymiou, V.: Semantic enrichment of data for AI applications. In: Proceedings of the Fifth Workshop on DEEM, pp.\u00a01\u20137 (2021)","DOI":"10.1145\/3462462.3468881"},{"key":"4_CR16","unstructured":"Pecan street research institute: Dataport from pecan street. https:\/\/dataport.pecanstreet.org\/academic. Accessed 16 Jan 2023"},{"key":"4_CR17","doi-asserted-by":"crossref","unstructured":"Portisch, J., Paulheim, H.: The RDF2Vec family of knowledge graph embedding methods. In: Semantic Web (2024)","DOI":"10.3233\/SW-233514"},{"issue":"11","key":"4_CR18","doi-asserted-by":"publisher","first-page":"4131","DOI":"10.3390\/s22114131","volume":"22","author":"R Reda","year":"2022","unstructured":"Reda, R., et al.: Supporting smart home scenarios using owl and SWRL rules. Sensors 22(11), 4131 (2022)","journal-title":"Sensors"},{"key":"4_CR19","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"498","DOI":"10.1007\/978-3-319-46523-4_30","volume-title":"The Semantic Web \u2013 ISWC 2016","author":"P Ristoski","year":"2016","unstructured":"Ristoski, P., Paulheim, H.: RDF2Vec: RDF graph embeddings for data mining. In: Groth, P., et al. (eds.) ISWC 2016. LNCS, vol. 9981, pp. 498\u2013514. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46523-4_30"},{"issue":"4","key":"4_CR20","first-page":"721","volume":"10","author":"P Ristoski","year":"2019","unstructured":"Ristoski, P., Rosati, J., Di Noia, T., De Leone, R., Paulheim, H.: RDF2Vec: RDF graph embeddings and their applications. Semant. Web 10(4), 721\u2013752 (2019)","journal-title":"Semant. Web"},{"key":"4_CR21","doi-asserted-by":"publisher","unstructured":"Steenwinckel, B., Vandewiele, G., Agozzino, T., Ongenae, F.: pyRDF2Vec: a python implementation and extension of rdf2vec. In: Pesquita, C., et al (eds.) ESWC, pp. 471\u2013483. Springer, Cham (2023). https:\/\/doi.org\/10.1007\/978-3-031-33455-9_28","DOI":"10.1007\/978-3-031-33455-9_28"},{"key":"4_CR22","unstructured":"W3C: Web of Things (WoT) thing description (2020). https:\/\/www.w3.org\/TR\/2020\/REC-wot-thing-description-20200409\/"},{"issue":"4","key":"4_CR23","doi-asserted-by":"publisher","first-page":"280","DOI":"10.1504\/IJMSO.2021.125893","volume":"15","author":"R van der Weerdt","year":"2021","unstructured":"van der Weerdt, R., de Boer, V., Daniele, L., Nouwt, B., Siebes, R.: Making heterogeneous smart home data interoperable with the SAREF ontology. IJMSO 15(4), 280\u2013293 (2021)","journal-title":"IJMSO"},{"key":"4_CR24","unstructured":"van\u00a0der Weerdt, R., de\u00a0Boer, V., Daniele, L., Siebes, R., van Harmelen, F.: Evaluating the effect of semantic enrichment on entity embeddings of IoT knowledge graphs. In: Proceedings of the 1st International Workshop on SWoCoT at ESWC 2023, vol. 3412 (2023)"},{"key":"4_CR25","doi-asserted-by":"crossref","unstructured":"van\u00a0der Weerdt, R., de\u00a0Boer, V., Siebes, R., Groenewold, R., van Harmelen, F.: OfficeGraph: a knowledge graph of office building IoT measurements. In: ESWC, pp. 94\u2013109 (2024)","DOI":"10.1007\/978-3-031-60635-9_6"},{"issue":"4","key":"4_CR26","doi-asserted-by":"publisher","first-page":"2635","DOI":"10.1109\/JIOT.2020.3019707","volume":"8","author":"C Xie","year":"2020","unstructured":"Xie, C., Yu, B., Zeng, Z., Yang, Y., Liu, Q.: Multilayer internet-of-things middleware based on knowledge graph. IEEE Internet Things J. 8(4), 2635\u20132648 (2020)","journal-title":"IEEE Internet Things J."},{"key":"4_CR27","doi-asserted-by":"crossref","unstructured":"Zhang, J., Xiao, F., Li, A., et\u00a0al.: Graph neural network-based spatio-temporal indoor environment prediction and optimal control for central air-conditioning systems. BE 242, 110600 (2023)","DOI":"10.1016\/j.buildenv.2023.110600"}],"container-title":["Communications in Computer and Information Science","Metadata and Semantic Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-81974-2_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,6]],"date-time":"2025-09-06T06:19:57Z","timestamp":1757139597000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-81974-2_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031819735","9783031819742"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-81974-2_4","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"value":"1865-0929","type":"print"},{"value":"1865-0937","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"26 February 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MTSR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Research Conference on Metadata and Semantics Research","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Athens","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Greece","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 November 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 November 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"mtsr2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/mtsr-conf.org\/home","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}