Towards aligning IoT data with domain-specific ontologies through Semantic Web technologies and NLP

Singh, Mandeep and Vakaj, Edlira and Rizou, Stamatia and Wu, Wenyan (2023) Towards aligning IoT data with domain-specific ontologies through Semantic Web technologies and NLP. In: SEMANTICS 2023 EU, 19th international conference on Semantic system 2023 20-22 September, 20th - 22nd September 2023, Leipzig, Germany.

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Internet of Things (IoT) data has the potential to be utilized in many domain-specific applications to enable smart sensing in areas that were not initially covered during the conceptualization phase of these applications. Typically, data collected in IoT scenarios serve a specific purpose and follow heterogeneous data models and domain-specific ontologies. Therefore, IoT data could not easily be integrated into domain-specific applications, as it requires ontology alignment of diverse data models with the end application. This poses a big challenge to semantic interoperability during the integration of IoT data into a pre-established system. In this line, the alignment process is cumbersome and challenging for an ontology engineer, since it requires a manual review of the relevant ontologies that could be aligned with the IoT data. Additionally, before aligning each term used in the IoT data with the concepts defined in the domain-specific ontologies, all similar/related terms in the given ontologies must be considered. In this paper, we propose a solution that supports the alignment process by utilizing semantic web technologies and Natural Language Processing (NLP). Our novel solution proposes an NLP-based term alignment with a similarity score that supports identifying the relevant terms used in IoT data and ontologies and stores the similarity scores among terms based on different similarity algorithms. We showcase our solution by aligning IoT sensor data with the water and IoT domain ontologies.

Item Type: Conference or Workshop Item (Paper)
1 September 2023Accepted
22 September 2023Published
Subjects: CAH11 - computing > CAH11-01 - computing > CAH11-01-01 - computer science
Divisions: Faculty of Computing, Engineering and the Built Environment > School of Computing and Digital Technology
Depositing User: Gemma Tonks
Date Deposited: 17 Oct 2023 12:18
Last Modified: 17 Oct 2023 12:18

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