{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T07:55:34Z","timestamp":1771919734712,"version":"3.50.1"},"reference-count":56,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2019,3,8]],"date-time":"2019-03-08T00:00:00Z","timestamp":1552003200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61872231, 61701297, 61772454, 61811530332, 61811540410"],"award-info":[{"award-number":["61872231, 61701297, 61772454, 61811530332, 61811540410"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In order to optimize intelligent applications driven by various sensors, it is vital to properly interpret and reuse sensor data from different domains. The construction of semantic maps which illustrate the relationship between heterogeneous domain ontologies plays an important role in knowledge reuse. However, most mapping methods in the literature use the literal meaning of each concept and instance in the ontology to obtain semantic similarity. This is especially the case for domain ontologies which are built for applications with sensor data. At the instance level, there is seldom work to utilize data of the sensor instances when constructing the ontologies\u2019 mapping relationship. To alleviate this problem, in this paper, we propose a novel mechanism to achieve the association between sensor data and domain ontology. In our approach, we first classify the sensor data by making them as SSN (Semantic Sensor Network) ontology instances, and map the corresponding instances to the concepts in the domain ontology. Secondly, a multi-strategy similarity calculation method is used to evaluate the similarity of the concept pairs between the domain ontologies at multiple levels. Finally, the set of concept pairs with a high similarity is selected by the analytic hierarchy process to construct the mapping relationship between the domain ontologies, and then the correlation between sensor data and domain ontologies are constructed. Using the method presented in this paper, we perform sensor data correlation experiments with a simulator for a real world scenario. By comparison to other methods, the experimental results confirm the effectiveness of the proposed approach.<\/jats:p>","DOI":"10.3390\/s19051193","type":"journal-article","created":{"date-parts":[[2019,3,8]],"date-time":"2019-03-08T11:21:59Z","timestamp":1552044119000},"page":"1193","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["Towards Semantic Sensor Data: An Ontology Approach"],"prefix":"10.3390","volume":"19","author":[{"given":"Jin","family":"Liu","sequence":"first","affiliation":[{"name":"College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunhui","family":"Li","sequence":"additional","affiliation":[{"name":"College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaohu","family":"Tian","sequence":"additional","affiliation":[{"name":"College of Information Engineering, Shanghai Maritime University, Shanghai 201306, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0229-2460","authenticated-orcid":false,"given":"Arun Kumar","family":"Sangaiah","sequence":"additional","affiliation":[{"name":"School of Computing Science and Engineering, Vellore Institute of Technology, Tamil Nadu 632014, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5473-8738","authenticated-orcid":false,"given":"Jin","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer &amp; Communication Engineering, Changsha University of Science &amp; Technology, Changsha 410114, China"},{"name":"School of Information Science and Engineering, Fujian University of Technology, Fuzhou 350108, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,3,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"9472075","DOI":"10.1155\/2018\/9472075","article-title":"An Enhanced PEGASIS Algorithm with Mobile Sink Support for Wireless Sensor Networks","volume":"2018","author":"Wang","year":"2018","journal-title":"Wirel. 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