{"id":5901,"date":"2025-02-25T15:49:23","date_gmt":"2025-02-25T14:49:23","guid":{"rendered":"https:\/\/dbis.rwth-aachen.de\/dbis\/?p=5901"},"modified":"2025-06-03T13:33:39","modified_gmt":"2025-06-03T11:33:39","slug":"an-ontology-based-agent-for-explainable-unstructured-iot-data","status":"publish","type":"post","link":"https:\/\/dbis.rwth-aachen.de\/dbis\/index.php\/2025\/an-ontology-based-agent-for-explainable-unstructured-iot-data\/","title":{"rendered":"An Ontology-Based Agent for Explainable Unstructured IoT Data"},"content":{"rendered":"\n<p>Sensor data is often unstructured and while available datasets show some clear use cases, for example calculating energy consumption over time, relationships between measurements can often go unnoticed without a thorough examination of the data. While exploratory data analysis can reveal connections, without a clear analytical direction the results may be limited to general information, such as clustering or embeddings. In many cases, stakeholders or key decision makers may however lack knowledge to go beyond such analysis. Using Graph Retrieval-Augmented Generation (Graph-RAG), LLMs can infer connections between entities within a given knowledge graph, potentially providing more accurate and meaningful outputs. In general, data based on Ontologies can be represented as such graphs and has already been used to enhance LLM Agents with domain-specific knowledge. Therefore, if an LLM agent would be able to infer and explain important characteristics of given data with the help of a data-focused IoT ontology and convey them to a stakeholder, one could directly go on to more expedient data analysis.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Sensor data is often unstructured and while available datasets show some clear use cases, for example calculating energy consumption over time, relationships between measurements can often go unnoticed without a thorough examination of the data. While exploratory data analysis can reveal connections, without a clear analytical direction the results may be limited to general information, [&hellip;]<\/p>\n","protected":false},"author":26,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[21],"tags":[],"class_list":["post-5901","post","type-post","status-publish","format-standard","hentry","category-thesis"],"acf":[],"_links":{"self":[{"href":"https:\/\/dbis.rwth-aachen.de\/dbis\/index.php\/wp-json\/wp\/v2\/posts\/5901","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/dbis.rwth-aachen.de\/dbis\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/dbis.rwth-aachen.de\/dbis\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/dbis.rwth-aachen.de\/dbis\/index.php\/wp-json\/wp\/v2\/users\/26"}],"replies":[{"embeddable":true,"href":"https:\/\/dbis.rwth-aachen.de\/dbis\/index.php\/wp-json\/wp\/v2\/comments?post=5901"}],"version-history":[{"count":3,"href":"https:\/\/dbis.rwth-aachen.de\/dbis\/index.php\/wp-json\/wp\/v2\/posts\/5901\/revisions"}],"predecessor-version":[{"id":6226,"href":"https:\/\/dbis.rwth-aachen.de\/dbis\/index.php\/wp-json\/wp\/v2\/posts\/5901\/revisions\/6226"}],"wp:attachment":[{"href":"https:\/\/dbis.rwth-aachen.de\/dbis\/index.php\/wp-json\/wp\/v2\/media?parent=5901"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/dbis.rwth-aachen.de\/dbis\/index.php\/wp-json\/wp\/v2\/categories?post=5901"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/dbis.rwth-aachen.de\/dbis\/index.php\/wp-json\/wp\/v2\/tags?post=5901"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}