{"type":"ScholarlyArticle","title":"Semantic Framework for Industrial Analytics and Diagnostics","authors":[{"name":"Gulnar Mehdi","slug":"gulnar-mehdi","given":"Gulnar","family":"Mehdi","affiliation":""},{"name":"Sebastian Brandt","slug":"sebastian-brandt","given":"Sebastian","family":"Brandt","affiliation":""},{"name":"Mikhail Roshchin","slug":"mikhail-roshchin","given":"Mikhail","family":"Roshchin","affiliation":""},{"name":"Thomas A. Runkler","slug":"thomas-a-runkler","given":"Thomas A.","family":"Runkler","affiliation":""}],"abstract":"Massive data streams from sensors and devices are prominent form of industrial data generated during condition-monitoring and diagnosis of complex systems. Data analytics and reasoning has emerged as a vital tool to harness massive data sets, providing insights into historical and real-time system conditions; enhanced decision support, reliability and cost reduction. However, application of data analytics is mainly challenged by the complexity of data-access, integration, domain-specific query support and contextual reasoning capabilities. The current state-of-the-art only uses dedicated scenarios and sensors, but this limits reuse, scalability and are not sufficient for an integrated solution. Our thesis investigates if semantic technology can be a potential solution to interact and leverage data analytics for operational use. First, we have studied related work and utilized ontology-based data access (OBDA) techniques for semantic interpretation of diagnosis for Siemens Turbine use-case. Secondly, we have extended our solution to support any analytical workflow by means of an ontology.","doi":null,"url":"https://ijcai.org/proceedings/2016/582","pdf":"https://ijcai.org/proceedings/2016/0582.pdf","markdown":"https://ijcai.org/proceedings/2016/582.md","bibtex":"https://ijcai.org/proceedings/2016/bibtex/582","volume":{"slug":"2016","title":"Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2016","url":"https://ijcai.org/proceedings/2016/","year":2016,"location":"New York, NY, USA","dates":"9–15 July 2016","editors":"Subbarao Kambhampati","isbn":"978-1-57735-770-4; 978-1-57735-771-1","publisher":"AAAI Press / International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":582,"pages":{"first":4016,"last":4016},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}