{"id":18322,"date":"2026-03-20T13:01:43","date_gmt":"2026-03-20T17:01:43","guid":{"rendered":"https:\/\/www.rochester.edu\/coe\/?p=18322"},"modified":"2026-03-31T11:26:40","modified_gmt":"2026-03-31T15:26:40","slug":"advancing-wavefront-sensor-performance-via-deep-learning-2","status":"publish","type":"post","link":"https:\/\/www.rochester.edu\/coe\/advancing-wavefront-sensor-performance-via-deep-learning-2\/","title":{"rendered":"Enabling Ontology Development in Graph Databases"},"content":{"rendered":"<p>PI Researcher: Carlos Rivero, Rochester Institute of Technology<br \/>\nCompany Partner: L3Harris<\/p>\n<p>L3Harris currently deploys ontologies that are experiencing data limitations, which compromise the performance and scalability of the applications. Thus, there is motivation to find an approach to migrate ontologies into a graph database that can provide performance, flexibility, and scalability benefits, particularly for applications involving complex and highly interconnected data. This project aims to investigate methods to enable ontology development into Neo4j, an open-source graph database, thereby empowering users to extract valuable insights from existing ontologies and expanding queries to extensive multi-domain data sets. Furthermore, the project aims to help users retrieve knowledge from existing ontologies, even when the users are not computing experts.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>PI Researcher: Carlos Rivero, Rochester Institute of Technology Company Partner: L3Harris L3Harris currently deploys ontologies that are experiencing data limitations, which compromise the performance and scalability of the applications. Thus,&hellip;<\/p>\n","protected":false},"author":122,"featured_media":17672,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[222],"tags":[232],"class_list":["post-18322","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-research-partnerships","tag-2026-funded"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.5 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Enabling Ontology Development in Graph Databases - Center of Excellence in Data Science and Artificial Intelligence<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.rochester.edu\/coe\/advancing-wavefront-sensor-performance-via-deep-learning-2\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Enabling Ontology Development in Graph Databases - Center of Excellence in Data Science and Artificial Intelligence\" \/>\n<meta property=\"og:description\" content=\"PI Researcher: Carlos Rivero, Rochester Institute of Technology Company Partner: L3Harris L3Harris currently deploys ontologies that are experiencing data limitations, which compromise the performance and scalability of the applications. 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