Ontology summit 2020 communiqué: Knowledge graphs
Author:
Baclawski Ken1, Bennett Michael2, Berg-Cross Gary3, Schneider Todd4, Sharma Ravi5, Singer Janet6, Sriram Ram D.7
Affiliation:
1. Northeastern University, Boston, MA, USA. E-mail: Ken@Baclawski.com 2. Hypercube Limited, London, UK. E-mail: mbennett@hypercube.co.uk 3. ESIP Semantic harmonization Co-Lead, Severna Park, MD, USA. E-mail: gbergcross@gmail.com 4. Engineering Semantics, Fairfax, VA, USA. E-mail: tsch@engsem.net 5. Senior Enterprise Architect, Elk Grove, CA, USA. E-mail: drravisharma@gmail.com 6. INCOSE, Scotts Valley, CA, USA. E-mail: jsinger@soe.ucsc.edu 7. National Institute of Standards & Technology, Gaithersburg, MD, USA. E-mail: ramdsriram@gmail.com
Abstract
An increasing amount of data is now available from public and private sources. Furthermore, the types, formats, and number of sources of data are also increasing. Techniques for extracting, storing, processing, and analyzing such data have been developed in the last few years for managing this bewildering variety based on a structure called a knowledge graph. Industry has devoted a great deal of effort to the development of knowledge graphs, and knowledge graphs are now critical to the functions of intelligent virtual assistants such as Siri, Alexa, and Google Assistant. The goal of the Ontology Summit 2020 was to understand not only what knowledge graphs are but also where they originated, why they are so popular, the current issues, and their future prospects. The summit sessions examined many examples of knowledge graphs and surveyed the relevant standards that exist and are in development for knowledge graphs. The purpose of this Communiqué is to summarize our understanding from the Summit in order to foster research and development of knowledge graphs.
Subject
Linguistics and Language,Language and Linguistics,General Computer Science
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