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. (shrink)

The Ontology Summit 2012 explored the current and potential uses of ontology, its methods and paradigms, in big systems and big data: How ontology can be used to design, develop, and operate such systems. The systems addressed were not just software systems, although software systems are typically core and necessary components, but more complex systems that include multiple kinds and levels of human and community interaction with physical-software systems, systems of systems, and the socio-technical environments for those systems which can (...) include cultural, legal, and economic components. The focus themes used for this exploration were Big Systems Engineering, Big Data Challenge, Large Scale Domain Applications, and cross-cutting aspects Ontology Quality, and Federation and Integration of Systems. The Ontology Summit 2012 consisted of over three months of intensive virtual collaborative elaboration of these issues in presentations, panels, and group email. The culmination of these activities was a face-to-face Symposium at the US National Institute of Standards and Technology (NIST), Gaithersburg, MD, USA, 12–13 April 2012. The primary product of this Ontology Summit is the communiqué reported here. But there are other products, some continuing as collaborative, more specifically focused analysis and modeling efforts aligned with various open standards activities. Behind all of these particular products, of course, is the real overriding purpose of the Ontology Summit 2012, which was: the joint collaboration of three distinct communities, the ontology, systems engineering and big systems stakeholder communities, who came together to address common problems, create common understanding and propose common solutions. (shrink)

Advances in machine learning and the development of very large knowledge graphs have accompanied a proliferation of ontologies of many types and for many purposes. These ontologies are commonly developed independently, and as a result, it can be difficult to communicate about and between them. To address this difficulty of communication, ontologies and the communities they serve must agree on how their respective terminologies and formalizations relate to each other. The process of coming into accord and agreement is called “harmonization.” (...) The Ontology Summit 2021 examined the overall landscape of ontologies, the many kinds of ontology generation and harmonization, as well as the sustainability of ontologies. The Communiqué synthesizes and summarizes the findings of the summit as well as earlier summits on related issues. One of the major impediments to harmonization is the relatively poor quality of natural language definitions in many ontologies. The summit surveyed the state of the art in natural language definition development, based on lexicographic principles, as well as examples of ongoing projects that are explicitly dealing with harmonization and sustainability. (shrink)