Knowledge Graph Exploration Systems: are we lost?

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review


Knowledge graphs (KGs) represent facts in the form of nodes and
relationships and are widely used to represent and share knowledge
in many different domains. However, their widespread adoption to
integrate different data sources and their generation processes have
made KGs very complicated and difficult to understand, leading
to the advent of new knowledge graph exploration approaches to
better understand their contents and extract relevant insights. Nevertheless, the needs of current KG exploration use cases are not met
(even neglected) by existing KG data management systems. Hence,
the question: are we lost? We hope not. Therefore, with the aim of
fostering research on these open issues, in this position paper, we
first present an overview of state-of-the-art approaches for KG exploration. Then, we identify the (currently unmet) requirements for
effective KG exploration systems, and finally, we highlight promising research directions for the realization of a system able to fully
support knowledge graph exploration.
Original languageEnglish
Title of host publicationProceedings of the 12th Conference on Innovative Data Systems Research : CIDR 2022
Publication dateJan 2022
Publication statusPublished - Jan 2022
EventAnnual Conference on Innovative Data Systems Research - Chaminade Resort & Spa, Santa Cruz, United States
Duration: 9 Jan 202212 Jan 2022
Conference number: 12


ConferenceAnnual Conference on Innovative Data Systems Research
LocationChaminade Resort & Spa
Country/TerritoryUnited States
CitySanta Cruz


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