Linked Data and Knowledge Graphs in Large Organisations

Dear Colleagues,

Knowledge graphs are large networks of entities, their semantic types, properties, and the relationships that interrelate such entities over various topical domains. Through the explicit representation of knowledge in well-formed ways, knowledge graphs provide expressive and actionable descriptions of the domain of interest and support logical explanations of reasoning outcomes based on the context of an entity according to the graph.

Knowledge graphs have proved to be a powerful technology across different areas of artificial intelligence, including e.g. natural language processing and the semantic web, and have been adopted by industry for different purposes, including semantic search, automated fraud detection, intelligent chatbots, advanced drug discovery, dynamic risk analysis, content-based recommendation and knowledge management systems, to name but a few. It is no surprise that knowledge graphs were featured in Gartner’s 2018 Hype Cycle as one of the emerging technologies in AI.

However, despite the success of public knowledge graphs, like DBpedia or Wikidata, or corporate ones, like Google’s KG, knowledge graphs still face important challenges for widespread adoption by large and medium enterprises, which involve not only technical aspects but also social ones. Among them, we highlight: i) addressing coverage, freshness and correctness at a scale of billions of entities and assertions; ii) Identity management, linkage and entity unification (“are these two products the same?”); iii) interoperability and distributed ownership (80% of enterprise knowledge is locked in silos); iv) change and long-term evolution; and v) sharing and reuse of common parts of knowledge graphs amongst organizations.

We invite authors to submit original articles addressing these and other challenges related to knowledge graphs. To this purpose we offer four different types of submissions: i) research papers, including reproducible experiments; ii) reports from the trenches, i.e. in-use experiences, challenges and lessons learnt; iii) survey papers; and iv) blue sky ideas. While the first three are full-length papers of 30 pages max, submissions of the latter type must not exceed 12 pages.

For illustrative purposes, below we provide a list of possible topics, which are neither exhaustive nor mutually exclusive. We particularly welcome interdisciplinary research over multiple topics, as reflected by our Guest Editorial Board, which includes members from both academia and industry.

Dr. Jose Manuel Gomez-Perez
Dr. Jeff Z. Pan
Dr. Panos Alexopoulos
Guest Editors

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