The Journal of Web Semantics invites submissions for a special issue on Knowledge Engineering, to be edited by Juan Sequeda, Paul Groth and Eva Blomqvist.
Submissions are due by October 18, 2022.
Knowledge graphs are central to a variety of intelligent applications including semantic search, recommendation, conversational agents and data analytics. Their construction and maintenance is facilitated by complex combinations of machine (e.g. information extraction, schema alignment) and human (crowdsourcing, curation) components. While there is significant previous work in the field of knowledge engineering, large-scale knowledge graphs give rise to new questions about knowledge modelling and knowledge acquisition, including the balance between humans and machines, and the ability to maintain knowledge and data at scale. In that light, this special issue seeks novel research in the area of knowledge engineering that tackles the challenges presented by large scale knowledge graphs,
Topics of interest include (but are not limited to) the following:
- Knowledge engineering methodologies for human-machine teams
- Agile knowledge engineering and prototyping
- Knowledge engineering for machine learning
- Machine learning support for manual knowledge engineering
- Knowledge graph evolution and maintenance approaches
- The combination of modern software engineering and knowledge engineering
- Design patterns in the area of large-scale knowledge engineering
- Ontology debugging and diagnosis for knowledge at scale
- The combination of knowledge and data engineering
- User studies for knowledge engineering human-machine teams
Guest Editors
Paul Groth - University of Amsterdam, p.groth@uva.nl,
Paul is Professor of Algorithmic Data Science at the University of Amsterdam where he leads the Intelligent Data Engineering Lab (INDElab). His research focuses intelligent systems for the integration and use of diverse information with a particular emphasis on data provenance. He has authored over 100 scientific publications in leading venues. He has served in senior organizational roles at ISWC, ESWC, and the Web Conference.
Eva Blomqvist - Linköping University, eva.blomqvist@liu.se
Eva is associate professor in Computer Science at Linköping University, in the Human-Centred Systems division, and the Semantic Web research group. Her research targets knowledge modelling and engineering, in particular the development and use of ontologies as schemas for knowledge graphs, and the use of knowledge graphs for semantic interoperability in various fields, such as security and e-health. Eva is the scientific program co-chair of the International Semantic Web conference in 2021, and has chaired several other scientific conferences. She has authored over 50 scientific publications in high-quality venues.
Juan Sequeda - data.world - juan@data.world
Juan Sequeda is the Principal Scientist at data.world. Juan's goal is to reliably create knowledge from inscrutable data. His research and industry work has been on designing and building Knowledge Graph for enterprise data integration where he has researched and developed technologies for semantic and graph data virtualization, ontology and graph data modeling and schema mapping, and data integration methodologies. Juan serves as a bridge between academia and industry through standardization committees and organizers of scientific venues, such as the general chair of The Web Conference 2023.
Review committee
- Frank van Harmelen (Vrije Universiteit Amsterdam)
- Stefan Schlobach (Vrije Universiteit Amsterdam)
- Steffen Staab (Universität Stuttgart)
- Oscar Corcho (UPM)
- Elena Simperl (King’s College London)
- Enrico Motta (Open University)
- Daniel Garijo (UPM)
- Katja Hose ( Aalborg University)
- Sofia Pinto (Technical University of Lisbon)
- George Fletcher (University of Eindhoven)
Additional reviewers TBC
Important Dates
- Call for papers: 28 March 2022
- Submission deadline: 18 October 2022
- Author notification: 4 January 2023
- Revisions: 4 February 2023
- Final Notification: 4 March 2023
- Publication: Q2 2023