Track chairs: (firstname.lastname@example.org)
- Axel Polleres (Vienna University of Economic and Business, Austria)
- Valentina Presutti (Università di Bologna, Italy)
We invite research contributions to the Semantics and Knowledge track at the 31st edition of the Web Conference series (formerly known as WWW), to be held online April 25-29, 2022, hosted by Lyon, France (https://www2022.thewebconf.org/).
Knowledge graphs and other forms of structured data models with machine-interpretable semantics are being widely adopted and serve as the basis for many advanced applications on the Web, powered by combinations of and use of Web Data, with techniques from machine learning, information extraction, and various other AI techniques. We can also see a significant fraction of web pages, emails and other types of documents containing semantic markup, including open, closed and even personal data, forming a parallel Web of linked, open datasets that are revolutionizing research in areas ranging from basic science and engineering to the social sciences and social goodness.
These successes have opened the doors to challenges that are the focus of the Semantics and Knowledge track. This includes the creation, publication and consumption of large scale, interlinked structured data corpora, bridging structured and unstructured data, and techniques for (human-assisted) semantic integration, enrichment and processing of large, real-world datasets in a Web context. This also includes aspects related to the management of provenance, trust, security and privacy, and ethics. We are looking for research that targets these challenges at Web-scale scenarios, and that is Web-based or at employs open world assumptions.
Topics include (but are not limited to):
- Scalable Techniques for the creation, curation, publication and consumption of Large, Web-based, Structured, Reusable, Knowledge Graphs, including Methods for Developing and Maintaining Shared Vocabularies/Ontologies
- Representation, Semantic Annotation, Enhancement, Enrichments, Access and/or Integration of a Variety of Data on the Web, including Semi-structured Data, Text, Multimedia and Sensor Data
- Data Modeling and Inference using Semantic Data in Support of Enabling Intelligent System Behavior, Explanations and User-friendly Interaction
- Provenance, Trust, Security and Privacy, and Ethical Issues in Managing Semantic Data
- Exploitation of Semantic Data for Machine Learning Tasks
- Applications of Semantic Technologies for Improving Search, Browsing, Personalization in Applications and Domains of Interest to the Web Community, e.g. News, Recommendations, Humanities, Social Sciences, Medical, etc.