This workshop brings together people with an interest in the future of standards relating to graph data, and its ever growing importance in relation to the Internet of Things, smart enterprises, smart cities, etc., open markets of services, and synergies with Artificial Intelligence and Machine Learning (AI/ML).
The scope includes:
Harmonising different perspectives on database management systems:
- The role of annotations, e.g. spatial, temporal, provenance, data quality, trust, etc. and opportunities for extending RDF to better support them;
- the relationship between RDF and other related approaches, e.g. Labelled Property Graphs and work by ETSI ISG CIM;
- requirements for graph query and update languages and
- requirements for rule languages for graph data.
Managing the silos, big data, AI and machine learning:
- Techniques for dealing with incomplete, uncertain and inconsistent knowledge;
- different kinds of reasoning, e.g. deductive, inductive, abductive, analogical, spatial, temporal, causal, social, and emotional and
- challenges for Big Data, AI/ML, and enterprise knowledge-graphs.
Scalability, security, trust, APIs and vocabulary development:
- Techniques for mapping data between vocabularies with overlapping semantics, as a basis for scaling across different communities;
- digital signatures for RDF and Property graphs, e.g. to verify that the graph hasn’t been tampered with;
- what’s next for remote access to data and information services;
- whether it is timely and appropriate to standardise a JavaScript API for Linked Data and
- how to make W3C a more attractive venue for work on vocabularies.
We aim to share experiences, use case studies, new directions and insights on what’s needed for the next generation of Web data standards.
