Semantic Materials Science
SeMatS 2026: 3rd International Workshop on Semantic Materials Science
In conjunction with
International Semantic Web Conference 2026
October 25-29, 2026
Nicolaus Hotel Bari
Bari, Italy
Applies semantic web and knowledge graph methods to materials science data and discovery. Materials data is heterogeneous, sparsely annotated and scattered across labs with incompatible conventions, which is exactly the problem semantic web methods were built for. A good example of the technology applied outside the web. Provenance matters unusually here, since a measurement is only interpretable alongside the exact conditions under which it was taken.
More workshops at International Semantic Web Conference 2026
- Data Management for Knowledge Graphs — Covers storage, querying, and management techniques for large-scale knowledge graphs on the web. Knowledge graphs...
- Evaluation of Language Models in Knowledge Engineering — Examines how to evaluate large language models when applied to knowledge engineering and ontology tasks....
- Graph-Enhanced LLMs for Web Data — Explores combining knowledge graphs with large language models for trustworthy management of web data. The...
- Knowledge Graphs and Model-driven Systems Engineering — Bridges knowledge graphs with model-driven engineering for building and maintaining software systems. Model-driven engineering and...
- Scientific Knowledge Representation and Discovery — Focuses on representing, discovering, and assessing scholarly and scientific knowledge as structured data. Scholarly knowledge...
- Wikidata Workshop — The community workshop on Wikidata, the collaborative knowledge base, covering its data, tooling, and research...
- Wiki-Based Knowledge Graph Question Answering — A challenge on answering natural-language questions over Wikidata and wiki-derived knowledge graphs. A challenge track,...