QuWeDa 2022 : 6th Workshop on Storing, Querying and Benchmarking Knowledge Graphs @ISWC2022

he constant growth of Knowledge Graphs (KGs) on the Web raises new challenges for querying and integrating massive amounts of data across multiple KGs. Such KGs are available through various interfaces, such as data dumps, Linked Data Platform, SPARQL endpoints and Triple Pattern Fragments. In addition, various sources produce streaming data. Efficiently querying these sources is of central importance for the scalability of Linked Data and Semantic Web technologies. To exploit the massive amount of data to its full potential, users should be able to query and combine this data easily and effectively. This workshop at the International Semantic Web Conference (ISWC) seeks original articles describing theoretical and practical methods and techniques for fostering, querying, consuming, and benchmarking KGs.

This workshop at the International Semantic Web Conference 2022 (ISWC 2022) seeks original articles describing theoretical and practical methods and techniques for fostering, querying, and consuming the Data Web. Topics relevant to this workshop include -- but are not limited to -- the following:

Representing and Storing the Web of Data as Knowledge Graphs
Efficient representation
Indexing
Caching and replication
Storage techniques
Real-time data warehousing from Web data

Querying the Web of Data as Knowledge Graphs
Centralized, decentralized, federated, and distributed
Source selection
Lightweight Linked Data interfaces
Web streams processing
Big Data techniques
Entailment regimes
Read and write queries
Linked Data documents and embedded Linked Data
Query relaxation and rewriting
Spatial Knowledge Graphs and GeoSPARQL querying

Benchmarking the Web of Data as Knowledge Graphs
Benchmarks
Ranking
Measures and metrics
Performance evaluation

Integrating different sources
Querying non-Linked Data sources
Combining public and private Linked Data
Querying personal Linked Data stores

Query languages for the Web
Domain-specific query languages (e.g., temporal and spatial queries)
Alternative languages for representing and querying the Web of Data
GraphQL applications and optimizations