QuWeDa 2020:  4th Workshop on Storing, Querying and Benchmarking the Web of Data


Half day virtual workshop at ISWC 2020
Sunday, November 1. Click here to join the Zoom video conferencing. 
Selected papers will be invited to the special issue of Semantic Web Journal

The constant growth of Linked Data on the Web raises new challenges for querying and integrating massive amounts of data across multiple datasets. Such datasets 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 the Web of Data.

This workshop at the International Semantic Web Conference 2020 (ISWC 2020) 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 Web of Data
    • Efficient representation
    • Indexing
    • Caching and replication
    • Storage techniques
    • Real-time data warehousing from Web data
  • Querying the Web of Data
    • 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
  • Benchmarking Web of Data
    • 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