QuWeDa 2017: Querying the Web of Data

Half Day Workshop at ESWC2017 Portoroz, Slovenia
Workshop day 2 - 29th May 2017

The constant growth of Linked Open Data (LOD) on the Web opens new challenges pertaining to querying such massive amounts of publicly available data. LOD datasets are available through various interfaces, such as data dumps, 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. The trend of publicly available and interconnected data is shifting the focus of Web technologies towards new paradigms of Linked Data querying. To exploit the massive amount of LOD data to its full potential, users should be able to query and combine this data easily and effectively. 
This workshop at the Extended Semantic Web Conference (ESWC) 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:
  • Centralized, federated, and distributed SPARQL query processing
  • SPARQL query processing in streams
  • Temporal and spatial queries
  • Querying embedded Linked Data 
  • Caching and replication in SPARQL query processing
  • Query processing under entailment regimes
  • SPARQL query processing in Map-Reduce and Big Data
  • SPARQL query optimization and source selection
  • SPARQL query processing benchmarks, especially those focusing on multiple measures
  • Ranking, measures, and performance evaluation of SPARQL querying engines
  • Query relaxation and rewriting
  • SPARQL query processing demos and applications
  • Lightweight Linked Data interfaces for querying
  • Live Linked Data querying
  • Query execution over Linked Data Fragments interfaces
  • Dividing query execution between clients and servers
  • User interfaces for querying
  • Security and privacy in querying the Web of Data
  • Alternative languages for querying the Web of Data
  • Analysis of the SPARQL query logs, i.e., real queries