Call for Papers ESWC 2019 Semantic Data Management and Data Infrastructures Track


While there exist effective solutions for semantic data management, Big Data characteristics like volume, variety, velocity, and veracity, as well as the decentralized nature of Linked Data, impact the deployment of such solutions at a large scale and in highly distributed settings. As such, Linked Data forms the basis for a platform for decentralized, interoperable Knowledge Graphs. The aim of this track is to gather researchers and developers from the Semantic Web, Databases, and Artificial Intelligence fields to discuss research issues, experiences, and results in designing, implementing, deploying, and evaluating theories, techniques, and applications related to semantic data management, with a particular focus on scalability and the challenges of Big Data (Volume, Velocity, Variety, Veracity, etc.) .

Topic of Interest

Topics of interest include but are not limited to:

  • Distributed & Decentralized infrastructures for Semantic Data Management
  • Semantic Data Management Techniques
  • Access Control and Privacy in Semantic Data
  • Synchronization Models
  • Semantic Data Integration and Quality Assessment
  • Traceability and Trustworthiness
  • Storage Models for Semantic Data
  • Semantic Searching and Browsing
  • Semantic Data Management for Dynamic (Streaming and Temporal) Data
  • Semantic Data Management and Polyglot Persistence
  • Management of Context (Provenance, Trust, Temporal Context, Usage Policies, etc.) of Semantic Data
  • Architectures, and Optimized Querying Techniques for Contextualized Linked Data and Knowledge Graphs beyond “pure” RDF (Property Graphs, etc.)
  • Architectures for Integrating Semantic Data Management, Data Analytics and Machine Learning
  • Empirical Studies and Evaluations of Semantic Data Management Techniques
  • Benchmarks for Semantic Data Management Techniques
  • Ontology-Based Data Management

Track Chairs

Oscar Corcho, Universidad Politécnica de Madrid, Spain
Axel Polleres, Vienna University of Economics and Business, Austria

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