Conference Information

SemBDM 2018: Semantics in Big Data Management

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Submission Date:
2018-06-24
Notification Date:
2018-07-02
Conference Date:
2018-09-18
Location:
Poznan, Poland
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Call For Papers

SemBDM 2018 (Semantics in Big Data Management) is an academic conference held in Poznan, Poland on 2018-09-18. The paper submission deadline is 2018-06-24. Acceptance notifications are sent on 2018-07-02.

The complexity of Big Data technologies and the variety of competences required to design applications relying on them has emphasized the relevance of systems for managing and documenting Big Data architectures. Documentation, reconfiguration, and verification are for example crucial tasks for a solid design of technological solutions but are not easily supported in the current landscape of Big Data technologies. Rethinking data and information management in the context of Big Data technologies is then a primary goal for future research. Methods, principles, and perspectives developed by the Data Semantics community can significantly contribute to this goal. Solutions for integrating and querying schema-less data, for example, have received much attention. Standards for metadata management have been proposed to improve data integration among silos and to make data more discoverable and accessible through heterogeneous infrastructures. A further level of application of Data Semantics principles into Big Data technologies involves Representing Processes, i.e. representing the entire pipeline of technologies connected to achieve a specific solution and make this representation shareable and verifiable to support a mature implementation of the Big Data production cycle. The symposium will bring together leading researchers, engineers, and scientists from around the world. Topics of interest for submission include, but are not limited to: Big Data Management Metadata Management Big Data Persistence and Preservation Big Data Quality and Provenance Control Big Data Storage and Retrieval Big Data Integration Architectures and Techniques Data Source Discovery Big Data Profiling and Semantics Discovery Querying Heterogeneous Big Data Repositories Caching and Materializing Query Results Quality of Big Data Services Big Data Service Performance Evaluation Big Data Service Reliability and Availability Reproducibility of Big Data Services Verifiability of Big Data Services Assurance in Big Data Services Big Data Visualization Real Time Visualisation Visualization Analytics for Big Data Big Social Media Mining Big Data Security and Privacy Big Data System Security and Integrity Big Data Information Security Privacy-Preserving Big Data Analytics Usable Security and Privacy for Big Data Performance of Big Data Architectures Query Optimization Optimal Selection of Analytics Physical Structures
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