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Introduction

The focus of this workshop is to elicit discussion and description of application areas and open challenges in managing large-scale graph-shaped data.
Experiences including use-case descriptions, war stories and benchmarks as well as system descriptions are important ingredients of the meeting.

The workshop is co-chaired by Peter Boncz (CWI) and Josep Lluis Larriba Pey (UPC).

Previous workshop proceedings are in the ACM Digital Library (2013, 2014, 2015, 2016) and in DBLP (2013, 2014, 2015, 2016).

Call for paper

Important date

2017-03-27
Draft paper submission deadline
2017-04-05
Draft paper acceptance notification
2017-04-19
Final paper submission deadline

Submission Topics

The following is a non-exhaustive list describing the scope of GRADES:

  • vision papers describing potential applications and benefits of graph data management.

  • descriptions of graph data management use cases and query workloads.

  • experiences with applying data management technologies in such situations.

  • experiences or techniques for specific operations such as traversals or RDF reasoning.

  • proposals for benchmarks for data integration tasks (instance matching and ETL techniques).

  • proposals for benchmarks for RDF and graph database workloads.

  • evaluation of benchmark performance results on RDF or graph database systems.

  • system descriptions covering RDF or graph database technology.

  • data and index structures that can be used in RDF and graph database systems.

  • query processing and optimization algorithms for RDF and graph database systems.

  • methods and technique for measuring graph characteristics.

  • methods and techniques for visualizing graphs and graph query results.

  • proposals and experiences with graph query languages.

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Important Date
  • May 19

    2017

    Conference Date

  • Mar 27 2017

    Draft paper submission deadline

  • Apr 05 2017

    Draft Paper Acceptance Notification

  • Apr 19 2017

    Final Paper Deadline

  • May 19 2017

    Registration deadline