The GDM workshop targets researchers that concentrate on all aspects of managing graph data such as: "How to store graph data?", "How to efficiently index graph data?" and "How to query graph databases?". Hence, we are interested in applications of graph databases in different practical domains. The workshop invites original research contributions as well as reports on prototype systems from research communities dealing with different theoretical and applied aspects of graph data management. Submitted papers will be evaluated on the basis of significance, originality, technical quality, and exposition. Papers should clearly establish the research contribution, and relation to previous research. Position and survey papers are also welcome.

Topics of interest include, but are not limited to:

Methods/Techniques for storing, indexing and querying graph data.
Methods/Techniques for supporting different types of graph queries.
Methods/Techniques for estimating the selectivity of graph queries.
Methods/Techniques for graph mining.
Methods/Techniques for compact (compressed) representation of graph data.
Methods/Techniques for measuring graph similarity.
Methods/Techniques for data integrity in the context of graph query processing.
Methods/Techniques for data privacy in the context of graph query processing.
Methods/Techniques for large scale and distributed graph processing.
Tools/Techniques for graph data management for social network applications.
Tools/Techniques for graph data management of chemical compounds.
Tools/Techniques for graph data management of protein networks.
Tools/Techniques for graph data management of multimedia databases.
Tools/Techniques for graph data management of semantic web data (RDF).
Tools/Techniques for graph data management for spatio-temporal applications.
Tools/Techniques for graph data management for Business Process Management applications.
Tools/Techniques for visualizing, browsing, or navigating graph data
Analysis/Proposals for graph query languages.
Advanced applications and tools for managing graph databases in different domains.
Benchmarking and testing of graph data management techniques.
Usability of graph databases.