SEA Graph workshop proposes a unique international venue for researchers and practitioners willing to share their insights, experience, and solutions in the management and analysis of heterogeneous Graph data.

The SEA Graph workshop will provide a forum for researchers and practitioners to exchange ideas, results, and visions on challenges in adopting graphs to handle data management, information extraction, exploration, and analysis of heterogeneous data and multiple data models at once.

Submission Guidelines

All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:

Regular research papers as well as system papers have a page limit of 6 pages (references included).

Experiments and Analysis papers have also a page limit of 6 pages (references included).

Vision papers, work-in-progress papers, and experiences papers have a page limit of 4 pages (references included).

SEA Data workshop 2024 is single-blind, and thus authors must include their names and affiliations in submissions.

List of Topics

Algebra and logics for graph databases

Graph query languages, algebra, and logics

Querying and analyzing semantic data lakes and polystores;

Comparison of graph data models to traditional data models

Schemas for graph databases

Semantic web graph data formats (e.g., RDF, OWL)

Graph mining and learning

Mining and profiling of graphs

Information retrieval on graph-structured data

Data explorations on graphs.

Graph pattern matching

Link prediction, clustering, node and graph classification

Automatic learning of graph embeddings or indexes

Extraction of vectors, matrices, and metapaths from graphs (e.g., as input for neural networks)

Graph data quality assessment

Graph data management

Search in graph databases

Flexible query answering on graph-structured data

Intelligent distribution of query processing

Indexing methods for graph processing

Storage systems for large-scale graph databases

Automatic distribution and replication of graph databases

Scalable algorithms for graph management

Applications

Biological and medical graph databases

Social Networks and Citation graphs

Visualizing, browsing, and navigating graph data

Contact

All questions about submissions should be emailed to

• Davide Mottin, Aarhus University
• Matteo Lissandrini, University of Verona
• Lisa Ehrlinger, Software Competence Center Hagenberg GmbH
• Sayan Ranu, IIT Deli