Big Graph Data Management and Processing

in Special Issue   Posted on September 28, 2020 

Information for the Special Issue

Submission Deadline: Mon 14 Sep 2020
Journal Impact Factor : 2.904
Journal Name : VLDB Journal
Journal Publisher:
Website for the Special Issue:
Journal & Submission Website:

Special Issue Call for Papers:

Aims and Scope

In our world, data is not just getting bigger, it is also getting more connected. Exploring, describing, predicting, and explaining phenomena connected to the interconnected world requires the use of an adequate data abstraction. Graphs are recognized as a general, natural, and flexible data-abstraction that can model complex relationships, interactions, and interdependencies between objects. Graphs have been widely used to represent datasets and encode problems across an already extensive range of application domains. The ever-increasing size of graph-structured data for these applications creates a critical need for scalable and even elastic systems that can process large amounts of it efficiently. Additionally, the complexity of using multiple datasets simultaneously in complex analysis, raises numerous challenges for graph processing, from new requirements to new capabilities.

This special issue focuses on recent advances in research and development in big graph data management and processing. 

Topics of Interest

The VLDB Journal solicits contributions to a Special Issue on “Big Graph Data Management and Processing.” Relevant topics include, but are not limited to:

* Graph query languages and constraints.

* Scalable, distributed and parallel graph processing techniques/systems.

* Scalable graph storage, indexing and querying methods

* RDF data management and analytics

* Graph streaming processing/analytics

* Interplay of graph and relational data management.

* Machine Learning/Deep Learning on graphs.

* Graph summarization, graph sampling and graph visualization techniques.

* Graph query optimization techniques.

* Spatial and temporal graph analytics.

* Benchmarking graph storage/processing techniques.

We solicit submissions of high-quality, original research and are particularly interested in system-oriented papers and practical use cases involving new technologies. We are also happy to consider well-written survey articles.

For experimental work, authors are encouraged to make available their software to enable readers to repeat experiments and to support future experimental comparisons with alternative approaches.

Guest Editors

* Angela Bonifati, Lyon 1 University, France ([email protected])

* Alexandru Iosup, Vrije Universiteit Amsterdam, The Netherlands ([email protected])

* Hannes Voigt, Neo4j, Germany ([email protected])

Important Dates

* Paper submissions: extended to September 14, 2020

* First round notifications: November 29, 2020

* Revised versions: January 3, 2021

* Second round notifications (tentative): February 3, 2021

* Final version (tentative): March 3,  2021

* Publication: May/June 2021

Submission Guidelines: 

  • Authors are encouraged to submit high-quality, original work that has neither appeared in, nor is under consideration by other journals. 
  • All papers will be reviewed following standard reviewing procedures for the Journal. 
  • Papers must be prepared in accordance with the Journal guidelines: 
  • Submit manuscripts to: (under “Article Type” choose “S.I.: Graphs 2020”)
  • Springer provides a host of information about publishing in a Springer Journal on our Journal Author Resources page, including  FAQs,  Tutorials  along with  Help and Support.

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