DBDM 2020: The 5th IEEE International Workshop on Distributed Big Data Management

Call for Papers

Goal of the workshop:

In the last few years there have been an increasing number of initiatives to develop distributed Big Data management platforms for diversified application domains, from e-science to large-scale sensor network monitoring. Many national and international research projects in academia, industry and government focus on the development and deployment of distributed Big Data management systems. Apart from companies working in the Big Data domain, there are also initial important investments in this field from social networks to Web advertisement, from astronomic data management to biological data management, as so forth. There are already several workshops oriented to Big Data management systems, however none of them focus on distributed Big Data management as major topic, where distributed models, techniques, algorithms and architectures play the first-class role. Thus the establishment of a new venue in which the definition of novel models, techniques, algorithms and architectures for supporting the distributed management of Big Data is discussed and disseminated, may enable new research ideas and launch new business pathways.

The DBDM 2020 workshop aims to synergistically connect the research community and industry practitioners. It provides an international forum where scientific domain experts, database researchers, practitioners and developers can share their findings in theoretical foundations, current methodologies, and practical experiences on distributed management of Big Data. DBDM 2020 provides a stimulating environment to encourage discussion, fellowship, and exchange ideas in all aspects of research related to distributed management of Big Data, including both original research contributions and insights from practical system design, implementation and evaluation, along with new research directions and emerging application domains in the area of distributed management of Big Data. The realistic outcome expected by DBDM 2020 is to define new problems in the context of distributed management of Big Data and achieving consolidated solutions to already-known problems. Also, another relevant goal is to create a focused community of scientists who create and drive interest in the area of distributed management of Big Data.

Workshop theme:

Big Data Management can be considered as one of the most emerging research topics we deal with. In particular, the management of Big Data in distributed settings (like Clouds) is demanding for innovative models, techniques and algorithms capable of dealing with the well-known Vs of such kind of data.

Indeed, traditional approaches are not suitable to manage Big Data in distributed environments, due to the Volume, Velocity and Variety of Big Data. Starting from this evidence, recently we experienced novel proposals that are trying to creating applications and systems that, running on top of distributed settings like Clouds, effectively and efficiently manage Big Data as to support a wide range of contexts, among which analytics, knowledge discovery and cybersecurity methods are just some relevant examples.

Despite these initiatives, lot of work still needs to be done in such research areas, as it encompasses a large collection of topics ranging from data management algorithms to high-performance techniques. Topics are both of theoretical nature (e.g., managing uncertain and imprecise distributed Big Data) and practical nature (e.g., Big Data dissemination in distributed environments).

Following the great success of the previous four editions, previously co-located with IEEE/ACM CCGRID conference series, the aim of the 5th International Workshop on Distributed Big Data Management (DBDM 2020) at COMPSAC 2020 is to capture the new research trends and results in terms of models, techniques, algorithms, architecture and applications for the management of Big Data in distributed environments. This workshop will also identify potential research directions and technologies that will drive innovations within this domain. We anticipate this workshop to establish a pathway for the development of future-generation large-scale Big Data management systems.

Scope of the workshop:

The DBDM 2020 workshop focuses on all the research aspects of distributed management of Big Data. Among these, an unrestricted list is the following:

  • Distributed Big Data: Fundamentals
  • Distributed Big Data: Modelling
  • Distributed Big Data: Statistical Approaches
  • Distributed Big Data: Novel Paradigms
  • Distributed Big Data: Innovative Protocols
  • Distributed Big Data: Algorithms
  • Distributed Big Data: Query Optimization
  • Distributed Big Data: Non-Conventional Environments (e.g., Spatio-Temporal Data, Streaming Data,
  • Cloud Data, Probabilistic Data, Uncertain Data)
  • Distributed Big Data: Systems
  • Distributed Big Data: Architectures
  • Distributed Big Data: Advanced Topics (e.g., NoSQL Databases)
  • Distributed Big Data: Case Studies and Applications
  • Innovative Models for Big Data Management in Distributed Settings
  • Innovative Techniques for Big Data Management in Distributed Settings
  • Innovative Algorithms for Big Data Management in Distributed Settings
  • Innovative Architectures for Big Data Management in Distributed Settings
  • Query Processing Approach for Big Data in Distributed Settings
  • Approximate Query Processing of Big Data in Distributed Settings
  • Uncertain and Imprecise Big Data Management in Distributed Settings
  • Privacy Preserving Big Data Management in Distributed Settings
  • Secure Big Data Management in Distributed Settings
  • Scalable Big Data Analytics in Distributed Settings
  • Data Warehousing over Big Data in Distributed Settings
  • OLAP over Big Data in Distributed Settings
  • Big Graph Data Management in Distributed Settings
  • Big RDF Data Management in Distributed Settings
  • Streaming Big Data Management in Distributed Settings
  • Virtual Big Data Management in Distributed Settings
  • Indexing Approaches for Big Data in Distributed Settings
  • Theoretical Models for Big Data Representation in Distributed Settings
  • Big Data Exchange Models and Algorithms in Distributed Settings
  • Big Data Fusion Models and Algorithms in Distributed Settings
  • Big Data Integration Models and Algorithms in Distributed Settings
  • Big Data Availability Models and Algorithms in Distributed Settings
  • Big Data Reliability Models and Algorithms in Distributed Settings

Likely participants: The DBDM 2020 workshop is targeted to researchers, practitioners and developers as well as domain experts with interest in the field of distributed management of Big Data. As a matter of fact, the workshop will be extremely useful even to PhD students and young researchers who want to get inside in the topic. The DBDM 2020 workshop will also cover a special panel on emerging topics and future research directions of distributed management of Big Data, where it is foreseen the participation of all the audience, with question time and interaction sessions.

The deadline has been extended to May 1.

Workshop Chair

Alfredo Cuzzocrea, University of Calabria, Italy
Email: alfredo.cuzzocrea@unical.it