DBDM 2023

 Big Data Management is of relevant interest at now, and it 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 area, 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 six editions, four co-located with IEEE/ACM CCGRID conference series and two co-located with IEEE COMPSAC, the aim of the 8th International Workshop on Distributed Big Data Management (DBDM 2023) 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. 

Workshop Theme and Topics 

The DBDM 2023 workshop focuses on all the research aspects of distributed management of Big Data. Among these, an unrestricted list is the following one: 

• 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