Track 1: Software architectures for big data management

Register

Description:

Big data management and applications largely involve storing and processing of extremely large data sets aiming to provide intelligent, personalized, and adaptive services to users and the information ecosystems. This trend has been largely supported by recent advances in parallel computing architectures, emergence of NoSQL databases, cloud computing and blockchain technologies, and continuous improvements in machine learning and other branches of Artificial Intelligence (AI). The challenges of big data on the software architecture can relate to scale, security, integrity, performance, concurrency, parallelism, and dependability, amongst others. Big data handling requires rethinking architectural solutions to meet functional and non-functional requirements related to volume, variety and velocity, as well as compliance to organisational and process regulations. Originating from the work done in the SPuMoNI project (www.spumoni.eu) the purpose of this track is to discuss technological solutions and elaborate on how software architectures can solve the challenges imposed by building big data software systems. Original research work and applied research experiences in industrial case studies including demonstrations, as well as visionary papers, will be presented. Overall design and performance issues and challenges will be also addressed.

Topics:

Blockchain architectures, data integrity, agent-based data management, regulation technology (regtech), ALCOA compliance, nosql databases, intelligent data analytics

Track organizers:

Prof. Dr. Horacio González-Vélez, National College of Ireland, Horacio.Gonzalez-Velez@ncirl.ie
Prof. Dr. Juan M Garcia-Gomez, Universitat Politecnica de Valencia, juanmig@ibime.upv.es
Prof. Dr. Anthony Karageorgos, University of Thessaly, karageorgos@uth.gr

Track Technical committee:

Dr. Adriana Chis, National College of Ireland, Adriana.Chis@ncirl.ie
Dr. Carlos Saez, Universitat Politecnica de Valencia, carsaesi@ibime.upv.es
Dr. Fatima Leal, University of Porto, fatimaleal2@gmail.com
Dr. Eythymios Lallas, University of Thessaly, elallas@uth.gr
Prof. Dr. Ilias Santouridis, University of Thessaly, isant@uth.gr

Submission Method:

Manuscripts must be submitted electronically via online submission system. For any questions, please contact with esse_info@academic.net.