Back to Top

A complete high-performant stack of technologies addressing the emerging needs of data operations and applications

13 March 2018

The new data-driven industrial revolution highlights the need for big data technologies to unlock the potential in various application domains. In this context, emerging innovative solutions exploit several underlying infrastructure and cluster management systems. However, these systems have not been designed and implemented in a “big data context”, and they rather emphasize and address the computational needs and aspects of applications and services to be deployed.

BigDataStack project aims to deliver an architecture of a complete stack based on a frontrunner infrastructure management system that drives decisions according to data aspects, thus being fully scalable, runtime adaptable and high-performant to address the needs of big data operations and data-intensive applications. Furthermore, the stack goes beyond purely infrastructure elements by introducing techniques for the dimensioning of big data applications, modelling and analysis of processes as well as the provision of data-as-a-service exploiting a proposed seamless analytics framework.

The Consortium is coordinated by IBM ISRAEL - SCIENCE AND TECHNOLOGY LTD (Israel) and consists of UNIVERSITY OF PIRAEUS RESEARCH CENTER (Greece), NEC EUROPE LTD (United Kingdom), RED HAT ISRAEL LTD (Israel), ATOS SPAIN SA (Spain), GFT ITALIA SRL (Italy), DANAOS SHIPPING COMPANY LIMITED (Cyprus), SINGULARLOGIC SA (GREECE), ATHENS TECHNOLOGY CENTER SA (Greece), LEANXCALE SL (Spain), UBITECH LIMITED (Cyprus), TRUST-IT SERVICES LIMITED (United Kingdom), UNIVERSIDAD POLITECNICA DE MADRID (Spain) and UNIVERSITY OF GLASGOW (United Kingdom).

ATC leads all the interaction mechanisms of the BigDataStack platform. These mechanisms will aim at: (i) Increased and predictable performance of data operations and data-intensive applications by dimensioning them regarding the required infrastructure resources. (ii) Efficiency and agility through declarative process modelling allowing the stakeholders to specify functionality-based process models that will be turned to process analytics and mining tasks in an automated way by the modelling framework and analyzed through the data mining mechanisms. (iii) Usability and extensibility by delivering a toolkit allowing big data practitioners both to ingest their analytics tasks (through declarative methods) and to set their requirements / preferences. (iv) Exploitation through the visualization environment of the analytics outcomes and providing a complete view of the data (e.g. outcomes of incremental queries) and also of the infrastructure. ATC is responsible to deliver the Declarative process modeling framework and the Visualization framework. Furthermore, ATC leads Innovation Management supporting the project innovation strategy and exploitation activities.

BigDataStack is a Research & Innovation Action (RIA) funded as part of the H2020 programme of the European Commission, which lasts 36 months and kicked off on the 1st January 2018.

For more infomation visit BigDataStack website and follow BigDataStack on Twitter and LinkedIn to keep abreast of all the latest news and forthcoming activities.