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Conceptual Architecture of GATE Big Data Platform

Published: 21 June 2019 Publication History

Abstract

Today we experience a data-driven society. All human activities, industrial processes and research lead to data generation of unprecedented scale, spurring new products, services and businesses. Big Data and its application have been a target for European Commission -- with more than 100 FP7 and about 50 H2020 funded projects under Big Data domain. GATE project aims to establish and sustain in the long run a Centre of Excellence as collaborative environment for conducting Big Data research and innovation, facilitated by GATE platform and Innovation Labs. This paper proposes a conceptual architecture of GATE platform, that is holistic, symbiotic, open, evolving and data-integrated. It is also modular and with component-based design that allows to position a mix of products and tools from different providers. GATE platform will enable start-ups, SMEs and large enterprises, as well as other organizations in a wide range of sectors, to build advanced Data driven services and applications. The usability of the proposed architecture is proven through a development of a sample time series data visualization application. Its architecture follows the proposed one through implementation of required components using open technology stack.

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  • (2022)AI-Based Hybrid Data PlatformsData Spaces10.1007/978-3-030-98636-0_8(147-170)Online publication date: 11-Mar-2022

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cover image ACM Other conferences
CompSysTech '19: Proceedings of the 20th International Conference on Computer Systems and Technologies
June 2019
365 pages
ISBN:9781450371490
DOI:10.1145/3345252
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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  • UORB: University of Ruse, Bulgaria

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 June 2019

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Author Tags

  1. Big Data
  2. Big Data Value Chain
  3. Emerging Architectures
  4. GATE Platform
  5. Smart City

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CompSysTech '19

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Overall Acceptance Rate 241 of 492 submissions, 49%

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  • (2022)AI-Based Hybrid Data PlatformsData Spaces10.1007/978-3-030-98636-0_8(147-170)Online publication date: 11-Mar-2022

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