Theta architecture: Preserving the quality of analytics in data-driven systems

Vasileios Theodorou*, Ilias Gerostathopoulos, Sasan Amini, Riccardo Scandariato, Christian Prehofer, Miroslaw Staron

*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

With the recent advances in Big Data storage and processing, there is a real potential of data-driven software systems, i.e., systems that employ analysis of large amounts of data to inform their runtime decisions. However, for these decisions to be trustworthy and dependable, one needs to deal with the well-known challenges on the data analysis domain: Data scarcity, low-quality of data available for analysis, low veracity of data and subsequent analysis results, data privacy constraints that hinder the analysis. A promising solution is to introduce flexibility in the data analytics part of the system enabling optimization at runtime of the algorithms and data streams based on the combination of veracity, privacy and scarcity in order to preserve the target level of quality of the data-driven decisions. In this paper, we investigate this solution by providing an adaptive reference architecture and illustrate its applicability with an example from the traffic management domain.

Original languageEnglish
Title of host publicationNew Trends in Databases and Information Systems - ADBIS 2017 Short Papers and Workshops AMSD, BigNovelTI, DAS, SW4CH, DC, Proceedings
EditorsJerome Darmont, Marite Kirikova, Kjetil Norvag, Robert Wrembel, George A. Papadopoulos, Johann Gamper, Stefano Rizzi
PublisherSpringer Verlag
Pages186-198
Number of pages13
ISBN (Print)9783319671611
DOIs
Publication statusPublished - 1 Jan 2017
Externally publishedYes
Event21st European Conference on Advances in Databases and Information Systems, ADBIS 2017 and 1st workshop on Data Driven Approaches for Analyzing and Managing Scholarly Data, AMSD 2017, 1st workshop on Novel Techniques for Integrating Big Data, BigNovelTI 2017, 1st International workshop on Data Science: Methodologies and Use-Cases, DaS 2017, 2nd International workshop on Semantic Web for Cultural Heritage, SW4CH 2017 - Nicosia, Cyprus
Duration: 24 Sep 201727 Sep 2017

Publication series

NameCommunications in Computer and Information Science
Volume767
ISSN (Print)1865-0929

Conference

Conference21st European Conference on Advances in Databases and Information Systems, ADBIS 2017 and 1st workshop on Data Driven Approaches for Analyzing and Managing Scholarly Data, AMSD 2017, 1st workshop on Novel Techniques for Integrating Big Data, BigNovelTI 2017, 1st International workshop on Data Science: Methodologies and Use-Cases, DaS 2017, 2nd International workshop on Semantic Web for Cultural Heritage, SW4CH 2017
CountryCyprus
CityNicosia
Period24/09/1727/09/17

Keywords

  • Big Data
  • Data veracity
  • Reference architecture

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