One of the most important aspects of applying distributed ledger technologies in the field of big data is ensuring the necessary data quality and calculating the corresponding metrics. The paper proposes a conceptual framework for working with Master Data in a decentralized environment. The greatest effect of this framework methods is increasing a real-time integrity for the data segments that have the direct impact on overall data quality. The proposed approach provides the result thanks to a special platform architecture similar to the blockchain and built-in artificial intelligence agents - oracles.
Original languageEnglish
Title of host publicationComputational Science and Its Applications – ICCSA 2020
Subtitle of host publication20th International Conference, Cagliari, Italy, July 1–4, 2020, Proceedings, Part III
EditorsOsvaldo Gervasi, et al.
Place of PublicationCham
PublisherSpringer Nature
Pages58-71
ISBN (Print)9783030588076
DOIs
StatePublished - 2020
Event20th International Conference on Computational Science and Its Applications, ICCSA 2020 - Cagliari, Italy
Duration: 1 Jul 20204 Jul 2020
http://iccsa.org/

Publication series

NameLNCS
PublisherSpringer Nature
Volume12251
ISSN (Print)0302-9743

Conference

Conference20th International Conference on Computational Science and Its Applications, ICCSA 2020
Abbreviated titleICCSA 2020
Country/TerritoryItaly
CityCagliari
Period1/07/204/07/20
Internet address

    Research areas

  • Data quality, Distributed ledger technologies, F-BFT consensus, Master data management

    Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

ID: 62498466