Standard
Data Quality in a Decentralized Environment. / Bogdanov, Alexander ; Degtyarev, Alexander ; Shchegoleva, Nadezhda ; Khvatov, Valery .
Computational Science and Its Applications – ICCSA 2020 : 20th International Conference, Cagliari, Italy, July 1–4, 2020, Proceedings, Part III. ред. / Osvaldo Gervasi; et al. Cham : Springer Nature, 2020. стр. 58-71 (LNCS; Том 12251).
Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › Рецензирование
Harvard
Bogdanov, A, Degtyarev, A, Shchegoleva, N & Khvatov, V 2020,
Data Quality in a Decentralized Environment. в O Gervasi & EA (ред.),
Computational Science and Its Applications – ICCSA 2020 : 20th International Conference, Cagliari, Italy, July 1–4, 2020, Proceedings, Part III. LNCS, Том. 12251, Springer Nature, Cham, стр. 58-71, 20th International Conference on Computational Science and Its Applications, ICCSA 2020, Cagliari, Италия,
1/07/20.
https://doi.org/10.1007/978-3-030-58808-3_6
APA
Bogdanov, A., Degtyarev, A., Shchegoleva, N., & Khvatov, V. (2020).
Data Quality in a Decentralized Environment. в O. Gervasi, & E. A. (Ред.),
Computational Science and Its Applications – ICCSA 2020 : 20th International Conference, Cagliari, Italy, July 1–4, 2020, Proceedings, Part III (стр. 58-71). (LNCS; Том 12251). Springer Nature.
https://doi.org/10.1007/978-3-030-58808-3_6
Vancouver
Bogdanov A, Degtyarev A, Shchegoleva N, Khvatov V.
Data Quality in a Decentralized Environment. в Gervasi O, EA, Редакторы, Computational Science and Its Applications – ICCSA 2020 : 20th International Conference, Cagliari, Italy, July 1–4, 2020, Proceedings, Part III. Cham: Springer Nature. 2020. стр. 58-71. (LNCS).
https://doi.org/10.1007/978-3-030-58808-3_6
Author
Bogdanov, Alexander ; Degtyarev, Alexander ; Shchegoleva, Nadezhda ; Khvatov, Valery . /
Data Quality in a Decentralized Environment. Computational Science and Its Applications – ICCSA 2020 : 20th International Conference, Cagliari, Italy, July 1–4, 2020, Proceedings, Part III. Редактор / Osvaldo Gervasi ; et al. Cham : Springer Nature, 2020. стр. 58-71 (LNCS).
BibTeX
@inproceedings{16577c21d5ad4922adc30da5630bcb1a,
title = "Data Quality in a Decentralized Environment",
abstract = "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.",
keywords = "Data quality, Distributed ledger technologies, F-BFT consensus, Master data management",
author = "Alexander Bogdanov and Alexander Degtyarev and Nadezhda Shchegoleva and Valery Khvatov",
note = "Bogdanov A., Degtyarev A., Shchegoleva N., Khvatov V. (2020) Data Quality in a Decentralized Environment. In: Gervasi O. et al. (eds) Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science, vol 12251. Springer, Cham. https://doi.org/10.1007/978-3-030-58808-3_6; 20th International Conference on Computational Science and Its Applications, ICCSA 2020 ; Conference date: 01-07-2020 Through 04-07-2020",
year = "2020",
doi = "10.1007/978-3-030-58808-3_6",
language = "English",
isbn = "9783030588076",
series = "LNCS",
publisher = "Springer Nature",
pages = "58--71",
editor = "Gervasi, {Osvaldo } and {et al.}",
booktitle = "Computational Science and Its Applications – ICCSA 2020",
address = "Germany",
url = "http://iccsa.org/",
}
RIS
TY - GEN
T1 - Data Quality in a Decentralized Environment
AU - Bogdanov, Alexander
AU - Degtyarev, Alexander
AU - Shchegoleva, Nadezhda
AU - Khvatov, Valery
N1 - Bogdanov A., Degtyarev A., Shchegoleva N., Khvatov V. (2020) Data Quality in a Decentralized Environment. In: Gervasi O. et al. (eds) Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science, vol 12251. Springer, Cham. https://doi.org/10.1007/978-3-030-58808-3_6
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - Data quality
KW - Distributed ledger technologies
KW - F-BFT consensus
KW - Master data management
UR - http://www.scopus.com/inward/record.url?scp=85092308038&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-58808-3_6
DO - 10.1007/978-3-030-58808-3_6
M3 - Conference contribution
SN - 9783030588076
T3 - LNCS
SP - 58
EP - 71
BT - Computational Science and Its Applications – ICCSA 2020
A2 - Gervasi, Osvaldo
A2 - , et al.
PB - Springer Nature
CY - Cham
T2 - 20th International Conference on Computational Science and Its Applications, ICCSA 2020
Y2 - 1 July 2020 through 4 July 2020
ER -
