Developing the Quality Model for Collaborative Open Data

D 2020

Developing the Quality Model for Collaborative Open Data

GE, Mouzhi a Wlodzimierz LEWONIEWSKI

Základní údaje

Originální název

Developing the Quality Model for Collaborative Open Data

Autoři

GE, Mouzhi (156 Čína, garant, domácí) a Wlodzimierz LEWONIEWSKI (616 Polsko)

Vydání

176. vyd. Verona, Italy, Proceedings of the 24th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems - KES 2020, od s. 1883-1892, 10 s. 2020

Nakladatel

Elsevier Procedia Computer Science

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10201 Computer sciences, information science, bioinformatics

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

elektronická verze "online"

Kód RIV

RIV/00216224:14330/20:00115620

Organizační jednotka

Fakulta informatiky

ISSN

DOI

http://dx.doi.org/10.1016/j.procs.2020.09.228

Klíčová slova anglicky

Data Quality Quality Assessment Collaborative Open Data Wikipedia Quality Model

Štítky

core_B, firank_B

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 10. 5. 2021 05:48, RNDr. Pavel Šmerk, Ph.D.

Anotace

V originále

Nowadays, the development of data sharing technologies allows to involve more people to collaboratively contribute knowledge on the Web. The shared knowledge is usually represented as Collaborative Open Data (COD), for example, Wikipedia is one of the well-known sources for COD. The Wikipedia articles can be written in different languages, updated in real time, and originated from a vast variety of editors. However, COD also bring different data quality problems such as data inconsistency and low data objectiveness due to the crowd-based and dynamic nature. These data quality problems such as biased information may lead to sentimental changes or social impacts. This paper therefore proposes a new measurement model to assess the quality of COD. In order to evaluate the proposed model, A preliminary experiment is conducted with a large scale of Wikipedia articles to validate the applicability and efficiency of this proposed quality model in the real-world scenario.

Návaznosti

EF16_013/0001802, projekt VaV

Název: CERIT Scientific Cloud

Citovat

GE, Mouzhi a Wlodzimierz LEWONIEWSKI. Developing the Quality Model for Collaborative Open Data. Online. In Proceedings of the 24th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems - KES 2020. 176. vyd. Verona, Italy: Elsevier Procedia Computer Science, 2020, s. 1883-1892. ISSN 1877-0509. Dostupné z: https://dx.doi.org/10.1016/j.procs.2020.09.228.

@inproceedings{1654177,
   author = {Ge, Mouzhi and Lewoniewski, Wlodzimierz},
   address = {Verona, Italy},
   booktitle = {Proceedings of the 24th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems - KES 2020},
   doi = {http://dx.doi.org/10.1016/j.procs.2020.09.228},
   edition = {176},
   keywords = {Data Quality Quality Assessment Collaborative Open Data Wikipedia Quality Model},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {Verona, Italy},
   pages = {1883-1892},
   publisher = {Elsevier Procedia Computer Science},
   title = {Developing the Quality Model for Collaborative Open Data},
   year = {2020}
}

TY  - JOUR
ID  - 1654177
AU  - Ge, Mouzhi - Lewoniewski, Wlodzimierz
PY  - 2020
TI  - Developing the Quality Model for Collaborative Open Data
PB  - Elsevier Procedia Computer Science
CY  - Verona, Italy
KW  - Data Quality Quality Assessment Collaborative Open Data Wikipedia Quality Model
N2  - Nowadays, the development of data sharing technologies allows to involve more people to collaboratively contribute knowledge on the Web. The shared knowledge is usually represented as Collaborative Open Data (COD), for example, Wikipedia is one of the well-known sources for COD. The Wikipedia articles can be written in different languages, updated in real time, and originated from a vast variety of editors. However, COD also bring different data quality problems such as data inconsistency and low data objectiveness due to the crowd-based and dynamic nature. These data quality problems such as biased information may lead to sentimental changes or social impacts. This paper therefore proposes a new measurement model to assess the quality of COD. In order to evaluate the proposed model, A preliminary experiment is conducted with a large scale of Wikipedia articles to validate the applicability and efficiency of this proposed quality model in the real-world scenario.
ER  -

GE, Mouzhi a Wlodzimierz LEWONIEWSKI. Developing the Quality Model for Collaborative Open Data. Online. In \textit{Proceedings of the 24th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems - KES 2020}. 176. vyd. Verona, Italy: Elsevier Procedia Computer Science, 2020, s.~1883-1892. ISSN~1877-0509. Dostupné z: https://dx.doi.org/10.1016/j.procs.2020.09.228.

Podrobný výpis o publikaci