Developing the Quality Model for Collaborative Open Data

D 2020

Developing the Quality Model for Collaborative Open Data

GE, Mouzhi and Wlodzimierz LEWONIEWSKI

Basic information

Original name

Developing the Quality Model for Collaborative Open Data

Authors

GE, Mouzhi (156 China, guarantor, belonging to the institution) and Wlodzimierz LEWONIEWSKI (616 Poland)

Edition

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

Publisher

Elsevier Procedia Computer Science

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

electronic version available online

RIV identification code

RIV/00216224:14330/20:00115620

Organization unit

Faculty of Informatics

ISSN

DOI

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

Keywords in English

Data Quality Quality Assessment Collaborative Open Data Wikipedia Quality Model

Abstract

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.

Links

EF16_013/0001802, research and development project

Name: CERIT Scientific Cloud

Citovat

GE, Mouzhi and 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. 176th ed. Verona, Italy: Elsevier Procedia Computer Science, 2020, p. 1883-1892. ISSN 1877-0509. Available from: 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 and 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}. 176th ed. Verona, Italy: Elsevier Procedia Computer Science, 2020, p.~1883-1892. ISSN~1877-0509. Available from: https://dx.doi.org/10.1016/j.procs.2020.09.228.

Detailed Information on Publication Record