Modeling Inconsistent Data for Reasoners in Web of Things

D 2021

Modeling Inconsistent Data for Reasoners in Web of Things

BLANCO SÁNCHEZ, José Miguel, Mouzhi GE and Tomáš PITNER

Basic information

Original name

Modeling Inconsistent Data for Reasoners in Web of Things

Authors

BLANCO SÁNCHEZ, José Miguel (724 Spain, guarantor, belonging to the institution), Mouzhi GE (156 China) and Tomáš PITNER (203 Czech Republic, belonging to the institution)

Edition

Szczecin, Procedia Computer Science, Volume 192, 25th KES International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2021, p. 1265-1273, 9 pp. 2021

Publisher

Elsevier

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Netherlands

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

electronic version available online

RIV identification code

RIV/00216224:14330/21:00122772

Organization unit

Faculty of Informatics

ISSN

DOI

http://dx.doi.org/10.1016/j.procs.2021.08.130

UT WoS

000720289001032

Keywords in English

Web of Things Internet of Things Semantic Web Reasoners

Abstract

V originále

With the recent developments of the Internet of Things and its integration in the web environment, the Web of Things and the real-time data submissions to Reasoners are enabled. However, the data that are fed to the Reasoners are often inconsistent. This can be possibly caused by the malfunction of certain Internet of Things device or by human errors. The data consistency issue is becoming more complex in the Web of Things network. This paper, therefore, proposes a new data processing model to tackle the inconsistent data, so that the processed data can be further used in Reasoners. The data processing model introduces an oversimplification of the Shramko-Wansing sixteen-valued trilattice, which is an extension of Belnap’s four-valued bilattice to assign the data classical truth-values. A preliminary implementation is demonstrated to validate the proposed model. The result shows that our model can avoid system collapse when contradictory outputs exist.

Citovat

BLANCO SÁNCHEZ, José Miguel, Mouzhi GE and Tomáš PITNER. Modeling Inconsistent Data for Reasoners in Web of Things. Online. In Procedia Computer Science, Volume 192, 25th KES International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2021. Szczecin: Elsevier, 2021, p. 1265-1273. ISSN 1877-0509. Available from: https://dx.doi.org/10.1016/j.procs.2021.08.130.

@inproceedings{1802049,
   author = {Blanco Sánchez, José Miguel and Ge, Mouzhi and Pitner, Tomáš},
   address = {Szczecin},
   booktitle = {Procedia Computer Science, Volume 192, 25th KES International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2021},
   doi = {http://dx.doi.org/10.1016/j.procs.2021.08.130},
   keywords = {Web of Things Internet of Things Semantic Web Reasoners},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {Szczecin},
   pages = {1265-1273},
   publisher = {Elsevier},
   title = {Modeling Inconsistent Data for Reasoners in Web of Things},
   year = {2021}
}

TY  - JOUR
ID  - 1802049
AU  - Blanco Sánchez, José Miguel - Ge, Mouzhi - Pitner, Tomáš
PY  - 2021
TI  - Modeling Inconsistent Data for Reasoners in Web of Things
PB  - Elsevier
CY  - Szczecin
KW  - Web of Things Internet of Things Semantic Web Reasoners
N2  - With the recent developments of the Internet of Things and its integration in the web environment, the Web of Things and the real-time data submissions to Reasoners are enabled. However, the data that are fed to the Reasoners are often inconsistent. This can be possibly caused by the malfunction of certain Internet of Things device or by human errors. The data consistency issue is becoming more complex in the Web of Things network. This paper, therefore, proposes a new data processing model to tackle the inconsistent data, so that the processed data can be further used in Reasoners. The data processing model introduces an oversimplification of the Shramko-Wansing sixteen-valued trilattice, which is an extension of Belnap’s four-valued bilattice to assign the data classical truth-values. A preliminary implementation is demonstrated to validate the proposed model. The result shows that our model can avoid system collapse when contradictory outputs exist.
ER  -

BLANCO SÁNCHEZ, José Miguel, Mouzhi GE and Tomáš PITNER. Modeling Inconsistent Data for Reasoners in Web of Things. Online. In \textit{Procedia Computer Science, Volume 192, 25th KES International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2021}. Szczecin: Elsevier, 2021, p.~1265-1273. ISSN~1877-0509. Available from: https://dx.doi.org/10.1016/j.procs.2021.08.130.

Detailed Information on Publication Record