Publication details
Modeling Inconsistent Data for Reasoners in Web of Things
| Authors | |
|---|---|
| Year of publication | 2021 |
| Type | Article in Proceedings |
| Conference | Procedia Computer Science, Volume 192, 25th KES International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2021 |
| MU Faculty or unit | |
| Citation | |
| Doi | http://dx.doi.org/10.1016/j.procs.2021.08.130 |
| Keywords | Web of Things Internet of Things Semantic Web Reasoners |
| Description | 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. |