DLR-Logo -> http://www.dlr.de
DLR Portal Home | Imprint | Privacy Policy | Contact | Deutsch
Fontsize: [-] Text [+]

An approach for assessing industrial IoT data sources to determine their data trustworthiness

Foidl, Harald and Felderer, Michael (2023) An approach for assessing industrial IoT data sources to determine their data trustworthiness. Internet of Things, 22, p. 100735. Elsevier. doi: 10.1016/j.iot.2023.100735. ISSN 2542-6605.

Full text not available from this repository.

Official URL: https://dx.doi.org/10.1016/j.iot.2023.100735


Trustworthy data in the Industrial Internet of Things are paramount to ensure correct strategic decision-making and accurate actions on the shop floor. However, the enormous amount of industrial data generated by a variety of sources (e.g. machines and sensors) is often of poor quality (e.g. unreliable sensor readings). Research suggests that certain characteristics of data sources (e.g. battery-powered power supply and wireless communication) contribute to this poor data quality. Nonetheless, to date, much of the research on data trustworthiness has only focused on data values to determine trustworthiness. Consequently, we propose to pay more attention to the characteristics of data sources in the context of data trustworthiness. Thus, this article presents an approach for assessing Industrial Internet of Things data sources to determine their data trustworthiness. The approach is based on a meta-model decomposing data sources into data stores (e.g. databases) and providers (e.g. sensors). Furthermore, the approach provides a quality model comprising quality-related characteristics of data stores to determine their data trustworthiness. Moreover, a catalogue containing properties of data providers is presented to infer the trustworthiness of their provided data. An industrial case study revealed a moderate correlation between the data source assessments of the proposed approach and experts.

Item URL in elib:https://elib.dlr.de/194369/
Document Type:Article
Title:An approach for assessing industrial IoT data sources to determine their data trustworthiness
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Foidl, HaraldUNSPECIFIEDhttps://orcid.org/0000-0002-6283-0419UNSPECIFIED
Felderer, MichaelUNSPECIFIEDhttps://orcid.org/0000-0003-3818-4442141022060
Date:July 2023
Journal or Publication Title:Internet of Things
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:Yes
Page Range:p. 100735
Keywords:Data trustworthiness Data source assessment Industrial Internet of Things
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Transport System
DLR - Research area:Transport
DLR - Program:V VS - Verkehrssystem
DLR - Research theme (Project):V - Energie und Verkehr (old)
Location: Köln-Porz
Institutes and Institutions:Institute for Software Technology
Deposited By: Felderer, Michael
Deposited On:23 Aug 2023 12:24
Last Modified:23 Aug 2023 12:24

Repository Staff Only: item control page

Help & Contact
electronic library is running on EPrints 3.3.12
Website and database design: Copyright © German Aerospace Center (DLR). All rights reserved.