Login (DCU Staff Only)
Login (DCU Staff Only)

DORAS | DCU Research Repository

Explore open access research and scholarly works from DCU

Advanced Search

AccTEF: A transparency and accountability evaluation framework for ontology-based systems

Basereh, Maryam, Caputo, Annalina orcid logoORCID: 0000-0002-7144-8545 and Brennan, Rob orcid logoORCID: 0000-0001-8236-362X (2022) AccTEF: A transparency and accountability evaluation framework for ontology-based systems. International Journal of Semantic Computing, 16 (1). pp. 5-27. ISSN 1793-351X

Abstract
This paper proposes a new accountability and transparency evaluation framework (AccTEF) for ontology-based systems (OSysts). AccTEF is based on an analysis of the relation between a set of widely accepted data governance principles, i.e. findable, accessible, interoperable, reusable (FAIR) and accountability and transparency concepts. The evaluation of accountability and transparency of input ontologies and vocabularies of OSysts are addressed by analyzing the relation between vocabulary and ontology quality evaluation metrics, FAIR and accountability and transparency concepts. An ontology-based knowledge extraction pipeline is used as a use case in this study. Discovering the relation between FAIR and accountability and transparency helps in identifying and mitigating risks associated with deploying OSysts. This also allows providing design guidelines that help accountability and transparency to be embedded in OSysts. We found that FAIR can be used as a transparency indicator. We also found that the studied vocabulary and ontology quality evaluation metrics do not cover FAIR, accountability and transparency. Accordingly, we suggest these concepts should be considered as vocabulary and ontology quality evaluation aspects. To the best of our knowledge, it is the first time that the relation between FAIR and accountability and transparency concepts has been found and used for evaluation.
Metadata
Item Type:Article (Published)
Refereed:Yes
Uncontrolled Keywords:FAIR data; Semantics; AI Governance
Subjects:Computer Science > Artificial intelligence
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Initiatives and Centres > ADAPT
Publisher:World Scientific
Official URL:https://dx.doi.org/10.1142/S1793351X22400013
Copyright Information:©World Scientific Publishing Company
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland Centre for Research Training in Digitally-Enhanced Reality (d-real) under Grant No. 18/CRT/6224, ADAPT Centre for Digital Content Technology under the SFI Research Centres Programme (Grant 13/RC/2106 2), European Regional Development Fund.
ID Code:27040
Deposited On:20 Apr 2022 09:39 by Annalina Caputo . Last Modified 01 Apr 2023 04:30
Documents

Full text available as:

[thumbnail of BIBTeX_ing_in_WSPC_BIB_Style.pdf]
Preview
PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Creative Commons: Attribution-Share Alike 4.0
418kB
Downloads

Downloads

Downloads per month over past year

Archive Staff Only: edit this record