Guarding accessibility - AI supported ontology engineering in the context of the MuseIT repository design

TY - GEN

T1 - Guarding accessibility - AI supported ontology engineering in the context of the MuseIT repository design

AU - Tykhonov, Vyacheslav

AU - Olson, Nasrine

AU - Johansson, Moa

AU - Ferguson, Kim B

AU - Jain, Nitisha

AU - May, Lloyd

AU - Scharnhorst, Andrea

PY - 2024/6/19

Y1 - 2024/6/19

N2 - Presented at the DARIAH Annual Event 2024 in Lisbon, Portugal on June 19, 2024. Abstract: The MuseIT project explores new technologies that facilitate and widen access to cultural assets and enables the co-creation of them. It builds upon the UN Universal Declaration of Human Rights and the Convention on the Rights of Persons with Disabilities, both proclaim human rights for all people, including people with disabilities. One of the key outcomes of MuseIT is to set up a content repository capable of indexing, storing and retrieving multisensory, multi-layered digital representation of cultural assets respecting FAIR principles and long term preservation. Dataverse is the envisioned platform to be used. This paper zooms into one important step: namely the creation of specific knowledge organisation systems suitable for the later archiving process. Based on ontology engineering we look for new ways to describe accessibility facets of artefacts in the MuseIT repository. We use the term accessibility here in the context of disability, following the Wikipedia definition that “accessibility is the design of products, devices, services, vehicles, or environments so as to be usable by people with disabilities”. If it comes to categorising disability we depart from the International Classification of Functioning, Disability and Health (ITC) released by the World Health Organisation. As in its name, this classification provides a medical view on disability. Additionally, we also use Wikipedia.EN (or a collection of web resources (MuseIT disability collection) stored as part of the Now.Museum (Vion-Dury et al. 2023) on a dataverse platform). In short, material which represents a more cultural view on a phenomena (e.g., Salah et al. 2012). In this paper, we present a new innovative knowledge engineering solution (EverythingData) through which ‘proto-ontologies’ are created by combining Large Language Models with structured data in the form of Knowledge Graphs (Pan et al 2024). It is schematically depicted in the figure below, and in essence relies on a set of APIs. Those enable workflow as such: (a) start with a term (group of terms) for instance ‘disability’ from the ITC (b) identify a related wikipedia (eng) page (or other texts) (c ) feed these texts into a LLM instance and receive a group of terms and their relations which in essence represent a proto-ontology (d) iterate this process and (e) evaluate the variants of a proto-ontology by a group of experts....

AB - Presented at the DARIAH Annual Event 2024 in Lisbon, Portugal on June 19, 2024. Abstract: The MuseIT project explores new technologies that facilitate and widen access to cultural assets and enables the co-creation of them. It builds upon the UN Universal Declaration of Human Rights and the Convention on the Rights of Persons with Disabilities, both proclaim human rights for all people, including people with disabilities. One of the key outcomes of MuseIT is to set up a content repository capable of indexing, storing and retrieving multisensory, multi-layered digital representation of cultural assets respecting FAIR principles and long term preservation. Dataverse is the envisioned platform to be used. This paper zooms into one important step: namely the creation of specific knowledge organisation systems suitable for the later archiving process. Based on ontology engineering we look for new ways to describe accessibility facets of artefacts in the MuseIT repository. We use the term accessibility here in the context of disability, following the Wikipedia definition that “accessibility is the design of products, devices, services, vehicles, or environments so as to be usable by people with disabilities”. If it comes to categorising disability we depart from the International Classification of Functioning, Disability and Health (ITC) released by the World Health Organisation. As in its name, this classification provides a medical view on disability. Additionally, we also use Wikipedia.EN (or a collection of web resources (MuseIT disability collection) stored as part of the Now.Museum (Vion-Dury et al. 2023) on a dataverse platform). In short, material which represents a more cultural view on a phenomena (e.g., Salah et al. 2012). In this paper, we present a new innovative knowledge engineering solution (EverythingData) through which ‘proto-ontologies’ are created by combining Large Language Models with structured data in the form of Knowledge Graphs (Pan et al 2024). It is schematically depicted in the figure below, and in essence relies on a set of APIs. Those enable workflow as such: (a) start with a term (group of terms) for instance ‘disability’ from the ITC (b) identify a related wikipedia (eng) page (or other texts) (c ) feed these texts into a LLM instance and receive a group of terms and their relations which in essence represent a proto-ontology (d) iterate this process and (e) evaluate the variants of a proto-ontology by a group of experts....

U2 - 10.5281/zenodo.12533424

DO - 10.5281/zenodo.12533424

M3 - Other contribution

ER -