2026-09-20T16:01:30Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/116184 2023-07-11 col_2142_5131 col_2142_8951 com_2142_5130 com_2142_8950 com_2142_150

Ludäscher, Bertram Ludäscher, Bertram Renear, Allen Wickett, Karen Franz, Nico 2022-08 application/pdf en text Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-15 without embargo terms The student, Yi-Yun Cheng, accepted the attached license on 2022-07-06 at 09:55. The student, Yi-Yun Cheng, submitted this Dissertation for approval on 2022-07-06 at 10:05. This Dissertation was approved for publication on 2022-07-07 at 10:43. DSpace SAF Submission Ingestion Package generated from Vireo submission #18150 on 2022-11-15 at 17:38:10 Agreeing to disagree: Applying a logic-based approach to reconciling and merging multiple taxonomies Cheng, Yi-Yun 2022-07-07 Taxonomies Taxonomy Alignment Knowledge Organization Systems Interoperability Taxonomies are used to classify concepts into hierarchies via parent-child (is-a) relation- ships. They are used in many contexts, ranging from everyday sorting decisions, enterprise website infrastructures, to controlled vocabularies in information systems. The proliferation of taxonomies leads to interoperability challenges when one attempts to incorporate existing taxonomies with a newly created taxonomy, or to integrate multiple data in a digital library that were annotated with different taxonomies. To address these interoperability challenges, methods to systematically align two taxonomies and merge them into a single merged view have been developed in the extant literature. However, merging taxonomies into a unified representation may result in the loss of important information that was present in the original taxonomies. The goals of this dissertation are thus to align taxonomies that: (1) preserve the information in both taxonomies in the merged solution(s); (2) provide multiple possible solutions to merge the taxonomies. Specifically, this dissertation explores the use of a logic-based approach to align taxonomies in which concepts in two taxonomies T1, T2 are inter-linked via a set of relations to yield merged solution(s). The merged solution(s) can be (1) a unique merged taxonomy T3 that preserves both T1 and T2’s information; (2) an inconsistent result that suggests the relations linking the taxonomies are contradictory; or (3) multiple merged solutions that present different possible ways (or possible worlds) in which T1 and T2 can be aligned. In this dissertation, I apply this logic-based alignment approach to taxonomies in socio-geographic contexts, including the United States maps, country taxonomies, indigenous peoples’ tribes, and historical sovereignties in biodiversity data. Through these use cases, it is demonstrated that the logic-based taxonomy alignment approach is feasible to reconcile conflicts in socio- geographic taxonomies. Thesis eng https://hdl.handle.net/2142/116184 Copyright 2022 Yi-Yun Cheng Ph.D. Dissertation Information Sciences University of Illinois at Urbana-Champaign Information Sciences