Agreeing to disagree: Applying a logic-based approach to reconciling and merging multiple taxonomies

Cheng, Yi-Yun

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https://hdl.handle.net/2142/116184 Copy

Description

Title

Agreeing to disagree: Applying a logic-based approach to reconciling and merging multiple taxonomies

Author(s)

Cheng, Yi-Yun

Issue Date

2022-07-07

Director of Research (if dissertation) or Advisor (if thesis)

Ludäscher, Bertram

Doctoral Committee Chair(s)

Ludäscher, Bertram

Committee Member(s)

• Renear, Allen
• Wickett, Karen
• Franz, Nico

Department of Study

Information Sciences

Discipline

Information Sciences

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

Taxonomies, Taxonomy Alignment, Knowledge Organization Systems, Interoperability

Abstract

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.

Graduation Semester

2022-08

Type of Resource

Thesis

Copyright and License Information

Copyright 2022 Yi-Yun Cheng

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