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2018 Networked Knowledge Organization Systems workshop- Full of beans: a study on the alignment of two flowering plants classification systems

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NKOS18

2018 Networked Knowledge Organization Systems workshop @ Porto, Portugal

Title-- Full of beans: a study on the alignment of two flowering plants classification systems

Author-- Yi-Yun Cheng, Bertram Ludaescher

Abstract

Advancement in technologies such as DNA analysis has given rise to new ways in organizing organisms in biodiversity classification systems. In this paper, we examine the feasibility of aligning two classification systems for flow- ering plants using a logic based, Region Connection Calculus (RCC-5) approach. The older “Cronquist system” (1981) classifies plants using their morphological features, while the more recent Angiosperm Phylogeny Group IV (APG IV) (2016) system classifies based on many new methods including genome-level analysis. In this approach, we align pairwise concepts X and Y from two taxon- omies using five basic set relations: congruence (X=Y), inclusion (X>Y), inverse inclusion (X<Y), overlap (X><Y), and disjointness (X!Y). With some of the RCC-5 relationships among the Fabaceae family (beans family) and the Sapin- daceae family (maple family) uncertain, we anticipate that the merging of the two classification systems will lead to numerous Possible Worlds, or merged so- lutions. This research demonstrates how the logic-based alignment can lead to ambiguities and show multiple merged solutions, which would not have been possible if aligning taxonomies, classifications, or other knowledge organization systems (KOS) manually. We believe that this work can introduce a novel ap- proach for aligning KOS, and the merged Possible Worlds can serve as a mini- mum viable product for engaging domain experts in the loop.

Keywords: taxonomy alignment, KOS alignment, interoperability

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To replay the use cases you can use the EulerX toolkit. There are two versions of the available. Please refer to the README of euler2 for more information on how to run the use cases of the paper.

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