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Matching biodiversity and ecology ontologies: challenges and evaluation results
The Knowledge Engineering Review ( IF 2.8 ) Pub Date : 2020-03-09 , DOI: 10.1017/s0269888920000132
Naouel Karam , Abderrahmane Khiat , Alsayed Algergawy , Melanie Sattler , Claus Weiland , Marco Schmidt

Biodiversity research studies the variability and diversity of organisms, including variability within and between species with particular focus on the functional diversity of traits and their relationship to environment. Managing biodiversity data implies dealing with its heterogeneous nature using semantics and tailored ontologies. These are themselves differently conceived, and combining them in semantically enabled applications necessitates an effective alignment between their concepts. This paper describes the ontology matching of biodiversity- and ecology-related ontologies. We illustrate diverse challenges introduced by this kind of ontologies to ontology matching in general. Real use cases requiring pairwise alignments between environment and trait ontologies are introduced. We describe our experience creating a new track at the Ontology Alignment Evaluation Initiative designed for this specific domain and report on the results obtained by state-of-the-art participating systems. The biodiversity and ecology use case turns out to be a strong one for ontology matching, introducing new interesting challenges. Even if most of the matching systems perform relatively well in the proposed matching tasks, there is still room for improvement. We highlight possible directions in that matter and elaborate on our plan to further progress with the track.

中文翻译:

匹配生物多样性和生态本体:挑战和评估结果

生物多样性研究研究生物的变异性和多样性,包括物种内部和物种之间的变异性,特别关注性状的功能多样性及其与环境的关系。管理生物多样性数据意味着使用语义和定制的本体来处理其异构性质。这些本身是不同的概念,并且在语义支持的应用程序中将它们组合起来需要它们的概念之间的有效对齐。本文描述了生物多样性和生态相关本体的本体匹配。我们说明了这种本体对一般本体匹配带来的各种挑战。介绍了需要在环境和特征本体之间成对对齐的实际用例。我们描述了我们在为该特定领域设计的本体对齐评估倡议中创建新轨道的经验,并报告了最先进的参与系统获得的结果。生物多样性和生态用例被证明是本体匹配的强大用例,引入了新的有趣挑战。即使大多数匹配系统在提出的匹配任务中表现相对较好,但仍有改进的空间。我们强调了这方面的可能方向,并详细说明了我们在轨道上进一步取得进展的计划。即使大多数匹配系统在提出的匹配任务中表现相对较好,但仍有改进的空间。我们强调了这方面的可能方向,并详细说明了我们在轨道上进一步取得进展的计划。即使大多数匹配系统在提出的匹配任务中表现相对较好,但仍有改进的空间。我们强调了这方面的可能方向,并详细说明了我们在轨道上进一步取得进展的计划。
更新日期:2020-03-09
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