Competency Evaluation of Plant Character Ontologies Against Domain Literature
Competency Evaluation of Plant Character Ontologies Against Domain Literature
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DOI：
10.1002/asi.21325
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发表时间：
2010-06-01
影响因子：
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通讯作者：
Cui, Hong
中科院分区：
文献类型：
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作者：
Cui, Hong
标本识别码仍然是系统生物学家获取生物多样性信息最常用的工具。创建识别密钥需要分析和综合来自标本及其描述的大量信息，并且是非常劳动密集型和耗时的活动。从文本描述中自动生成标识键成为生物多样性领域中一个非常有吸引力的文本挖掘应用。对生物体的形态描述进行细粒度的语义标注是从文本生成关键字的必要的第一步。在这个过程中需要机器可读的本体，因为大多数生物特征仅仅是隐含的（即，未说明）。要问的直接问题是“现有本体对语义注释和自动密钥生成的支持程度如何？“为了选择现有的本体或基于现有的本体开发统一的本体，本文评估了生物多样性特征本体和三个可能变成本体的植物词汇表的覆盖范围，语义一致性和本体间协议。本体/术语表的覆盖范围和语义一致性与权威领域文献，即北美的植物群和中国的植物群进行了检查。评价结果表明，需要做更多的工作，以提高本体/词汇的覆盖面和互操作性。需要将更多的概念添加到本体/词汇表中，并且需要仔细工作来提高语义一致性。本文中使用的方法来评估本体/词汇表可以用来提出新的候选概念，从领域文献，并建议适当的定义。
Specimen identification keys are still the most commonly created tools used by systematic biologists to access biodiversity information. Creating identification keys requires analyzing and synthesizing large amounts of information from specimens and their descriptions and is a very labor-intensive and time-consuming activity. Automating the generation of identification keys from text descriptions becomes a highly attractive text mining application in the biodiversity domain. Fine-grained semantic annotation of morphological descriptions of organisms is a necessary first step in generating keys from text. Machine-readable ontologies are needed in this process because most biological characters are only implied (i.e., not stated) in descriptions. The immediate question to ask is "How well do existing ontologies support semantic annotation and automated key generation?"With the intention to either select an existing ontology or develop a unified ontology based on existing ones, this paper evaluates the coverage, semantic consistency, and inter-ontology agreement of a biodiversity character ontology and three plant glossaries that may be turned into ontologies. The coverage and semantic consistency of the ontology/glossaries are checked against the authoritative domain literature, namely, Flora of North America and Flora of China. The evaluation results suggest that more work is needed to improve the coverage and interoperability of the ontology/glossaries. More concepts need to be added to the ontology/glossaries and careful work is needed to improve the semantic consistency. The method used in this paper to evaluate the ontology/glossaries can be used to propose new candidate concepts from the domain literature and suggest appropriate definitions.