Travillian Ravensara S, Adamusiak Tomasz, Burdett Tony, Gruenberger Michael, Hancock John, Mallon Ann-Marie, Malone James, Schofield Paul, Parkinson Helen
EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK.
J Biomed Semantics. 2011 Aug 9;2 Suppl 4(Suppl 4):S3. doi: 10.1186/2041-1480-2-S4-S3.
To evaluate how well current anatomical ontologies fit the way real-world users apply anatomy terms in their data annotations.
Annotations from three diverse multi-species public-domain datasets provided a set of use cases for matching anatomical terms in two major anatomical ontologies (the Foundational Model of Anatomy and Uberon), using two lexical-matching applications (Zooma and Ontology Mapper).
Approximately 1500 terms were identified; Uberon/Zooma mappings provided 286 matches, compared to the control and Ontology Mapper returned 319 matches. For the Foundational Model of Anatomy, Zooma returned 312 matches, and Ontology Mapper returned 397.
Our results indicate that for our datasets the anatomical entities or concepts are embedded in user-generated complex terms, and while lexical mapping works, anatomy ontologies do not provide the majority of terms users supply when annotating data. Provision of searchable cross-products for compositional terms is a key requirement for using ontologies.
评估当前的解剖学本体在多大程度上符合现实世界用户在其数据注释中应用解剖学术语的方式。
来自三个不同的多物种公共领域数据集的注释提供了一组用例，用于使用两种词汇匹配应用程序（Zooma和本体映射器）在两个主要的解剖学本体（解剖学基础模型和Uberon）中匹配解剖学术语。
识别出约1500个术语；Uberon/Zooma映射提供了286个匹配项，而对照组和本体映射器返回了319个匹配项。对于解剖学基础模型，Zooma返回了312个匹配项，本体映射器返回了397个。
我们的结果表明，对于我们的数据集，解剖学实体或概念嵌入在用户生成的复杂术语中，虽然词汇映射有效，但解剖学本体并未提供用户在注释数据时提供的大多数术语。为组合术语提供可搜索的交叉产品是使用本体的关键要求。
