Partitioning to Support Auditing and Extending the UMLS

描述(由申请人提供)：UMLS对生物医学界来说是一个无价的资源。然而，元词典的大小和复杂性可能会阻碍其实用性。我们提出了一些分而治之的技术，以方便审计和扩展元数据的任务。分而治之的方法将大量项目分解为更易于管理的单元。在这项研究中，结果将是元数据的新划分。每个分区都将用于审计元数据。UMLS的语义网络(SN)不将元划分为不相交的集合。我们首先创建一个精炼的语义网络(RSN)，它确实将元数据划分为互不相交的概念集(范围)。RSN由SN派生而来，结合了交集类型和纯语义类型，并在许多方面改进了UMLS，例如，它包含语义一致且(通常)范围较小的类型。除了RSN，还将对范围应用三种额外的、新颖的划分技术：沿着关系相似性维度进行划分；创建单根子组；以及细分错综复杂的多根层次结构。每个分区(通常)都会暴露新的错误。我们建议对2006AA UMLS进行大规模审计，集中于通过划分获得的小群体。预计将发现的错误类型包括：概念歧义和同义词、错误和遗漏IS-A与语义关系、不一致和不正确的分类和遗漏。我们将对UMLS的基因组部分进行强化审计。为此，我们将创建一个精化基因组SN(RGSN)。我们将构建一个包含RSN和三个附加分区级别的审计软件工具。计划对该工具进行一次有人参与的正式评价，并对审计结果进行两级专家评价。最后，在RSN的基础上，将新的术语集成到UMLS中。综上所述，我们将：1)创建RSN，将元划分为不相交的单元；2)为语义类型的范围设计三种新的划分技术；3)审计小群体的概念；4)设计用于审计基因组概念的改进的基因组SN(RGSN)；5)构建审计工具；6)设计和评估术语的集成技术。

DESCRIPTION (provided by applicant): The UMLS is an invaluable resource to the biomedical community. However, the Metathesaurus's (META's) size and complexity can hinder its usefulness. We propose a number of divide and conquer techniques that facilitate the tasks of auditing and extending the META. The divide and conquer approach breaks down a large collection of items into more manageable units. In this research, the outcome will be new partitions of the META. Each partition will be employed in auditing the META. The UMLS's Semantic Network (SN) does not partition the META into disjoint sets. We first create a Refined Semantic Network (RSN) that does partition the META into disjoint sets of concepts (extents). Derived from the SN, the RSN incorporates intersection types along with pure semantic types and improves the UMLS in a number of ways, e.g., it contains types with semantically uniform and (usually) smaller extents. In addition to the RSN, three additional, novel partitioning techniques will be applied to extents: Partition along the dimension of relationship similarity; create singly rooted subgroups; and subdivide tangled, multi-rooted hierarchies. Each partition will (normally) expose new errors. We propose a large scale audit of the 2006AA UMLS concentrating on small groups obtained by the partition. The kinds of errors expected to be uncovered include: concept ambiguity and synonymy, wrong and missing IS-A and semantic relationships, inconsistent and incorrect classifications and omissions. We will perform an enhanced audit of the genomic component of the UMLS. For this we will create a Refined Genomic SN (RGSN). We will build an auditing software tool that incorporates the RSN and the three additional levels of partitioning. A formal evaluation, with human subjects, of the tool and a two-level expert evaluation of the auditing results are planned. Finally we focus on the integration of new terminologies into the UMLS, based on the RSN. In summary we will: 1) Create the RSN that partitions META into disjoint units; 2) Design three new partitioning techniques for extents of semantic types; 3) Audit the concepts of small groups; 4) Design a Refined Genomic SN (RGSN) for auditing genomic concepts; 5) Build an auditing tool; 6) Design and evaluate an integration technique for terminologies.