Zhu Wei, Tao Shiqiang, Cui Licong, Zhang Guo-Qiang
Case Western Reserve University, Cleveland, Ohio, USA.
The University of Texas Health Science Center at Houston, Houston, Texas, USA.
AMIA Jt Summits Transl Sci Proc. 2020 May 30;2020:740-749. eCollection 2020.
Non-lattice subgraphs are often indicative of structural anomalies in ontological systems. Visualization of SNOMED CT's non-lattice subgraphs can help make sense of what has been asserted in the hierarchical ("is-a") relation. More importantly, it can demonstrate what has not been asserted, or "is-not-a," using Closed-World Assumption for such subgraphs. A feature-rich web-based interactive graph-visualization engine called WINS is introduced, for supporting non-lattice based analysis of ontological systems such as SNOMED CT. A faceted search interface is designed for querying conjunctively specified non-lattice subgraphs. To manage the large number of possible nonlattice subgraphs, MongoDB is used for storing and processing sets of concepts, relationships, and subgraphs, as well as for query optimization. WINS' interactive visualization interface is implemented in the open source package D3.js. 14 versions of SNOMED CT (US editions from March 2012 to September 2018), with about 170,000 subgraphs in each version, were extracted and imported into WINS. Two types of non-lattice based ontology quality assurance (OQA) tasks were highlighted to demonstrate use cases of WINS in sense-making of such non-lattice subgraphs.
非格状子图通常表明本体系统中存在结构异常。可视化SNOMED CT的非格状子图有助于理解在层次（“是一个”）关系中所断言的内容。更重要的是，利用此类子图的封闭世界假设，它可以展示未被断言的内容，即“不是一个”。引入了一个名为WINS的功能丰富的基于网络的交互式图形可视化引擎，以支持对诸如SNOMED CT等本体系统进行基于非格状的分析。设计了一个分面搜索界面，用于查询联合指定的非格状子图。为了管理大量可能的非格状子图，MongoDB用于存储和处理概念集、关系集和子图集，以及进行查询优化。WINS的交互式可视化界面是在开源包D3.js中实现的。提取了14个版本的SNOMED CT（2012年3月至2018年9月的美国版本），每个版本约有170,000个子图，并将其导入WINS。强调了两种基于非格状的本体质量保证（OQA）任务，以展示WINS在此类非格状子图理解中的用例。
