Collaborative Development of Biomedical Ontologies and Terminologies

描述(由申请人提供)：定义实体和它们之间关系的本体论的发展已经成为生物医学中现代工作的关键。本体论帮助人类和计算机管理生物和医学中普遍存在的迅速增长的数据。对高通量数据集的注释、检索和集成，处理自然语言，以及构建决策支持系统的需要，促使许多调查人员社区致力于构建大型本体。到目前为止，这些本体开发人员小组一直受到缺乏促进大规模本体和词汇表的分布式协作工程的方法和工具的限制。在这份提案中，我们概述了三个具体目标。首先，我们将探索协作本体工程所必需的基本计算方法。我们将研究表示不同协作工作流的方法、有关变更和概念历史、信任和来源的信息，以及记录决策和设计原理的方法。对现有本体开发项目的经验分析将为我们构建协作开发工作流模型提供信息，这些模型将指导创作、审查和管理生物医学本体的过程。其次，我们将使用我们第一个特定目标的结果来构建cProtigi，这是一组强大的、可定制的交互工具，用于支持分布式用户的协作工作，以构建和编辑术语和本体。第三，我们将在真实世界的大规模本体工程项目的背景下评估我们的工作，包括国家自闭症研究数据库的自闭症本体；世界卫生组织国际疾病分类的第11次修订；由NIH支持的广泛研究人员正在开发的生物医学调查本体；以及NCI正在开发的BiomedGT。想象研究人员可以创建独立工作的生物医学本体论已经不再可行。我们将研究的协作方法和我们将构建的工具将带来更多的机会，以支持Bisti、CTSA、NCBC和无数需要强大、可扩展的本体的生物医学倡议中的各种数据和知识密集型活动。公共卫生相关性：现代医学以知识为基础的本质要求使用本体论和术语来处理和整合数据。本体论开发本身成为一个协作的过程，更大的研究社区的成员对新兴的本体论做出贡献和评论。我们计划扩展Protigi本体编辑器--当今使用最广泛的本体编辑器，拥有近10万注册用户--以支持本体的协作开发，并通过在世界卫生组织和其他环境中部署新工具来对新工具进行评估。

DESCRIPTION (provided by applicant): The development of ontologies that define entities and the relationships among them has become essential for modern work in biomedicine. Ontologies help both humans and computers to manage the burgeoning data that are pervasive in biology and medicine. The need to annotate, retrieve, and integrate high-throughput data sets, to process natural language, and to build systems for decision support has set many communities of investigators to work building large ontologies. To date, these groups of ontology developers have been limited by the lack of methods and tools that facilitate distributed, collaborative engineering of large-scale ontologies and vocabularies. In this proposal, we outline three specific aims. First, we will explore basic computational methods that are essential for collaborative ontology engineering. We will investigate methods for representing diverse collaborative workflows, information about changes and concept history, trust, and provenance, and for recording decision making and design rationale. Empirical analysis of existing ontology-development projects will inform our construction of models for collaborative development workflows that will guide the processes of authoring, reviewing, and curating biomedical ontologies. Second, we will use the results from our first specific aim to build cProtigi, a set of robust, customizable, interactive tools to support distributed users in their collaborative work to build and edit terminologies and ontologies. Third, we will evaluate our work in the context of real-world, large-scale ontology-engineering projects, including the autism ontology of the National Database for Autism Research; the 11th revision of the WHO's International Classification of Diseases; the Ontology for Biomedical Investigations, under development by a wide range of NIH-supported researchers; and BiomedGT, under development by NCI. It is no longer feasible to imagine that investigators can create biomedical ontologies working independently. The collaborative methods that we will study and the tools that we will build will lead to expanded opportunities to support the diverse data- and knowledge-intensive activities that pervade BISTI, the CTSAs, the NCBCs, and myriad biomedical initiatives that require robust, scaleable ontologies. PUBLIC HEALTH RELEVANCE: The knowledge-based nature of modern medicine requires the use of ontologies and terminologies to process and integrate data. Ontology development itself becomes a collaborative process, with members of the larger research community contributing to and commenting on emerging ontologies. We plan to extend the Protigi ontology editor-the most widely used ontology editor today, with almost 100,000 registered users-to support collaborative development of ontologies and to evaluate the new tools by deploying them at the World Health Organization for the development of ICD-11 and in other settings.