Protege: An Ontology-Development Platform for Biomedical Scientists

描述(由申请人提供)：定义应用领域中的实体和它们之间的关系的本体论工程已经成为现代生物医学工作的关键。本体论帮助人类和计算机管理迅速增长的数据数量。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。PROT系统已成为庞大的国际科学家社区不可或缺的开源资源--支持世界各地的生物医学研究人员开发、维护和使用本体论和电子知识库。注册保护用户的数量已从2002年的3,500人增加到撰写本报告时的19.5万多人。然而，到目前为止，本体在生物医学中的使用一直受到本体开发工具复杂性的限制，这往往使许多生物医学科学家无法访问本体。在这项提案中，我们将开发新的方法和工具，以显著降低本体开发的进入门槛，扩大范围，在本体的整个生命周期中提供直观和用户友好的本体获取方法。我们的计划包括五个具体目标。首先，我们将开发能够以非正式方式使用列表和图表对本体术语进行初始规范的方法。科学家将能够开始对他们的领域进行建模，而不必考虑正式的本体论区别。其次，我们将为本体规范提供直观、易用的工具，帮助开发人员开始形式化他们的模型。第三，我们将跟踪本体必须解决的需求，并根据这些需求开发评估本体覆盖的新方法。第四，对于本质上具有复杂的内部结构而不能仅使用简单的本体构造来完全表示的本体，我们将开发方法来创建覆盖本体中规则结构的模板。然后，科学家将能够根据这些模板填写表格，并在后台生成相应的逻辑结构。第五，我们将继续扩大和支持蓬勃发展的PROTG用户社区，因为它扩大到包括生物医学科学家，他们现在将能够构建本体来支持他们的数据驱动的研究和发现。

DESCRIPTION (provided by applicant): The engineering of ontologies that define the entities in an application area and the relationships among them has become essential for modern work in biomedicine. Ontologies help both humans and computers to manage burgeoning numbers of data. 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. The Prot¿g¿ system has become an indispensable open-source resource for an enormous internationa community of scientists-supporting the development, maintenance, and use of ontologies and electronic knowledge bases by biomedical investigators everywhere. The number of registered Prot¿g¿ users has grown from 3,500 in 2002 to more than 195,000 users as of this writing. To date, however, the use of ontologies in biomedicine has been limited by the complexity of the ontology-development tools, which often make ontologies inaccessible to many biomedical scientists. In this proposal, we will develop new methods and tools that will significantly lower the barrier of entry for ontology development, expanding Prot¿g¿ to provide intuitive and user-friendly ontology-acquisition methods throughout the ontology lifecycle. Our plan entails five specific aims. First, we will develop methods that enable initial specification of ontology terms in an informal manner, using lists and diagrams. Scientists will be able to start modeling their domain without having to think in terms of formal ontological distinctions. Second, we will provide intuitive, easy-to-use tools for ontology specification that will aid developers as they start to formalize their models. Third, we will track the requirements that an ontology must address and develop novel methods for evaluating ontology coverage based on these requirements. Fourth, for ontologies that inherently have complex internal structure that cannot be represented fully using only simple ontology constructs, we will develop methods that will create templates covering regular structures in the ontology. Scientists will then be able to fill out forms based o these templates, with Prot¿g¿ generating the corresponding logical structure in the background. Fifth, we will continue to expand and support the thriving Prot¿g¿ user community, as it expands to include the biomedical scientists who will now be able to build the ontologies to support their data-driven research and discoveries.