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及其之间关系的本体工程已成为现代生物医学工作的必要条件。本体帮助人类和计算机管理迅速增长的数据数量。注释、检索和集成高通量数据集、处理自然语言和构建决策支持系统的需求，使许多研究人员社区开始构建大型本体。prot系统已经成为一个庞大的国际科学家社区不可或缺的开源资源——支持世界各地生物医学研究人员对本体和电子知识库的开发、维护和使用。在撰写本文时，注册的prot用户已从2002年的3500人增长到19.5万多人。然而，迄今为止，由于本体开发工具的复杂性，使得许多生物医学科学家无法使用本体，因此在生物医学中使用本体受到了限制。在本提案中，我们将开发新的方法和工具，这些方法和工具将大大降低本体开发的进入门槛，扩展prot<s:2>在整个本体生命周期中提供直观和用户友好的本体获取方法。我们的计划包含五个具体目标。首先，我们将开发方法，使用列表和图表，以非正式的方式对本体术语进行初始规范。科学家将能够开始建模他们的领域，而不必考虑形式本体论的区别。其次，我们将为本体规范提供直观的、易于使用的工具，这将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，并开发基于这些需求评估本体覆盖的新方法。第四，对于本质上具有复杂内部结构的本体，仅使用简单的本体结构无法完全表示，我们将开发方法来创建涵盖本体中规则结构的模板。然后，科学家们就可以根据这些模板填写表格，而protegase会在后台生成相应的逻辑结构。第五，我们将继续扩展和支持蓬勃发展的prot<s:1>用户社区，因为它扩展到包括生物医学科学家，他们现在可以建立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 Protégé 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 Protégé 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 Protégé 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 Protégé generating the corresponding logical structure in the background. Fifth, we will continue to expand and support the thriving Protégé 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.