BioPortal: An Expansive Knowledgebase of Biomedical Entities and Relations

摘要 生物医学中使用最广泛和最通用的知识库是本体， 定义对医疗保健或生命科学的不同方面至关重要的实体和关系。 当本体在一个集成的框架中聚集在一起时，启用术语表示相同或 类似的实体彼此相关，并允许计算基础设施跨 本体-则本体的集合为用户提供附加能力。 我们的团队开发了一个非常受欢迎的知识资源，称为BioPortal，它提供了一个 几乎所有世界上公开访问的生物医学本体的独特知识库。采用BioPortal 已经很了不起了每个月，来自学术界、政府和工业界的75，000多名独立用户 访问我们的本体存储库的内容，我们的API服务超过1600万个请求。至少 根据Google Scholar的数据，有7,850篇科学论文提到了BioPortal的使用。 我们提出以下4个具体目的：（1）我们会继续管理及维持“生物入门网站 通过加强知识库向生物医学界提供的服务，加强知识库。（二） 我们将通过创建BioPortal来提高用户与知识库交互的效率 知识图谱。该图-这将是一个可查询的知识资源本身-将整合所有 知识库中的本体，它将提供到其他知识源的链接，允许用户执行 扩展了所有本体的查询。(3)我们将允许BioPortal的用户提出更改请求， 扩展本体，并查看更改的历史和更改请求时，本体是 在Git仓库中管理。其结果将是一个更有效的工作流程， 本体开发人员和监视组件本体的更改历史以通知本体的能力 选择特定的最终用户任务。(4)我们将提供增强的机制，使BioPortal的用户 在远程BioPortal服务器中搜索、访问和浏览知识。用户将不再需要知道 推进特定知识可能存储的地方，他们将有能力轻松整合 通过服务器网络存储的互补科学学科知识。 其结果将是世界上最广泛访问的生物医学概念和关系的知识库- 支持生物医学中语义技术的所有其他工作，并使所有生物医学知识库 更标准化，更易于集成，更公平。

ABSTRACT The most widely used and most general-purpose knowledgebases in biomedicine are the ontologies that define the entities and the relationships that are central to different aspects of health care or the life sciences. When ontologies are brought together in an integrated framework—enabling terms denoting the same or similar entities to be related to one another and allowing computational infrastructure to operate across ontologies—then the aggregate collection of ontologies provides additional capabilities for users. Our group has developed an enormously popular knowledge resource, known as BioPortal, that provides a unique knowledgebase of nearly all the world’s publicly accessible biomedical ontologies. Adoption of BioPortal has been remarkable. Each month, more than 75,000 unique users from academia, government, and industry access the contents of our ontology repository, and our API services more than 16 million requests. At least 7,850 scientific papers mention the use of BioPortal, according to Google Scholar. We propose the following four specific aims: (1) We will continue to govern and maintain the BioPortal knowledgebase by enhancing the services that the knowledgebase provides to the biomedical community. (2) We will improve the efficiency with which users interact with the knowledgebase by creating the BioPortal Knowledge Graph. The graph—which will be a queryable knowledge resource in its own right—will integrate all ontologies in the knowledgebase and it will provide links to other knowledge sources, allowing users to perform expanded queries across all ontologies. (3) We will enable users of BioPortal to make requests for changes or extensions to ontologies, and to view the history of changes and change requests when ontologies are managed in Git repositories. The result will be a much more efficient workflow for making suggestions to ontology developers and the ability to monitor the change history of component ontologies to inform ontology selection for particular end-user tasks. (4) We will provide enhanced mechanisms to enable users of BioPortal to search, access, and browse knowledge in remote BioPortal servers. Users no longer will need to know in advance where particular knowledge might be stored and they will have the ability to easily integrate knowledge from complementary scientific disciplines stored across a network of servers. The result will be the world’s most widely accessed knowledgebase of biomedical concepts and relationships— supporting all other work in semantic technology in biomedicine and making all biomedical knowledgebases more standardized, more easily integrated, and more FAIR.