BioPortal: An Expansive Knowledgebase of Biomedical Entities and Relations

摘要 生物医学中使用最广泛、用途最广的知识库是 定义对卫生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结合在一起时-使术语能够表示相同或 相似的实体相互关联，并允许计算基础设施跨 本体-然后，本体的聚合集合为用户提供额外的功能。 我们的团队开发了一个非常受欢迎的知识资源，称为生物门户，它提供了一个 几乎世界上所有可公开访问的生物医学本体论的独特知识库。采用Bioport. 已经很了不起了。每个月，超过75,000名来自学术界、政府和行业的独立用户 访问我们本体库的内容，我们的API为1600多万个请求提供服务。至少 根据谷歌学者的数据，7850篇科学论文提到了生物门户的使用。 我们提出以下四个具体目标：(1)我们将继续管理和维护生物门户网站 通过增强知识库向生物医学社区提供的服务，实现对知识库的支持。(2) 我们将通过创建Bio门户来提高用户与知识库交互的效率 知识图谱。该图本身将是一种可查询的知识资源，它将整合所有 知识库中的本体，它将提供指向其他知识源的链接，允许用户执行 扩展了所有本体中的查询。(3)我们将允许Bio门户的用户提出更改或 对本体的扩展，并在本体被 在Git存储库中管理。其结果将是一个更高效的工作流程，用于对以下各项提出建议 本体开发人员以及监控组件本体的更改历史以通知本体的能力 针对特定最终用户任务的选择。(4)我们会提供更完善的机制，让生物门户网站的使用者 搜索、访问和浏览远程Bio门户服务器中的知识。用户将不再需要知道 在可能存储特定知识的位置推进，他们将能够轻松集成 来自互补科学学科的知识存储在服务器网络中。 其结果将是世界上访问最广泛的生物医学概念和关系知识库- 支持生物医学中语义技术的所有其他工作，并建立所有生物医学知识库 更规范、更容易融合、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.