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论 定义对医疗保健或生命科学不同方面至关重要的实体和关系。 当本体被整合到一个集成框架中时，可以使用表示相同或相同的术语 相似的实体相互关联，并允许计算基础设施跨区域运行 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种非常流行的知识资源，称为 BioPortal，它提供了 几乎世界上所有可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。每个月都有超过 75,000 位来自学术界、政府和行业的独立用户 访问我们本体存储库的内容，我们的 API 服务超过 1600 万个请求。至少 根据 Google Scholar 的数据，7,850 篇科学论文提到了 BioPortal 的使用。 我们提出以下四个具体目标：（1）我们将继续治理和维护BioPortal 通过增强知识库向生物医学界提供的服务来建立知识库。 (2) 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。该图本身就是一个可查询的知识资源，它将整合所有内容 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 扩展了跨所有本体的查询。 (3) 我们将允许 BioPortal 用户提出更改请求或 本体的扩展，并在本体被修改时查看变更历史记录和变更请求 在 Git 存储库中管理。结果将是一个更高效的工作流程，可以向以下人员提出建议 本体开发人员以及监控组件本体的更改历史以告知本体的能力 针对特定最终用户任务的选择。 (4) 我们将提供增强的机制，使BioPortal的用户能够 搜索、访问和浏览远程 BioPortal 服务器中的知识。用户不再需要知道 推进可能存储特定知识的地方，并且他们将有能力轻松集成 来自存储在服务器网络中的互补科学学科的知识。 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—— 支持生物医学语义技术的所有其他工作并制作所有生物医学知识库 更标准化、更容易集成、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.