A Common Dialect for Infrastructure and Services in Translator

Translator 中基础设施和服务的通用方言

• 批准号: 10057176
• 负责人: Christopher Bizon
• 金额: $ 95.83万
• 依托单位: OREGON STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-01-23 至 2021-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10057176
• 关键词: Address; Agreement; Algorithms; Aloral; Architecture; Biological; Collaborations; Communication; Communities; Computer software; Consensus; Data; Development; Documentation; Ensure; Fruit; Infrastructure; Investments; Knowledge; Libraries; Modeling; Nature; Ontology; Pharmaceutical Preparations; Process; Protocols documentation; Provider; Registries; Resources; Services; Source; Standardization; System; Testing; Update; Validation; Voting; Work; biomedical ontology; collaborative environment; data infrastructure; data lake; data modeling; data standards; design; disease phenotype; innovation; knowledge graph; next generation; novel strategies

1) We will build a robust, dynamic Translator Standards and Reference Implementations Component (SRI) that integrates the collaborations and investments that the NCATS Translator has made to date. This component will consist of a suite of standards and products, a model for their governance, and processes to coordinate integration and shared implementation: ● Community governance coordination will be developed with community buy-in to ensure an effective collaborative environment, and drive consortium-wide consensus on the other components. ● Architecture and API specifications will drive community efforts to define details of project architecture and communication protocols across Translator Knowledge Providers (KPs), Autonomous Relay Agents (ARAs), and the Autonomous Relay System (ARS). ● The BioLink model will define the standard entity types, relationship types, and a schema shared by all Translator components. This includes related utility libraries and a novel approach to accommodate multiple alternate data modeling perspectives. ● Integrated reference ontologies will provide BioLink-compliant terms and relationships. We will draw on the ROBOKOP Ubergraph framework [1] , the Monarch integrated ontologies, and other ontologies from Open Biological and Biomedical Ontologies (OBO) [2] . ● A continually-updated knowledge graph and data lake will provide Translator with a standardized and integrated global view of the whole information landscape. ● Next-generation Shared Translator Services will integrate features of ROBOKOP [3] , Monarch [4] , BioLink [5] , and the reasoner APIs to remove integration barriers. These services will provide validation, lookup, and mapping functionality for use across Translator. ● A registry of Translator KPs, ARAs, and shared services will increase efficiency, eliminate duplication of effort, and promote collaboration. 2) Our proposed SRI will address the problem of connecting together different components and data/information sources at scale, with community buy-in, and with a plan for sustainability. 3) For the development of the standards component of the SRI, our plan will begin with accepted Translator standards, and we will work with the ARS, ARAs, and KPs to identify gaps. We will have a community process for contributing to the standards, making use of GitHub pull requests and voting, to help everyone contribute effectively and fairly with clear attribution. We will ensure rigorous documentation and testing. For the reference implementation component, we will stand up core Translator services, and will include additional services if they are useful to more than one Translator component rather than used by only one. 4) Consensus-building is hard. Our team has proven expertise and resources to identify needs, refine solutions, and find agreement , thereby successfully bringing infrastructure to fruition. Our team also has the technical and biological expertise to design and test the necessary standards, having been at the forefront of multiple ontology, data standards, and large enterprise software initiatives. 5) The Translator infrastructure is by nature heterogeneous, distributed, and growing; consequently, the most significant data and infrastructure challenge is managing the validity, currency, equivalency, and typing of entities (diseases, phenotypes, drugs, etc.). Our group has developed several innovative algorithms for managing this and related problems; these algorithms are in use for other integration projects and will be modified to suit Translator needs.

1）我们将构建强大的动态翻译标准和参考实现 集成了NCAT翻译人员的合作和投资的组件（SRI） 到目前为止。该组件将由一套标准和产品组成，一个模型 他们的治理和协调集成和共享实施的过程： ●社区治理协调将通过社区买入来确保 一个有效的协作环境，并在另一个方面推动整个财团的共识 成分。 ●体系结构和API规格将推动社区努力定义项目的详细信息 翻译知识提供商（KPS）的架构和通信协议， 自主继电器代理（ARA）和自主继电器系统（ARS）。 ●Biolink模型将定义标准实体类型，关系类型和模式 由所有翻译组件共享。这包括相关的公用事业库和小说 适应多个替代数据建模观点的方法。 ●集成的参考本体将提供符合生物链接的术语和关系。我们 将在Robokop Ubergraph Framework [1]上绘制，君主集成了本体， 以及开放生物学和生物医学本体论（OBO）的其他本体论[2]。 ●连续更新的知识图和数据湖将为翻译器提供一个 整个信息格局的标准化和整合的全球视图。 ●下一代共享翻译服务将集成Robokop [3]， Monarch [4]，Biolink [5]和推理器API去除集成屏障。这些 服务将提供验证，查找和映射功能，以供跨翻译器使用。 ●翻译KP，ARA和共享服务的注册表将提高效率， 消除努力的重复，并促进协作。 2）我们提议的SRI将解决将不同组件连接在一起的问题 数据/信息源大规模，具有社区买入以及可持续性计划。 3）为了制定SRI的标准部分，我们的计划将开始 接受的翻译标准，我们将与ARS，ARA和KPS合作以识别差距。 我们将有一个社区流程来促进标准，并利用GitHub拉力 请求和投票，以明确的属性帮助每个人有效，公平地做出贡献。我们 将确保严格的文档和测试。对于参考实现组件， 我们将站立核心翻译服务，如果它们对 多个翻译器组件，而不是仅使用。 4）建立共识很难。我们的团队拥有经验丰富的专业知识和资源来确定需求， 完善解决方案并达成协议，从而成功地将基础设施带入流动。我们的 团队还拥有技术和生物学专业知识，可以设计和测试必要的标准， 在多个本体，数据标准和大型企业软件的最前沿 倡议。 5）翻译基础设施本质上是异质，分布和增长的； 因此，最重要的数据和基础设施挑战是管理有效性， 实体（疾病，表型，毒品等）的货币，同等性和类型。我们的小组有 开发了几种用于管理此问题和相关问题的创新算法；这些 算法正在用于其他集成项目，并将修改以适应翻译人员的需求。