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: 10330632
• 负责人: Christopher Bizon
• 金额: $ 56.95万
• 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/10330632
• 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、动态的翻译器标准和参考实现 集成NCATS翻译人员的协作和投资的组件(SRI 到目前为止已经取得了进展。该组件将由一套标准和产品、一个模型 他们的治理，以及协调整合和共享实施的流程： 社区治理协调将与社区收购一起发展，以确保 有效的协作环境，并推动整个财团就另一方达成共识 组件。 架构和API规范将推动社区努力定义项目细节 跨翻译知识提供商(KPS)的体系结构和通信协议， 自主中继代理(ARA)和自主中继系统(ARS)。 Biolink模型将定义标准实体类型、关系类型和架构 由所有翻译器组件共享。这包括相关的实用程序库和一本小说 一种适应多个备用数据建模视角的方法。 集成的参考本体将提供符合Biolink的术语和关系。我们 将借鉴ROBOKOP Ubergraph框架[1]，Monch集成的本体， 以及来自开放生物和生物医学本体(OBO)的其他本体[2]。 不断更新的知识图谱和数据湖将为翻译人员提供 标准化、集成化的全球信息版图。 下一代共享翻译服务将集成ROBOKOP[3]的功能， Monch[4]、Biolink[5]和Reasoner API来消除集成障碍。这些 服务将提供验证、查找和映射功能，以便在Translator中使用。 翻译员KPS、ARAS和共享服务的注册将提高效率， 消除重复劳动，促进协作。 2)我们建议的SRI将解决连接不同组件和 大规模的数据/信息来源、社区参与和可持续发展计划。 3)关于SRI标准部分的发展，我们的计划将从 公认的翻译员标准，我们将与ARS、ARAS和KPS合作确定差距。 我们将有一个社区流程，利用GitHub Pull为标准做出贡献 请求和投票，以帮助每个人有效和公平地做出贡献，并明确归属。我们 将确保严格的文档和测试。对于参考实现组件， 我们将建立核心翻译服务，并将包括其他服务，如果它们对以下方面有用 多个转换器组件，而不是仅由一个使用。 4)建立共识是困难的。我们的团队拥有成熟的专业知识和资源来确定需求， 完善解决方案，并达成一致，从而成功地实现基础设施建设。我们的 团队还拥有设计和测试必要标准的技术和生物专业知识， 在多种本体、数据标准和大型企业软件方面处于领先地位 首创精神。 5)翻译基础设施本质上是异质的、分布式的和不断增长的； 因此，最重要的数据和基础设施挑战是管理有效性， 货币、等价性和实体分类(疾病、表型、药物等)。我们的团队已经 开发了几个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，并将进行修改以满足翻译人员的需求。