II: Data Cooperatives: Rapid and Incremental Data Sharing with Applications to Bioinformatics

II：数据合作社：快速增量数据共享及其在生物信息学中的应用

• 批准号: 0513778
• 负责人: Susan Davidson
• 金额: $ 129.53万
• 依托单位: University of Pennsylvania
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-07-15 至 2009-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0513778&HistoricalAwards=false
• 关键词: II; Data; Cooperatives; Rapid; Incremental

Generic tools and technologies for creating and maintaining data cooperatives- confederations whose purpose is distributed data sharing-will be developed to overcome the difficultiess encountered in the sharing of information in life sciences, specifically in bioinformatics.The vision of large-scale data sharing has been a long-time goal of the bioinformatics field, much of it proceeding through data integration efforts. However, conventional approaches to data integration do not have the necessary flexibility and adaptability to make the existing and future plethora of data accessible and usable to typical biologists, while keeping it rapidly extensible to new concepts, domains, and types of queries, and thus fostering new research developments. The main reasons are that (1) different biologists work with different types of data and at differing levels of abstraction; (2) schemas in the bioinformatics world are typically large and complex; (3) queries and mappings may "break" without warning because of asynchronous updates; (4) it is logistically, economically and politically difficult to operate centralized data integration facilities. In response to these difficulties data cooperatives emphasize: decentralization for both scalability and flexibility, incremental development of resources such as schemas, mappings, and queries, rapid discovery mechanisms for finding the resources relevant to a topic, and tolerance for intermittent participation of members and for approximate consistency of mappings.More specifically, the technical goals of the proposal include: (1)collaboratively developed yellow pages of biological topics; (2) schema templates, capturing the part of the structure of data pertaining to a specific interest and functioning also as visual templates from which a query form created; (3) incremental specification of mappings; (4) reasoning about uncertainty in mappings by measuring with statistical tools their degree of reliability and using it in query answering; (5) multi-path answering for queries with caching and replication in a large-scale data cooperative where the participation of individual members may not always be assured.Data cooperatives will have broader impact through applications in a variety of scientific and industrial fields, but it is in the field of bioinformatics that they are likely to have an immediate and significant impact. Therefore, a specific data cooperative as a biological testbed for evaluating the proposed technologies. This testbed is based on a small set of databases which are already collaborating and exchanging data related to Plasmodium falciparum. Broader impact will be also be achieved through the proposed educational initiatives, specifically through a "compu-tational orchestra" bioinformatics course which will expose students to data integration issues through project work, and a workshop for the Greater Philadelphia Bioinformatics Alliance (GPBA). Minority involvement will also be encouraged through a GPBA internship program.

用于创建和维护数据合作社的通用工具和技术 - 分配数据共享的目的是要开发出来，以克服生命科学信息共享时遇到的困难，特别是在生物信息学中，大规模数据共享的愿景一直是BioInformatics Field Field Field Field Field of It It It It It It Itsions intection intection intection int it It Itsions intection int it It it It it It it It it It it It it It it It it It it It it Itsions intection ressection ressection ressection ressection ressection ressection ressection。但是，传统的数据集成方法没有必要的灵活性和适应性，可以使现有和未来的大量数据可访问且可用于典型的生物学家，同时使其可迅速扩展到新概念，域和查询类型，从而促进新的研究发展。主要原因是（1）不同的生物学家与不同类型的数据和不同的抽象水平一起工作； （2）生物信息学世界中的模式通常是大而复杂的； （3）由于异步更新而无需警告而无需警告，查询和映射可能会“断开”； （4）在逻辑，经济和政治上很难运营集中数据集成设施。为了应对这些困难数据合作社的强调：用于可伸缩性和灵活性的权力化，诸如模​​式，映射和查询等资源的增量发展，迅速的发现机制，以找到与某个主题相关的资源的快速发现机制，以及对成员间歇性参与的容忍度以及对映射的近似映射的信息，包括蓝色的目标。 （2）模板模板，捕获与特定兴趣和功能相关的数据结构的一部分，也是创建查询形式的视觉模板； （3）映射的增量规范； （4）通过使用统计工具测量其可靠性并将其用于查询答案，从而对映射的不确定性进行推理； （5）在大规模数据合作社中缓存和复制的查询的多路径回答，在该数据合作社中，个人成员的参与可能并不总是得到保证。DATA合作社通过在各种科学和工业领域的应用中的应用会更广泛，但在各种科学和工业领域的应用中，它可能在生物信息领域中产生直接和重大影响。因此，特定的数据合作社作为用于评估所提出技术的生物测试床。该测试台基于一小部分数据库，这些数据库已经在协作和交换与恶性疟原虫有关的数据。 还将通过拟议的教育计划来实现更广泛的影响，特别是通过“构成乐团”生物信息学课程，该课程将通过项目工作使学生陷入数据整合问题，以及大费城生物信息知识联盟（GPBA）的研讨会。还将通过GPBA实习计划来鼓励少数派参与。