CAREER: Orchestra - Managing the Collaborative Sharing of Evolving Data

这个职业项目开发、实现和验证Orchestra，这是一个用于支持协作数据共享的通用中间件层：在松散的科学合作者联盟之间有效地交换数据和更新，他们可能不同意他们的首选模式，甚至不同意哪些数据项或更新是正确的。提出的方法是“对等”和“自下而上”的：它提供了一种机制，通过将新的数据源映射到联盟内的现有模式，然后指定要信任和接受的更新，用户可以通过这些机制快速加入数据共享联盟。数据交换的主要方式是通过协调本地进行的修改和其他地方进行的(受信任的)更新；来自其他地方的操作总是可以在本地被覆盖。此外，该研究还开发了跨所有数据源和模式的全局查询机制。这项工作自然扩展了数据集成和同行数据管理的技术。广泛的影响：这项工作使科学界，特别是生物信息学更多地共享数据：它侧重于生物信息学数据库和仓库中信息的使用、派生和共享，并将在此类应用中进行评估。开发的系统将在网上传播，并通过在宾夕法尼亚生物信息学中心和区域大费城生物信息学联盟以及其他科学论坛举办的研讨会进行宣传。该研究项目将被纳入一个教育项目(研究生和本科生)，在更广泛的背景下教授数据管理，重点是数据集成和交换以及传统的databases.http://www.cis.upenn.edu/~zives/orchestra/

This CAREER project develops, implements, and validates Orchestra, a general middleware layer for supporting collaborative data sharing: the effective exchange of data and updates between loose confederations of scientific collaborators who may disagree about their preferred schema, or even about which data items or updates are correct. The proposed methodology is "peer-to-peer" and "bottom-up" in style: it provides mechanisms by which one can rapidly join a data sharing confederation, by mapping a new data source to existing schemas within the confederation and then specifying what updates are to be trusted and accepted. The primary means of data exchange is through reconciling modifications made locally with those (trusted) updates made elsewhere; operations from elsewhere can always be overridden locally. Additionally, the research develops mechanisms for globally querying across all data sources and schemas. The work naturally extends techniques from data integration and peer data management.Broader Impact: This work enables greater data sharing in the scientific community, especially bioinformatics: it focuses on the use, derivation, and sharing of information in bioinformatics databases and warehouses, and it will be evaluated in such applications. The developed system will be disseminated on the Web and promoted through seminars delivered at the Penn Center for Bioinformatics and the regional Greater Philadelphia Bioinformatics Alliance, as well as other scientific forums. The research project will be integrated into an educational program (graduate and undergraduate) to teach data management in the broader context, focusing on data integration and exchange as well as traditional databases.http://www.cis.upenn.edu/~zives/orchestra/