Collaborative Research: Core Database Technologies to enable the Integration of AToL Information

合作研究：支持 AToL 信息集成的核心数据库技术

• 批准号: 0629702
• 负责人: Reed Beaman
• 金额: $ 21.99万
• 依托单位: Yale University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-10-01 至 2008-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0629702&HistoricalAwards=false
• 关键词: Collaborative; Research; Core; Database; Technologies

The AToL (Assembling the Tree of Life ) is a large-scale collaborative research effort sponsoredby the National Science Foundation to reconstruct the evolutionary origins of all living things. Currently 31projects involving 150+ PIs are underway generating novel data including studies of bacteria, microbial eukaryotes, vertebrates, flowering plants and many more. The data being generated by these projects include and are not limited to: (i) Specimens and their provenance including collection information, voucher deposition, etc.; (ii) Phenotypic descriptions and their provenance; (iii) Genotypic descriptions and their provenance; (iv) Interpretation of the primary measurements including homology ; (v) Estimates of phylogenies and methods employed; and (vi) Post-tree analyses such as character evolution hypotheses.While the data collection, storage, and dissemination within each projects are well coordinated, there is a critical need to develop the infrastructure to integrate all ATOL data sources, allowing the individual efforts to become multipliers for global hypotheses. Furthermore, as the projects continue to expand and address diverse corners of the Tree of Life, efficient project management will be greatly aided by workflow and data management tools targeted towards the ATOL problem domain. The project will develop new, compact, abstract data models for phylogenetics, leveraging use cases from a broad survey of empirical projects. The integration system will develop novel mappings between different phylogenetic data domains, and allow individual projects to join a network of integrated databases in an incremental manner. The data provenance system, which allows tracking of how each data object was created, will be unique tosystematics data management. The provenance system will not only allow tracking of what kinds of decisions were made in producing a particular tree or a particular column of a data matrix, but will also allow tracking of alternative data lineages such that, for example, different opinions on character homology might be tracked. The results of the research will be delivered in robust software tools that can be used by the entire evolutionary biology community. The study will develop a community-based formal model of data objects used in systematics, primarily through a continuing set of workshops. This activity will not only develop new data management tools, but will also have the effect of synthesizing disparate views of the phylogenetics research domains. The results of the system will be extensible to other domains of evolutionary biology, thereby contributing to the broader mission of evolutionary synthesis. The project will also provide training for the general systematics community in latest database technologies. Finally, by leveraging existing outreach efforts at the Penn Center for Bioinformatics, the project will link to other biological database efforts in genomics and biomedical sciences, disseminating phylogenetic information to the broad biomedical research community.

AToL（组装生命之树）是一项由美国国家科学基金会赞助的大规模合作研究项目，旨在重建所有生物的进化起源。目前，涉及150多个pi的31个项目正在进行中，产生了新的数据，包括细菌，微生物真核生物，脊椎动物，开花植物等的研究。这些项目产生的数据包括但不限于：(i)标本及其来源，包括收集资料、凭证存放等；（ii）表型描述及其来源；（iii）基因型描述及其来源；解释主要测量结果，包括同源性；估计系统发生和采用的方法；（vi）后树分析，如性格演化假说。虽然每个项目中的数据收集、存储和传播都得到了很好的协调，但迫切需要开发基础设施来整合所有ATOL数据源，从而使个人努力成为全球假设的乘数器。此外，随着项目的不断扩展和解决生命之树的各个角落，针对ATOL问题领域的工作流和数据管理工具将极大地帮助高效的项目管理。该项目将开发新的、紧凑的、抽象的系统发育数据模型，利用来自广泛的经验项目调查的用例。集成系统将在不同的系统发育数据域之间开发新的映射，并允许个别项目以增量方式加入集成数据库网络。数据来源系统允许跟踪每个数据对象是如何创建的，这将是系统数据管理的独特之处。来源系统不仅允许跟踪在生成特定树或数据矩阵的特定列时所做的决定，而且还允许跟踪替代数据谱系，例如，可能跟踪关于字符同源性的不同意见。研究结果将通过健壮的软件工具发布，供整个进化生物学社区使用。这项研究将主要通过一系列持续的讲习班，发展一个以社区为基础的数据对象的正式模型，用于系统学。这项活动不仅将开发新的数据管理工具，而且还将具有综合系统发育研究领域的不同观点的效果。该系统的结果将扩展到进化生物学的其他领域，从而有助于更广泛的进化综合任务。该项目还将向一般系统学界提供最新数据库技术方面的培训。最后，通过利用宾夕法尼亚大学生物信息学中心现有的外展工作，该项目将与基因组学和生物医学科学方面的其他生物数据库工作联系起来，向广泛的生物医学研究界传播系统发育信息。