Core D: CURATION

摘要 对通过PENTACON生成的所有数据进行准确和彻底的整理是 将项目捆绑在一起的粘合剂；财团之间共享出版前数据将几乎 如果没有如此强有力的监管努力，这是不可能的。此外，所有流入PENTACON并可以 根据合规规则发布的报告将向更大的研究社区公开提供。我们将分发 数据都通过PENTACON数据库，该数据库将包括复杂的搜索和分析工具， 取决于数据之间的适当注释和连接(参见数据库和集成核心)， 以及所有适当的公共储存库和/或模型生物体数据库。因此，这一巨大的影响 收集经过良好注释的数据将远远超出财团本身的范围。虽然一般而言，策展工作是 昂贵的努力对像我们这样新奇和复杂的企业的成功至关重要 在这里求婚。为了控制成本，我们的方法是拥有一支相对精简但永久的策展人团队，他们 将负责整个过程的监控和几项不同的更具体的任务。我们会带上 符合PENTACON最低要求的切实可行的方法和策划 研究人员(足以使这些来自不同学科的研究人员能够在共同的 语言)和公共存储库为特定数据类型设置的标准，而不是详尽的 非常理想。例如，在第一年的早些时候，我们将调查PENTACON中的数据建模师，以确定确切的 他们需要利用代谢组学数据。通过注释建模师所需的信息以及任何 作为发布代谢组学数据的标准的其他信息，我们将满足 绝大多数想要使用这些数据的研究人员。我们希望我们在这两个方面的管理工作 PENTACON生成的数据和外部数据将对研究产生重大影响。我们将提供一个丰富的， 各种数据的注解良好的来源，科学界可以在 以重要和科学严谨的方式将发现联系在一起的大型研究。

Summary Accurate and thorough curation of all of the data generated via PENTACON is a necessary ingredient of the glue that will bind the project together; sharing of pre-publication data amongst the consortium would be nearly impossible without such robust curation efforts. In addition, all data that flow into PENTACON and can be released under compliance rules will be publicly available to the greater research community. We will distribute data both through the PENTACON database, which will include sophisticated search and analysis tools that depend on the appropriate annotation and connection between data (see Databases and Integration Core), as well as all appropriate public repositories and/or model organism databases. Thus, the impact of this large collection of well-annotated data will go far beyond the consortium itself. While curation efforts in general are expensive endeavors, they are vital to the success of an enterprise as novel and as complex as we are proposing here. To limit the costs, our approach is to have a relatively lean but permanent staff of curators who will be responsible for overall monitoring of the process and several different more specific tasks. We will take a practical approach and curate to the extent necessary to meet the minimum requirements of PENTACON researchers (sufficient that these investigators from diverse disciplines can communicate in a common language) and the standards set by public repositories for a particular data type, rather than to an exhaustive ideal. For example, early in Year 1, we will survey the data modelers in PENTACON to determine exactly what they need to utilize metabolomics data. By annotating the information that the modelers require plus any additional information that is standard for publication of metabolomics data, we will have met any needs of the vast majority of researchers who want to use the data. We expect that our curation efforts on both PENTACON-generated and external data will have a significant impact on research. We will provide a rich, well-annotated source of a wide variety of data that will be able to be accessible to the scientific community at large to connect findings together in an important and scientifically rigorous manner.