Biomedical Data Translator Technical Feasibility Assessment and Architecture Design

卡罗莱纳生物医学数据转换器（CBDT）将解决以下重大挑战： 允许临床医生、护士、生物医学研究人员进行临床和转化研究， 临床科学家查询，利用，并有助于联合收集复杂和高度 具有医学重要性的不同数据。这个数据联邦--一个“准全面”的医疗 将使审讯人员能够提出有关人类健康和疾病的问题， 这是迄今为止无法想象的。我们预计，这些分析将增加， 我们对新的治疗方法和治疗目标的理解， 疾病和疾病传播的机制，环境触发因素，药物 再利用、分子候选物和系统生物学途径。 为了实现这一愿景，我们提出了一个轨道，允许实现这样一个 Federation.我们打算开始适度和原型CBDT使用独特的工具，我们有 一直在为其他信息学项目构建，然后迭代地改进CBDT， 与NCATS合作。最终，CBDT联合会需要社会化， 允许，并培育，以实现其全部潜力。我们认为，最大的 唯一的挑战将是建立一个治理模式， 从各个机构和组织中提取的信息。我们将在第节讨论这个问题 2.2.1. CBDT必须： ·动态：定期更新，以适应新数据和数据源的增加; ·敏捷：可修改用于原始设计之外的用途，并可适应其他数据分析; ·可用性：允许不同的访问和访问级别（查看、编辑等）数据，以及 允许专家和受过适当培训的新用户使用; ·合理性：数据将具有临床和科学相关性，并根据政策提供信息 和协议，系统将提供具有上下文元数据的答案;以及 ·精选：数据将具有相关的来源和质量指标，包括 适当的统计相关性。 我们设想一个动态系统，支持数据摄取和后续的 管理、联合和利用（见图）。我们组建了一个 拥有跨学科合作和开放式开发记录团队 源工具。我们提出了一个示范项目，这是可行的，在2年 时间框架，但演示了所有的关键功能， 系统必须具备。

The Carolina Biomedical Data Translator (CBDT) will address the significant challenges in clinical and translational research by permitting clinicians, nurses, biomedical researchers, and clinical scientists to query, exploit, and contribute to a federated collection of complex and highly disparate data with medical importance. This data federation—a “quasi-comprehensive” medical federation—will enable interrogators to pose questions about human health and disease that could not heretofore have been imagined. We anticipate that these analyses will increase, in ways that are paradigm shifting, our understanding of new treatments and treatment targets, mechanisms of disease and disease transmission, environmental triggers, opportunities for drug repurposing, molecular candidates, and systems biology pathways. To realize this vision, we propose a trajectory that permits the realization of such a federation. We intend to start modestly and prototype the CBDT using the unique tools we have been building for other informatics projects, and then iteratively improve the CBDT in collaboration with NCATS. Ultimately, the CBDT federation will need to be socialized, permitted, and nurtured in order to realize its full potential. Indeed, we believe that the biggest single challenge will be establishing a governance model that permits the assembly of information pulled from across institutions and organizations. We discuss this issue in Section 2.2.1. The CBDT must be: • Dynamic: regularly updated to accommodate the addition of new data and data sources; • Agile: modifiable for uses beyond the original design and adaptable for other data analysis; • Usable: permitting differential access and levels of access (view, edit, etc.) to the data, and permitting use by both experts and new users with modest training; • Rational: the data will be clinically and scientifically relevant, as well as informed by policy and protocols, and the system will provide answers with contextual meta-data; and • Curated: the data will have associated provenance and quality measures, including statistical relevance where appropriate. We envision a dynamic system that supports data ingestion and subsequent curation, federation, and exploitation (see figure). We have assembled a team that has a track record of interdisciplinary collaboration and development of open source tools. We propose a demonstration project that is feasible in the 2-year time frame, but demonstrates all of the key functionality that the final system must possess.