SEIII: Automatic Tool Generation for Ad Hoc Scientific Data

在每一个科学学科中，研究人员都在将他们的知识数字化并使用计算方法。 这一过程产生了大量的临时数据，而这些数据的标准数据处理工具并不容易获得。 这类数据对用户和操作它的软件都提出了挑战。为了最大限度地提高科学家处理临时数据的效率和准确性，新的工作将扩展现有的数据描述和处理语言。 处理流行类型数据源的能力将得到扩展，并对系统进行修改，以便以强大且自动的方式生成工具。 这将允许系统提供一种方式，将关于数据的描述性信息直接提供给工具。 将系统形式化，以证明工具的正确性。 该研究结合了新颖的编程语言设计，高性能系统工程和理论分析，以解决关键的数据处理问题。 该系统将进行测试，以解决真实的问题，如欺诈检测和基因组途径建模的背景下，以及在宇宙学数据。 研究生和本科生都从事跨学科的研究。

In every scientific discipline, researchers are digitizing their knowledge and using computational methods. This process has generated enormous amounts of ad hoc data, data for which standard data processing tools are not readily available. This kind of data poses challenges to both the users and the software that manipulate it. In order to maximize the efficiency and accuracy with which scientists deal with ad hoc data, new work will expand the existing data description and processing language. The ability to process prevalent kinds of data sources will be expanded and the system modified to generate tools in a robust and automatic way. This will permit the system to provide a way to provide descriptive information about the data directly to the tools. The system will be formalized to prove the correctness of the tools. The research combines novel programming language design, high-performance system engineering and theoretical analysis to solve crucial data processing problems. The system will be tested to address real problems such as fraud detection and in the context of genomic pathway modeling, as well as in cosmology data. Both graduate and undergraduate students are engaged in the interdisciplinary research.