RUI: Framework: Data - An Open Semantic Data Framework for Data-Driven Discovery

该项目有助于简化注释、共享和搜索异构数据集。 它侧重于本科生培训，强调应用于一系列科学问题的数据科学能力。 该项目使用结构化框架实现异构数据集的聚合、搜索和推理，通过将框架编码为用于关联数据的JavaScript对象表示法（JSON）（JSON-LD）文档，允许数据和元数据链接。 该方法建立在现有的发展，如科学数据（SciData）框架和相关的本体，已开发的PI，形状约束语言（SHACL）形状，以提供有效的搜索，浏览和可视化的数据。 其结果扩展了现有的方法来链接数据和元数据，并使数据易于共享。 该活动强调本科院校的研究（RUI），培训了30多名本科生、研究生和一名博士后学生，将数据科学技术应用于一系列科学问题。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

The project makes contributions to the ease of annotating, sharing, and searching heterogeneous data sets. It focuses upon undergraduate training, emphasizing data science capabilities applied to a range of science problems. The project enables aggregation, search, and inference with heterogeneous datasets using a structured framework allowing data and metadata to be linked by encoding the framework as a JavaScript Object Notation (JSON) for Linked Data (JSON-LD) document. The approach builds on existing developments such as the Scientific Data (SciData) framework and associated ontology that has been developed by the PI, and Shape Constraint Language (SHACL) shapes to provide efficient searching, browsing, and visualization of data. The result extends existing approaches to link data and metadata and make data easily discoverable. The activity emphasizes Research in Undergraduate Institutions (RUI), training more than 30 undergraduates, graduate students and a post-doctoral student in the application of data science techniques to an array of science problems.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.