Open Standards-Based Data Extraction Web Tool for Complex Longitudinal Datasets

描述（由申请人提供）：NIH资助了许多长期的纵向研究，这些研究收集了大量的数据。这些调查继续为其数据集增加额外的数据收集波，从而增加了收集到的信息的丰富性。不幸的是，随着额外波的不断加入，研究人员的工作数据变得更加复杂。当研究包含数千个变量时尤其如此。研究人员通常对与他们的研究问题相关的数据子集感兴趣，但必须遍历多个数据文件和许多页文档才能找到与他们的主题相关的变量。复制研究也变得具有挑战性，因为它多次涉及到同样繁琐的步骤。为了应对这一挑战，研究人员需要先进的工具来从大型纵向研究中导航和提取数据。该项目旨在创建一个基于开放标准的网络工具，以提供从大型公共使用纵向调查中提取的数据。该工具将允许研究人员选择变量和变量组来创建数据提取。该工具还将为摘录创建代码本文档和标准化的数据文档计划（DDI） 3元数据，使摘录能够使用DDI标准进行引用。通过使用社会科学研究的DDI开放标准，该工具也将被推广到适用于多项研究，这是对当今一代基于每项研究开发的一次性工具的创新。第一阶段可行性研究的目的是分析准备在线数据提取研究所需的数据准备和元数据创建工作流程，验证使用数据文档计划的DDI 3标准作为该工具的基础，并创建基于web的数据提取软件原型。虽然重点是纵向调查，但拟议的系统也将处理横断面、时间序列和非重复研究。其目的是通过简化用于发现、检索和分析与研究人员调查相关的数据的过程来改进研究方法。

DESCRIPTION (provided by applicant): The NIH funds many long running longitudinal studies that have collected massive amounts of data. These surveys continue to add additional data collection waves to their datasets which increases the wealth of information collected. Unfortunately, as additional waves continue to be added the data becomes more complex for researchers to work with. This is especially true when the study contains many thousands of variables. Researchers are often interested in a subset of the data pertaining to their research question, but have to traverse multiple data files and many pages of documentation to find the variables associated with their topic. It also becomes challenging to replicate research, since it many times involves going through these same burdensome steps. To address this challenge, advanced tools for researchers are needed to navigate and extract data from large longitudinal studies. This project aims to create an open standards based web tool to provide data extracts from large public use longitudinal surveys. The tool will allow researchers to select variables and variable groups to create data extracts. The tool will also create codebook documentation and standardized Data Documentation Initiative (DDI) 3 metadata for the extracts, enabling citation of the extract using the DDI standard. The tool will also be generalized to work for multiple studies by using the DDI open standard for social science research, which is an innovation over today's generation of one-off tools developed on a per study basis. This Phase I feasibility study aims to analyze to data preparation and metadata creation workflow needed to prepare a study for online data extraction, to validate the use of the Data Documentation Initiative's DDI 3 standard for the basis of such a tool, and to create prototype web-based data extraction software. While the focus is on longitudinal surveys, the proposed system would also handle cross-sectional, time-series, and non-repeated studies. The aim is to improve research methodologies through a simplification of the process used for discovering, retrieving, and analyzing data relevant to a researcher's investigation. PUBLIC HEALTH RELEVANCE: Researchers who wish to use public use data from longitudinal studies or replicate other's research must currently navigate thousands of variables across multiple waves and datasets to answer simple analysis questions. The proposed web tool allows researchers to create data extracts that are directly related to their queries, allowing more time to be spent on public health research questions instead of data management.