SQRQuerier: A Visual Querying Framework for Cross-national Survey Data Recycling
Yamei Tu, Olga Li, Junpeng Wang, Han-Wei Shen, Przemek Powalko, Irina, Tomescu-Dubrow, Kazimierz M. Slomczynski, Spyros Blanas, J. Craig Jenkins

TL;DR
SDRQuerier is a visual querying framework that enhances access and exploration of a large harmonized international survey database, aiding social scientists in data retrieval, evaluation, and model improvement.
Contribution
It introduces a BERT-based query system, a visual data availability interface, and reveals relational patterns among variables in a large cross-national survey dataset.
Findings
Effective in helping social scientists find relevant data.
Facilitates evaluation and improvement of regression models.
Demonstrated success through multiple case studies.
Abstract
Public opinion surveys constitute a powerful tool to study peoples' attitudes and behaviors in comparative perspectives. However, even worldwide surveys provide only partial geographic and time coverage, which hinders comprehensive knowledge production. To broaden the scope of comparison, social scientists turn to ex-post harmonization of variables from datasets that cover similar topics but in different populations and/or years. The resulting new datasets can be analyzed as a single source, which can be flexibly accessed through many data portals. However, such portals offer little guidance to explore the data in-depth or query data with user-customized needs. As a result, it is still challenging for social scientists to efficiently identify related data for their studies and evaluate their theoretical models based on the sliced data. To overcome them, in the Survey Data Recycling…
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Taxonomy
TopicsData Visualization and Analytics · Mental Health Research Topics · Human Mobility and Location-Based Analysis
