  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 (SDR) international cooperation
research project, we propose SDRQuerier and apply it to the harmonized SDR
database, which features over two million respondents interviewed in a total of
1,721 national surveys that are part of 22 well-known international projects.
We design the SDRQuerier to solve three practical challenges that social
scientists routinely face. First, a BERT-based model provides customized data
queries through research questions or keywords. Second, we propose a new visual
design to showcase the availability of the harmonized data at different levels,
thus helping users decide if empirical data exist to address a given research
question. Lastly, SDRQuerier discloses the underlying relational patterns among
substantive and methodological variables in the database, to help social
scientists rigorously evaluate or even improve their regression models. Through
case studies with multiple social scientists in solving their daily challenges,
we demonstrated the novelty, effectiveness of SDRQuerier.
