User-generated Structured Query Language (SQL) queries are a rich source of information for database analysts,
information scientists, and the end users of databases. In this study a group of scientists in astronomy and computer and
information scientists work together to analyze a large volume of SQL log data generated by users of the Sloan Digital
Sky Survey (SDSS) data archive in order to better understand users' data seeking behavior. While statistical analysis of
such logs is useful at aggregated levels, efficiently exploring specific patterns of queries is often a challenging task due
to the typically large volume of the data, multivariate features, and data requirements specified in SQL queries. To
enable and facilitate effective and efficient exploration of the SDSS log data, we designed an interactive visualization
tool, called the SDSS Log Viewer, which integrates time series visualization, text visualization, and dynamic query
techniques. We describe two analysis scenarios of visual exploration of SDSS log data, including understanding
unusually high daily query traffic and modeling the types of data seeking behaviors of massive query generators. The
two scenarios demonstrate that the SDSS Log Viewer provides a novel and potentially valuable approach to support these
targeted tasks.
Conference Committee Involvement (2)
Visualization and Data Analysis 2013
4 February 2013 | Burlingame, California, United States
Visualization and Data Analysis 2012
23 January 2012 | Burlingame, California, United States
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