Abstract
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.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of SPIE-IS and T Electronic Imaging - Visualization and Data Analysis 2012 |
| DOIs | |
| Publication status | Published - 2012 Feb 16 |
| Event | Visualization and Data Analysis 2012 - Burlingame, CA, United States Duration: 2012 Jan 23 → 2012 Jan 25 |
Publication series
| Name | Proceedings of SPIE - The International Society for Optical Engineering |
|---|---|
| Volume | 8294 |
| ISSN (Print) | 0277-786X |
Other
| Other | Visualization and Data Analysis 2012 |
|---|---|
| Country | United States |
| City | Burlingame, CA |
| Period | 12/1/23 → 12/1/25 |
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All Science Journal Classification (ASJC) codes
- Electronic, Optical and Magnetic Materials
- Condensed Matter Physics
- Computer Science Applications
- Applied Mathematics
- Electrical and Electronic Engineering
Cite this
}
SDSS Log Viewer : Visual exploratory analysis of large-volume SQL log data. / Zhang, Jian; Chen, Chaomei; Vogeley, Michael S.; Pan, Danny; Thakar, Ani; Raddic, Jordan.
Proceedings of SPIE-IS and T Electronic Imaging - Visualization and Data Analysis 2012. 2012. 82940D (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 8294).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - SDSS Log Viewer
T2 - Visual exploratory analysis of large-volume SQL log data
AU - Zhang, Jian
AU - Chen, Chaomei
AU - Vogeley, Michael S.
AU - Pan, Danny
AU - Thakar, Ani
AU - Raddic, Jordan
PY - 2012/2/16
Y1 - 2012/2/16
N2 - 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.
AB - 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.
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UR - http://www.scopus.com/inward/citedby.url?scp=84863020206&partnerID=8YFLogxK
U2 - 10.1117/12.907097
DO - 10.1117/12.907097
M3 - Conference contribution
AN - SCOPUS:84863020206
SN - 9780819489418
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Proceedings of SPIE-IS and T Electronic Imaging - Visualization and Data Analysis 2012
ER -