T.Rex Visual Analytics for Transactional Exploration
Abstract
T.Rex is PNNL's visual analytics tool that specializes in tabular structured data, like you might open with Excel. It's a client-server application, allowing the server to do a lot of the heavy lifting and the client to open spreadsheets with millions of rows. With datasets of that size, especially if you're unfamiliar with the contents, it's very hard to get a good grasp of what's in it using traditional tools. With T.Rex, the multiple views allow you to see categorical, temporal, numerical, relational, and summary data. The interactivity lets you look across your data and see how things relate to each other.
- Publication Date:
- Research Org.:
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1136971
- Resource Type:
- Multimedia
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 97 MATHEMATICS AND COMPUTING; VISUAL ANALYTICS; EXCEL; CSV; VISUALIZATION; T.REX SOFTWARE; SOFTWARE; COMPUTING; PROGRAM; DATA MANAGEMENT
Citation Formats
. T.Rex Visual Analytics for Transactional Exploration. United States: N. p., 2014.
Web.
. T.Rex Visual Analytics for Transactional Exploration. United States.
. Tue .
"T.Rex Visual Analytics for Transactional Exploration". United States. https://www.osti.gov/servlets/purl/1136971.
@article{osti_1136971,
title = {T.Rex Visual Analytics for Transactional Exploration},
author = {},
abstractNote = {T.Rex is PNNL's visual analytics tool that specializes in tabular structured data, like you might open with Excel. It's a client-server application, allowing the server to do a lot of the heavy lifting and the client to open spreadsheets with millions of rows. With datasets of that size, especially if you're unfamiliar with the contents, it's very hard to get a good grasp of what's in it using traditional tools. With T.Rex, the multiple views allow you to see categorical, temporal, numerical, relational, and summary data. The interactivity lets you look across your data and see how things relate to each other.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Jul 01 00:00:00 EDT 2014},
month = {Tue Jul 01 00:00:00 EDT 2014}
}