An interactive graphical tool for exploring sequential dependencies in categorical data

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Description

As monitoring and data storage devices have become cheaper and more readily available, it has become common practice to establish automated monitoring processes which collect enormous amounts of data. For example, in a waste storage facility, waste from several different sources may be combined and stored in a single storage container. Within this unit, many different types of chemical and microbiological reactions may take place over the course of time, not all of which are completely understood. Thus, it is important to monitor the levels of several different chemical compounds within the system, in order to ensure that the waste ... continued below

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6 p.

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Fitzgerald, M. December 31, 1997.

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Description

As monitoring and data storage devices have become cheaper and more readily available, it has become common practice to establish automated monitoring processes which collect enormous amounts of data. For example, in a waste storage facility, waste from several different sources may be combined and stored in a single storage container. Within this unit, many different types of chemical and microbiological reactions may take place over the course of time, not all of which are completely understood. Thus, it is important to monitor the levels of several different chemical compounds within the system, in order to ensure that the waste is being stored safely. The monitoring devices record any anomalous behavior of the system, such as when the presence of a certain chemical compound exceeds some prescribed expectation, the pressure within the container increases beyond a tolerance threshold, the temperature drops more than .5{degree}, etc. These monitoring systems may thus collect large quantities of data in fairly short periods of time. The challenge is then to utilize these massive data sets to bring about an understanding of the process and discover potential avenues of intervention. This report describes an interactive graphical tool, written in XLISP-STAT, for exploratory data analysis of dependencies in sequences of categorical data. Both global and local views of the dependency structure can be insightful, and allowing the user the flexibility to change critical parameters and switch between views in a simple, interactive, point-and-click environment can make the task of exploring dependencies among a large number of categories feasible and lead to a better understanding of the sequential properties of the data.

Physical Description

6 p.

Notes

INIS; OSTI as DE98001453

Source

  • Interface `97, Houston, TX (United States), May 1997

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  • Other: DE98001453
  • Report No.: LA-UR--97-2219
  • Report No.: CONF-9705217--
  • Grant Number: W-7405-ENG-36
  • Office of Scientific & Technical Information Report Number: 563306
  • Archival Resource Key: ark:/67531/metadc697168

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

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Creation Date

  • December 31, 1997

Added to The UNT Digital Library

  • Aug. 14, 2015, 8:43 a.m.

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  • May 20, 2016, 3:19 p.m.

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Fitzgerald, M. An interactive graphical tool for exploring sequential dependencies in categorical data, article, December 31, 1997; New Mexico. (digital.library.unt.edu/ark:/67531/metadc697168/: accessed December 11, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.