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Title: Exploratory Analysis of Visual Search Data.


Abstract not provided.

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Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
OSTI Identifier:
Report Number(s):
DOE Contract Number:
Resource Type:
Resource Relation:
Conference: Proposed for presentation at the Augmented Cognition / Human Computer Interaction International held August 2-7, 2015 in Los Angeles, CA.
Country of Publication:
United States

Citation Formats

Stracuzzi, David John, Speed, Ann, Silva, Austin Ray, Haass, Michael Joseph, and Trumbo, Derek. Exploratory Analysis of Visual Search Data.. United States: N. p., 2015. Web.
Stracuzzi, David John, Speed, Ann, Silva, Austin Ray, Haass, Michael Joseph, & Trumbo, Derek. Exploratory Analysis of Visual Search Data.. United States.
Stracuzzi, David John, Speed, Ann, Silva, Austin Ray, Haass, Michael Joseph, and Trumbo, Derek. 2015. "Exploratory Analysis of Visual Search Data.". United States. doi:.
title = {Exploratory Analysis of Visual Search Data.},
author = {Stracuzzi, David John and Speed, Ann and Silva, Austin Ray and Haass, Michael Joseph and Trumbo, Derek},
abstractNote = {Abstract not provided.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = 2015,
month = 2

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  • Abstract not provided.
  • Rapid increases in high performance computing are feeding the development of larger and more complex data sets in climate research, which sets the stage for so-called big data analysis challenges. However, conventional climate analysis techniques are inadequate in dealing with the complexities of today s data. In this paper, we describe and demonstrate a visual analytics system, called the Exploratory Data analysis ENvironment (EDEN), with specific application to the analysis of complex earth system simulation data sets. EDEN represents the type of interactive visual analysis tools that are necessary to transform data into insight, thereby improving critical comprehension of earthmore » system processes. In addition to providing an overview of EDEN, we describe real-world studies using both point ensembles and global Community Land Model Version 4 (CLM4) simulations.« less
  • Exploratory data analysis is an iterative process in which the results of one analysis step suggest several new ways of viewing and further analyzing the data. The analyst may follow several different paths of inquiry during the course of the analysis. Each path may involve minor to major modifications to the data have different assumptions and produce its own intermediate results and displays. Several kinds of data management capabilities are required to support this sort of use. Because analysis is iterative, the analysis and data management tools must be integrated so that analysis results are preserved for subsequent use. Datamore » of many different shapes and sizes must be stored. Efficient storage of multiple versions and subsets of data are needed to support multiple analysis paths. No single data management package provides all these capabilities, although various existing packages are identified that provide them individually. There is also a need for automatic tracking of analysis paths and steps. A new approach to data analysis management, using data analysis environments has been developed and is currently being implemented to meet these data manipulation requirements.« less
  • Sampling of toxic organic compounds in air and precipitation began at US sites in the Integrated Atmospheric Deposition Network (IADN) on the Great Lakes in late 1990, and continues to the present. A parallel program of sampling at additional sites for the Lake Michigan Mass Balance (LMMB) program began in spring, 1994, and ended in fall, 1995. The purpose of his paper is to describe initial results of exploration of the structure of the data. The authors examined gas-phase concentrations at three US IADN sites and two LMMB sites using principal components analysis. This approach provides a broad perspective onmore » similarities and differences in the data from a variety of sampling locations.« less
  • The past few years have seen a virtual revolution in computing, particularly in the area of small computers. For statistical and graphical data analysis, intense commercial competition has lead to the availability of a wide variety of general purpose statistical and graphical packages with extraordinary versatility and capabilities. This work will examine two of these currently available software systems as applied by the author to a variety of climate research tasks. This work is not an attempt to either provide an exhaustive survey or to rank available software as to best,'' or to serve as an endorsement of any particularmore » software, but rather to illustrate, through real examples, some of the power now available to the researcher through such software. For a more detailed, feature by feature intercomparison of several statistical packages, see two recent surveys: Seiter and Best and Moganstein. Attention here is focused on the Macintosh computer, primarily because of its wide availability and ease of interaction. Two packages that provide some particularly novel capabilities are illustrated: for statistics, Data Desk; and for graphics, Spyglass.« less