Abstract
In this paper the results of studies aimed to determinate communication peculiarity between researcher and undefined data visual model are presented. The quantitative features system of visual models and the mode of its measuring are proposed. Derived results allow to forecast cognitive importance for worked up solution visualization tasks. In this item authors describe experimental research technique representing the sequence of three types measuring data model characteristics. It is confirmed high dependence of some interpretability characteristic on researchers personal features. There are assigned visual models attributes allowing to compare representing data modes and to optimize its analysis tools. Conducted researches show appropriateness of transition to use of visualized data successive analysis, based on human perception features and his new data interpretation.
| Original language | English |
|---|---|
| Pages (from-to) | 95-107 |
| Number of pages | 13 |
| Journal | Scientific Visualization |
| Volume | 8 |
| Issue number | 1 |
| Publication status | Published - 1 Jan 2016 |
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Keywords
- Cognitive systems
- Data mining
- Data visualization
- Information
- Visualization metaphor
ASJC Scopus subject areas
- Software
- Computer Vision and Pattern Recognition
Cite this
Measurable features of visualization task. / Zakharova, A. A.; Shklyar, A. V.; Rizen, Y. S.
In: Scientific Visualization, Vol. 8, No. 1, 01.01.2016, p. 95-107.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Measurable features of visualization task
AU - Zakharova, A. A.
AU - Shklyar, A. V.
AU - Rizen, Y. S.
PY - 2016/1/1
Y1 - 2016/1/1
N2 - In this paper the results of studies aimed to determinate communication peculiarity between researcher and undefined data visual model are presented. The quantitative features system of visual models and the mode of its measuring are proposed. Derived results allow to forecast cognitive importance for worked up solution visualization tasks. In this item authors describe experimental research technique representing the sequence of three types measuring data model characteristics. It is confirmed high dependence of some interpretability characteristic on researchers personal features. There are assigned visual models attributes allowing to compare representing data modes and to optimize its analysis tools. Conducted researches show appropriateness of transition to use of visualized data successive analysis, based on human perception features and his new data interpretation.
AB - In this paper the results of studies aimed to determinate communication peculiarity between researcher and undefined data visual model are presented. The quantitative features system of visual models and the mode of its measuring are proposed. Derived results allow to forecast cognitive importance for worked up solution visualization tasks. In this item authors describe experimental research technique representing the sequence of three types measuring data model characteristics. It is confirmed high dependence of some interpretability characteristic on researchers personal features. There are assigned visual models attributes allowing to compare representing data modes and to optimize its analysis tools. Conducted researches show appropriateness of transition to use of visualized data successive analysis, based on human perception features and his new data interpretation.
KW - Cognitive systems
KW - Data mining
KW - Data visualization
KW - Information
KW - Visualization metaphor
UR - http://www.scopus.com/inward/record.url?scp=84963628554&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84963628554&partnerID=8YFLogxK
M3 - Article
VL - 8
SP - 95
EP - 107
JO - Scientific Visualization
JF - Scientific Visualization
SN - 2079-3537
IS - 1
ER -