KEYWORDS: Visualization, Data visualization, Associative arrays, Data modeling, Visual analytics, Visual process modeling, Space operations, Binary data, Information visualization, Human-machine interfaces
We describe a meta-notation devised to express the major structural characteristics in widely-used data visualizations. The
meta-notation consists of unary and binary operators that can be combined to represent a visualization. Capturing structural
features of a visualization, our meta-notation can be applied to match or compare two visualizations at a conceptual level.
For example, a user's request for a visualization can be compared with visualization tools' presentation capabilities. The
design of the operators is discussed as we present their underlying concepts and show examples of their use. To illustrate
how expressive the meta-notation is, we explore some commonly-used data visualizations. A benefit of our approach is that
the operators define a set of required capabilities on which a visualization system can be organized. Thus, the meta-notation
can be used to design a system that interconnects various data visualization tools by sending and receiving visualization
requests between them.
KEYWORDS: Visualization, Data modeling, Data visualization, Human-machine interfaces, Visual process modeling, Systems modeling, Visual analytics, 3D modeling, 3D displays, Volume visualization
We describe a novel data visualization framework named Reservoir Model Information System (REMIS) for the display of complex and multi-dimensional data sets in oil reservoirs. It is aimed at facilitating visual exploration and analysis of data sets as well as user collaboration in an easier way. Our framework consists of two main modules: the data access point module and the data visualization module. For the data access point module, the Phrase-Driven Grammar System (PDGS) is adopted for helping users facilitate the visualization of data. It integrates data source applications and
external visualization tools and allows users to formulate data query and visualization descriptions by selecting graphical icons in a menu or on a map with step-by-step visual guidance. For the data visualization module, we implemented our first prototype of an interactive volume viewer named REMVR to classify and to visualize geo-spatial specific data sets. By combining PDGS and REMVR, REMIS assists users better in describing visualizations and exploring data so that they can easily find desired data and explore interesting or meaningful relationships including trends and exceptions in
oil reservoir model data.
KEYWORDS: Visualization, Human-machine interfaces, Data modeling, Data visualization, Databases, Associative arrays, Computing systems, Visual analytics, Data analysis, Visual process modeling
A Phrase-Driven Grammar System (PDGS) is a novel GUI for facilitating the visualization of data. The PDGS integrates
data source applications and external visualization tools into its framework and functions as a middle-layer application to
coordinate their operations. It allows users to formulate data query and visualization descriptions by selecting graphical
icons in a menu or on a map. To specify data query and visualization intuitively and efficiently, we designed Graphical
User Interface and a natural-language-like grammar, Phrase-Driven Grammar (PDG). The formulation of PDG data
query and visualization descriptions is a constrained natural-language phrase building process. PDG phrases produce
graphical visualizations of the data query, allowing users to interactively explore meaningful data relationships, trends,
and exceptions.
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