Apparatus and method for identifying and abstracting a visualization point from an arbitrary two-dimensional dataset

Abstract

A system and method for determining a set of visualization points from any given two-dimensional dataset to best describe a given visual analytic. A first user selection is received in a data processing apparatus for a chart. A chart type associated with the first user selection is identified for the chart. One or more visualization strategies are accessed from a strategy pool database based on the chart type. A second user selection is received in the data processing apparatus for a two-dimensional dataset from a data provider in communication with the data processing apparatus. The two-dimensional dataset is analyzed to determine a best strategy from the one or more visualization strategies accessed from the strategy pool database. Metadata representing the two-dimensional dataset is generated based on the best strategy, and a display representing the metadata is generated to visualize the two-dimensional dataset according to the best strategy.

Description

technical field [0001] The present disclosure relates generally to computer system visualization tools, and more particularly, to devices and methods for identifying and abstracting visualization points (which optimally describe a given visual resolution) from an arbitrary two-dimensional dataset into unified metadata for further use. method. Background technique [0002] Algorithms exist today that allow data consumers to take a dataset as input and then determine the optimal visual resolution to describe that dataset. A visual resolution may be any visual component for display in a graphical user interface, for example, a line graph. Where both the data set and the visual resolution are defined, one approach is to determine the visualization points from the given data set that best describe the given visual resolution. The term "visualization point" refers to data that will be displayed in Visual Interpretation, including data points, class labels, series names, etc. Ho...

AI Technical Summary

Problems solved by technology

[0006] There are at least two problems with this general approach: 1) Complexity - the data provider can only format the dataset in the most general way, so neither the data provider nor the data consumer can handle complex scenarios, at least in Can't without human interaction; and 2) flexibility - data provider and data consumer (e.g. charting engine in this case) are closely linked, so often a data provider can only provide data for one specific data consumer set for use

If other data consumers want to use the same data, there will be compatibility issues

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