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Smart Visualization Palette and Markers Service

IP.com Disclosure Number: IPCOM000239544D
Publication Date: 2014-Nov-14
Document File: 3 page(s) / 52K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed is a knowledge base and learning system that ensures consistency of colors and markers throughout data visualizations in a system that uses dashboards.

This text was extracted from a PDF file.
This is the abbreviated version, containing approximately 52% of the total text.

Page 01 of 3

Smart Visualization Palette and Markers Service

Color and markers are two of the most important aspects of data visualization and usable dashboards . The tools in the market allow users to select these properties for data visualization, but also allow users to create dashboards that are inconsistent and cause confusion. The main problems in the dashboard are that users select the same color and markers for several unrelated data items, and do not consistently use the same color for an item throughout all visualizations on a dashboard or various dashboards. In addition, not all users have the skills to select colors and markers that are both aesthetically pleasing and successfully visually communicate the required information.

Some existing solutions attempt to address these problems. For instance, allowing the user to set color to data items at a single visualization level is one of the methods that some products already support. The other interesting approach is specifying the colors of objects based on images returned in search results.

No existing approach allows users to select relevant colors/markers, achieve consistency at the dashboard or even among several dashboards, at the system level without a significant amount of work.

The novel contribution is a knowledge base and learning system that ensures consistency of colors and markers throughout data visualizations in a system that uses dashboards. The system remembers the colors/markers for data items at the system level by storing the colors/markers associated to the data in a knowledge base, associating colors/markers with concepts, and learning the user preferences.

The system comprises smart metadata engine that detects data concepts and the associated colors /markers in a knowledge base. The data store associates data items with colors/markers and stores specific colors/markers that are associated to concrete data items as opposed to concepts. A learning component learns user preferences and identifies new concepts and the associations

with the colors/markers. The palette/marker recommender component...