Visualization of Large Multi-Dimensional Datasets

ABSTRACT

Multi-dimensional data are encountered in nearly every technical field, from stock prices and television viewership to countless analytical scientific instruments. With increasing dimensionality comes increasing size and complexity and visualization of such data becomes quite difficult. The Seeker desires a software solution to efficiently visualize and explore multi-dimensional datasets containing spatial, temporal, and other types of dimensions. Solutions for this Challenge must be able to process and visualize 5-dimensional data with tens of millions of points on a standard quad-core computer.

This is a Reduction-to-Practice Challenge (RTP) that requires written documentation, output from the visualization software, and submission of source code and/or executable for the software.

 

OVERVIEW

Multi-dimensional data is ubiquitous in many technical fields and track the variation of a dependent variable as a function of multiple independent variables. These independent variables may be spatial, temporal, or other types such as species, mass, etc. Typically, this data exhibits peaks and/or valleys that convey information via their position in space, time, or other characteristics. While visualization and characterization of data is well established in cases of one or two independent variables it becomes increasing complex and difficult as more dimensions are added. Features of interest that overlap along one dimension might be well-separated in another, but this may not be discovered without sophisticated visualization of the data. The added dimensions not only complicate how to visualize and explore the data they also make handling the data more cumbersome, quickly leading to situations that overwhelm standard software packages on typical desktop computers. The Seeker is seeking software tools for efficient visualization and exploration of these multi-dimensional datasets. The data for this Challenge consists of multiple data files of varying sizes containing 5-dimensional data. The largest data file contains more than 45 million data points.

A submission to the Challenge should include the following:

1. A detailed description of the proposed solution addressing specific Technical Requirements presented in the Detailed Description of the Challenge. This should also include a thorough description of the software accompanied by a well-articulated rationale for the methods employed.
2. Sample visualization output. Demonstrate the output with a video of the data visualization showing regions of interest for the largest data set. Include a description of the hardware and software system used to run the demonstration.
3. Region of Interest exported data. Demonstrate the ability to extract the region of interest to the same data format as above to be included in the entry.
4. Solution usage guidelines. Explain how the software is generally used – we are not looking for a user guide.
5. Source code and/or an executable of the solution software with sufficient documentation to enable the Seeker to compile, execute, and validate the software using additional validation data sets.

The Challenge award is contingent upon theoretical and practical evaluation of the software by the Seeker based on its visualization output and performance.

To receive an award, the Solvers will not have to transfer their exclusive IP rights to the Seeker. Instead, Solvers will grant to the Seeker a non-exclusive license to practice their solutions. 

Submissions to this Challenge must be received by 11:59 PM (US Eastern Time) on 26-Jul-2022.
Late submissions will not be considered.

 

What is InnoCentive?

InnoCentive is the global innovation marketplace where creative minds solve some of the world's most important problems for cash awards up to $1 million. Commercial, governmental and humanitarian organizations engage with InnoCentive to solve problems that can impact humankind in areas ranging from the environment to medical advancements.

What is an RTP Challenge?

An InnoCentive RTP (Reduction to Practice) Challenge is a prototype that proves an idea, and is similar to an InnoCentive Theoretical Challenge in its high level of detail. However, an RTP requires the Solver to submit a validated solution, either in the form of original data or a physical sample. Also, the Seeker is allowed to test the proposed solution. For details about treatment of Intellectual Property (IP) rights, please see the Challenge Specific Agreement.