# DVP: Data Visualization Platform

## TL;DR

DVP is a data visualization platform that seamlessly integrates visualization tools with scientific computing environments, enabling interactive data analysis and modeling within a unified interface.

## Contribution

This paper introduces DVP, a novel platform that bridges the gap between visualization tools and scientific computing environments for enhanced data analysis.

## Key findings

- DVP enables seamless interaction between visualization and computation.
- The platform supports both desktop and online interfaces.
- A demo of DVP is available online.

## Abstract

We identify two major steps in data analysis, data exploration for understanding and observing patterns/relationships in data; and construction, design and assessment of various models to formalize these relationships. For each step, there exists a large set of tools and software. For the first step, many visualization tools exist, such as, GGobi, Parallax, and Crystal Vision, and most recently tableau and plottly. For the second step, many Scientific Computing Environments (SCEs) exist, such as, Matlab, Mathematica, R and Python. However, there does not exist a tool which allows for seamless two-way interaction between visualization tools and SCEs. We have designed and implemented a data visualization platform (DVP) with an architecture and design that attempts to bridge this gap. DVP connects seamlessly to SCEs to bring the computational capabilities to the visualization methods in a single coherent platform. DVP is designed with two interfaces, the desktop stand alone version and the online interface. To illustrate the power of DVP design, a free demo for the online interface of DVP is available \citep{DVP} and very low-level design details are explained in this article. Since DVP was launched, circa 2012, the present manuscript was not published since today for commercialization and patent considerations.