DVP: Data Visualization Platform
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. DVP with its structure and planned features is a unique software that serves a great deal of parties, including university research, governmental decision support and country's economy modeling, traffic analysis and control, financial sector and companies, and any other party interested in data analysis and interpretation. A free demo for the online interface of DVP is available \citep{DVP}. Since DVP was launched, circa 2012, the present manuscript was not published since today for commercialization and patent considerations.