SandDance is a web-based application that enables you to more easily explore, identify, and communicate insights about data. SandDance provides ease of use for data visualizations, pattern identification, trends, and insights. It provides better decision-making capabilities through its dynamic and customizable interface, allowing views of both aggregate and individual data. The app also supports and encourages collaboration, allowing multiple people to work with the same dataset. Furthermore, SandDance showcases Microsoft Research data visualization innovations and novel natural user interaction techniques.
You can use your own datasets to create visualization and explore your data on a conventional desktop or on a touchscreen interface. SandDance offers better decision-making capabilities through its dynamic and customizable interface, providing views of both aggregate and individual data.
Released as Open Source
SandDance has been re-released built completely from scratch as an Open Source project available here: SandDance Github.
About the research behind SandDance
SandDance is a research project from the Visualization and Interactive Data Analysis Team (VIDA) in Microsoft Research, spearheaded by Steven M. Drucker , Dan Marshall, and Roland Fernandez. It experiments with a new genre of visualizations, where every data element is always represented on the screen, to help people explore, understand, and communicate insights in their data.
Many people have helped SandDance get where it is today in addition to Steven Drucker and Roland, including: Alicia Edelman Pelton, Richard Hughes, Tony Carbary, Irina Spiridonova, Lynn Powers, Robin Moeur, Danyel Fisher, Curtis Wong, Dave Brown, Mike Pell and the Garage Team, Christian Marc Schmidt and his folks at Schema Design, and Mary Czerwinski.
Microsoft Research is committed to driving innovations in computer science and helping Microsoft reinvent productivity. SandDance experiments with a new genre of visualizations, where every data element is always represented on the screen, to help people explore, understand, and communicate insights in their data.
The new release, was written by Dan Marshall, and is based on two, well known, open source projects, VEGA, from the UW IDL and DeckGL from Uber.