Open Source
Keshif Keşif (Turkish): Discovery & exploration. Made with
Data Made Explorable
The fastest way from data to insights - enabled by effective visual interactive dialogue with data.
Explore sample datasets with Keshif | Learn with 5-minute tutorial | Explore your data | Get the code
Explore and discover rich trends and relations. It is as simple as: mouse-over to highlight , click to filter , lock to compare . Change measures by count, sum, average. See overview and most relevant first, then get details.
Focus on your intuitive dialogue with data, not on which chart type / color to use, how to calculate, etc.
Charts that are easy to read.
Effective bar-charts, histograms, line charts, maps, matrices, and networks. Designed to match data & you.
Interaction that is easy to learn. Minimal features are designed to work together to create a more powerful tool for data exploration.
Browsers that are easy to create. Import data. Author browser by drag-and-drop. Customize attributes. Save as Gist. Share the URL. Done!
Consistent, unified, fully synchronized, and scalable design.
Keshif just works for many tabular (spreadsheet) datasets.
Learn once, use many times to explore your data rapidly.
Built for the open web.
Customize with HTML, JS, and CSS. Based on simple JS config API.

Publications

AggreSet: Rich and Scalable Set Exploration using Visualizations of Element Aggregations. M. Adil Yalçın & Niklas Elmqvist & Ben Bederson. IEEE Transactions on Visualization and Computer Graphics (INFOVIS 2015)

Media Coverage

Mentions

Team

M. Adil Yalçın
Designer & Developer
Ph.D. Candidate, Human Computer Interaction Lab, Computer Science, UMD - College Park
Niklas Elmqvist
Advisor
Associate Professor, iSchool, University of Maryland, College Park
Ben Bederson
Advisor
Professor, Computer Science, University of Maryland, College Park

Contact

Join the maillist to share your question or use cases of Keshif.
Post to Github Issues to share your bug reports or specific feature requests.
For other inquiries, contact

License

Released under BSD license 2016 University of Maryland

Notes

Partially supported by the National Socio-Environmental Synthesis Center (SESYNC) through a grant from NSF to UMD #DBI-1052875 (2015-2016) - Partially supported by Huawei (2013-2014)