This summer I had an opportunity to lunch with Fernanda Viegas and Martin Wattenberg, a couple of the brains behind ManyEyes--the brilliant data visualization tool that remains an IBM toy. When I met them, the pair had recently started Flowing Media, a start-up focused on visualization solutions for media data. It was a short-lived venture--Google came calling and Martinanda decided to take their talents to a newly-minted Google "Big Picture" data visualization group.
Before the move, Flowing Media released an open-source desktop visualization tool for event-based data. TimeFlow was created along with Sarah Cohen, a professor and journalist, as a tool for reporters to analyze historical data.
The motivation behind TimeFlow comes from Sarah’s realization that visual analytical tools for reporters are rare. There are good visual presentation tools out there, but those that allow journalists to mull over hundreds and thousands of data points, slicing and dicing the information as they go along are harder to come by. Given this mandate, we set out to rethink timelines, striving to always show as much textual detail about the data as possible (a goal dear to reporters that, interestingly, goes against the visualization impulse to always aggregate).
Here's what I like most: Flowing Media took a common analysis problem and built a focused solution to solve that specific problem. Most analytical solutions attempt to be all things to all people--and fail in the process. With about 1,000 downloads, I doubt TimeFlow has found its way to all the people who could benefit. In my non-exhaustive tour of the tool, I found that it does a bunch of things well:
- Easy start-up. For a non-technical person, TimeFlow may seem a bit intimidating. It is hosted on Github and downloads as a .jar file. However, I had it up and running seconds on my Mac.
- Uploading data. TimeFlow makes uploading a simple, flat file easy by letting you paste into a text box or selecting an existing CSV file.
- Smart options for data views. It provides a variety of relevant ways to present this timeline based data, including a timeline visualization, calendar, list, table, and bar chart.
- Data summary. An unexpected little feature is a summary of your data file (below). This is the type of useful view that only true data-lovers would think to include.
- In-line data editing. I was pleased to see that you can edit your data as you go. If you see something in a chart that doesn't make sense, simply right-click to change any of the fields on the fly.
Now that Fernanda and Martin have moved on to Google, we'll be curious to see what project they take on. It is not hard to imagine an extension of this TimeFlow visualization tool applied to Google news search results.