Quick look at Managing News

Managing News is a “robust news and data aggregation engine with pluggable visualization and workflow tools.” Mo Jangda set up an instance on his server that I finally had the chance to check out. My initial impression was that, like the website, the development team put a tremendous amount of effort into polishing the user interface. It’s a super shiny way to aggregate RSS feeds.

There are nuggets I was able to suss out, however. If you’ve indexed your feeds, there are search capabilities that will also give you the frequency of any given term. The mapping functionality is also very slick. You can get all of the recent stories on a map, or stories limited to a specific term. It’s misleading to have the initial view of the map be the entire world, though, because the most useful view to an end user will be whatever region they’re interested in.

This brings me to my biggest observation: a tool like this would be most useful for managing feeds of raw data, not feeds of news articles. News articles are products where the data has already been through the rock tumbler. Where Managing News wants to be headed, I think, is towards building a tool that allows you to map and visualize all manners of data.

The difficulty then is both building the visualization tools and finding, or even brainstorming, properly geo-coded RSS feeds of the data you’re interested in.

2 responses

  1. Hey Daniel – This seems to be the exact type of work their are doing. Check out: http://afghanistanelectiondata.org

    1. Thanks for the example, Kevin. Two relevant observations: it looks like there’s been customization to the out of the box implementation, and that the visualization is based off a mostly static data set. I think what I’m really interested in is visualization of real-time data streams and the tools to better manage that stream.

      From what I know, I think Swift River is working towards this. What it would mean for an event like elections in Afghanistan, I suppose, is that you could mash together geo-coded data like Twitter updates and photos posted to Flickr to identify the fraud before it becomes too big of an issue. Obviously you probably won’t be getting enough of this data out of rural Afghanistan for it to be useful but I think that’s the potential of the tool.

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