The U.S. Congress produces thousands of bills every year -- so it’s difficult to figure out which are significant, and which aren’t so much. Some data is available on official government websites, but usually without real-world context for determining which bills affect the things you care about. Non-profit organizations and issue-based groups could use more helpful ways to follow their interests in Congress.

OpenCongress.org is a free and open-source public resource that combines official government data with news and blog coverage about Congress. Recently, we launched a set of new features for tracking and sharing the best info about bills, issues, and Members. But this is just the start of how social data on “My OpenCongress” can bring you closer to what’s really happening in Congress.

New data mashups on “My OpenCongress” will allow users to customize the stream of info they receive about their tracked items. In other words, it can be a lot easier to separate the signal from the noise on Capitol Hill-- to figure out what bills and votes are important or meaningful to you. Users will have access to a wider variety of content, more streams of helpfully-curated data about their interests, and more social wisdom from around the web.

Here’s an example of how these mashups would work: a user reads about a bill of interest, and adds it to her “My OpenCongress” profile as a tracked item. On her page of Tracked Bills (view sample), she would then be able to choose from a few simple options for how much info to display for that bill: every news article and blog post that mentions it, or just those rated highly from different data sources, or blends of the various options.

Adding this social data would enhance the value of peer-to-peer communication throughout the site and make "My OpenCongress" a more useful public resource (register or login). These mashups can serve as tools for greater government transparency, combating the influence of corruption, and opening up our democratic process.

Writers have always written, not knowing about who or where their readers are. This mashup will show where the readers are coming from, who read a writer's article, or where the readers come from, who care about the same topics as any tag in the system.

We will use zip codes, which we have on record, for our members, or IP address, for non-registered visitors, to map where readers of a specific article come from. Since articles are also tagged, we can pull tag contact data for people as well, and map tags based on who's visited from where-- for any article.

When writers know more about where their readers come from, that could/will change the way they think about their readers and could change how they write.

This could have a powerful effect upon editorial decisions too. Since thousands of tags will be easily checked for how they "map", it will be possible to asses reach of the site and editorial policy in new ways.

Writing, news, Op-eds, the media-- they are essential elements of democracy. Understanding which aspects of the writing are reaching WHERE, for each article, or groups of articles, or by the author-- all of these should be easily pulled together using the system we've already built for managing content. Even on more local levels, if we can tap the power of google analytics to pull IP info and map it to local, county or state levels, this could be powerful, since we also tag our content by locale. For example, if a writer writing on water pollution discovers that the lower part of a county is seeing the articles, but not the upper level, and a river runs through the county, that could easily help the writer identify where further outreach is needed.