I found this article (http://www.fipp.com/Research.aspx?PageIndex=2527&ItemId=15992) very inspiring and therefore I share it with you, the readers of the Lost Resort Blog. I hope you will find the time, strength or team to create similar applications as the one described here, be they for developing your own skills in that field or for the benefit of the community to which you belong or address.
The idea presented in the article and in this post is to create data-based apps that enable users to extract the relevant information for them by using easy-to-use interactive features, and also to share via social network services like Facebook or Twitter the stories that they find through the online data exploration.
In the Ed-data app developed by ProPublica (http://projects.propublica.org/schools/), the analysis allows generating stories about the educational opportunities provided by high schools in the U.S. The educational opportunities are classified into five groups: Advanced Placement course, gifted-and-talented programs, and advanced math, chemistry and physics classes. The data comprises 85,000 schools representing 75% of all public high schoolers in the U.S. The user can get reports for specific schools, districts or states in a visual & interactive presentation of facts such as how many students are enrolled, the percentage of inexperienced teachers (i.e., two-year experience or less), the percentage or students that receive free or reduced-price school lunch (as an indicator of poverty), and the percentage of students attending AP and advanced math courses. Moreover, the user can compare these facts across neighboring schools, or compare to lower and higher poverty-ranked schools, or to specific schools.
In addition to providing easy access to meaningful content, the app also facilitates sharing this content via Facebook. The developers say about the interface of the app that “we were focusing a lot more on what behaviors we wanted to encourage” and that sharing was one of these behaviors. This social aspect of the app was not however designed for its own sake, but to create an impact on both “a personal and a policy level”. Because data analysis is a time-consuming process (that starts with acquiring the data, cleaning it, and then making sense of it), it is important that the obtained information reaches those people that need that information and insight.
Thus, I think this app is a good model to follow for packaging and sharing information that is generated from large amounts of data, and which can be viewed from different perspectives and at different levels of detail based on the user interest.