Useful Data Points

I've been thinking about the recently published information about salaries of PPS employees, and about why it struck me as pretty worthless from all perspectives: data journalism, informing the public, exposing something that was kept in the dark, helping forward the public good, etc.

So, in the interest of turning lemons into lemonade, here are some ways that dataset could be contextualized and extended to allow us to see something useful, instead of just putting a spreadsheet online.

The datasets outlined below would provide some different methods to provide detail around the salary data. The display of these datasets should be supported by faceted browsing and map-based visualizations.

Pay Scale and Job Description

This would have provided a reference point about the stated expectations of each role. Without this basic information, it's hard to say if someone is overpaid or not.

This would also separate union from non-union positions, and show how experience and education is (or isn't) valued.

More info available here: http://www.pps.k12.or.us/departments/hr/2763.htm

The choice not to include, or at least link to, this information decreases the value of the data.

School Data

For Oregon, you can grab some useful datasets from http://www.ode.state.or.us/data/reports/toc.aspx

National datasets are available from NCES: http://nces.ed.gov/datatools/index.asp?DataToolSectionID=4

School data, especially overall student population and % of students on the free and reduced lunch plan, should appear alongside teacher data. This would allow people to see number of students per school balanced against number of teachers/teacher salaries. It would also be good to see how some admin and support positions (assistant principals, counselors, etc) are spread across school populations.

Neighborhood Demographic Data

A good portion of this data is available from national census data. Other data points, like crime stats, liquor licenses, and lottery information, should be available from the state or local government. Portland has done some work around open civic data that could be useful here.

• Percentage of renters to owners in the neighborhood
• Crime stats from the neighborhood
• Median income in the neighborhood
• Liquor licenses, by type (restaurant, bar, sales)
• Permits for lottery machines/gambling

Good Data Supports Good Questions

These data points would allow us to ask some more interesting questions.

• How do teacher salaries compare in neighborhood schools where the majority of people rent versus the majority of people own?
• Is there equivalency in salaries across school populations? How does this break down when comparing schools with a higher percentage of students on free and reduced lunch programs?
• Are there any discernible patterns between salary levels and neighborhood demographics?
• Are there any discernible patterns with depth of staffing/support and neighborhood demographics?

Conclusions

The people at Oregon Capitol News just made a spreadsheet searchable. It's a small step up from Excel, but not by much. If we want work with data to actually mean something, we need to have higher standards. Part of having higher standards involves providing additional information, data points, and tools to help interpret the data we are discussing. Mapping and visualization tools seem like pretty obvious additions.

And, we also have an obligation to advocate for the use of data in support of public good. As a point of common human decency, the names of people working in the schools should be anonymized. It's intrusive and unnecessary to publish the salary information of people working within schools. Salary data is one thing, but the argument that publishing personal financial information about people working with kids provides a public good is tenuous at best.

Image Credit: "Life gave us lemons" taken by Steve Mohundro, published under an Attribution-NonCommercial-ShareAlike license.