The Promise of Data.gov

Data.gov WebsiteLast month I had the incredible opportunity to participate in several Gov 2.0 events. One of the greatest take aways for me was finding all the people who are either working directly on the Data.gov project or involved in related initiatives. Data is a big deal for local government – particularly for those of us working in engineering and public works. We spend significant amounts of our time developing, finding, analyzing, juggling, and publishing data. We do just about everything to it but eat it!

And while I had been aware of the Data.gov site, it wasn't until I met and talked to all these people that I realized its significance and promise. Today, the front face of the site is a publication platform, but someday it could be leveraged on the back end as a collaborative platform for sharing ideas about data development, priorities, standards, education, and guidance.

Crowdsourcing Data Models

A group of us working for local governments in our region have started trying to crowdsource and standardize our datasets so we all follow one model. But we realize it would be so much better if this could be done on a national scale. We know that ESRI has offered some guidance in this area, but as government agencies, it makes more sense for this direction to come from the federal government. We need to start realizing that data is a national asset. Data not only supports security efforts but it offers tremendous opportunity for economic development. The use of Data is already starting to build a new industry; leveraged, protected, and standardized it will move this growth along and sustain it.

We could use space on the Data.gov site to crowdsource a national data model for all datasets we use. The majority of these datasets are going to be similar for all local governments. Why not get this worked out now? I realize a lot of cities already have their GIS and other data systems established – they do not have to change to a national model if it does not make sense for them at this time. But many local governments still do not have a GIS or other data system in place. Having a data model will at least encourage them to implement a system faster and more efficiently while allowing for standardization.

Prioritizing Data

GIS was recently moved back over to engineering where I work. One of my first challenges in taking on this responsibility was prioritizing development of data. While I had no problem making decisions about developing what I call "foundation data" such as centerlines, I did not want to be the one to determine what datasets were most important to our city  – this needed to be an agency decision. So I set up an Ideascale based site and invited our staff to submit and vote on ideas for our GIS. (I also tried using Bubbleideas but just could not get the invite function to work.)

This idea of prioritizing data development could be expanded to a national scale. If certain data sets are necessary for national security or encouraging economic development, we should work on developing them over sets that are interesting but not necessary. But only by asking people and crowdsourcing that information can we learn what matters most.

Education

There is a lot of discussion online about how important it is to not just publish data but help others use and understand it. This educational component could be added to the Data.gov site allowing others to learn how to develop, use, and publish data. The material can be broken down for citizens, developers, government agencies, students, and businesses.

Delivering the Promise

Over the next few months I hope to continue to be part of the data-related discussions at my local level and at the federal level. Hopefully Data.gov moves to build a collaborative platform so others who are dedicated and passionate about data can join in and work together to create and deliver a national infrastructure of data. And in the meantime, I want to also give a shout out to just of the few awesome data folks I met:

Jeanne Holm (data.gov evangelist), Ethan McMahon, Karen See, Kelly Fahey

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