A Call for an Open Spatial Data Infrastructure


Today I’m getting on my soapbox. I’ve long been a vocal advocate of open public data in the geospatial arena. The “open” provides us all the opportunity to build shared spatial data infrastructures so critical to addressing public, private, and broader societal needs. I’m concerned that even with the most open of data, we may yet be compounding essential problems regarding a critical goal of spatial data infrastructures: authoritative and consistent data. Consistency is key.

For example, in Jonathan Feldman’s recent article “How To Fix The GIS Data Mess,” he pleads for consistent data shared among all potential users. In my own experience, beyond accuracy and unfettered access to geospatial data, consistency of those data among users is critical. When agencies and organizations rely on geospatial data for critical decision making and those data differ, the decisions based on those data will necessarily be different, notwithstanding the best intentions.

Are emergency responders and non-profit agencies looking at different authoritative data sources to deploy rescue efforts to save your pets and family members? Are construction crews, development companies, city officials, and recreational groups looking at different data sources when trails are cleared for a building project? Data consistency is vital – for public safety and for the public interest. Consistent data (and implied shared maintenance) is key to helping make consistent decisions and controlling costs.

I am a big fan of efforts such as Open Street Map (OSM) in democratizing geospatial data. OSM is an effort to be applauded. Clearly, its sweeping early successes, particularly in areas of the world where geospatial data are less public than the US, demonstrates that people are ready and eager to create and support open data sources. I am myself. But I lend a word of caution as well… What do we do when other authoritative data that are open already exist? How do we determine which is THE authoritative? How do we share maintenance? These questions remain largely unanswered.

Members of the National States’ Geographic Information Council (NSGIC) are working with public and private organizations at all levels to address these very questions.

In Indiana for example, the community is working together to overcome institutional obstacles and build a statewide spatial data infrastructure that is open and consistent (see the Indiana Geographic Information Council). Local agencies are providing data publicly, such as street centerlines and parcel boundaries, and the state is integrating and publishing rather than duplicating those efforts. The State is contributing as well, not only through coordination and infrastructure but also with statewide data sets such as aerial photography that make sense to maintain at broader coverage. And the effort doesn’t stop there. With university participation, those data are made public (view and download) through the IndianaMap. They are provided to federal agencies, such as U.S. Census for map modernization. In recognition that not everyone comes to government sources for their decision-making, statewide aerial photography (2005) was shipped to Google and Microsoft to integrate into their map services.

Such a model holds out a glimmer of hope that statewide, national, and international spatial data infrastructures are not only possible but also within reach. However, even with such open data, when the process is ill-defined and under-funded we may miss the target. How, for instance, will the IndianaMap data be incorporated into other open source efforts the likes of OSM? With a desire by all parties, how might maintenance be addressed? These questions remain unanswered.

We must continue to strive for solutions which focus on process. Consistent data are vital if geospatial data are used to solve problems at the most local to the most global of scales. While “any data” may be better than no data at all, the preponderance of inconsistent data may be our industry’s Achilles heel. There are inherent problems when local data (cities and counties) differ from state data, differ from federal, private, non-profit, and open data. That is why a National Spatial Data Infrastructure is necessary.