Why We Should Treat Public Data Like Water

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Curated from civichall.org →

The revolutionary potential of the internet means that we can do more than simply build a more beautiful user interface for antiquated government operations.

“Citizens of the 21st century need public technologists like citizens of the 19th century needed municipal engineers to build the drains and clean water supplies.”

For three years, Advanced Research in Government Operations Labs (ARGO Labs) has envisioned, planned, and deployed public data infrastructure for integrated urban water use data across California. After Governor Brown’s historicexecutive order in May 2016to “make water conservation a way of life,” our team calculated how much water Californian retail water utilities should reasonably expect their residential customers to need, and created a data visualization based on that data to analyze user selected scenarios. Our work leveraged freely available imagery and academic research partnerships to deliver those statewide estimates of reasonable water use for just 5 percent of the $3 million the state originally budgeted for the project.

This increased focus on efficiency highlights the transformational changes underway in the California water industry. Water utilities were originally created to supply and sell clean water. Today, fresh from California’s worst drought in 600 years and faced with future water supply uncertainty, we need to modernize that business model to maximize the benefit of an increasingly scarce resource. Yet most industries are not in the business of getting customers to buy less of their product. So with local utility partners, we have developed and deployed open source analytics to power an integratedvisionfor the future of water resource planning, rate setting, and water efficiency program development so that utilities can both incentivize more efficient water use and pay for fixed infrastructure costs.

Since embarking on this work, I have begun to wonder: Why not manage public data like water — a public resource required for all life? We too quickly forget that “legacy” institutions like public water utilities were radical innovations for their time. For most of the 19th century, clean water was a luxury. The concept of a public utility enabled (near) ubiquitous access to clean drinking water and the creation of infrastructure that safeguarded water supplies for future generations. California’s water industry in particular has a long history of pioneering everything from man-made aqueducts that can be seen from space to advanced recycled water technologies. Perhaps most importantly, public water utilities provide the institutional structure to ensure that a vital public resource is stewarded for the benefit of everyone.

So as we look to answer the call in Tom Steinberg’s manifesto, what might the public technology movement learn from the public utility model of the California water industry? First off, public data should be managed professionally, and local governments should prioritize funding public technologists who can build the digital equivalent of the physical drains and pipes we take for granted. The California State Water Project—a transformational aqueduct supplying water to twenty five million people—wasn’t built on nights and weekends. Digital infrastructure shouldn’t be either. Building modern public data infrastructure requires seed capital to catalyze change and reallocate existing funds.

For example, this summer ARGO’s data team conducted an IT audit of 235 systems from 14 water utilities. A single Oracle data system from one of those utilities costs more than 200x the amount invested in ARGO’s water data work. Rather than powering modern open source analytics, that system requires utility staff to work with multiple consultant-created query tools to actually access their own data.

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Yves Mulkers

Yves Mulkers is the founder of 7wData and a widely followed voice in the data and AI community. He curates the 7wData and AI Beat newsletters, reaching hundreds of thousands of data and AI professionals, and writes on data strategy, analytics, AI, and the evolving data ecosystem.