Protect your 'Smart' Data by Learning the "Language of the City"

Today’s post is the second in our “SmartSpeak” series, which provides a forum for SmartCities thought leaders to provide guest posts.  The “Austin Series”, a bimonthly feature, is graciously authored by thought leaders within our very own city government.  Today’s post is authored by Ted Lehr, City Data Architect.  It’s a detail-oriented post for those interested in supporting, or engaging in, City projects that leverage new data streams and archives, while shedding light on the mindset that it will take to develop the public-private partnerships necessary to achieve a “Smart City” vision.

 

SmartSpeak: The Austin Series

Protect your 'Smart' Data by Learning the "Language of the City"

How's this for a nightmare?  You've just spent the last year helping your community and city imagine, design, plan and commence implementation of a great smart city project only to learn that no one budgeted for archiving all that data the project is generating:  "We thought this was for operations?" you are told.  Then,word comes that, "We can only keep six month revolving windows of data, " and that the City will delete data once it ages beyond the window.

That primal scream you're roaring at these irregular and inopportune moments is wholly avoidable.  With foresight, you can institute new approaches to data that support the development of profound and corroborating insights,  behavioral models that lead to improved operations processes, and curated data that can support policy discussions.  But first you need to learn the Secret Language of the City.

Let’s break it down: There are four basic steps to ensuring that a city will maintain the right kind of data archives, and develop the right kind of analysis, to support a “Smart City” vision.  And the core principle that supports all of these steps is understanding a few words of “Cityspeak.”  That is, you need to understand how Cities define and use concepts like “assets”, “valuations”, “costs” and “projects”.   If you don't take the time to express the thing you care about in these terms, you will vastly increase the probability  that the organism we call a "City" will not even detect its existence.

And here are the steps:

  1. Make data an asset

  2. Assign a cost to the asset

  3. Designate, and plan to measure, the value returned for paying that cost

  4. Attach the asset, its cost, and, the appropriate metrics to an existing project

Now, let's consider each of these in order.

Data as an Asset

You can begin to make data exist in the eyes of the City by identifying the physical assets that generate, carry, use or store it. “Assets” as known by cities, and certainly for the City of Austin, are tangible things: signs, roads, computers, swing sets are all assets. But, data? You can't touch data! As a result, it will be difficult to assign it an asset code. The devices that generate or store the data, however, can be treated as assets. So sensors, networks and storage are assets. Even non-touchable cloud storage can be an asset because it has what are known as “physical equivalents”.

Assigning Costs to the Data Assets

The second step is to assign costs to data assets. This step is more straightforward. Costs can be expressed in terms like:  

  • dollars per Gigabyte of storage  

  • dollars per Gigabit per second of network demand

  • dollars per unit of data processing capacity

These costs can be tiered in such a way that helps us budget and evaluate projects more efficiently. For example, raw data from sensors on a city's streets might have one cost. Data combined and curated to produce neighborhood or corridor specific data might have another, larger cost.

Designating the Value Returned from the Data

We next need to answer the questions of, “Why is the city going to spend public dollars on these data assets?” and “What value will the community derive?”  Importantly, the valuation of the return on a city asset does not have to be expressed in financial terms.  For example “values” might include:

  • Reducing pedestrian injuries at intersections

  • Increasing or maintaining neighborhood satisfaction with their local parks

  • Being able to measure, understand, describe and eventually control greenhouse gas emissions

  • Understanding whether City parks and services are used equitably

It is best to describe such values in the context of stated city objectives.  These might be objectives like “reducing traffic fatalities,” “increasing access to affordable health care,” “developing walkable communities,” etc.

Now that you have defined the “value” of your data, make sure that, these valuations are measurable. You will need to define value metrics the City can monitor as well as associated target values, so that the city can assess the return it is getting. For example baselining and tracking pedestrian traffic injuries at a set of intersections with a goal of reducing them by 30% would constitute a value metric and goal.

Attaching the Data Assets to Projects

Congratulations!  Your City can now ‘see’ your assets. But it can’t pay for it yet!  The last thing you need to do is to attach your data assets to an existing, or planned and budgeted, project. Then, your data can live, and you can pursue your most imaginative data science dreams!  

Conclusion:  Don't forget to consider the Data Market

You’ve completed my course today. But there’s a bonus opportunity, for the ambitious: you might ponder developing a cost recovery plan for the data assets. Instead of drawing on traditional revenue like the tax base, perhaps there are fees or other charges you can suggest the City impose on the external use of the data. For example, raw data could be free to the community, while curated or analyzed data could incur a charge. Or, if a business would like to make the data mission critical and therefore requires SLAs on throughput and response time, you could propose a tiered pricing mechanism for these additional premium services.

These are just a few ideas that can help to make the foundational element of the Smart City of the future, data, better available, better curated, and better analyzed. We will need the creativity of thousands of entrepreneurs and officials to effectively leverage data and technology to serve urban residents. But, we cannot get there if we don’t attend to the sometimes boring work of learning to speak the City’s language.