We tend to talk about transportation as if the ultimate goal were mere movement, measured in speed, time and capacity. We build roads to carry as many cars as quickly as possible (safely, that is). We measure a highway's rush-hour performance in miles per hour. We assess public transit by how many passengers ride a subway system, or how quickly buses travel through town.

The ultimate goal of transportation, though, isn't really to move us. It's to connect us -- to jobs, to schools, to the supermarket. And recognizing this means viewing transportation in a slightly different way. It means looking at New York City, for instance, like this:

That map, from an  interactive tool recently released by the metro New York urban research and advocacy group the Regional Plan Association, shows how many finance-industry jobs are available within half an hour on public transit to someone living at the corner of East 34th Street and Fifth Avenue in Manhattan.

Now let's say that same person works in manufacturing:

Or that the person has 45 minutes to commute instead of an hour, and that he or she travels by car:

All of these maps portray transportation within the New York region through the lens of job access. And they answer an enormously complex question, depending on your mode of transportation, where you live, and how much time you have: How many jobs can you get to? Or rather: how good is your job access using the transportation available to you?

This tool, created in partnership with the software development firm Conveyal, is one of a new suite of transportation-mapping projects that are using open data to redefine how we think about transportation and how cities could plan for roads, bus routes and even bike lanes going forward.

"I think people understand more now that it’s less about how fast our subway moves, how fast our car moves, and more about 'what are the opportunities within a reasonable commuting distance?" says Juliette Michaelson, the vice president for strategy at the Regional Plan Association.

These latest maps were built with Census data on job statistics by industry and location, local traffic modeling data, public transit feeds and open-source mapping information from OpenStreetMap that enables route planning by foot, by bike, by car or by transit. Add all of that together, and it's possible to pinpoint any spot in the city -- theoretically in any city with available data -- and measure its accessibility to jobs or good public schools or hospitals.

It's possible then to answer questions about the future: Where should a city build new housing? Which communities would be harmed by service cuts to public transit? How would the above maps change if, say, you closed the George Washington Bridge from New Jersey into Manhattan, strangling not just commutes but job access?

"What would happen if you dedicated one lane of every major highway in New Jersey to express buses?" Michaelson asks. "What would happen if you built bike superhighways like the Danes are building? How much farther could you get in the suburban landscape on a bike?"

The RPA is planning to roll out another Census map layer that would look not just at the location of jobs, but the location of labor. Where do tech workers live? If you were opening a new software firm, what neighborhood would be within a quick commute of as many potential employees as possible?

Tools that can answer all of these questions could revolutionize both how planners and engineers design the future of infrastructure, and how they sell those abstract plans to the public. They could also fundamentally alter how we think of the function of transportation in any city (and why we should invest in it).

"Many of us have been trying to shift the focus of how we measure things in urban transportation towards accessibility," says Shomik Mehndiratta, a lead transport specialist at the World Bank. "This really gives you much better handle of how the city as a system is doing, in terms of serving its citizens."

The World Bank is working on similar open-data mapping projects in Buenos Aires and Mexico City, developing underlying, unser-friendly tools that could be replicated elsewhere.

"The promise of open data is not the use, but the reuse," Mehndiratta says., "If you’re only using data for one thing, it doesn’t matter if it’s open or not. What really makes open data valuable is the serendipity of second, unexpected uses."

Release transit schedules or traffic data, and suddenly something like this is possible, to say nothing of the third- and fourth-order uses: