All posts in Trawling - a blog by Big Lake Data tagged with maps

Because how many people actually read the report?

When the San Francisco County Transportation Agency released its in-depth report on transportation network companies (TNCs), it also launched an interactive data map. Well-designed custom apps, like this one, are excellent ways to engage policy makers and the broader public.

Take a moment to explore the TNCs Today map.

The map strikes a fine balance between offering the user many ways to interact with the data, while still providing an understandable interface. You can tell that the San Francisco County Transportation Agency put quality work into this – clearly considering the map to be an important piece of its research and policy effort. Nicely done.

Interested in learning more about custom data maps and how they can support your work? Drop us a line, we excel at making tools like this.

Unknown Pleasures

Sometimes beauty is inherent. Sometimes it’s familiar. And sometimes it’s both.


For me, John Cheshire’s visualization of the world’s population is both. First, there’s an elegance and economy by which the data is encoded. Then, there’s the striking similarity between his map and Joy Division’s Unknown Pleasures iconic album cover, which featured a plot of pulsar radio signals.


If you’re a fan of British post-punk rock and Edward Tufte – you’ll probably find Cheshire’s work beautiful in both ways. Heck, you can even order a print of his world map and hang it on the wall right next to your stacks of vinyl.

(As a bonus for R users, Ryan Brideau has a neat post on how he reverse-engineered the visualization and applied it to New Brunswick.)

breathing city

Joey Cherdarchuk at DarkHorse Analytics created this visualization of home and work population patterns in Manhattan.


His blog post on the viz development is a fun read and familiar for those of us who have been down similar roads.

See, it is super easy and takes almost no time at all to create something like this, as long as your definitions of “super easy” and “no time” are flexible enough to include difficult and time-consuming.

So true.

Building non-profit capacity

Milwaukee’s IMPACT Planning Council has a new blog post about a recent web map training I led with Virginia Carlson.

Two weeks after the training, attendees returned for a discussion and the opportunity to share maps. Several of the group members had successfully created a map, and most people came back with questions. The group spent the second meeting discussing the maps that had been created by attendees, sharing frustrations, exploring solutions and celebrating successes. Virginia and Matt went through step-by-step solutions to problems brought up by participants.

With rise of open source software and open data, today’s non-profits have new ways to effectively analyze and present their spatial data. Having a lean budget is no longer a reason for not doing this well.

By sponsoring these type of skill-building trainings, IMPACT Planning Council is shaking things up in Wisconsin’s non-profit community. They’ve identified a need and are enthusiastically moving to build this type of capacity in our community.


High Traffic

Wow. The Milwaukee Ages web map has really been making the rounds – it surpassed 28,000 views this week.

We’re pleased to help improve the world’s impression of Milwaukee. This little city by the big lake really is quite beautiful.

Want do drive traffic to your organization’s website? Let Big Lake Data build an awesome web map for you.

Vizual Statistix

Seth Kadish, blogging at Vizual Statistix, has a great data visualization comparing the orientation and congruity of various U.S. metropolitan street grids.

The plots reveal some stark trends. Most of the counties considered do conform to a grid pattern. This is particularly pronounced with Chicago, even though much of Cook County is suburban. Denver, Jacksonville, Houston, and Washington, D.C., also have dominant grid patterns that are oriented in the cardinal directions. … Downtown Boston has some gridded streets, but the suburban grids are differently aligned, dampening the expression of a single grid on the rose diagram. Finally, the minimal geographic extents of the grids in Charlotte and Honolulu are completely overwhelmed by the winding roads of the suburbs, resulting in plots that show only slight favoritism for certain street orientations.


And then he does the same for some European metros:



Rustbelt Makeover

”Whatever their purpose or subject matter, even the most rudimentary of maps have an inherent beauty, an attraction in their way of ordering things.” – Antonis Antoniou

Milwaukee Ages Map

This map is built with a simple data series: the ages of 139,931 residential buildings in Milwaukee, Wisconsin. The building data, maintained by the City of Milwaukee as part of a larger property dataset, has been hidden in plain sight for years. (Click here to explore the complete, zoomable map.)

Using only the age of a building plus the shape of the property that it sits upon, this map invites you to explore a city in a new way. Even a casual user can find quick insight in the data – perhaps noting new infill development in Milwaukee’s core (an indicator of urban renewal?).

Milwaukee Ages Histogram

Or, seeing how past housing booms still shape the nature and distribution of the City’s existing housing stock.

Milwaukee Ages Histogram

One of Big Lake Data’s core competencies is building custom interactive maps for clients.

Yet, this particular map is simply for the city itself. Here’s some of your rough government data, Milwaukee. With a new cut and polish, you really shine.


Building age data and parcel geometries come from the January 2014 Master Property and September 2013 Parcelbase datasets maintained by the City of Milwaukee. 139,931 residential parcels are colored by the year the building that stands upon the parcel was built. Identifying parcels by building age highlights meaningful historical periods in the growth and development of the city.

Roughly 21,000 Milwaukee parcels have no associated building age. This includes not only vacant land (6,501 parcels), but also tax-exempt property (i.e., public schools, non-profit institutions) (4,817 parcels), condominiums and large apartment buildings (1,182 parcels), commercial (9,134 parcels), and industrial properties (620 parcels). They are not colored, but if you zoom in you can see their outlines.


This map is chiefly inspired by WAAG’s magnificent map of every single building in the Netherlands. The color palette takes its cue from this Ken Kornacki treatment of a cream city brick building, which is typical of Milwaukee.


This map was made entirely with open source technologies. R was used to process the data and plot the histogram legend. Quantum GIS was used to join the building data to parcel geometries. TileMill was used to style and create the map tiles.

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