About 4 years ago we wrote a post about setting up a map server with Mapnik and PostGIS. It’s still one of the most popular posts on the site but it’s VERY OLD. I wanted to update it with a slightly easier install method and some newer software. What’s in the stack? I’m glad you asked!

Unlike the previous guide, this one won’t cover basics of Linux and the command line. It’s also written for a Red Hat Enterprise Linux (RHEL) 7.2 server instead of Ubuntu. Let’s do it.

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Ever since the San Francisco map sold out over the holidays we’ve been eager to get it reprinted and back up for sale. Of course, before doing so, we couldn’t resist making a few changes to refresh and update the design. The new version, pictured above, is the third in six years. Read down the page for a quick rundown of what’s new, or skip it and go straight to the typographic maps store where you can check out the map of San Francisco and our collection of other typographic cities.

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For the past few weeks, we’ve been working through the soft launch of imagineRio, a project we’ve been working on for a couple of years with Rice University. Fun fact: The Portuguese translation of imagineRio is imagináRio which directly translates to imaginary. There’s more background information about the project on the Rice Humanities Research Center website, but in short, the goal of the project was to create a platform to display spatially and temporally accurate reference of Rio de Janeiro from 1500 to the present day. The current front-end for the project uses these maps to display a range of iconography, including maps, plans, urban projects and images of the city (with viewsheds).

The project has numerous technical challenges (which of course pale in comparison to the challenge of digitizing all that historical data), but I just wanted to focus on one of them for this post: data probing and feature identification on a raster map. I’ve always considered data probing in the browser to be something that is exclusive to vector maps. Raster maps are just a collection of pixels. We don’t know the features that are there so we can’t interact with them. Usually that’s OK. Interactive maps are vector thematic data on top of raster base tiles, right? Not always (and yes, we’ll talk about vector tiles another time, this project started 2 years ago):

• What if the thing your map is about is the type of thing usually reserved for basemaps (roads, buildings, natural features, etc)?
• What if you need more map rendering oomph (compositing, labels, etc) than the browser can provide?
• What if your dataset is just too big for the browser to handle as vectors?

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I wanted to title this post: You Won’t Believe This Cartographer’s 4 Weird Tricks for a Nicer Map. That seemed like a bit much (plus the length of this post got away from me so it’s now more Longreads than Upworthy), but the sentiment isn’t entirely untrue. Design (big-D Design—I would’ve capitalized it even if it didn’t start the sentence) is an intimidating and amorphous topic. Academic cartography provides good guidelines for thematic cartography, but interactivity and user-interface design are often “I know it when I see it” type of things. What follows are 4 quick design concepts and techniques that can be applied in many situations to improve the look and feel of an interactive map.

These concepts were taken from a map we made for the Eshhad project tracking sectarian violence in Egypt. It’s a relatively straightforward map with:

1. A point dataset with a handful of attributes of various types (date, categories, short / long text, URLs)
2. A Leaflet implementation with basemap tiles
3. A responsive design for mobile

These are 3 very common circumstances for an interactive map, which should make these tips transferrable to a wide variety of projects.

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We recently finished work on a live election map as part of The Tahrir Institue for Middle Eastern Policy’s parliamentary election coverage. Egypt’s complex (and ever-changing) election laws made this an interesting and challenging project, one that required novel mapping techniques to represent the data.

Stripes

The overview map uses value-by-alpha to display the results. Each district is colored according to the party that won the most seats. Transparency is controlled by the number of seats won in that district (not the number of seats available). Because Egypt uses a proportional system representation for each district, a party wins seats in proportion to how much of the vote they won. This leads to lots of ties, especially in the individual results list where the districts are very small with only 2 - 4 seats up for grabs, and many candidates running unaffiliated with any political party.

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Last weekend saw the close of a six-month exhibition by the Norman B. Leventhal Map Center at the Boston Public Library titled “We Are One: Mapping America’s Road from Revolution to Independence,” a piece of which we at Axis Maps had the pleasure of creating. A commemoration of the 250th anniversary of the Stamp Act, the exhibition featured an impressive collection of contemporary maps from the years prior to the American Revolution through the early years of the new nation, documenting and providing context for the events leading to American independence.

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Most of the work we do here at Axis involves coding Javascript interactive maps. Frequently, the map will have elements controlled by UI components and/or charts and/or timelines. Calling each of the map functions after a UI component gets interacted with (or chart/timeline/etc…), can get exponentially convoluted if you aren’t careful.

If you are fairly new to coding you may not be familiar that code can have design patterns. Just like there are cartographic principles that help with everything from layout to typography to color, there are coding principles that help with code clarity, maintainability, and efficiency.

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We’re a mapping company that’s most at home on the web. So when a more traditional static cartography job came along, we even took that to the web.

The ongoing project involves producing a set of four maps for each of thirty-three different countries, showing GDP along with flood and earthquake risk. To make 132 maps, clearly we need to set up a good, easily-repeatable workflow. Because the map themes and symbologies are the same for each country, essentially we need a set of templates into which we can throw some data and get an appropriately styled map that we can export for refinement in Illustrator, and finally layout in InDesign.

Ordinarily that’s where GIS software like QGIS or ArcGIS comes in. But using GIS can be a slow, repetitive task. In the interest of creating a faster process suited to our purpose specifically, we thought it would be easier to develop our own web-based tool to handle the parts of the workflow normally handled by GIS. Fortunately, it’s easy to do such a thing with D3.

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Last month, Andy gave a talk at the OpenVis Conference entitled Blindfolded Cartography. Essentially, things to look out for when designing maps (especially interactive ones) so that when real data comes in, the map/design/page doesn’t get wonky. Things like too long text, missing data, skewed data, etc… The last week or so, we’ve been working on adding accessibility features to one of our projects and wanted to share a few thoughts and lessons on Cartography with an actual blindfold.

First off, what are accessibility features and why should you care? Accessibility features are features and general design patterns that allow people with disabilities to view and interact with your content. This can range from simply allowing keyboard navigation all the way up to screen readers. Now, why should you care? We can get fairly pedantic about whether a font size should be 16pt or 18pt, should this light brown text be #f2e1cb or #f8f1e7, should this div have a margin of 20px or 22px? If we as developers take that much care about things that a lot of users aren’t going to consciously notice, shouldn’t we take at least some care with things that some of the users are really really going to notice?

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This is an adaptation of a talk I gave at the 2015 OpenVis Conference in Boston, expanded in a few spots and abbreviated in others. You can see slides and, ugh, video from the talk.

At Axis Maps, a rough napkin sketch of our projects often looks like this:

We're tasked with designing and building interactive maps of data that, for one reason or another, we can't yet see. Sometimes the client doesn't have data ready soon enough. Sometimes we expect data to change or be added after our work is done. Sometimes it's just too vast for us to lay eyes on all of it. Whatever the reason, this reality of web mapping is a significant departure from what we knew back in cartography school.

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