CartoDB | Blog

PGCon: The-most-advanced-database-in-the-world Conference

Tue, 21 May 2013 16:50:00 +0200

Did you know that CartoDB runs atop PostgreSQL, the most advanced database in the world? Which also happens to be open source? And the fastest growing database in the market?

We actually contribute extensively to our favorite extension of it, PostGIS.

A lot of what is possible in CartoDB is thanks to this flexibility and extensibility of PostgreSQL. (And it still amazes us, all the cool things that can be done in just good, old, plain SQL (size sorting, distance queries, or digging into data).

PostgreSQL has some of the most advanced and replicated technologies, with extremely powerful extensions and analysis SQL. But even more importantly for us at CartoDB, with PostGIS, PostgreSQL offers exceptional geospatial support. PostGIS performs better and with superior functionalities than Oracle, MongoDB, SQL Server, and well, any other database out there. And the fact that PostGIS is just an extension to PostgreSQL demonstrates how extensible and powerful that database is.

Every year the PostgreSQL community gathers together to discuss the future of our favorite database and share ideas. This event is called PGCon, and it happens in Ottawa this week! Our CEO Javier de la Torre will be there to hear from others and share some of CartoDB’s experiences.

Or, if you ever want to talk about maps and PostGIS in general please ping us. We’d love to show you CartoDB, talk about maps with millions of records, hosted PostgreSQL services, etc.

But hopefully — see you in Ottawa!

The open source geospatial community comes together again at FOSS4GNA

Mon, 20 May 2013 16:06:00 +0200

The open source geospatial community has some of the best people and the most exciting ideas. That’s why we are always excited to take part in one of a few conferences that bring so many of those great people and amazing ideas into the same place for a few days. This Wednesday marks the start of FOSS4G-NA, a fairly new meeting meant to give the North American FOSS4G community an additional and slightly easier way to get together outside of the big FOSS4G conference. It has been a great addition.

Right now, we are putting the finishing touches on a couple of presentations we will be giving at the conference. The first presentation is a lightning talk titled, The future of geospatial data formats at CartoDB. In that talk, we want to show you some of the ways we are using novel formats and the modern web to push geospatial data visualization. The second is titled, Building Geospatial Applications that can read and write data to CartoDB without proxy. In that presentation, we are showing how CartoDB can be used without any additional backend infrastructure to do some interesting things on the web.

If you can’t make it, be sure to follow the conversation on Twitter. If you can make it, find us (@CartoDB or @andrewxhill) and let us know what you are up to using CartoDB or ask us any questions you are dying to get answered. Looking forward to seeing everyone there!

Make maps from data you collect in Google Forms

Fri, 17 May 2013 16:27:00 +0200

While many CartoDB users arrive to the service with data on hand others look to use CartoDB to host and map data from ongoing collection. For those users, we offer a number of useful client libraries and tutorials for using our APIs. For businesses, scientists, and students that still want a little easier way to collect data, we thought we would put together this tutorial covering how to collect data with Google Forms and have it inserted directly into a CartoDB table.

In our example, we create a simple form to collect people’s favorite color and their location in the world. Using Google Forms plus a small Google App Script, we then insert those results into our CartoDB table where we have a live map that shows the latest and greatest results to the world. Be sure to fill the form out yourself and see your vote show up on the map!

We have included all the code plus the screencast for you to create your own forms for data collection. It only takes about 5 minutes! Have fun and remember to share the cool things you come up with!

The versatility of retreiving and rendering geospatial data with CartoDB

Thu, 16 May 2013 11:15:00 +0200

We have been discussing a lot lately how we can summarize CartoDB in a short and sweet sentence. A lot of adjectives have been tested. One of the options we have liked the most is, CartoDB allows you to render your data on a map. As simple as the phrase sounds, it packs a lot of meaning. Let us explain…

How CartoDB serves geospatial data, the common

At its core, CartoDB gets the data from a database and renders it to tiles. Tiles are a clever solution where images of data instead of complete datasets are transferred over the internet, saving a lot of bandwidth. They also are created on a regular grid that makes them perfect for caching. Once delivered to the browser, those tiles are rendered by any client side API of your liking (e.g. Leaflet, Google Maps, OpenLayers, ModestMaps). Besides being a clever solution to displaying large-scale data on the web, rendering tiles is fast and compatible with old browsers and mobile devices.

Tiles are not a magic bullet for maps on the web. Most obviously, when we don’t have a lot of data there isn’t much gain from tiles versus sending the real data itself. For example, if you need to render 100 points, you will need 100*4*2 (4 bytes per float, latitude and longitude), 800 bytes. It is very likely that the tile or tiles you would need to render these points would take much more than 800 bytes. You also get all the benefits of dynamically changing your data (e.g. adding, removing, or moving points) and you can add things like hover effects that can not be done with tiles alone.

Luckily, CartoDB is way more than just tiles.

How CartoDB serves geospatial data, the non-tile way

CartoDB has a nice API to access to the data, the SQL API. It takes a SQL statement and returns the resulting data. You could use it for simple things like, get the points in your table, to complex things like we do with Torque. Torque is built around the idea that a powerful SQL function can be run to turn any CartoDB table with temporal geometry into a moving visualization in the browser. That can’t be done with tiles.

The SQL API also gives developers a few options for data formats, those include a flat JSON format, TopoJSON and GeoJSON. The GeoJSON format is meant for us mappers, it allows you to transfer geographic information (including metadata) using JSON as container, but in a predictable schema that many of your client side mapping libraries already know. Sounds good, eh?

Getting the data from your cartodb account to your JavaScript application can be done really easily using CartoDB.js. Here is an example of the JavaScript API:

http://gist.github.com/javisantana/25d62c1a9dca447b771e

Rendering vector data using Leaflet

Using Leaflet as an example, we render that GeoJSON data on our map with just two more lines of code:

http://gist.github.com/javisantana/f571b8938618c706fd0b

You can see it running here.

Rendering vector data using Google Maps

Google Maps does not support GeoJSON natively but there is a library that fills the void, GeoJSON-to-Google-Maps. The library works in a different way than Leaflet and takes a few more lines of code. You can see a simple example with source code here.

CartoDB is built for your dynamic data

Okay, that was fun but the best thing is yet to come. CartoDB is a dynamic service and that means you have some powerful flexibility in how you retrieve your data for the web. You could execute queries to only get a subset of your data. Or you could query for only the latests data inserted into your tables. You could optimize your maps by changing the quality of the data depending the device your viewers are using. Or you could animate your data if it is linestrings or points with timestamps. This is where the SQL API really gets powerful.

Filtering the data

Imagine you want to get the countries of a particular size, say 1,000,000 Sq Km. Here, we’ll use the SQL API with a little bit of geospatial filtering (ST_Area is going to return meters, so we divide by 1 Sq Km):

https://gist.github.com/javisantana/3936f073bf5f4ab5ddab

Here, we can query for only the points close to known location, specifically the wifi hotspots nearest a viewer.

See the complete example with custom point markers.

(Click anywhere in Manhattan below to see the closest WiFi locations)

Simplify geometries

Sometimes geometries, such as country borders, are really complex, meaning they also make for large files to transfer over the web. We can fix this easily with CartoDB and on-demand geometry simplification over the SQL API:

https://gist.github.com/javisantana/d5b5eddf75a555d82ce6

This can be really useful for developing mobile applications, where data transferred is a very important consideration.

Hover effects

Now that we are rendering data directly in the browser, hover effects are as simple as changing the style of the target:

https://gist.github.com/javisantana/7db55fce5d9c7d65b354

See the hover example for a full example.

Advanced usage

Apart of these simple examples you can go a lot further and do animations, add effects using D3, draw on canvas, or integrate your geospatial data with other web technologies. For inspiration, take a look at this animated visualization showing the earthquakes using D3 or Torque, our library to create animations using canvas.

Conclusions

Now you’ve seen how CartoDB can dynamically filter data based on user actions and can provide vector layers to display right on Leaflet and Google Maps. This is one of the key advantages of CartoDB, it allows you to show your dynamic data. Not only based on changes to your request, but as soon as you add or update data in your table, you will see it realtime on the map. This is true whether you choose to to use vector data or tiles! And not even that, CartoDB provides all the infraestructure to support millions of map views, see eRepublik’s dynamic maps use case.

If you have ever been curious about why you would choose CartoDB, we hope this helps you make the decision!

Did you know you can do dynamic graphs with CartoDB? The Policy Climate Interactive project

Thu, 09 May 2013 19:26:32 +0200

Even though our blog gives a lot of attention to maps, CartoDB is a great tool for a lot more than just maps. We have seen in the past how the CartoDB APIs can do all sorts of dynamic queries to CartoDB hosted data. While dynamic queries CartoDB can be geospatial in nature, even returning GeoJSON formatted results, we haven’t spent much time highlighting the fact that they don’t have to be geospatial. That is why we are excited by the latest project released by the Climate Policy Initiative, the Policy Climate Interactive.

The Policy Climate Interactive is an online tool, focused on the key economies driving both climate change and climate policy in the world. The report highlights both the good and the bad through the use of interactive data visualization driven by the CartoDB APIs. No other platform available gives the flexibility to dynamically query hosted data in a way that you can create client side visualizations so simply.

In this case, the D3 framework was used to build some really beautiful graphs of the data underlying global climate policy. We were really impressed to see how beautifully CartoDB works with D3 for doing these data visualizations without any maps! This project highlights how powerful CartoDB can be even for non-map based data visualization. Take a look through some of the results,

The way the project uses the D3 library and data coming directly from CartoDB is cool for many reasons. A clear one is the data curation and management flexibility it give the project administrators. Administrators can easily add and modify the source data on CartoDB and the results will immediately appear in the graphs online! CartoDB also gives users the ability to create download links for particular subsets of data, by adding a link to the API query with and indicating the export format (e.g. CSV, Excel, etc).

We are excited to share this project and are honored to have CartoDB be part of such an important project. Congratulations to [Climate Policy Initiative](http://climatepolicyinitiative.org/) for delivering such a forward thinking website and data publishing platform.

eRepublik Brings CartoDB’s Dynamic Mapping to Online Gaming

Thu, 02 May 2013 15:37:52 +0200

For years we at CartoDB have been dedicated to visualizing geospecific data to gain analytic insight and tell compelling stories. Our real-time rendering and time-lapse technologies have helped illustrate phenomena all over the earth from Barcelona traffic to Kenyan elephant movements to the history of meteorite strikes on the planet. Now for the first time CartoDB’s power of dynamic mapping is also enhancing a virtual world with massively multiplayer online game eRepublik.

eRepublik is a popular free-to-play strategy game with hundreds of thousands of users globally. Players in eRepublik’s New World claim allegiance to a specific country, for which they build companies, develop diplomatic strategies, and fight on battlefields for more territory. While maps are an especially apt visualization for this kind of gaming application, eRepublik had a hard time to provide them for so many players with any useful accuracy. The game’s very popularity and the volume of rapidly changing content posed the greatest obstacle to successful mapping. CartoDB, however, gives eRepublik a means of producing accurate maps for their many users for a fraction of the cost charged by other SaaS mapping companies.

CartoDB, unlike other mapping platforms, is in fact designed to handle dynamic content at large scales efficiently. With our API eRepublik no longer needs to generate new maps after each player’s action. Instead, as the game progresses eRepublik simply modifies the map data, and the platform renders the changes automatically. Map content gets updated at least once every twenty minutes and players are able to see a visual representation of the game’s current state with practically real-time accuracy. CartoDB handles approximately two million map views in eRepublik daily.

We’re pleased at CartoDB to share this use of our platform by eRepublik both because we’re proud of how it showcases our exceptional dynamic rendering and scaling capabilities, and because for us it’s new territory. Games like eRepublik demonstrate that not every community organizes around real space, and geospatial data is not the only kind that produces interesting map stories.

Let us know if you have more ideas for alternative-space uses of CartoDB, and as always, don’t be shy about sharing your own map stories!

Guest Post: TeamUP wins third prize in Urban Data Challenge

Wed, 10 Apr 2013 16:04:00 +0200

Today we here from Chong Zi Xin and a team of hackers that took part in the recent, Urban Data Challenge. The team reached out a few months ago about using CartoDB for their challenge entry and the other day we found that their entry had won 3rd place. We were really impressed with some of the maps they produced, including perspective views with integrated bar charts (wow!).

The Urban Data Challenge is a competition that aims to improve transportation through the visualization of urban data sets by drawing meaningful insights. Public transport data such as trams, buses, bicycles and pedestrians from Zurich, Geneva and San Francisco is provided for participants to merge and compare mobility data sets from these three cities.

The project, titled “A City’s Heartbeat”, done by core members of three start-ups, won third prize in the Urban Data Challenge. The project utilizes Geneva’s trams and their passenger flow information to help improve urban mobility, tourism experience as well as businesses (such as cafes near tram stops) to make better decisions.

Our first challenge, is to render big, time-series data of tram movements over a two day period. This temporal mapping was achieved by using the CartoDB SQL API and reusing code from their Torque examples. The basic idea is to treat the database table as a cube, while only downloading and visualizing a few slices of the data at a time. It worked beautifully.

Develop geo apps and maps at NYC BigApps 2013 with CartoDB

Sat, 06 Apr 2013 18:43:00 +0200

This year’s BigApps competition is kicking off right now in New York City. The competition challenges developers and designers to create applications that help the city tackle big issues, help make people’s lives a little better, and help people engage in the city around them.

We have been supporting the competition for a few years now, and we have seen cool applications like Scene Near Me developed using CartoDB. For this years challenge, the City has opened some great new datasets and has even expanded the rules of what you can use to participate on the challenge. As part of that expansion, CartoDB is now one of the official APIs and developing your app using CartoDB qualifies you to enter into the competition. We would love to see one of you win any of the great prices.

We are at the NYC BigApps 2013 Expo and Hackathon Weekend at eBay presenting our API and helping developers with anything geo and maps. If you are around, Andrew Hill can give your team a free upgrade to a Magellan account on CartoDB.

We can imagine lots of different applications that can be developed for the great city of New York. There are some areas in particular where we think CartoDB can really help participants. If your application has:

Maps that are interactive and that are dynamic
You need to find what is the closest subway, park, museum or whatever to a location.
You what to intersect location data from phones with any other dataset, in real-time.
You need a backend to store your data and be able to query on it live.
You need to analyze multiple datasets, merging them via location. For example what neighborhoods are more “bike friendly”.

We are really excited on this challenge and we look forward to help all participants with their GEO needs! Good luck everybody.

Guest Post: Michael Keller from Newsbeast Labs

Thu, 04 Apr 2013 00:22:00 +0200

As some of you may already know, Newsweek / The Daily Beast has been using CartoDB for some time now, and as such today’s blog post comes from Michael Keller of Newsbeast labs. We’d also like to take the opportunity thank Michael for his amazing contributions to the CartoDB community. Thanks!

A number of recent stories at the Daily Beast have had some kind of mapping component. We use them often to let people see how a national topic affects readers’ local areas.

I have been reusing code from former projects and so it was about time I standardized them into reusable templates with Leaflet.js. I released them on Github this week.

I made three categories: basic map with hover states, hover states + hover infowindow, and all of that with templated infowindows using Underscore.js.

In each of these categories you’ll see a template for a point map, a polygon map, and a map with both points and polygons.

Some features:

• On point + polygon templates, the polygon hover state turns off when you hover over a point.

• Hover windows follow the mouse and respect the boundaries of the map-canvas. I find it most useful to have hover windows close to the mouse so your eye doesn’t have to leave that map region to see that region’s details

• Templates with Underscore.js hover windows include sample formatHelper functions to act as a formatting layer between your data values and how you want them to display. For instance, you could store all your feature attributes as boolean variables and run them through various formatHelpers functions to return nice display strings.

• The hover states work by storing a simplified GeoJSON representation of that feature as a feature attribute. On featureOver, that GeoJSON is plotted as a vector using Leaflet.js.

• Point + polygon templates add a secondary style class to hover windows when hovering over points to differentiate from polygons.

If you have any questions, I’m at @mhkeller. If you have improvements, pull requests at http://github.com/mhkeller/cartodb-templates

Time based map visualizations unveil new patterns and insights

Wed, 20 Mar 2013 18:12:00 +0100

Over the past months you have probably come to realize, we love data that moves. Moving data can make your maps and visualizations really come to life and data you can use to build these visualizations can come in a lot of forms. Whether it’s data that crawls and zips across a map through time, data that bursts and comes to life as you watch, or data that changes form or intensity, it all can lead not to some really amazing visualizations.

Seeing data come to life on your computer screen is more than just fireworks that people find pretty. Showing data move on maps isn’t new, but we have really been trying to push new research into how to effectively display dynamic data on interactive maps. Seeing and also interacting with data that changes through time can be incredibly useful for gaining insights into your data and communicating those insights to a broader audience. The application of these visualizations can be anywhere from business intelligence, to smart grid development, to conservation planning.

That is why we were particularly excited to see a recent visualization from Jeffery Stephens and Space for Giants. Jeffery used Torque and CartoDB to start looking at how elephants moved across the landscape. In particular, these elephants have a bad habit of crossing a fence from protected areas into nearby farming areas. It is a bad habit that can lead to really bad consequences and fixing it requires understanding how and where it is happening and organizing a multifaceted solution. To help share the issue with colleagues, collaborators, and others, they put together a really unique visualization of the elephants moving across the landscape.

In the visualization above (click the image to see the live map), a year’s worth of elephant movement was reduced into a single day. Next, the data was mapped over a 24-hour clock, showing the dominant patterns of where and when the elephants were crossing the fence. We absolutely love this map, and hope it can help the wonderful work of Space for Giants. We weren’t alone, there was a really nice write-up in O’Reilly the other day too.If you want to try your hand at similar visualizations, take a look at our Torque library available on GitHub. We are still working hard to incorporate this directly into the CartoDB user-interface, but in the meantime, you can fairly quickly get a look at your dynamic data using the sandbox tool. We would love to see any interesting visualizations you come up with!

Exploring the differences in dynamic data through time

Tue, 19 Mar 2013 12:51:00 +0100

We often find ourselves exploring what interesting things can be found in data that changes through time. In recent blog posts about the Mobile World Congress (MWC), we have published a couple interesting experiments with temporal data. In the first, we showed how CartoDB could be used to map traffic in Barcelona.

The map was built to automatically update every 15 minutes through the day. In the second map, we show a fun visualization of credit card purchases in Barcelona during MWC compared to purchases over a similar period not during the MWC.During the development of the second example, we realized how important it can be to show two maps simultaneously, side-by-side. In the credit card transaction example, each map show the view what happened at a different point in time.

The side-by-side technique can be really useful. For example, here we have recreated the Barcelona traffic map, now showing the traffic during the start of MWC and the traffic exactly one week later.

The utility of the side-by-side map example is that you can allow users to zoom and pan into areas of interest. While traffic may not appear immediately different, if you are driving in Barcelona, you may want to explore the map close to discover the intricacies and maybe learn how large crowds influence the flows in that city. These insights are already helping some CartoDB users to build data dashboards to support their missions of creating smart cities.

We feel that a lot of CartoDB users will find an easy to use dual map visualization helpful for telling stories about their data. For that reason, we have developed an example as an easy to use template in our templates library. Grab a copy and start using it immediately with your CartoDB data!

The Ides of John Snow

Fri, 15 Mar 2013 16:21:58 +0100

March 15th is more widely known as the Ides of March, and the day that Julius Caesar was assassinated in the Roman senate. However for those of us in the mapping, data visualization and Epidemiology March 15th is the birthday of John Snow, an English physician and a leader in the adoption of anaesthesia and medical hygiene.

Considered one of the fathers of modern epidemiology, in part because of his work in mapping the 1854 cholera outbreak in Soho, London, with this possibly the earliest use of a geographic methodology in epidemiology.

Using a dot map to illustrate the concentration of cholera cases around a particular public water pump and using statistics to illustrate the connection between the quality of water sources and cholera cases, Snow gave birth to visual analysis using maps. Through his map, Snow was able to confirm that the Southwark and Vauxhaull Waterworks company was delivering sewage-polluted water to homes and leading to increased incidence of cholera.

While the basic elements of topography and theme existed previously in cartography, the John Snow map was unique, using cartographic methods not only to depict but also to analyze clusters of geographically dependent phenomena.

In order to celebrate John Snow’s birthday, we’re offering a 20% perpetual discount on all new John Snow plans with the code “happybdaymrjohnsnow“. Simply upgrade your free account and enter the code. This offer expires on March 16th, so be sure to act quickly.

Cheers!

How NewsBeast Labs Visualized Roe V' Wade

Wed, 27 Feb 2013 22:10:00 +0100

The following post was initially published on the NewsBeast Labs tumblr, and comes to us via Michael Keller, senior data reporter at Newsweek & the Daily Beast.

Michael is a reporter, designer and programmer working on ways to create interactive stories that let readers see how they fit into the story and, in reader feedback stories, ways to see how readers lives have intersected with the story’s subject matter. What follows is a repost from their blog.

Last month we published a package of stories marking the fortieth anniversary of the Roe v. Wade decision. It had a few moving parts but I’ll just go over some of them briefly here.

How it started

This summer you probably heard the story about the last abortion clinic in Mississippithat was threatened to close due to stricter state laws. Allison Yarrow, who sat across from me at the time, was covering the story and it got us thinking: the line “The Last Abortion Clinic in Mississippi” is attention grabbing, but it doesn’t tell the whole story. That is to say, what you really want to know is how far are people away from their nearest clinic, regardless of state boundaries. One state may have five clinics but if they’re all in the southwest corner of the state and you live in the northeast corner, and your adjoining states have multiple clinics but only at their borders farthest from you, then you’ll have a hard time getting to a clinic, even if you had many in your state. To see where this might be the case and where access to services was compounded by new restrictive provisions (over 150 nationally in the past two years) we made as close to a comprehensive database as possible of every abortion clinic. Our goal was to see what parts of the country were farthest from a clinic. From start to finish, this process took about six months.

We got our address data from a variety of publicly available sources: Planned Parenthood, the National Abortion Federation, anti-abortion websites that keep their own lists and others. We needed to verify that the address information was correct, though, so we called over 750 clinics to confirm. We also asked them up to how many weeks they offer services. The resulting database is the only one of its kind that we know of. The Guttmacher Institute undertook an abortion provider census in 2008 but they didn’t separate clinics from hospitals from private doctors offices, which represent different levels of care that we thought was an important distinction.

What it became

We started this in July and the project evolved. We thought the election might bring the issue of abortion access to the fore but it didn’t and that gave us more time. Allison brought up the fortieth anniversary of Roe v. Wade and that let us think much bigger about the project. Because this was such a personal subject matter, we knew readers’ comments would feature prominently (from both sides of the issue) and we wanted a strong narrative component, too.

To give a human voice to the Geography of Abortion Access map, Allison flew to Wichita, Kansas, one of the areas that stood out both on our map, as a metro area far from a clinic, as well as in recent memory as the site of the 2008 murder of late-term abortion provider George Tiller. To add a broader perspective, Sam Register who runs the Newsweek Archivist tumblr went through the Newsweek archives so people could follow the topic’s coverage from the 70s through the 00s.

What we learned from reader’s stories

Over the course of the week, we shifted the question we were asking from why do you support or oppose legal abortion to a conversation about pro-life and pro-choice labels as a way to get more nuanced opinions and show the complexity of the issue. We asked readers to complete either the phrase “I’m pro-life but…” or “I’m pro-choice but…” We got more responses from our other reader-based projects but we were happy in how thoughtful and honest people were. Read our roundup of interesting responses to those questions as well as our free form “Tell us your story” prompt here.

Under the hood on the map

How to represent this dataset was tricky. We had three main issues: anonymity, unbiased geography, and context.

Anonymity: Although we got our data from publicly available websites that anyone could find and was often information that anti-abortion groups already held, we weren’t comfortable publishing addresses, names, or exact latitudes and longitudes. We took great care to do things like scrub our final database of anything identifiable and we partially randomized each clinic’s location so they weren’t pinpoint-able from our map. On the presentation level, we added the magenta circle big enough to span multiple hexagons (our base geography layer) to let people know that an address was approximate. Even if you backtrack and find our database, you won’t get any information that would let you de-anonymize the data.

Unbiased geography: As I wrote above, we wanted to get away from the arbitrary state and county borders that most all of the research we encountered was based on. We did some initial plots using Census tracts but that presents exactly the same problem [photo]. We ended up making a hexagonal grid using the Repeating Shapes plugin for ArcMap, which lets you make a grid out of your choice of shape and size. The trick to making a hexagonal grid for the web so that the hexagons will be regular (all sides equal) no matter what degree of latitude they fall on is to make the grid in your output projection, Web Mercator EPSG: 3857. You can reproject it to do your analysis in whatever you like, but because it will eventually be displayed in Web Mercator, it will need to be created in that so as not to come out distorted in the browser. If you want a 20,000 meter in diameter hexagonal grid, here’s the one we used: Shapefile, KML, GeoJSON.

And here’s another one that Brian Abelson, current Knight-Mozilla Fellow at the New York Times, made while he was helping out on the project. They are also 20,000 meter hex grids. This one has the state borders preserved in case you want to assign state values to each hexagon: Shapefile, KML, GeoJSON.

Context: Generating our distance map wasn’t enough to tell a story with. We added three other pieces of information that would walk people through the significance of the patterns they were seeing. The first was a map of female population aged 15-44 so that people could see the areas where women lived that were farthest away from clinics and identify significant metro areas (the pink dot density overlay). The second was the different legal restrictions that each area was subject to (areas with highlighted transparency). Again, this was an interesting way to visualize this data because we didn’t highlight every hexagon in Kansas, for example, to show that certain laws were applicable in Kansas. Instead, we highlighted hexagons whose closest clinic was in Kansas. This gave us a very realistic map so that people could see what state laws they would be subject to if their nearest clinic was across state lines. It also visually demonstrates how state laws can affect people that don’t live in that state. And third, we selected our own highlights from going through the data, such as the areas where telemedicine is banned in conjunction with mandatory in-person counseling. The combination of these laws in Arizona, for instance, means some women travel over a hundred miles and spend two days to get a prescription for the abortion bill.

More under the hood

The map itself we built using CartoDB, which allowed us to very flexibly add the different highlighted views of the map without rebaking our tiles each time.The slider that shows clinics that only offer services up to X weeks we did by loading four tile layers on top of each other at once and show/hiding them depending on the slider value. This made the map slightly slower on initial load but it made the transitions between map states super fast — so a trade-off.

For the highlighted states, those restyle and reload all four map layers as well. We used Leaflet.js’s ability to plot vectors to draw the line between the hexagon you’re hovering over and the closest clinic to provide some more descriptive interaction.

A few months ago we spoke with Andrew Hill, Senior Scientist at Vizzuality (who makes CartoDB) on some experimental ways to map the data. The line on hover came out of some of his renderings and you can see in the photos below some of the experimental line styles.

All in all it was a lot of team work, Allison, Abby, Brian, Caitlin, Lizzie, Sam and a number of other people all helped with parts of it over the course of six months. If you have any other questions about it, let me know at michael.keller@newsweekdailybeast.com

-Michael

Before we settled on the Value-by-alpha approach for showing the different state laws, some failures:

We tried outlining the different shapes and showing them in different colors:

We tried coloring the hexagon outline by the different laws that were in effect. Creating a sensical hierarchy proved difficult:

Lines instead of hexagons:

Highlighting Peurto Rico:

A value-by-alpha chart where census tracts are shaded by their percentage of women of reproductive age. Unfortunately, it’s not that intelligible and the heat map overlay is a much cleaner way of showing this relationship:

Before we made the hexagon grid, how the map looks if you use census tracts:

A CartoDB and BBVA visualization on the economic impact of the Mobile World Congress in Barcelona.

Mon, 25 Feb 2013 10:53:00 +0100

The economic impact of the Mobile World Congress conference in Barcelona is estimated to be in excess of 300 million euros, making it one of the city’s most important annual events. With over 1,500 exhibitors and 70,000 visitors from 200 difference countries transferring the city into the de-facto mobile communications industry capitol.

In order to showcase the real economic impact of the MWC on the city, and utilizing Big Data technology, BBVA analyzed millions of credit card and terminal transactions over the course of a two week period.

Dividing the data into transactions from the week before, and week during the conference, we created a temporal visualization using HTML and Torque, and then showcased those same millions of transitions by local and foreign ones, topographically, over the City of Barcelona. The visualization is available at www.mwcimpact.com.

We feel that this visualization serves as a model to the type of business intelligence applications that could potentially be built on top of CartoDB, and we truly hope you enjoy exploring it as much as we did building it.

We’ll be at Mobile World Congress from February 25th through the 28th (Congress Square - Lower Level - Stand CS60) and would love for you to stop by.

Edit feature properties directly from the map.

Thu, 21 Feb 2013 12:48:01 +0100

This is one of those features that has come directly from requests of our users. At CartoDB, we love your feedback and we love working to make your requests come to life.

One of the most powerful capabilities that CartoDB delivers is the ability to clean or create new geospatial datasets from scratch using the Map View. Sometimes you find a feature in an incorrect location, or maybe you use CartoCSS to style your features and find something obviously wrong; in these cases, it would be great to update data directly in the map. Now you can do it.

With the new feature editing modal window you are able to edit the properties of your data directly on the map. You only need to click on the feature you want to edit and then click the editing icon on the left-hand side.

This will open a modal window where you can update or add new content for any cell. After you change the fields you want, simply click Save and close and your data is written back to the table.

This makes the map view a great data editing interface and we hope this improve your experience working with data on CartoDB.

As always, we would love to know what do you think about this and keep sending us your feature requests!

Enjoy!

Every recorded meteorite strike on Earth mapped

Tue, 19 Feb 2013 17:35:00 +0100

Two days ago The Guardian Data Blog published a map about all meteorites that scientist have found. We help them creating a screencast on how to make it. Since then we can see that it has become quite a hit! It is been linked from major sites like The Verge, Digg, HackerNews and of course The Guardian.

We promised, this map was done pretty quickly, checkout the screencast, and of course the map!

Introducing beautiful info-windows with image support

Mon, 18 Feb 2013 12:59:00 +0100

By far one of the most popular feature requests we’ve received since launching almost a year ago has been more customizable info-windows. With the release of CartoDB.js, we made info-window customization easier than it has ever been, however, this still left a lot of our non-technical users out in the cold. However, we’re happy to announce that this is no longer going to be the case.

From now on, CartoDB users will have access to new info-window feature that will allow you to display an image linked directly from an external URL, much like we did on our The Hobbit video recording locations map, and all this will be available from the info-window customization panel.

In order to get this up and running, you’ll need to put your image URLs in a table column, and then use that column in the first position of the info-window field list. Displayed in the image below.

Easy, right? We also highly recommend that you process your images and optimize the prior to putting them into your visualization as to improve the browsing experience of your visitors.

We hope you enjoy this brand new info-windows template.
Happy mapping!

CartoDB won "Startup showcase" at the Tools of Change for Publishing conference

Fri, 15 Feb 2013 16:43:09 +0100

This past Wednesday we attended O’Reilly’s Tools of Change for Publishing conference in New York as a Startup Showcase final contestant, and on the following day we were informed that we had been selected as one of three winners.

The ten finalists, and even the semi-final twenty were all great projects with monumental potential in the publishing space.

As a company that is not centrally focused on publishing, being treated with such high regard in the community is not only a great honor to us, but we’re absolutely humbled by the amazing reaction which we received from the publishing and journalism community. It is a great demonstration of the flexibility of our product to match different needs on different sectors.

In order to acknowledge this, we have decided to offer a limited three month 10% discount code for this week only on all new paid CartoDB accounts. Simply enter the code “TOCCONPUBLISHER” when you sign up for a paid plan to receive the discount.

Thanks you all so much, and we look forward to seeing many more maps and visualizations built by the publishing and journalism communities in the months to come. Stay tune!

Add context and custom content to your maps with our publishing templates

Wed, 13 Feb 2013 16:57:51 +0100

The data in CartoDB maps are often better understood in the context of your own webpages and external sites. Up to now, this has been possible using the embed tool or using a little coding knowledge. However, as more and more users create visualizations of ‘biodiversity data’ or ‘real-time traffic information’ we feel it is time to go one step further. We are now providing a few templates that will help you go from CartoDB map to published webpage faster than ever before.

We have prepared two responsive design* templates for you to start using today. The first is designed to add editorial, rich, textual content to your maps. The template allows you tell a story with your CartoDB map. The second template moves the textual content to a panel on the right side of the map, adding emphasis to your visualization. Both templates come in a dark and a light theme.

These templates are now live, and you can download them on our developer page Download them, link to them, or fork them, and start designing your own.

In the coming months, we will be adding additional CartoDB publishing templates. Hopefully, you also come up with some of your own and share those with us; we would love to create a community template showcase.

And of course, we look forward to hearing your feedback and seeing your creativity at work!

Real time maps with CartoDB: Barcelona traffic

Mon, 11 Feb 2013 17:33:28 +0100

One of CartoDB’s more interesting functionalities is its dynamic rendering. When hosting your data in the cloud with CartoDB, your maps and visualizations have the possibility to automatically update. As you can imagine this represents a fundamental paradigm shift in the map making process where you no longer need to publish a static map and manually update it, inserted with CartoDB you publish it once with live data, and the visualization will perpetually update.

A great example of this is a city’s traffic status map. A typical traffic status map will represent traffic density by coloring the streets different colors and as new data becomes available update the map dynamically. CartoDB shines in these types of use cases and we would like to show you an example.

We took traffic data from the City of Barcelona’s Open Dara Portal, and then dynamically imported it into CartoDB. This data, and now henceforth the map, will automatically updates every fifteen minutes.

Click on the image to check out the demo.

To get this map running, we synchronized the external data using Google App Engine with CartoDB, and in order to get you started with live data and dynamic mapping, we’ve provided all source code for this visualization, along with detailed instructions on GitHub.

Dynamic rendering is at the heart of CartoDB, and is one of its more interesting functionalities, either for live queries, or like we’ve shown here, real time data. Paired with our mechanism for content distribution, using Amazon Cloud Front, we ensure that you’ll be distributing the most recent rendition of your maps and visualizations with the latest data and at maximum speed and scalability.

Finally, we’ll be at the Mobile World Congress in Barcelona starting the 25ht of February showcasing this technology, so please stop by our booth to see how CartoDB can make this, and other cool maps.