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5 Questions with Paul Ramsey

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Paul Ramsey

It only takes a little bit of time working in the geospatial industry before you hear the name, Paul Ramsey. His work on PostGIS and helping to cultivate an amazing community around the open source geospatial technology is humbling. Beyond that though, a simple scan of his blog posts and you’ll see that he thinks deeply about not only open source, but how it does and should affect many aspects of business and government. He can move from a conversation about personally identifiable information to a conversation about the procurement process of local governments with impressive ease.

We have been longtime fans of Paul and finally today, get to announce that he is joining us here at CartoDB. To share this moment with you, we thought we would present a special blog post… 5 Questions with Paul Ramsey.

What do you think your favorite feature of PostGIS 2.2 is going to be?

PostGIS 2.2 is still a work in progress, but among the currently completed features, the most interesting are the raster overview features that allow you to build overviews in the database (previously you had to build them externally in GDAL). I also quite like the aggregate function for raster summary statistics (ST_SummaryStatsAgg), because it really cleans up the SQL needed to pull states from a raster collection.

As you know, we’ve been pirating PostGIS for a long time. But we are excited to get your expertise impacting a lot of the CartoDB technology stack! Where are you most looking forward to getting your hands dirty?

I was excited to learn that CartoDB is actually using Foreign Data Wrappers (FDW) in production, since I just recently learned something about how they work, so I’m looking forward to get my hands dirty there, teaching the PostgreSQL native FDW wrapper how to speak spatial. I also have a big performance improvement to ST_Distance/ST_DWithin calculations that has been in my private tree for almost two years which I would love to unleash on the world (perhaps for PostGIS 2.2).

In your blog, you touch on so many diverse subjects. One I’m interested in that seems to thread them all is: what are some key skills to be teaching the future geospatial community?

People who can take clean data and make a map or visualization are a dime a dozen. People who can clean up dirty data and make it tractable in the first place, those ones are really valuable. Knowing some kind of scripting language that can access files, database, and web services and apply regular expressions is the baseline to being able to work with data. Everything else is icing on the cake.

To my mind the key skills remain in scripting: you can explore a data manipulation process visually for a while in an interface, but after a while you need to automate it, if only so you can efficiently handle updates to the source data. During my vacation I did a big data analysis project using PostgreSQL and R. I ended up with a couple files of SQL and R commands, and could run the whole analysis from start to finish with one command. This was really useful when it turned out that some of the effects I was seeing at the end of the analysis in R were actually driven by mistakes I made early in the process during the spatial SQL steps of merging the data. A few small changes to the SQL, and 5 minutes of CPU time later, I was back in business.

You’ve seen a lot of geospatial database technologies come and some go, what keeps PostGIS exciting?

PostgreSQL remains an incredible (and underappreciated) data integration environment, and PostGIS is the geospatial part of that, but still only one part. The sheer variety of data transformation and analysis that can be done in the database alone is amazing, and because PostgreSQL is so extensible the amount of options keeps growing. My little extension side projects, like pgsql-http, and pgsql-ogr-fdw are about adding to the reach of PostgreSQL as an integration point. So are language bindings like PL/R and PL/V8.

Why did we all end up with elephants?

We got the general elephant theme from PostgreSQL, which in turn seems to have gotten it from a suggestion on a mailing list many years ago, noting that “an elephant never forgets”. The community PostGIS elephant– the friendly one balancing a globe – was drawn by the wife of one of the initial developers (he wrote the first cut of the Shape file loader) shortly after our first release and we’ve kept it ever since.

Thanks Paul!

A huge welcome to Paul from both our New York and Madrid offices today. We are all excited to get this new collaboration started.


Can you hear me now? Talking TeleMaps at the Mobile World Congress

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We’re gearing up for the Mobile World Congress in Barcelona, where the conference agenda highlights the blistering pace of growth and innovation in mobile communications. Mobile healthcare? Remote education? 5G?

To make all this newness possible, mobile network operators are racing to install new antennas in order to expand and improve coverage. They’re laying new infrastructure so fast, in fact, that sometimes their coverage maps can’t keep up.

And those maps are serious business. In the US, Verizon recently got into hot water for portraying T-Mobile’s map inaccurately. T-Mobile just upgraded its map to better show its 4G LTE coverage at different frequencies. Last summer, Free Mobile and SFR were fined by French authorities for flawed coverage maps.

That’s where TeleMaps comes in. For network operators, TeleMaps cuts the time it takes to update your coverage map from days to minutes. Our business partner Elecnor Deimos built TeleMaps on CartoDB in order to make it super easy to update, clean, publish and report on network coverage via fast, highly-accurate, branded maps.

App Screenshot

If you’re a telecom provider, your network is your brand. When choosing a cellular provider, the first thing a consumer does is check the coverage at their home and work locations. So having an up-to-date coverage map is crucial.

While we’re in Barcelona, we’re interested in talking with telecom providers about their experience running and updating those popular coverage maps on their sites, and about how TeleMaps might help. Please drop us a line, and we’ll set up a time to talk.

Global Forest Watch - Only you can prevent closed data

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GFW MAP

Global Forest Watch and Vizzuality have come together to make visualizing ecological data in maps that much more useful and effective. CartoDB is excited to take part in GFW’s mission in forest preservation.

Whether you’re a journalist, scientist, policy-maker, campaigner or community organizer, Global Forest Watch offers a growing number of tools and apps. Did you know that GFW allows you to calculate forest change statistics within a user defined area, subscribe to tree cover loss alerts, view and download data for a specific country?

GFW apps are customized web tools to meet the unique information needs of a specific audience. For example, the GFW Commodities app enables companies to monitor deforestation in supply chains of major commodities like palm oil. The GFW Fires app helps governments in Southeast Asia to rapidly respond to fires and haze. Upcoming is the Forest Watcher app, which will allow local communities and forest rangers to access GFW alerts from their mobile phones.

Using CartoDB’s sync feature and the import API, Global Forest Watch has almost automated the process of adding and updating datasets from heterogeneous sources. Soon there will be raster datasets in GFW hosted by CartoDB.

GFW launched nearly one year ago and is not just a forest monitoring platform. It is part of a growing global movement seeking transparency, innovation, and action to conserve and sustainably manage the world’s remaining forests.

GFW community box

Want to see what’s new and exciting in our community? The GFW homepage will highlight all of the latest updates to the platform and posts from our users.

More awesome work by our partners, Vizzuality. If your company is interested in becoming a CartoDB Partner, check out our information page

Building A Culture Of Innovation

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reach new heights

Innovation is never easy. It takes time, commitment and dedication. Our team here at CartoDB is no stranger to the challenges that come along with new and forward thinking ideas. How do technological innovations such as CartoDB help professionals solve problems and visualize ideas? How can we continue to innovate and bring new tools and applications to the table? As we move into 2015 it is apparent that more and more people are asking these challenging questions. Important and potentially revolutionary competitions such as the Innovating Planning Apps for Planners: A Student and Emerging Professional Challenge brought to us by the American Planning Association and the 2015 Undergraduate Geospatial Technology Skills Competition are rethinking how Geo-spatial tools and technology are used, applied, and created. As we follow these exciting happenings, we are eager to provide tools and knowledge that contribute to this discourse!

As you may know, we at CartoDB are committed to empowering pioneers, and fostering a culture of innovation however we can. While our Start-Up Grants program as well as our Climate Program help start-ups take their ideas to a new level, we want to bring our commitment to students and young professionals to new heights by offering free upgraded student accounts to all of our future professionals and innovators. Simply follow this link and sign up for a souped-up student account to get you started.

Furthermore, if you are participating in one of the exciting competitions for technological innovation, geo-spatial science, or forward thinking design, shoot us an email and we will do our best to give you an extra bump in making sure you have everything you and your team need to take your ideas to new heights. The future is being made today, and we are here to elevate our growing communities every step of the way. How’s that for innovation?

Happy Mapping!

Welcome Brittany

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Brittany Micek

We’re excited to introduce our latest addition to our NYC team, Brittany Micek! Brittany is going to be working in the Community team as a Content Writer.

She hails from Chula Vista, California, a small town with a funny name – it roughly translates to Cute View.

Even though she is hesitant in saying so herself, she is a true writer with a professional background in all sorts of styles - from newspapers to Amazon.com.

Brittany has always had a slight obsession with location - whether physical, geographical, or mental. She is often known to ask - “where are you and where are you going?” Brittany hopes working at CartoDB will definitely help her approach her inner questions in a different way.

When not writing or mapping you can find her outdoors, as she loves challenging herself running, hiking, kayaking or even rock climbing! Reading and exploring new music and films (especially French or Spanish ones) are also passions of hers.

Brittany is mesmerized by Torque maps, especially the visualization of how people all over the world reacted to the release of Beyoncé’s new album.

Welcome Brittany!

Introducing CartoDB Heat Maps

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Today, we’re releasing an all-new type of heat map that brings the classic thematic map to CartoDB users with a modern twist.

CartoDB Heat Maps leverage the power of Torque to transfer very large datasets to the client to efficiently render and publish.

Torque Heatmap in the UI

Fast, beautiful design

The combination of heat maps and Torque has allowed us to integrate beautiful static heatmaps into the CartoDB Editor that you can design and customize quickly.

EcoHack

Animated heat maps like never before

As map aficionados may have already noticed, CartoDB Heat Maps can be animated! We leveraged the temporal capabilities of the Torque library to bring animation to heat maps efficiently and beautifully. You can use the CartoCSS styling tool to cut and style temporal data in amazing new ways.

Other great examples

CartoDB Heat Maps are already in your account, start using them today! For some inspiration, take a look at this map made by Chicago Sun-Times, or take a look at the map below to see a real farmer working with Agroguía.

The feature is continuation of a lot of work started by Mapnik and Leaflet.js, it’s awesome. Have fun and show us what you come up with!

Announcing GME2Cartodb.com - Data Migration Tool

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Recently, we announced the availability of CartoDB on Google Cloud Platform. Our intention is to provide a great resource for those projects making use of the Google Maps API and help former Google Maps Engine customers continue their projects into the future.

Today we are presenting a tool to help the migration from Google Maps Engine to CartoDB. This online tool will let you choose your datasources from GME and move them to your CartoDB account.

GME2CartoDB Migration tool

It is a fairly easy process with just 4 steps

  1. Go to http://gme2cartodb.com
  2. Authenticate with your Google credentials.
  3. Select the Datasources you want to migrate.
  4. Insert your CartoDB username and API key.
  5. Let the tool do the rest of the work.

Some important considerations to take into account

  • The tool will only migrate vector datasources.
  • It will re-import the files you uploaded to CartoDB. If you have programmatically modified some data through the GME APIs this tool will not take them into consideration.
  • It will also not acknowledge if you have modified the data using the GME User Interface.
  • The tool will not recreate the Maps you created on GME, you will have to login into CartoDB and recreate them using the CartoDB editor.

If you have modified your data inside GME, we recommend you using FME tool. It has support for CartoDB and it will allow you to do transformations on the data on the migrations process.

Check out this video.

There is also the option to use ogr2ogr, the Open Source tool to do the migration. Expect an update on that soon.

What to do with Imagery data?

If you have imagery loaded on GME there is also another tool we have in the works to let you migrate it to CartoDB. Contact us for an early demo.

We hope this tool will help users of both platforms to easily migrate their existing projects. Remember you can always contact us to help you on your migration project.

We would like to thank our partners BigMapping for the help on creating the tool. You guys rock!

Have a nice data migration day!

Save humanity and do other things with FME and CartoDB

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FME, a product of CartoDB partner Safe Software, is the most flexible glue around for connecting two applications via their spatial data. And FME now supports CartoDB. Supporting more than 325 file formats, FME is a real workhorse. In fact, FME is so versatile, we think it could be a handy way to prep for the Yellowstone Supervolcano. You know, just in case.

Here’s how:

1) Connect Minecraft to CartoDB to get in the zone

The Yellowstone Caldera is a massive supervolcano that could maybe, possibly someday erupt, creating a lava field 40 miles wide and ejecting poison and ash that would travel for hundreds of miles. Sure, the scientists say we need not worry. But, what if?

If it happened, it would create a landscape that we can hardly imagine. Mental prep is crucial.

So fire up Minecraft. Once you’ve collected a huge pile of Redstone in the Nether and avoided those Griefers, you’ll be mentally equipped to harvest resources in the real world. And you’ll need the practice!

Next, use FME to connect Minecraft and CartoDB, so that you can can share your city layouts with others who will help in the post-volcano redevelopment effort.

minecraft

2) Migrate from Google Maps Engine to CartoDB

FME has a nice drag-drop interface, so you can easily set up connections and transformations.

In this 2 minute video, you can see how to use FME to migrate from Google Maps Engine (GME) to CartoDB. FME is just one way of migrating your data from GME (here’s another).

However you do it, you do definitely want to migrate your important information - fresh water sources, deep caves perfect for hoarding food, wind patterns needed for avoiding the worst of the toxic ash, whatever - to CartoDB for analysis, posterity, and easy map publishing.

3) Ready your LiDAR Point Clouds

Knowing the terrain is going to be pretty important once the supervolcano erupts.

Use FME to convert point cloud data for use in CartoDB. With elevation and terrain mapped out, you’ll have a better sense of where to stay high and dry once the massive volcano heats the atmosphere and causes sea levels to rise.

LiDAR of Lone Star Geyser

4) Connect your CAD software to CartoDB

FME supports Google SketchUp, and it also supports the major CAD packages like AutoCAD.

So data on all those buildings you’ve been designing in CAD can be connected with other data - demographic, political, environmental - and published on a CartoDB map.

Mountain Town

5) Bring it all together.

Between terrain (LiDAR), building plans (CAD), other data from Google Maps Engine, and the worldbuilding prep you’ve done via Minecraft, you’ll be ready to publish the maps that help us find shelter and rebuild civilization after the eruption.

Interested in how FME can help you connect data and applications to CartoDB? Learn more here, and sign up for our webinar at 11am EST on Wednesday, February 18.

Survive and thrive!


Mapentines: Love is Like a Stack of Static Maps

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This week marks a winter slurry of holiday occasions, including Lincoln’s Birthday (Wednesday), World Radio Day/Friday the 13th (Friday), Valentines Day (Saturday!), and Halfprice-Chocolate Day (aka, Sunday)! In the spirit of the latter (two), we celebrated this week with our community at Monday’s Geo-NYC Meetup, prefiguratively themed “Love Stinks.” Our plan was simple/typical: make some cool maps to give people hope this holiday season. Read on to learn how we did it.

Not too long ago, CartoDB launched the Static Maps API, built by popular demand from our community members. We often field requests about exporting maps as images for print, images that are compelling and dynamic as their originals in digital form. While this might seem like a simple utility, it’s something of great value to many of our community members, and no-time like the present to make that part of our festive program of 20% projects in the office. For Valentines Day and to promote the API, we sent out a survey to all attending meetup members of Geo-NYC requesting simply.

We thought it might be nice to turn these distance relationships into drawn trajectories on OSM basemaps, and then provide postcard prints to the survey responders. What followed was a series of steps to auto-craft them the perfect map-nerd valentines and distribute them for mailing at this week’s GeoNYC.

Test Images

Process

Step 0: Get Data

After collecting and closing the survey, we exported the Google form data and did some quick cleaning and standardization of the location data, so that we could pull lat/longs from Google’s geocoder API and build our map. Depending on the quality of your data, you can also just load it into CartoDB and select the geom column to test our auto-georeferencer by place names or admin level.

Here’s a JS-Bin where you can test this if you’re interested.

Step 1: Set Geom

Once loaded into CartoDB, we set the geom to accept multi-string coordinates (that is map the pair of lat/longs to eachother with a MakeLine) and then checked the display to confirm they plotted as we had hoped.

They hadn’t. There was some jank in the way the lines plotted as they crossed tile blocks. How to fix? PostGIS.

Test Images

Step 2: SQL/Image Magick

With a few lines of SQL in the editor we were able to smooth the lines across distances, give them a slight arc and then apply a heart png to the centroid of the line plotted.

Post-SQL

We then wrote that SQL and associated CartoCSS into an html template to test the image plotted, selecting on the cartodb_id for each row in our table so that we could plot each pair of trajectories individually on personalized postcards.

SELECTcartodb_id,ST_Transform(ST_Segmentize(ST_Transform(ST_MakeLine(ST_PointN(ST_GeometryN(the_geom,1),1),ST_PointN(ST_GeometryN(the_geom,1),3)),953027),10000),3857)ASthe_geom_webmercator,labelFROMgeonyc_connections

Options:

  • You can customize your visual further with CartoCSS, in this case we rounded the line endpoints and adjusted the color to hex-match our heart.

  • You can check an html template that illustrates all-of-the-above here.

  • Likewise, you can set the extension for your image file, my default was PNG, but keep in mind that RGB/PNG is not an appropriate print format for most printers.

It’s best to post-process your batch of photos with Image Magick or use Photoshop/another image processor to convert to CMYK proofs.

Like this:

Image Magick - Terminal

Step 3: Polish + Package the Postcards

We then set the images in an InDesign template for printing, selecting the light basemaps so that the color quality would be a bit more intelligible.

The dark basemaps were a bit too tonally subtle to render in print:

Dark Basemap

Other basemap options are available in the CartoDB docs, which you can set in the basemap config of your html template (linked above).

By manipulating the "urlTemplate" custom basemaps can be used in generating static images. Supported map types for the Static Maps Api are:


'http://{s}.basemaps.cartocdn.com/dark_all/{z}/{x}/{y}.png',
'http://{s}.basemaps.cartocdn.com/dark_nolabels/{z}/{x}/{y}.png',
'http://{s}.basemaps.cartocdn.com/light_all/{z}/{x}/{y}.png',
'http://{s}.basemaps.cartocdn.com/light_nolabels/{z}/{x}/{y}.png',
	

It’s Mapenti[m]e

Once printed and cut, the result was a series of twee valentines that GeoNYCers totally dug. Some of our favorite pairs include

  • Noel ♥ The Mayor

Noel

  • David ♥ Santa

David

You can browse all of the mapentines in this pdf doc here.

I documented the process in a github repo, complete with the image composite script for attaching html elements to your images and upping the quality to suit your print needs. Feel free to fork and build your own mapentines for the ones you love, near and far.

Happy Mapping!

Map of the Week: Mob-Media: Lynching and the Press

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This past week, the NYTimes posted an extended piece on mapping county-level lynching data, a topic of interest to some of our academic users and in particularly, Michael Weaver. Michael is a Ph.D candidate in Political Science at Yale University, where he investigates the causes and consequences of ethnic violence.

His dissertation is on how the changing nature of publicity helped turn Americans against lynching, and this week, his Torque map is our Map of the Week. Read on to learn about his research in his own words.

Lynching

On April 23, 1899, Sam Hose, a young black man, was lynched by a crowd of hundreds in Newnan, Georgia. Several days earlier Hose was accused of murdering his employer and raping his employer’s wife. When he was captured, a large crowd gathered and special trains were chartered to bring him and to the county jail. Despite the pleas of former Georgia governor William Atkinson to respect the rule of law, the mob dragged Hose to the outskirts of town, tortured and burned him to death before more than a thousand onlookers.

This event was not unique; dozens of so-called ‘spectacle’ lynchings, in which the victim was tortured and killed before a large crowed, occurred. More broadly, historians estimate that well over 4,000 people died at the hands of lynch mobs between 1880 and the 1930s, the vast majority of whom were African American.

This map, produced by the Tuskegee Institute, shows an earlier attempt to map lynchings by county from 1900 to 1931:

Tuskegee Institute Map

This map appeared recently in The New York Times, showing the number of lynching victims by count

New York Times Map

I, like many today, had associated lynching with ugly racist violence done in secret. In fact, lynchings were often committed the open, sometimes widely attended, commemorated in postcards and songs, and reported in local and national press. Press accounts often justified or defended lynching. Almost always, lynchings were recounted using archetypal narratives that cast black victims as both guilty of some crime and subhuman. Because newswire services depended on local journalists for stories, these local justifications for lynching were disseminated across the country and appeared in even urban Northern papers like The New York Times. Across the country, the public sphere was filled with arguments and narratives that justified lynching as expressions of popular sovereignty, an acceptable alternative to corrupt and inefficient courts, and a necessary deterrent to ‘black criminality’.

Front page of the The Macon Telegraph, from April 24, 1899.

Between 1890 and 1930, a there was a sea-change in public opinion about lynching. While local support for lynching may have persisted in many places across the South, the national public debate turned decisively against lynching. The previously unimpeachable reputation of the mob came into question. Newspapers reported that the crimes of the lynch mobs equaled if not exceeded the alleged crimes of the victims. Victims of lynching were no longer excessively dehumanized and presumed guilty. In time, the vigilante acts came to be seen as scandalous breaches of law and civilization, and drew national and international outrage and scrutiny.

Two things struck me about this history: on one hand, I was horrified to see how lynchings had been lauded or defended. On the other, I was left asking: How did this moral revolution against lynching take place? In my dissertation, I attempt to understand how public debate turned against lynching. To answer this question, I need to know where, when, and how the press was talking about lynching. This blogpost is about mapping the where and when.

Getting the data

Today, public debates embedded in newspaper articles, blog posts, and tweets all originate in a digital format, making them relatively easy to find and use example. I wanted to capture the dynamics of a public debate that started more than a hundred years ago and was recorded on paper.

Luckily, several different archives are engaged in large-scale scanning and digitization of historical newspapers. Proquest, Readex, NewspaperArchive, Newspapers.com, and Chronicling America. While the purposes of these archives aim at different audiences, from the general public, to academics, to family history buffs, they all provide functions to search the newspaper text. Each of these archives contains issues from dozens to hundreds of newspapers.

An example of search results from Chronicling America

In total, these archive contain well over 2,000 newspapers between 1880 and 1940, ranging from big-city dailies to small rural weeklies. To search these newspapers, I wrote Python scripts to submit search queries and collect the metadata for matching articles. I made extensive use of the requests module to access sites that required logging in and BeautifulSoup module to extract data from the page html.

You can check out the code for scraping Chronicling America here.

While each site provided slightly different metadata on each search result, I was able to extract the:

  1. Name of the newspaper
  2. The place of publication
  3. Date of publication

Because I was scraping this data myself, I cleaned the location and date data as I went. Finally, once the data were collected, I geocoded the newspapers. To speed this up, I identified unique city-state pairs and used GEOLocate and the Google Geocoding API to geocode these unique locations.

The data presented here show newspapers that make explicit references to lynching: lynching/s, lynched, lynches, and lyncher/s. While I could have included other terms used to describe lynching or “lynch” by itself, these terms would mostly likely have capture too many false positives. For instance, searches for “lynch” often yield hits for the last name or Lynchburg, Virginia.

One advantage of the scripts I have written is that I can easily expand this initial data by searching for other keywords related to lynching - such as pro- and anti-lynching arguments - or keywords related to other historical questions.

Mapping the data

This search for explicit mentions of lynching yielded approximately 1.2 million articles. With this data, I could start to see where and when the press addressed lynching as an issue.

Given the spatial and temporal dimension to the data, creating a Torque visualization was a natural choice.

I made a few aesthetic choices to make it easier to see patterns in the data.

  1. I gave the markers slightly longer trails. Because I have daily data over 60 years, even with a long animation, markers without trails disappeared too quickly to see any patterns.
  2. I chose a low opacity to make it possible to see where there was a greater intensity of publications about lynching.
  3. Finally, in early versions of the map, the daily nature of the data resulted in a synchronized pulsation as every location lit up at once. This was distracting. To remedy the problem, I simply “jittered” the data by adding a random number of minutes from 0 to 1440 to the date and time of the publication. This yielded a more fluid visualization without substantially altering the underlying data.

What can we learn

A few things are immediately apparent when looking at the map.

  1. The digitization of newspapers is not uniform in space or time. Some states, such as Indiana, Kansas, and North Carolina have had far more newspapers digitized than others. After the 1920s, the number of digitized newspapers drops precipitously. One way to address this problem is to visualize all newspapers that are searchable on a given day as well as which print something about lynching. I have collected this data and will soon test various ways of visualizing this.
  2. Lynching was in the press extremely frequently. During the 1890s and 1900s, lynching seems to have been in many city papers weekly if not daily. One awful implication of this is that African Americans were not just subject to the physical violence of lynching, but also to a constant barrage of news and debate about these killings. This experience must have been unbearable. Conversely, white Americans had to have been very aware of this pervasive violence.
  3. It is also possible to see the dynamics of major lynching events. While larger cities seemed to see a steady stream of articles mentioning lynching, sometimes a story would sweep the nation and reach far into the hinterlands. This drives home one similarity between the historical debate about lynching and the current debate of policing and racial violence: these events gripped and polarized the entire nation.

Future Steps

This is a project still in its infancy. Obvious next steps include mapping where newspapers did not publish about lynching as well as the sites of lynchings and attempted lynchings. As I am able to collect more data using my search scripts, I will be able to use layers and color schemes to visualize whether articles took on a pro- or anti-lynching position, and possibly match articles to particular lynching events.

It is high time we had an answer to this question: why did lynching, a widespread and accepted practice of local “justice”, suddenly become a national scandal and eventually come to represent one of the darkest chapters in the story of race relations in America? I hope that bringing “big data” into the past will help answer riddles about lynching and race violence that have never been properly addressed.


Thank you, Michael, and thanks for reading! You can learn more about Torque in our CartoDB docs and tutorials, in the Torque sandbox and on Github. Feel free to message Aurelia if you have any questions about this post or want to get in touch with Michael!

Happy Mapping!

Fedor Baart: The Science of Escape from Alcatraz

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With this third installment of our Developer Interview series, we welcome Fedor Baart to join the discussion about how scientists and developers using CartoDB for research and geospatial science!

Recently, Fedor and his team used cartoDB to create a water current simulation to determine if the infamous 1962 Alcatraz escapees could have survived. Using currents data from the appropriate date and time, and releasing 50 virtual boats from various possible launching locations on the island every 30 minutes. Over half a century after the escape, they determined that survival for the men was possible - If they set sail between 11 PM and midnight. Check out the Washington Post article here!

Fedor is a specialist in computer simulations at Deltares, an independent institute for applied research in the field of water, subsurface and infrastructure.


What are your CartoDB powered projects?

This was my first project where I used CartoDB. I had tried CartoDB and advised it to some of my colleagues because it’s very easy to generate a beautiful annotated map based on your own data.

I normally create very custom maps. We have developed a cloud based platform for running interactive hydrodynamic computer simulations. There I use technologies like:

Why did you choose CartoDB for your geospatial projects?

For the Alcatraz animation I thought I’d try CartoDB. I had seen how nice the visuals can be when using the torque framework and wanted to reproduce that. CartoDB uses several visual effects that make particles floating around very attractive.

For example, when particles swarm together in a tight location they are hard to separate. A common technique is to use transparency to give a sense of density. With CartoDB you can use opacity but also make particles light up if the opacity is not enough to show the range in density. That gives a nice high tech look to the animation, similar to throwing glow sticks in the water .

What, as a developer, do you value most about CartoDB?

What I really like as a researcher is that I can share the animation and the corresponding dataset. Open data is very important in research. It allows others to check your work and continue upon your research.

Deltares, where I work, is an open source institute so we tend to prefer to work with open source software. When I see something missing or broken in the software I can easily add or fix it and contribute it back. With commercial software you often have to wait for weeks or months for things to get fixed. That allows you to continue working and not having to work around things.

If you would have to explain to a fellow developer what CartoDB’s best feature is, what would it be?

I was impressed by the performance of CartoDB. Together with the other researchers, Olivier Hoes and Rolf Hut, we presented our results for national television at the eScience Center video wall, which is a 8k resolution 5x2m screen.

The framerate hardly dropped. I don’t think that that would have been possible a few years ago.


Thank you Fedor and Deltares for a fantastic interview, an amazing map, and for taking the time to share your experiences. If you are a geospatial developer interested in a modern platform to develop on, take a look at this intro presentation: CartoDB for Developers.

If you are already developing geospatial products using CartoDB, take a look at our Developers Program, and stay tuned for more developer interviews. And if you’d like to share your experiences, please write to stories@cartodb.com.

Happy Mapping!

Introducing CartoDB static maps

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If you missed our Valentine’s Day blog post you may have also missed that CartoDB now has the ability to generate static images of dynamic maps from your accounts. Now we’ve added the capability directly to your CartoDB Editor. From any visualization, quickly generate static images to embed in your presentations, share over email, or anything else your heart’s desire.

The cool thing about the Static Maps API is that you aren’t limited to only using it from your CartoDB Editor, but you can use it directly from our API or integrate it into your website using CartoDB.js. We know you’ll love this litte feature as much as we do!

Happy Mapping!

New plugin using CartoDB maps in Cesium

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Putting beautiful and dynamic maps onto a 3D globe has never been easier. Using a little JavaScript, you can now put your favorite CartoDB visualization on a 3D globe. The awesome open source JavaScript API Cesium, authored by AGI, renders 3D maps in the browser using WebGL.

To help you leverage the power of Cesium combined with CartoDB, we have release a CartoDB plugin for Cesium. By combining CartoDB.js’s Core API functionality with Cesium, you can now make a map like this with your CartoDB data. Want to see more? Explore our little gallery of demos.

Now the sky is the limit!

Cesium + CartoDB

Do you recognize that basemap? Yep, it’s our wonderful Positron basemap but on a globe!

Do you love open source software? We do!

Happy Mapping!

CartoDB at the MWC - The Next Generation Mapping platform will be Open Source

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People looking at their phones

From March 2-5, we will be at the Mobile World Congress in Barcelona showcasing our latest developments in geospatial platforms and other mapping technologies. The CartoDB team will be ready to engage in and demonstrate the use and efficacy of location-based services and maps—a considerable part of the mobile experience.

Apart from learning about CartoDB, don’t miss ‘The Next Generation Mapping platform will be Open Source,’ a panel we are hosting with some of the most influential people in the mapping industry. The panel will be on March 4 at 3:30 p.m. in the presentation area of the Spanish Pavilion (Congress Square CS60).

People looking at their phones

In the mobile industry, location and mapping are key features; location- based services and location analytics are becoming increasingly central to business intelligence. And at the heart of mapping, open source is winning. Together with open data, open source data is redefining what the future mapping platform will look like, and we are thrilled to present an incredible panel of speakers who are defining this future.

About the panelists:

Randy Meech

Randy Meech is CEO of Mapzen, an open source mapping lab based in New York City. Mapzen builds mobile apps and services using all open software and data, and is working to provide collaborative solutions for geocoding, navigation, and vector rendering. Moving between startups and larger companies through his career, Randy worked at Google followed by a number of startups, one of which sold to AOL. At AOL he led the engineering team at MapQuest, focusing on OpenStreetMap tools and services. He holds a master’s from Harvard and a bachelor’s degree in English literature and history.

Eric Gundersen

As CEO of Mapbox, Eric coordinates product and business development. Eric is passionate about open data and building open source data visualization tools focused on speed and design. Prior to Mapbox, Eric co-founded Development Seed. Eric is a recognized expert on open data and open source software and has been featured in publications including The New York Times, Nightline, NPR, and others. He is frequently invited to speak on topics including open data, data visualization, and open source business models and has presented at conferences such as SXSW, Web 2.0, Where 2.0, GOSCON, and NodeJam. He holds a master’s degree in international development from American University in Washington, D.C., and has a bachelor’s degree in economics and international relations.

Tyler Bell

Tyler joined Factual in 2010 as VP of Product, where he leads the company’s initiatives in Mobile Location, Geo Technology, and Audience Targeting.

Before joining the Factual team, Tyler led Product for Yahoo’s Geo Technologies Group. Tyler has broad interests in place-based information systems, mobile technologies and personalization. He blogs occasionally at http://strata.oreilly.com/tylerb and tweets more frequently at https://twitter.com/twbell.

Tyler received his PhD from the University of Oxford, and is a former archaeologist.

Javier de la Torre

Javier de la Torre is the CEO of CartoDB, a global startup democratizing data analysis and visualization on maps. He is a former scientist with a research focus on biodiversity informatics and global environmental change, and is a recognized expert on open data, open source software, and data visualization.

CartoDB’s presence this year puts us on the edge of innovation. If anything is happening in mobile, it can be found at MWC—a truly global event.

You can find us at booth number 40 in the Spanish Pavilion (Congress Square CS60)

Happy World Radio Day!

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World Radio Day was celebrated around the world last week in acknowledgment of the impact and importance of radio. We’re late to the party, but couldn’t think of a better way to celebrate the importance of radio than with a torque heatmap of Low Power FM radio stations going on the air - tracking the expansion of LPFM service from 2000 - March 2011 with data provided by the FCC.

In what ways is Low Power FM radio, otherwise known as independent or community radio, so important? Jason Sigal, who has been involved in independent radio since 2002, most recently at WFMU, emphasizes how important it is to have, “centralized places to broadcast local ideas, local music and local news” in a time when, “we have so much choice in what we could spend time listening to.”

Jason got involved with independent radio in high school, “because there were these other kids who were my age who knew about all this amazing music and cultural things and they learned about it by hanging out at the radio station.” Low Power FM radio stations fill a void building community and sharing local news.


Beyond Potholes: Data you can collect with Fulcrum

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Fulcrum, which allows you to collect data in a distributed way on mobile devices, is popular among experts in disaster recovery, environmental management, real estate, and other fields where quick, distributed data gathering is critical.

It’s easy to sync your Fulcrum-collected data with CartoDB, and you can learn more about Fulcrum in our March 18 webinar.

But there are also plenty of lesser-known uses for Fulcrum, such as:

Siberian craters

Dozens of giant holes have ‘appeared’ in the Russian hinterland recently, raising some alarm. What made them? Where will they appear next? How do I avoid falling in one?

With Fulcrum, you can collect data anywhere, even offline. So when you return from outer Siberia, your crater measurements and other observations will be safe and synced.

Microbes around town

After some serious research, it turns out the New York City subway is filthy. But how does your city compare?

If you’re a researcher swabbing city infrastructure for germs, accuracy during lengthy, labor-intensive collection projects is pretty important.

Fulcrum automatically location- and time-stamps your data, so you can ensure you’re getting accurate information from your sleep-deprived grad students.

Doing bike counts

Is your local bike advocacy group still using paper checklists? You know, the ones that always seem to come back incomplete, or with coffee stains on them?

Because Fulcrum’s mobile surveys are so flexible, you can limit input to the specific types or options you need, so it’s easy for any of your volunteers to get started.

Film location scouting

Parking space large enough for Michael Keaton’s ego trailer? Check. Good dive bar nearby? Check.

Collect video in Fulcrum, and hold onto data from multiple scouting projects, so that it’s easy to look back through your location options for your next blockbuster.

There are a million other uses for Fulcrum, and the March 18 webinar will walk you through all the features. We’re excited to see what you come up with!

Geobeers at Mobile World Congress

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The Geobeers will be taking the Mobile World Congress by storm on Wednesday 4th at 8 PM! A few mapping companies will be at Mobile World Congress and we thought it would be a great idea to get together to talk and have some beers.

People from Mapzen, CartoDB, Mapbox, and Factual will be around and we are inviting anyone else to meet us to talk about the present and future of mapping. The event is organized by the local group #geoinquiets. Geobeers will start at 8PM until… well, we will see.

We are grateful to our host Itnig!

Geobeers meets at: Carrer Àlaba 61, 5-2 Barcelona, Spain (see map above)

See you there & Happy Mapping!

Music Map Mashup

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When Sade sang in ‘Smooth Operator’ – “Coast to coast, LA to Chicago” – she obviously hadn’t consulted a map.

For starters, L.A. - Los Angeles (not to be confused by the abbreviation of Louisiana, a southern U.S. state) is on the coast but what about Chicago? Only if you count the coast of Lake Michigan.

After my careful scrutiny of Sade’s entire discography, I began to wonder about how I’ve been using geography to engage with music. In recent conversation with a friend, I came up with a not too accurate theory on the origins of American Jazz. It is surprisingly global and geographically spatial. My colleague Javier Arce from CartoDB is one step ahead of me with his awesome Spotimap.

Javier cataloged on his Spotimap, 7,681 songs and 212 cities across the globe using the songs listed in the Wikipedia article “List of songs about cities.”

To create this map Javier extracted a list of the cities with their respective countries and created a table. Then he geocoded that table to get the position of each city on the map.

Next, he extracted all the song information in the main article using regular expressions and infinite amounts of patience. It generated a CSV file that he imported into his CartoDB account. Javier ended up having a table that contained the name of the song, the author, and the city.

He repeated the same process for many of the cities listed in the article that have their own page. For example, Berlin. This was a little tedious because each list has a slightly different formatting. Javier had to modify the regular expression or fix some mistakes by hand and in some cases used Open Refine to spot and correct problems with the data.

After that process was finished, Javier got two tables. One for the songs and one for the cities:

spotimap-songs
spotimap-cities

Finally, Javier used the CartoDB JavaScript library cartodb.js, the Spotify API and their Play Button Widget to create the map.

The styling is pretty simple. There are just two layers. One for the cities, indicated by a green, beamed eighth note icon and another one with the countries (which is a Choropleth map created with the CartoDB wizard).

And the geospatial queries are very straightforward too. Since both the ‘songs table’ and the ‘cities table’ use the notation for the name of the city, Javier used that as a key to join both tables:

SELECT cities.* FROM spotimap_citiescities, spotimap_songssongsWHERE songs.city=cities.cityANDsongs.availableISNOTfalse

You can find all the information related to the map, the sources, and the code on his GitHub account: https://github.com/javierarce/spotimap.

CartoDB + Plotly + IPython Notebooks

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Earthquake Magnitude vs. Depth

CartoDB, Plotly, and IPython notebooks work beautifully together. The plot above was made on Plotly from data imported into an IPython notebook using the CartoDB SQL API.

Plotly is a cloud-based graphing and analytics platform with Python, R, & MATLAB APIs where collaboration is easy. Using Plotly with CartoDB’s SQL API leads to endless possibilities.

Together with Matt Sundquist at Plotly, I’ve made an IPython notebook that allows the following data flow: CartoDB’s SQL API → Python pandas dataframe → beautiful plotly plots. Because of IPython’s rich display system, you can also easily embed your CartoDB maps into IPython notebooks.

Head over to Plotly’s website to see the notebook that Matt and I made.

We’re excited by how easily CartoDB and Plotly work together. Watch this space for more experiments between the CartoDB and Plotly teams.

Happy Mapping and Graphing!

We are buying pizza for a world... of map makers

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Maptime

Take a look at the nice little post over on Maptime blog. Basically, we get nice tweets from Maptime members around the world pretty much every week. So we wanted to say thanks. And maybe the global equivalent of a group hug is to just all bite into a pizza at the same time. Feel the warmth :)

Keep the maps coming!

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