According to an article written by esteemed musicologist Chris Brewer, we unconciously use music to develop the pyschology of our moods. That is to say, we use music to indicate love or heartbreak, to dance, to bring back memories, and to help us relax. Music is a powerful provider of individual, personal expression that situates, frames, or even locates important experiences. Simply put, music can be highly effective in enhancing our everyday lives.

Recently, Spotify, located the power of song with its Musical Cities map, an interactive data visualization that sets distinctive playlists to over 1,000 cities across 59 countries.

“Distinctive music,” explains Eliot van Buskirk, Data Storyteller for Spotify, “is music that people in each city listen to quite a bit, which people in other cities do not listen to very much. So it is, exactly, the music that makes them different from people everywhere else.”

Does this sound a little familiar? That’s because in 2015, Eliot made this Musical Cities map. That map was a huge success and generated a ton of traffic, to the tune of millions of visitors. The global brand for music streaming decided to relaunch this visualization with custom branding and even more hits, collected from user data around the world.

The data is derived from 23 billion listener/track relationships and uses our Google Drive Connector to create a map with idiosyncratic, 100 - song playlists for cities around the world using a basemap customized to align with Spotify’s unique branding.

Spotify’s Musical Cities map provides users with a lot of information on international music tastes, but here are five additional ways to start navigating these global sound waves:

• Listen to the distinctive music of an upcoming travel destination
• Pump up the volume of bookings with music that reflects popular locales
• Infuse your playlists with international notes
• Book musicians with local appeal
• Grow business demographics along musical scales

Our collaboration with Spotify has also been an exciting opportunity to expand the meaning of location intelligence. Transforming data on aural behaviors, such as music streaming, into visual information redefines the meaning of “where,” while also pioneering the next generation of location intelligence.

CARTO has also started a CARTO Tunes playlist featuring songs with lyrics that relate to maps, directions, and geography. Check out CARTO Tunes. Did we miss an obvious song? Let us know by tweeting us recommendations @CARTO with the hashtag #CARTOtunes.

The Yeah, Yeah, Yeahs may not love “Maps”, but you will after hearing songs from around the world with Spotify’s Musical Cities map.

Happy Data Mapping!

Today we are excited to introduce CARTOColors.

CARTOColors is a collection of intelligent color schemes that allow you to transform your raw data into actionable insights. Insights that help with decision making, foster exploration, and highlight the important stories in your data.

Background

Color use on maps has been researched by cartographers for decades and is one of the most important forms of map communication. Choosing the right colors based on your data aids storytelling, engages your map reader, and visually guides people to uncover interesting patterns that could otherwise be missed.

Well-known standards like ColorBrewer have defined best practices for color use on thematic maps. Using these foundational pieces as building blocks, we created a set of custom color schemes that are optimized for the web, CARTO basemaps, and thematic maps made with Builder.

To explore each color scheme in more detail, check out our CARTOColors landing page.

CARTOColors in Action

CARTOColors are available to use right now in Builder. Based on the type of map you are making, we apply a default CARTOColor scheme. The schemes are broken into three categories: sequential and diverging for numeric data, and qualitative for non-numeric data.

Below are some examples of CARTOColor schemes on a variety of maps made with Builder.

Tree Types at Sloans Lake

The map below colors each tree at Sloans Lake in Denver, Colorado based on its type and sized by its diameter. Because we are displaying categories (type of tree) we are using a CARTOColor qualitative scheme to assign a unique color to each tree based on its type.

Qualitative Schemes

County-to-County Commuter Flow

This map shows the county-to-county flow of commuters in New York state. Because we are showing amounts (number of commuters), the map uses a CARTOColor multi-hue sequential scheme. The scheme has been flipped for use on Dark Matter to increase contrast. These decisions help distinguish commute patterns in the state. Light colors indicate flows with a large number of people while flows with less people are pushed to the background using darker colors.

Sequential Schemes

Ocean Temperatures

This map visualizes ocean temperatures using a CARTOColor diverging scheme. Cool colors indicate where temperatures are low transitioning to warm colors for higher temperatures. The subdued yellow is used to provide a generalized view of where shifts in ocean temperatures begin to happen.

Diverging Schemes

Car Crashes in 2015

The map below shows the density of car crashes that occured in 2015 using Builder’s Hexbin aggregation method. The coloring is based on density and uses a CARTOColor aggregation scheme. Aggregation schemes are a type of modified sequential scheme. These schemes are multi-hue and use colors with more saturation. With aggregation schemes, light colors represent high density and dark colors low density.

More to Come

As demonstrated in the maps above, CARTOColors used in conjunction with Builder, provide users with intelligent color schemes with best practices built-in. This in turn helps reveal patterns more quickly in your data, leading to faster insights.

In the coming weeks, we will take a deeper dive into how to best use CARTOColors, the design methodology of the schemes themselves, and more interesting tidbits that might not be noticeable at first glance!

Happy Map Designing!

There is no denying the increased potential of efficient, smart cities through the collaborative efforts of municipal governments, citizens, universities, and innovative businesses. Just last year, President Barack Obama’s Administration announced a new Smart Cities Initiative to invest over $160 million in research, at home and abroad, to help cities tackle key challenges in sustainability and efficiency.

This year, Harvard’s Technology and Entrepreneurship Center brought together a diverse group of academics, entrepreneurs, and leading companies, including our friends at Telefónica, Angel Ventures, Citi, and Yahoo! to discuss opportunities and challenges in the creation of digital prosperity across Latin American cities.

The two day Strategic Innovation Symposium: Digital Life in Latin American Cities, held in Miami, focused on embracing technology, initiatives to enhance confidence in digital infrastructure, and the Internet of Things (IoT). Key learnings from the symposium were gathered into the white paper, Digital Life in Latin American Cities to inform global policy decisions that support local economies and community initiatives.

Successful approaches by Mexico City, Medellín, and Buenos Aires have helped to solve challenges, embrace opportunities, and create a better society through technology.

A very strategic component of success for these aforementioned cities is location intelligence. As Community Development Strategist and contributing author to the Digital Life in Latin American Cities white paper, it is evident the increasing importance of solutions like CARTO, which enable governments, businesses, and citizens to leverage open data, regardless of individual levels of technical expertise. Cities depend on spatial data visualizations and analysis as a mechanism to demonstrate transparency, ensure accountability, and increase livability.

CARTO represents the massive potential to turn diverse and complex data into actionable insights, while empowering all city stakeholders to make better decisions and create value in all the key sectors that help operate and sustain today’s cities.

Now is the time to engage industry and government leaders to drive policies that will present solutions to challenges in order to create digital prosperity for global cities. We are very proud to have taken part in the symposium and we look forward to further collaboration with innovative thinkers and doers in the future.

Happy data mapping!

Indoor maps often direct users to emergency exits, which has limited our context of mapping to external geographical spaces. With the rise of Indoor Positioning Systems (IPS), however, the field of data visualization is turning inward to pioneer new paths to purchase with indoor maps.

Situm, a member of Telefónica’s Open Future initiative, and known as the “GPS for indoor” start-up, analyzes indoor traffic for various sectors using location intelligence. Despite an exponential rise in mobile purchasing, the Department of Commerce reports that 90 percent of retail purchases are transacted offline, which means managing in-store traffic is crucial to maintaining a competitive edge. But aside from providing directions for customers, what, exactly, can IPS offer? Well, as we learned during a recent collaboration with Situm, the answer is a lot.

Situm and CARTO partnered to create an application visualizing the flow of foot-traffic inside a shopping mall. Checkout the image below. Notice the darker points? Those points indicate high volumes of consumer traffic throughout the indoor mall:

Additionally, users of the application can answer crucial business questions for strategic store planning, management, and security based on operating hours, amplified by the temporal scrub bar.

The core technology behind Situm is a multi-sensor data fusion algorithm created during seven years of research and development in mobile robotics, using state of the art AI techniques. All the information that a smartphone is able to capture is used to improve location accuracy and detect a user’s or object’s position.

Think about it. There was a time when businesses were satisfied with a certain level of mapping behavior. For these organizations, using isolines or other types of LDS was especially beneficial in determining where to place malls, hospitals, or additional operations. Businesses could establish how long it took to go to various location points via walking or driving using spatial data for strategic analysis and intelligence. This type of intelligence was essential for setting competitive prices, optimizing your distribution channels, or knowing your target audience.

But what if you could take those insights a step further, inside your establishment? What if you could offer your clients optimum analysis on traditionally unseen patterns and trends? With Situm and CARTO you can go from location (data) to intelligence (decisions).

Situm’s positioning service is open for a free trial to anyone who registers. And CARTO, which can be connected to Situm, is uniquely situated to support the visualization of indoor positioning data through the enhancement of location intelligence.

Happy indoor mapping!

Zika, a virus that can lead to neurological complications, presents serious public health challenges to millions of people in nearly 50 countries. To confront these challenges, however, the development community has enlisted CARTO’s location intelligence services.

In the last decade, cities and countries have greatly improved their capacity to document new cases of communicable diseases in real time. Data only truly becomes useful once leveraged with data visualization, location intelligence and analytics tools. A comprehensive spatial analysis of the current impact and future threat is an important part of the efforts being made to minimize Zika’s impact, prevent the disease from spreading, and prepare at-risk communities. Zika is transmitted not only by mosquitos but also through sexual intercourse, thus increasing the likelihood of rapid transmission and an epidemic. Women of childbearing age and pregnant women are high-risk portions of the population as Zika causes birth defects in children.

A holistic approach to addressing Zika relies on engagement between international development organizations, local and federal level public sector agencies, and public health experts equipped with the latest technological tools and most current data. The Inter-American Development Bank organized the Alerta-Zika Hackathon in Rio de Janeiro, Brazil earlier in December. The event engaged students and experts alike in the fields of epidemiology, technology and public health to leverage data, location intelligence and other analysis tools to derive new insight about Zika’s impact on communities in Rio de Janeiro. Brazil has more confirmed cases than any other country and Rio de Janeiro has been of particular concern since the city received millions of visitors during the Summer 2016 Olympics.

The Bank teamed up with FGV/EMap, Municipal Health of Rio de Janeiro, Rio Lab, PUC Rio, Amazon Web Services, and CARTO to collaborate on ways to predict possible transmission routes using available data and spatial analysis. The Hackathon was the beginning of an important multi-stakeholder collaboration, which will hopefully yield new findings about the past, present, and future of Zika. The spatial implications of the disease and its future are crucial for predicting where it might spread and how to properly prepare communities. Incorporating census and demographic data into the analysis can help prioritize the allocation of resources to these vulnerable populations. To sort through these types of datasets during the hackathon, Team Z3O2, turned to CARTO. The team members included Eduardo Reis (Machine Learning), Gabriel Ligneul (Programming Language), and Sasha Nicolas (Computer Graphics) the latter of whom stated:

We modeled a neural network (NN) to predict future nearby cases based on patients in a neighborhood. After having this NN established, we will develop a stochastic simulator to create a scenario of a Zika outbreak. The simulation will give us an overview of the spread of the Zika epidemic in order to plan ahead the whole outbreak, and the NN predictor will give authorities spots in the city they should be applying containment actions.

We are proud to announce that team Z3O2 placed second in the competition, and again demonstrated our belief that democratizing location intelligence will help us understand and solve today’s problems. The lessons learned in Brazil, moreover, will be expanded upon in future hackathons throughout the region, and we look forward to continuing our engagement with communities, businesses, governments and organizations in Latin America, the Caribbean, and the United States.

Stay tuned to see where CARTO and the Inter-American Development Bank head next to fight the Zika virus in Latin America.

Hapy Data Mapping!

Solid GEAR solves drivers’ refueling conundrum– drive less but pay more at a nearby gas station or drive more but pay less at a distant station–with the new Petrol App.

Petrol App, an iOS application locating nearby gas stations that helps users save, is the first venture between CARTO and Solid GEAR drawing upon both companies expertise in Mobile SDK and mobility, respectively.

Solid GEAR developed an algorithm using geodata to calculate a user’s distance from fuel stations, gasoline prices, and the rate of fuel consumption by vehicle type to determine recommendations. CARTO’s Mobile SDK provided back-end support including a routing API that charts possible directions for users, online/offline mapping, daily data sync with Spain’s Ministry of Energy for up-to-date gasoline prices, and the capacity to visualize a dataset consisting of over 9,000 stations nationwide on one basemap.

Mobile apps exist for drivers looking to find cheap gas prices, but what sets Petrol App apart from competitors is its holistic understanding of saving. Our Mobile SDK enables Petrol App users to account for various factors while determining a destination that can save time, money, and energy. Petrol App also allows iOS users to

• Compare gas prices region-by-region across Spain
• Filter data of national gas stations to display by brand
• Rank nearby stations according to distance, price of gasoline, travel cost to station, etc.

Solid GEAR, as a telecommunications start-up providing mobility software development and consultancy services, understands that the value of geodata is in crafting customized services. This ethos, in fact, resounds in the company’s business practice known as the “Solid GEAR Method,” a customer-centric listening practice. We’re thrilled that our Mobile SDK could help meet those needs in the form of the Petrol App, and we look forward to collaborating on geodata projects such as this to enhance user experiences.

Happy Mobile Mapping!

The Cajamar Group finds shared interests between the financial sector and data scientists worthy of future investments with the help of location intelligence.

One of Spain’s premiere financial institutions, the Cajamar Group serves the banking needs of four million clients across 1,200 branches, has found that location intelligence bolsters productivity across their organization’s various departments. The Business Analytics Team, for instance, found CARTO to be an asset in managing Cajamar’s Strategic Branch Optimization Plan. Maintaining optimal performance at current branches while also locating areas in which to expand requires studying both micro and macro level geodata, a process made simpler through data visualizations. Our platform’s easy to integrate software helped the Business Analytics team develop dashboards whose intuitive design allowed colleagues without a background in GIS training to collaborate across various departments.

“CARTO has improved our productivity,” explains Antonio Font Pérez, “and also has given more visibility to our work, internally and to our clients.”

But Cajamar is also collaborating beyond the banking and financing industry with its Cajamar Data Lab. Cajamar Data Lab recently hosted a Python Hack, which tasked contestants with visually representing 890,610 card transactions across Almería. The winning submission in the Card Category Analytics competition, from StyleSageMapppers, used CARTO to create a data visualization of consumption patterns across the province. In the image below, for example, StyleSageMapppers’ data visualization maps transactions across the region, and with the widget dashboard viewers can explore the dataset by areas of interest.

We’re delighted to see collaborations such as Cajamar Data Lab because it reminds us all of how geodata informs a growing number of day-to-day operations across many industries. Can’t wait to see what collaborations 2017 has in store!

Happy Data Mapping!

Deeply understanding and visually exploring the complex data of a city is key to understanding how to make timely and effective decisions. It is essential to how we improve the lives and well-being of residents. Data visualization allows for insights into the progress being made, the challenges that remain, and where important decisions must be made.

New York City has been a long-time champion in data management and civic innovation, regularly pushing the envelope for building a better future through leading data collection and optimization practices. Because of rapid advances in government and technology, it has become increasingly important for decision makers and their teams to rapidly make sense of, and act on, the data being generated across agencies and by its residents. The rapidly changing nature of today’s data challenges, and New York City’s commitment to leading the pack in data and analysis for government, is in part why vizzuality and Hyperakt have developed New York City’s new real-time data dashboard powered by CARTO. The dashboard puts key city indicators from a wide range of data sources at the fingertips of City Hall. Showing a wide variety of city indicators including up-to-date crime statistics, service provision performance, health figures, infrastructure project updates, public works, 311 data, environmental indicators, housing and homelessness statistics, and many others, the dashboard allows for easy monitoring of changes to these indicators across both spatial and temporal dimensions.

Created in partnership with the New York City Mayor’s office, the dashboard is tailored to tackle the increasingly complex data needs of modern government. This includes features that enable the city to add, update and synchronize social, political, human development, environmental and economic indicators in an easy and efficient manner.

Using location intelligence platforms enables the Mayor's Office of Operations to generate actionable dashboards to manage NYC more efficiently; building on our robust performance management and data collection practices to offer a better service to our citizens

James Perazzo, NYC Mayor’s Office of Operations

In order for the New York City Mayor’s Office to have a clear understanding of the city day to day, it was important for the dashboard to pull in data from a wide range of city agencies. Agency data available in the dashboard includes indicator data for everything from the New York City Housing Authority, to the NYPD, to the Department of Housing Preservation & Development and many others.

This powerhouse of up-to-date data and indicators is now available in one place in a variety of visual formats. From anywhere, city hall officials can understand the city numerically, in charts, and in dynamic interactive maps. Versatility in how the data is presented allows for the visual language of the dashboard to quickly convey clear insight to decision makers and City Hall employees.

This insight can quickly be translated into action that saves the city large amounts of both time and money, while establishing a common ground to measure and improve how the city operates. Residents of New York are positioned to benefit from these improvements massively, as the city can now identify and act on important situations in specific parts of the city unlike ever before.

In addition to the near real-time insight presented, the interface enables officials to take a deeper look into data trends and progress on specific agency goals. With a few clicks, officials can compare the current state of the city across various time intervals. From trends this year, to understanding how the city currently compares to last year, to quickly identifying short-term changes by day, week, or month, the New York City Mayor’s dashboard makes it easy for patterns and trends to be discovered and acted upon rapidly.

Included in the dashboard are numerous features such as the option to set up notifications at various indicator thresholds, and the ability to click and send indicators to other city officials in a matter of moments. Temporal trends are now easily accessible in indicators and include graphs of past city performance indicators at both a city and district/borough level. These features help officials understand and share insight quickly, drastically improving communication workflows and efficiency. Residents of New York are positioned to benefit from these improvements as the city identifies and acts on important situations in specific parts of the city as they happen.

The functionality and design of the dashboard powered by CARTO allows for degrees of insight and communication that allow us to streamline city operations like never before.

James Perazzo, NYC Mayor’s Office of Operations

The New York City Mayor’s Office dashboard allows for previously difficult levels of urban understanding to be reached. This solution is leveraging NYC’s already robust performance management and data collection practices in incredible ways, and the impact of these innovations shape the ways in which we think about and define the next iteration of modern government. As we strive to create the future of location intelligence, we also become the instruments that shape our urban futures.

Happy Data Mapping!

The location intelligence industry experienced steady progress in the last twelve months, from a surge in business platform integration to advances in indoor mapping. The growth that we’ve made would not have been possible without the continuous support, and fervent momentum, of our amazing Partners. We’d like to thank our expanding Partners network for their unwavering support throughout 2016.

During the year, our company acquired Nutiteq, rebranded, and introduced Builder. In that time our network of Partners increased from 90 to 160. This led us to hire more Partner managers, a team now composed of Tony Ferreira (LATAM), Isabel Gárate (EMEA), Joe Pringle (NA), Fernando Carrasco (APAC), and most recently Tim Marston (UK).

Our Partners’ diligent outreach and promotion helped expand our international presence to more than 44 countries.

Here’s a small sampling of recent work from our Partners:

• inAtlas helped INFORMA add a location intelligence component to their ecommerce services in Europe.
• Geographica introduced CARTO to the Universidad Complutense de Madrid’s Cultural Landscape Research Group.
• Usabledata brought our platform to Nepal’s financial sector.

One resolution we have made for 2017 is to continue to support our Partners by offering more training events, workshops, and webinars to help ease the transition to CARTO Builder.

With all the progress made in the last year, we cannot wait to see the potential of location intelligence and what our Partners innovate. Check back soon for more Partner-specific announcements!

Happy Data Mapping in 2017!

The number of charitable organizations around the world increases every year. There are more than 1.5 million nonprofit organizations registered in the United States alone, according to the National Center for Charitable Statistics. These organizations are committed to helping communities by providing charitable resources like sending relief aid, conducting research, or creating educational programs.

In order to better distribute precious resources, NGO’s often collect data related to their efforts. However, it’s also common for nonprofits to lack the bandwidth or knowledge to analyze the data they collect. With the use of Location Intelligence tools like CARTO, companies can help to improve impact and operations for these types of organizations. One company that is committed to this effort is Azavea, a geospatial software development firm based in Philadelphia.

Azavea utilizes CARTO to complete a wide range of projects for clients in the nonprofit and public sector. Azavea’s mission is to apply geospatial technology for positive civic, social, and environmental impact while advancing the field through research.

How can you use location intelligence to help communities?

Visualize Green Initiatives in Your City

Azavea used CARTO to build projects that support the implementation and documentation of “Greenworks,” Philadelphia’s comprehensive sustainability plan initiated by the Mayor’s Office of Sustainability. The Building Energy Benchmarking interactive web application displays two years of Energy Benchmarking results for large facilities in Philadelphia. The Greenworks map is an interactive visualization of Greenworks Projects completed by the City of Philadelphia and its partners from 2009 to 2015. Using the CARTO database and web map tile server infrastructure enabled Azavea to complete these projects efficiently.

Azavea built the Building Energy Benchmarking interactive web application for the Philadelphia Mayor’s Office of Sustainability using CARTO as the backend

Show the Effects of Legislation

The Azavea Data Analytics team recently completed a map for WHYY Keystone Crossroads that allows users to visualize how each of Pennsylvania’s 500 school districts would be affected if lawmakers chose to implement the Commonwealth’s new funding formula more rapidly. The team stored the data in CARTO and used the cartodb.createVis method through the CARTO API to pull in the visualization. The team designed with similar styles to CARTO widgets and set the map to re-style based on user input.

Help Nonprofits Accomplish Their Mission

In addition to using CARTO for client work, Azavea uses the platform as part of charitable projects.

Summer of Maps fellows often use CARTO to develop custom interactive web maps for nonprofits. Summer of Maps is a fellowship program that matches nonprofit organizations that have spatial analysis needs with talented students pursuing careers in geospatial data analysis to complete projects over a three-month period during the summer.

During the summer of 2016, an Azavea Summer of Maps fellow worked with Transportation Alternatives to engage the public in exploring connections between traffic crashes and poverty in NYC. The fellow developed an interactive web application built on CARTO and D3 that integrates geospatial and statistical views of the data. Other projects that have used CARTO include:

• An interactive application displaying air pollution that visualizes nationwide air quality developed for the Chemical Heritage Foundation
• An interactive web map of major injury and fatal crashes from 2010 to 2015 displayed with Indicators of Potential Disadvantage by census tract
• A torque map showing the growth of the Philadelphia LandCare Program over a 15 year period

Why CARTO?

The Azavea team chooses CARTO for projects because it provides a scalable PostgreSQL database for small datasets that can pull data via a REST API. Azavea developers can also create, display, and tweak visualizations based on client data via Leaflet maps on the websites they build.

Know a Nonprofit that Needs Geospatial Data Analysis?

The Azavea Summer of Maps program is now accepting project proposals from nonprofit organizations. The nonprofit applications are open until Feb. 5th, 2017. Nonprofits that can benefit from geospatial data analysis, location intelligence, and mapping services should visit the Summer of Maps website to apply.

Read more about the impact of the Summer of Maps program or watch this video to learn more about Summer of Maps.

Student GIS fellowship applications will open in February 2017.

Visit Azavea.com for more information about their products and services centered on having a positive civic and social impact, including predictive policing software, urban forest management tools, and a high-performance geographic data processing engine.

If you are an NGO or not for profit organization interested in partnering with CARTO or utilizing location intelligence for civic and social good please apply for a Grants for Good.

This is a guest post from our valued Partner, Azavea.

Happy Data Mapping!

Citizen-led organizations are working in cities across the world to better understand the intricacies of housing markets, housing policy, tenant rights, as well as the socioeconomic and demographic evolution of neighborhoods. Geospatial technology and Location Intelligence have become fundamental tools for analysis, communication, storytelling, monitoring and evaluation. CARTO’s Grants For Good Program connects academics and organizations to the technology they need to create impactful projects. In a three part series we will highlight influential civic mapping projects in New York City, San Francisco, and Chicago.

New York City

Rising rents, gentrification, crime reduction and immigration trends are changing the demographic makeup of neighborhoods across New York City. The Citizens Housing and Planning Council (CHPCNYC) is a non profit organization and a community of people that share ideas and shape practical solutions to help NYC government and the housing industry ensure residents’ housing needs are met. CHPC’s mission, since 1937, is to develop and advance practical public policies to support the housing stock of the city by better understanding New York’s most pressing housing and neighborhood needs.

Much of CHPC’s recent work focuses on aggregating and segmenting demographic data that demonstrates the demographic and socioeconomic shifts taking place in neighborhoods over a ten year period. CHPC released an extensive report, Making Neighborhoods, as well as an insightful interactive map allowing users to explore the rich temporal, qualitative, and geographic data. Explore the map for yourself to see how neighborhoods in NYC have changed over a ten year period!

The study used ‘cluster analysis,’ as a way of parsing large amounts of data into groups with shared traits. Populations clusters were identified in 2000 and tracked again in 2010. Dillon Massey, Housing Informatics Designer, played a leading role in the project and managed the entire data visualization and mapping.

“Using 16 demographic variables to measure race, age, foreign birth, household type, education level, and poverty, the model formed 14 ‘clusters’ of census tracts where populations share these characteristics.”

Citizen-led initiatives are complemented by innovative approaches by the public sector for better citizen centric and participatory governance. The New York City Mayor’s Office is doing just that with new real-time data dashboard powered by CARTO. The dashboard shows indicators including up-to-date crime statistics, service provision performance, health figures, infrastructure project updates, public works, 311 data, environmental indicators, housing and homelessness statistics.

It is crucial to fully comprehend how a city is performing, how neighborhoods are changing and who is being affected by policy. This understanding is achieved by analyzing, monitoring and evaluating the constantly shifting social, economic and political tides of a city.

Stay tuned for the next piece in this series which shares the work Anti-Eviction Mapping Project is doing in civic mapping and housing rights advocacy in San Francisco.

Happy Data Mapping

After the inauguration of President Trump, and the mobilization of millions of people around the world to protest his presidency, it seems timely to examine the data behind the results of the U.S. Presidential Election. Citizens were fueled and deflated by pollster data, with many believing random data from divergent news sources as absolute fact. The 2016 Presidential Election data revealed that the United States may actually be more divided than assumed. Election results combined with census data from the Data Observatory in a CARTO dashboard explore that divide.

Maps made by the New York Times liken Clinton’s United States to an archipelago of islands amidst an ocean of Trump supporters, and other maps demonstrate how the divide has widened over the last several elections. What characterizes that separation?

This CARTO dashboard allows users to explore the election results with widgets on selected county-level demographic data. Filter by educational attainment and household income to see how the vote turned out for subsets of the United States.

By selecting only counties with higher levels of educational attainment, predominantly urban counties or counties with college towns are represented. In counties in which over 70% of the population have at least some college education, Clinton wins the election by a landslide with 10.8 million votes compared to Trump’s 6.7 million.

In the inverse, counties with lower levels of educational attainment, the data visualization displays rural counties in Appalachia and the South. Counties where less than 40% of the population have achieved beyond a high school diploma voted for Trump almost 3 million to 1.2 million. The divide is not as stark when comparing how counties voted based on income.

Generally, wealthier counties voted for Clinton and poorer counties voted more for Trump, but the margin is not as wide as the educational divide. In this election, educational attainment played a major role in how people voted. Choropleth maps, like this one, can be problematic when representing this kind of data because large shapes tend to dominate smaller ones. In this case, it looks like most of the United States went red and that Trump won support by and large. However, the widgets tell a very different story (Clinton won the popular vote). So why use a choropleth map then?

This kind of map is one of the easiest to understand with only one type of symbology (color). People usually process one piece of information better than multiple pieces at once, therefore using two types of symbology is typically more complicated. For example, with two types of symbology, the viewer has to process both the size and color of a symbol and on a map, proportional symbols and colors can get cluttered. A choropleth map also preserves the relative location of a place, making it easier for users to find their home county.

In this map, each county is represented by a circle. The size of the circle is proportional to the number of votes and the color corresponds to the winner in the county. Smaller red circles are now balanced by larger blue circles and neither color dominates, but it’s much harder to identify which circle represents which county. The symbols can also overlap in neighborhoods of small, densely populated counties.

Find out more about election mapping and how to use census data and the Data Observatory to power local, regional, and federal campaigns or provide accurate data representations in your stories with this election webinar.

Happy Data Mapping!

In creating these maps, only votes for the Democratic or Republican parties were used for calculations and third-party votes were ignored. Election results were scraped from the New York Times on December 19th, and demographic data came from the US Census ACS 2010 - 2014. Alaska is omitted because results are not reported at the county level.

If you are a student developer looking to work with cutting-edge location intelligence tools, then do we have good news for you!

Engaging with students interested in location data and spatial analytics is one of the most rewarding features of working at a company committed to democratizing access to location intelligence. CARTO empowers the next generation of developers, analysts, and mappers, but I also learn a ton from engaging with up-and-coming developers. To continue fostering this relation, we’re excited to join GitHub’s Student Developer Pack, a service providing access to the latest tools from industry leaders for free!

We are so proud to join the amazing community Github has assembled, while also continuing to help current and future students. Within the Student Developer Pack, CARTO provides resources that introduce our platform’s services like LEARN, information about our Ambassador’s program, and support for hackathons.

A student with a Github-verified student account can sign up for a CARTO account and receive an upgraded database storage as well as all the bells and whistles needed to take your geospatial project to the next level.

Stay tuned to learn more about how we’re empowering students and educators.

Happy Data Mapping!

If you are a student developer looking to work with cutting-edge location intelligence tools, then do we have good news for you!

The Anti-Eviction Mapping Project, a collection of volunteers with a reputation for conducting deep analysis of eviction, gentrification, and housing rights in San Francisco has found a correlation between foreclosure rates, race, and the redlining policies of the 1930’s through a spatial analysis and visualization.

Academic institutions and research centers play an important role in monitoring, evaluating and predicting housing markets. Housing markets influence the demographic makeup and overall health of a neighborhood.

Socioeconomic discrepancies among neighborhoods of different racial and ethnic compositions can often be explained through an analysis of historical policies like redlining, a discriminatory policy that labeled certain neighborhoods with predominantly black neighborhoods as unworthy of financial loans and capital investment that correlated to increases in minority residents.

Telling this story and visualizing the impact of this discriminatory practice has been difficult for cities. The Anti-Eviction Mapping Project is changing that with their approach to location intelligence, delivering insight through visualizing and analyzing location data.

In this mapping project, AEMP enriched eviction data and foreclosure rates with extensive demographic and census information provided by datasets from CARTO’s Data Observatory, adding historical context to their findings. This type of visualization makes it easy to fully understand the realities of urban policy by providing important additional context and insight to the research and advocacy taking place in these spaces.

“Ultimately, redlining has driven both racial stratification and foreclosures, two of the major features of modern gentrification. Contemporary reinvestment in poor areas has not resulted in a lessening of these ails; rather, reinvestment has further increased the strain upon poorer residents and minorities, often leaving them without a place to live.”
Erin McElroy, Director of Anti-Eviction Mapping Project

Cities are complex.

Today’s cities are a product of the people that inhabit them, past and present policies, and fluctuating economic markets that help determine the rate of growth or decline. The multitude of trends any given city might experience over time are better understood and communicated by taking a location intelligence approach to visualizing and analyzing your city’s location data.

How have historic policies affected your city’s foreclosure rates or influenced the demographic makeup of neighborhoods and communities? We would love you to show us! CARTO’s Github Developer’s Package and the Grants For Good Program allow professors, students, non-profit organizations and companies, to access Location Intelligence tools? for free.

Happy Data Mapping!

Retail investments in technology reached an all-time high in 2016, a sign of the industry’s sustained commitment to providing smarter, data-driven retail experiences. But how can retailers ensure a return on these investments in 2017? It all comes back to location data.

Retailers are gaining more and more data about their customers, but making informed business decisions with that data has proven difficult and expensive. Retailers are moving toward more cost-effective solutions that work with a company’s pre-existing setup. Location intelligence platforms work remarkably well with pre-existing systems because location data requires flexibility.

This contributes to Dresner Advisory Services recent ranking of location intelligence mapping software among its most important business intelligence-related technologies for 2017. In fact, more than 50% of respondents stated it was “critical” or “very important” to their organization.

Here are three ways you can integrate smarter, data-driven location intelligence solutions throughout your retail business to ensure 2017 is your best revenue-generating year to date:

1. Analyze Consumer Behaviors with Indoor Maps

While customers are becoming more and more informed through online research, an overwhelming number of customers still purchase products at in-store locations.

Retailers are bridging this “brick-and-mortar” and “brick-and-click” divide by creating indoor maps featuring customized basemaps tailored to an individual store’s floorplan. In addition, retailers can apply spatial interaction models to these data visualizations to create heat maps that can help redesign floorplan layout as well as reassign staff to high traffic areas to optimize workforce performance.

Warby Parker, for example, designed their stores to have a mirrored layout because they found that customer flow throughout their stores was improved when customers didn’t have to jostle with each other over the same pair of glasses.

2. Provide In-Store Product Recommendations with Location Data

Amazon changed our retail experiences when it introduced algorithms to make product recommendations to shoppers based on past purchases. Customers now expect this same level of personalized attention in-store too.

Predictions for retail trends in 2017 point toward greater integration of artificial intelligence (AI) and machine learning, but retailers working with location intelligence are already ahead of the curve. Retailers can pinpoint a shopper’s in-store coordinates in real-time with location data to recommend similar products available at that specific store branch.

Target has steadily expanded the availability of its retail application for smartphone users who opt-in to receiving updates from the retailer. Despite a slower than expected start, retailers should be optimistic in the viability of location applications since 73% of customers indicated that these types of updates increased the likelihood that they would make a purchase while at a store.

3. Create Custom Location Applications for Smarter Retailing

While location applications are helping retailers enhance customer experiences, they are also helping retailers improve operational efficiency.

Leroy Merlin, a French-based home improvement retailer with over 300 branches internationally, needed assistance in managing their product supply chain to ensure each store location offered a robust selection of products for customers.

They created a custom location application with a data repository accessible to remote managers and executives. These datasets were enriched using a data curation capability that visualized not only customer demographics for each store, but also nearby competitors. “One of the main advantages that we now have,” explained Jeremy Chatelain, Project Manager for Leroy Merlin, “is the ability to analyze competitors and where our clients are coming from.”

Retailers looking to mirror Leroy Merlin’s success can start developing their own retail location applications with CARTO!

Next Steps

Technology budgets are likely to increase again in 2017 as more and more location data becomes available. But retailers who are seeing returns on past investments are those using location intelligence tools, including indoor mapping, spatial analysis, location-based marketing, and even custom made location applications. Location intelligence offers smarter, data-driven solutions, which retailers looking to retain a competitive edge will need in the upcoming year.

Happy Data Mapping

Anticipation for one of the formative insider tech experiences is mounting. With 2,200 exhibitors and over 100,000 tech and mobile professionals from 200 countries descending on the Catalan capital, there are several sessions that will be truly revelatory for 2017 and years to come. Remember how crazy the industry went in 2014 when Mark Zuckerberg gave his keynote?

Mobile World Congress (from February 27 to March 2) promises to be full of cool, new tech (think the latest and greatest in Android devices, VR, and location intelligence) and many of 2017’s most high-profile technologies and applications are likely to be announced over the course of the summit. If you’re heading to Barcelona this month, and you definitely should be, here are the top five experiences – 3 is sure to inspire — that can’t be missed! Disclaimer: Our list may be slightly biased!

1. Networking Break featuring the Showcase Stage 1

February 27, 10:30 - 11:00AM
With Javier de la Torre, CEO at CARTO at Conference Village, Hall 4

The Showcase Stage is back by popular demand! This stage is designed to showcase the brightest new companies and facilitate impactful and informal conversations and demonstrations with attendees.

2. Networking Lunch featuring the Showcase Stage 2

February 27, (1:30 - 3:00PM)
With Miguel Arias, COO at CARTO at Conference Village, Hall 4

3. Connected Tourist - Pilot Project

February 27, (4:00 - 6:00 PM)

“Connected Tourist - Pilot Project”, with Mobile World Capital and Javier de la Torre, CEO of CARTO – Stand CS70-MWCB at Congress Square, between Hall 4 and 5

It’s tourism in the time of Big Data! The “Connected Tourist” is a pilot project by Mobile World Capital and CARTO. The presentation will explain the rationale of the project and how big data tech can help in the decision making process to improve the tourism experience, using the city of Barcelona as an example. With your MWCongress pass you can praticipate in the presentation, RSVP here!

4. Smart Cities, Connected Citizens

February 28, (3:30 - 4:40PM)
With Alphonso Jenkins, from NYC DOITT and Rosalía Simón, from Telefónica– Auditorium 2, Hall 4

While most smart city deployments exist in silos, platforms are emerging to facilitate communication. As more cities become ‘smart’ they can learn more from each other, make more decisions to continue to improve its citizens’ quality of life.

5. Enabling IoT Platforms

March 1, (11:00AM - 12:10PM)
With Vicente Muñoz, Global IoT Chief Officer, Telefónica – Hall 4, Auditorium 2

By 2025, Machina Research estimates that public and private enterprises will be spending over US$1 Trillion on IoT. As the volume of services, data and opportunities continue to expand, enabling technologies and platforms will need to surface and be widely adopted to create an IoT ecosystem across industry sectors.

As in previous years, the location for the mobile communication sector’s big rendezvous is in Barcelona, Spain at the Fira Gran Via conference facility, which is home to an impressive 8.7 miles of fiber optic cables, 32.3 miles of ethernet cables, and 1,200 wifi hotspots. It’s the most “connected” place to be at the beginning of year. Read about our past MWC experiences here.

See you there!

When California went on record as experiencing one of the most exceptional droughts in history, even “untouchable” movie stars were fined for watering their lawns.

For the first time since 2014, news outlets reported that no area in California was designated as experiencing “exceptional” drought conditions.

Sensors, beacons, GPS data, and satellites have been able to generate a deluge of big data for state officials and scientists. However, organizations are finding more meaningful value in “small data” because of its ability to be acted upon immediately.

Mamata, our senior cartographer, created an interactive data visualization built upon data from the US Drought Monitor to show how anyone can find meaningful insights by taking a “small data” approach to location data.

1. Small data’s immediate impact

Although big data provides the raw material for small data, data visualizations can keep you afloat while searching for smaller subsets across multiple layers of information.

Below are two images from the drought data visualization. The image on the left hand side, displaying national data for all severity levels since 2014, presents so much information that local trends can be hard to spot.

The image on the right hand side, however, has been filtered only to display conditions for the final week of January 2017. The visualization confirms that California did not exhibit “exceptional” drought conditions, but also locates national occurences of each drought category.

Subsequently, you can now start to consider how local officials in cities like Santa Barbara, California and Fort Smith, Arkansas have responded to “severe” drought conditions, while also identifying shared climate conditions between the two cities.

Small data provides this type of local insight that is not always available when talking about national trends in terms of statistics, percentages, and figures. Visualizing a data category is a great way to translate an abstract space to a meaningful place for further exploration.

2. Spatialize trends, not territory

Another benefit of visualizing location data is the ability to spot areas of interest that fall beyond the purview of traditional performance metrics.

If you’re running a year-over-year report, for instance, measuring profit increases and decreases may not account for valuable information contributing to annual performance.

When working with small data, however, spatial analysis can be applied to non-spatial patterns, trends, and occurrences to expand your understanding of the situation.

Droughts present a similar challenge as cartographers equipped with geospatial tools confront unpredictable temporal occurrences. John Nelson, for instance, has discussed these cartographic limitations for visualizing the “movingness” of droughts, but let’s see how styling trends can help visualize changes that move over time.

The map above displays drought data from the final week of January in both 2015 and 2016. The blue areas represent 2015 data, the yellow areas represent 2016 data, and the mixing of the two produce the green areas, which represent locations experiencing drought conditions in both years.

This map’s categorical color scheme helps locate areas otherwise unnoticed were you only to measure for statistical increases and decreases. Moreover, the data visualization features responsive labeling to draw attention to cities like Twin Falls, Idaho and Klamath Falls, Oregon whose drought conditions have not received as much national as metropolitan areas.

Small data enables this more expansive approach to spatial analysis, which can help you see occurrences beyond previously defined geographic boundaries.

3. Smaller comparisons can reveal bigger stakes

The only business intelligence buzzword more overused than “big data” is “predictive analytics.”

While big data can help build models to locate an unknown value for future planning, small data helps build descriptive models that present information on current conditions.

The added value attracting businesses to small data, and descriptive analytics more generally, is found in providing insights on present conditions that can be acted upon immediately.

In the map below, for example, “exceptional” and “extreme” drought conditions are represented for the final week of January from 2014 through 2017.

While the map above locates a high number of areas within California experiencing exceptional and extreme drought conditions, the data visualization also locates areas in New England, such as Hartford, Connecticut and Springfield, Massachusetts. That western and central states have experienced extreme or exceptional drought conditions is far less surprising than seeing that this trend has occurred in the northeast as well.

Visualizing this small subset of data can provide an impetus for local officials across the nation to begin collaborating on sustainable solutions that better prepare cities, counties, and municipalities for future water shortages.

Conclusion

Instead of plunging into the sink-or-swim waters of big data, business analysts are finding more success working with small data. Whether you are mapping drought data or not, smaller data sets help you ask smarter questions whose answers can be acted upon in the present.

Happy (Small) Data Mapping!

In the age of global technopolis, open government data reigns.

In 2016, 70 countries participated in the Open Government Partnership, a big increase from just 7 in 2011, and 52 countries hosted their own open data portals.

Most citizens around the globe probably aren’t aware that they use open government data every day. From asking Google, “what’s the weather?” to deciding which bus or subway route to take, many of our daily actions are made possible by open government data.

Yet, according to The Open Data Barometer, a comprehensive international survey of 92 countries, evidence of open data’s impact still remains limited to a handful of countries.

Open data policies, often related to smart city initiatives, claim to be the missing component for enabling government transparency. But is open government data really improving the quality of life for citizens?

It’s true: stand-out examples of open data initiatives have dramatically changed citizen engagment and civic tech innovation.

Why, then, is it so hard to find statistical evidence that open data creates measurable global impact? And what can we do to speed up the process?

The history of open data

Conceptually, the free use, reuse, and redistribution of data came about in the late 1950s during the Cold War scramble to establish World Data Centers, hubs designed to minimize the risk of data loss, and maximize data accessibility.

Fast forward 50-plus years to the emergence of data wranglers and manipulators, passionate souls willing to clean and re-issue raw data for popular use. These “hackers” opened the door to a new kind of engagement, civic hacking. Cities and local governments embraced this citizen participation, and began to leverage local volunteer developers to assist in building new and interesting municipal applications.

The untapped potential of open data

At the global level, most government datasets go unused, and over 90% of government data still isn’t even open.

Out of the hundreds of thousands of datasets released by tens of thousands of government agencies every year, only a handful make their way into a consumer experience in any meaningful way.

The leaders of open data

The civic tech landscape continues to grow with new tech companies (like us!) leading the way.

At CARTO, we believe in building an ecosystem where open data becomes the raw material that drives more effective decision-making, spurs economic activity, and empowers citizens to take an active role in improving their own communities.

We’ve worked with many leaders in the open data and smart city movements, including New York City, Mexico City, and other nonprofits and corporations.

What do all of these leaders have in common? They put location intelligence at the center of their open data initiatives.

Here’s what that means:

1. They enrich their data with geospatial information

   GROW.LONDON was developed by JLL and London & Partners to show what types of businesses citizens may need in different areas. The project uses information from open data such as population growth, economic output, and property prices to identify emerging market clusters for potential investors.

   Helping businesses choose the right location to expand and grow creates more economic opportunity for citizens and helps cities plan for future expansion of services in those areas.

2. They visualize location data to discover hidden patterns and correlations

   The Anti-Eviction Mapping Project created an easy-to-understand map that revealed correlations between foreclosure rates, racial demographics, and redlining policies that denied services to residents of certain areas of San Francisco based on race or ethnicity.

   Until now, it was difficult for cities to easily show the dramatically negative impact that redlining policies have had on the housing market, especially for traditionally marginalized communities. By visualizing location data, urban policy advocates working with city government agencies now have new evidence, insights, and tools to use in their efforts to improve urban living for all citizens.

3. They analyze location data in real-time

   Location data provides the most value to cities when decision makers and city hall employees can analyze it in real-time. The New York City Mayor’s Office created a real-time dashboard showing a wide variety of city indicators, from up-to-date crime statistics and 311 data, to infrastructure project updates. City officials can now, in real-time, translate insight into action.

   Residents of New York are positioned to benefit from these improvements massively, as the city can now identify and act on important situations in specific parts of the city unlike ever before. The dashboard allows for easy monitoring of changes to these indicators across both spatial and temporal dimensions.

4. They radically reduce time-to-insight to respond to citizens’ needs

   San Diego’s Performance and Analytics Department created StreetsSD, an interactive data visualization allowing city residents to track progress on the Mayor’s infrastructural pledge to repair 1,000 miles of city streets by 2020.

   This location analysis tool informs residents about a host of concerns such as street rankings, the type of scheduled repair, and the status of repairs.

The future of open data

The time is here to finally deliver on the promise of open government data at a global level.

Open data is not an empty promise; it is a movement going global.

It’s time to make the workings of governments transparent, accountable, and responsive to citizens. It’s time to deliver on the ideals of democracy, public works, and civic engagement.

Here at CARTO, we’re excited to be at the forefront of this movement.

Happy Data Mapping!

In honor of New York City’s Open Data Week 2017 we’ve compiled a resource featuring 40 smart, data-driven projects reminding us of open data’s value.

The rate of urban migration around the world is rising at an alarming rate. Experts estimate that 70 percent of the world’s population (more than six billion people!) will reside in urban areas by 2050. In response, government officials are investing in data sharing technologies to discover ways to provide public services more efficiently.

This form of city planning has invariably been described as “smart”, “intelligent”, “responsive”, “resilient”, and, more recent, “senseable”. But how do these initiatives use open data to address the concerns of residents? In answering this question we discovered projects whose originality left us speechless and dedication to social justice inspired.

We’ve assembled the list below both to recognize these accomplishments and promote more work with open data! The examples are categorized by service type and alphabetically listed because projects democratizing access to open data should be celebrated equally:

1. Navigating Open Data Sources
2. Transparency and Accountability
3. Performance Management
4. Transportation and Infrastructure
5. Resilient City Planning
6. The IoT of Smart Cities
7. Civic Engagement

Navigating Open Data Sources

Building an open data portal is expensive, and returns on this investment can be difficult to measure. To ensure citizen engagement with open data portals city officials and third party partners are designing constituent-centric interfaces and applications. Here are our favorite web and mobile applications designed to help citzens navigate open data.

Dat
If you’re looking to get started with open data, then Dat is the place to start! Dat is an open sourced, decentralized data sharing tool trying to do for open data what Git did for source codes. Check it out!

LocalData LocalData is a mobile application allowing community groups to participate in open government data planning. In Detroit, for example, community groups surveyed city streets to collect data in areas needing infrastructural renovations, which exemplifies one way that open data projects can engage city residents.

Open Data Impact Map
The Open Data Impact Map is a geospatial platform identifying communities around the world engaged in open data projects. If you’re looking for inspiration on what to do with open data, then check it out!

OpenGrid
OpenGrid, an interactive map platform, is raising situational awareness for Chicagoans. Residents can easily search curated datasets, including those provided by the City of Chicago, and visualize the results on an interactive map.

Resident Card
Tel Aviv’s Resident’s Card App allows residents to customize their interactions with local officials by opting to receive real time updates from city services of interest.

SmartAppCity
SmartAppCity uses a Public-Private Partnership framework to encourage local businesses in Madrid, Spain to participate in city-wide open data initiatives by sharing their data in the city’s open data portal.

Transparency and Accountability

Among the objectives for smart city projects is the goal to improve efficiency, and these open data projects help citizens cut through bureaucratic red tape faster than ever.

Clear My Record
Clear My Record is a free web application that centralizes criminal records in a repository shared among various government agencies in effort to help citizens have low-level offenses expunged from their records. The level of efficiency provided led the San Francisco Public Defender’s Office to implement the app to optimize operational performance.

Commonwealth Connect
Commonwealth Connect is a mobile app facilitating data sharing between government officials throughout Massachusetts. Residents can now report non-emergency issues that are housed in a data repository before being dispatched to the appropriate city or state agency.

DataHaven
DataHaven’s mission to collect, interpret, and share open data for better decision-making across Connecticut. Data visualizations, for example, are helping elected officials understand the interrelations among city and state services such as income-based segregation, which has caused significant urban structural strain.

InvestigativePost
Investigative Post’s Dan Telvock used open data to expose higher than reported levels of lead in Buffalo’s drinking water. Open data empowers citizens to hold local officials accountable!

OpenDurham
The City of Durham avoided creating a city-wide data silo by building a shared city and county open data portal. Now local and municipal agencies can work together to improve services for their constituents.

openlaws
Staying informed about one country’s initiatives, regulations, and laws is hard enough let alone for each member state of the European Union (EU)! But thanks to openlaws, EU residents working across national borders can sign up for mobile updates on latest information and changes to ensure all legal requirements are met.

OpenStates
OpenState provides a resource for U. S. citizens to research upcoming local legislature as well as compare legislative proposals to other states.

Performance Management

Local governments have adopted and adapted the service industry’s motto, “The customer is always right,” with the help of open data. Check out the examples below to see how open data ensures that the constituent is always right!

BOS:311
The City of Boston pioneered Constituent Relation Management (CRM) with a technological update that turned the existing Mayor’s Hotline into BOS:311. This web and mobile app lets residents report non-emergency issues to the city’s Constituent Service Center, which dispatches request to appropriate agencies across Beantown.

ChattaData
ChattaData’s High Performing Government Dashboard provides progress reports on initiatives to cultivate a more inclusive city. Chattanooga set a goal to increase Diverse Business Entities (DBE) participation by 14 percent, and thanks to transparent community outreach, fair and equal access to procurement opportunities, and open government data the city exceeded its goal in September 2016!

Residential Typology Analysis Tool
Data Driven Detroit (D3) developed the Residential Analysis Typology Tool, a geospatial tool using cartographic and satellite images, to identify high and low residential density areas, which help city planners prioritize data smart renovations.

NOLAlytics
ResultsNOLA, a scorecard tracking progress data-driven projects across New Orleans, not only ensures clear communication between city services, but also encourages interdepartmental collaborations on more open data project with NOLAlytics.

Urban Spatial
With open data from Philadelphia’s OpenDataPhilly portal, Urban Spatial built predictive models that pinpointed buildings in need of city inspection and created a data visualization to communicate these findings.

Young Europeans
Young Europeans uses open data from Eurostat to provide demographic sketch of EU youth ages 16 to 29. This web application is a great tool for youths throughout EU to stay informed on economic opportunities in neighboring countries.

Transportation and Infrastructure

Transportation and infrastructure form a city’s lifeline, which explains why open data advocates have focused heavily on these two areas. The projects below make use of open data, and in some cases are literally changing what it means to be data-driven.

CoAXs
Anson Stewart, an affiliate of MIT’s CoAXs group, created job maps for Boston, Massachusetts and Los Angeles, California with the Census Bureau’s Longitudinal Employer-Household Dynamics open data. Locating job growth across a city is a great way to prioritize smart city projects in order to encourage further economic development.

Citi Bike NYC
Citi Bike NYC, the largest bike sharing system in the United States, provides open data on riderships, routes, and even individual bikes! Sara Robinson used this data to create a data visualization displaying gender patterns for bike routes across New York City, which is a great example of what open data can tell us about our own cities!

Digital Matatus
Digital Matatus is a great example of a cross-sector solution to the problem of limited government resources. Developers and private citizens in Nairobi, Kenya are helping local officials standardize a city-wide transit system by collecting location data with mobile devices to establish an open data network. An amazing first step toward becoming open data-driven!

MARTA on the Go
MARTA on the Go is a mobile app providing commuters real time service conditions for bus and rail transit throughout Atlanta’s Metropolitan Area. MARTA is committed to building “livable” communities in areas with limited access to public services by building transit stops to encourage urban renewal in these locations.

Red Eléctrica de España (REE)
In compliance with the City of Madrid’s open government data initiative, Red Eléctrica de España (REE) created an open data platform with help from Vizzuality and CARTO to discern power supply usage across Spain. Subsequently, residents can now monitor electricity usage and explore its economic impact on their local communities.

Smart Columbus
Can smarter public transportation address public health concerns? Yes, according to Smart Columbus, a holistic approach toward smart cities proposed by officials in Columbus, Ohio. Transit centers will be built in areas throughout Franklin county where open government data reveals alarmingly high rates of infant mortality that exceed the national average. Can’t wait to see how this project unfolds!

Resilient City Planning

Climate change has helped accelerate the rate of urban migration. From apps monitoring flood conditions in Germany to radiation level warnings in Japan, these examples highlight cross-sector partnerships using open and public data to better prepare cities around the world to confront the challenges ahead.

BINGO
Portugal’s Laboratório Nacional de Engenharia Civil is leading an international coalition that is leveraging open data from EU member states to improve water management resources. SmartWater planning is a growing area with the field of open data and smart city planning, and we’re thankful for this work!

LevelAlarm
LevelAlarm is a free platform featuring mobile emergency response app alerting residents about rising water levels at nearby bodies of water across Europe.

National Operational Assessment of Hazards (NOAH)
NOAH is the Philippine government’s disaster mitigation system that measures water and rainfall levels to identify areas exposed to high risks of landslides, flooding, and other health concerns related to water contamination.

Partnership for Resilience and Preparedness (PREP)
The Partnership for Resilience and Preparedness (PREP) is an international partnership dedicated to making climate data accessible and meaningful for non-specialists to promote resilience planning. CARTO is honored to support to such a worthwhile cause, and we hope PREP inspires more cross-sector collaborations!

Safecast
Following the devastating tsunami and subsequent nuclear power plant meltdown in Fukushima, Japan in 2011, a global network of volunteers created Safecast. This geospatial web and mobile application visualizes open environmental data to provide accurate information to residents at risk of radiation exposure.

The IoT of Smart Cities

Recent efforts to improve smart city grids and networks has led to the creation of sensor networks capable of monitoring a range of issues impacting residential living conditions. The Internet of Things (IoT) has enabled local officials to connect various devices throught the city to this type of sensor network, which some are calling Smart City 2.0. The examples below both eased our fears of Big Brother and excited us about open data’s future.

Autolib
Autolib is changing the way Parisians get around the city of lights. As an intelligent public car-sharing service, Autolib’s fleet of electric vehicles harness a constant stream of open data from kiosks and sensors around Paris not only to optimize commutes, but also help in reducing air and noise pollution.

Array of Things (AoT)
The Array of Things (AoT) serves as a “fitness tracker” for Chicago. But instead of monitoring individual residents, sensors monitor the city at a macro-level to ensure privacy rights remain intact. The data collected from AoT sensors will be made open to encourage developers to create more applications aimed at improving living conditions for Chicago residents.

RideKC Streetcar
Kansas City is piloting an Internet of Things (IoT) corridor along the RideKC Streetcar downtown route as part of an energy conservation initiative. Local officials are installing interactive kiosks with real-time updates on service conditions, free WiFi hotspots, and a responsive sensor system to monitor traffic flows so as not to waste energy during off-peak hours.

Smart Nation Singapore
Singapore is aiming to become the world’s first “smart” nation thanks to its open government data portal, which also functions as a data repository for collected public sector data. What intrigues us about Smart Nation Singapore is its definition of “smart,” which has less to do with “technology” and more with how well society uses technology to address social inequality.

Smart Benches
Smart benches located throughout London are built with sensors to monitor and collect open data on traffic volume and environmental conditions. At the same time, these smart benches provide more access to WiFi hotspots and solar-powered charging stations throughout London!

Urbanflow
Urbanflow has situated responsive, ‘living’ screens throughout Helsinki projecting an interactive city map overlayed with a wealth of information to keep residents and visitors informed on local events. An interesting twist on our addiction to screens!

Civic Engagement

Access to open data has helped bridge the information gap between elected officials and their constituents. But what else can citizens do with open data to improve their neighborhoods, communities, and cities? Well, as the examples below demonstrate, a lot!

BA Accessible
BA Accessible, a mobile application for residents of Buenos Aires, is crowdsource tool that provides accessibility information for spots around the city. Not only does this inclusive project provide valuable information for residents with impaired mobility, but it also alerts local officials to areas that need to be made handicap accessible.

The Displacement Alert Project (DAP)
The Displacement Alert Project (DAP) exemplifies how location intelligence can be used for public good. The Dap.Map is an interactive, web-based data visualization built with open data provided by city, state, and national agencies. The Association for Neighborhood and Housing Development is dedicated to ending the affordable housing shortage, and alerting New Yorkers at risk of displacement is an important step in the right direction.

GetCalFresh
CalFresh is a web and mobile application for California residents in need of food assistance. Residents can now apply electronically for assistance, which helps ensure resident’s needs are met in a dignified manner.

Mapping Police Violence
Open data does not always present the full picture. The Mapping Police Violence project is a timely and important initiative demonstrating the need for even more transparency from open government data as it leverages data from various sources to address and redress racial injustice across the United States.

Conclusion

A 2016 Digital Citizen Survey found that since 2014 United States citizens’ expectations for digital government services have increased 15 percent, and satisfaction with current services during this same two year span doubled.

Data-smart city planning is here to stay, and we’re excited to support these important initiatives that make meaningful use of open data.

Did we miss a great project using open data? Connect with us on Twitter, Facebook, or LinkedIn and let us know!

Happy Open Data Mapping

Good maps lie at the heart of any location application. When analyzing data on maps, proper design can be the difference between interesting and insightful.

But effective design is easier said than done.

Choosing which attributes to symbolize, how many attributes to include, and what kind of thematic map type to use can be challenging. Add in data distributions, classification methods, and appropriate methods of symbology and things get even more confusing.

You might find yourself asking questions that only an expert cartographers or GIS professionals could answer, like:

• Is my classification method right?
• When should I use a diverging color scheme vs a sequential one?
• Is there enough distinction between the colors on my map?
• What is the best way to symbolize multiple attributes?

All of these decisions impact the usability of the map.

Announcing Auto-Style

Our research team at CARTO has been experimenting with ways to solve this challenge and help non-GIS experts optimize map design to improve their analysis. We’re excited to announce a new capability inside CARTO Builder called Auto-Style.

Auto-Style analyzes your data to determine and apply the best visualization type by default. It takes the guesswork out of thematic map design and turns one map into many. By default, it provides the optimal visualization automatically.

To illustrate the impact of proper data-driven map design, let’s look at a common map type - a choropleth map of US Census county-level data from our Data Observatory - to understand how median income varies between demographics.

The map below symbolizes all counties in the US equally. We have added CARTO Dashboard Widgets for each of our variables of interest. Interacting with these widgets updates the visualization to summarize the current view.

Dynamically explore variables

As a first step, Auto-Style can be used to explore each variable of interest. Doing this with traditional workflows requires going back to the drawing board for each view.

Behind the scenes, CARTO analyzes the distribution of the data in the current map view, classifies the data using the best method to detect the patterns, and then applies an appropriate color scheme (we call these CARTOColors).

For example, if we want to visualize the percent of population that is Hispanic or Latino in each county, we can specify the Percent Hispanic or Latino widget. The map automatically updates to a choropleth map and the bars of the histogram widget update to function as the legend.

Filter, re-analyze, and visualize

What if we want to compare the Hispanic or Latino populations only in Texas? If we filter the data to only show Texas, Auto-Style recalculates the distribution for those counties and re-applies the color scheme only as it relates to your selected criteria. This not only adjusts the map visually, but also quantifies it proportionally in the interface.

By filtering counties with at least 50% Hispanic or Latino population and visualizing the filtered results with median income, we begin to uncover patterns of income and demographics in Texas.

By combining multiple filters with Auto-Style, anyone can quickly understand and act on visual analysis hidden in their location data.

Try filtering various criteria to take a deeper look into demographic and economic distributions to discover new patterns and insight. For example, combining demographic filters and Auto-Style by median income exposes patterns that can be used in everything from retail planning to government service distribution.

The Change for Map Users

As location data (and maps) becomes more pervasive in analytics for organizations of all kinds, proper visualization techniques become even more important in how data is understood and acted on.

Features like Auto-Style are reducing skill barriers and enabling a broader set of users to unlock the power of their location data.