The Internet Is on PolicyMap (and Vice Versa!)

Chances are, if you’re reading this blog, you have a high-speed internet connection. I remember my family’s first DSL connection. I was in 8th grade, and the internet flowed in at a glorious 768 kilobits per second. Today, that might not be enough to watch a good cat video.

Of course, high-speed internet is important for a lot more than sharing vacation pictures and cat videos. It’s often essential for things like finding a job, managing money, doing school work, reading news, and basic communication. Without broadband internet, you wouldn’t be able to access PolicyMap!

With internet becoming almost as essential as electricity and phone service, it’s important to see where it’s in limited supply. The National Broadband Map (NBM) is a geographic database with that information. Created by the National Telecommunications & Information Administration, it collects data on all broadband internet services provided throughout the country. It tells the name of the provider, the technology type (cable, fiber optic, wireless, etc.), the speed, and the area served.

The data is provided at the block level (which is even smaller than block groups), and we aggregate that data up to the block group, the smallest geography visible on PolicyMap. With this granular data, we can look at a lot of interesting maps:


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Mapchats – Neighborhood Rx: Mapping Community Health

Mapchats: Neighborhood Rx
Curious about how disease rates can be measured at a local level? Hear from public health researchers at Emory University and the New York City Department of Health and Mental Hygiene about their use of data to understand disparities and improve care and community well-being.

Join us for another installment of our popular Mapchats series on September 23, 2015 to discuss the challenges and opportunities of putting local health on the map. This webinar will feature Patrick Sullivan, MD of Emory University’s Rollins School of Public Health, Arti Virkud, MPH from the New York City Department of Health and Mental Hygiene, and Morgan Robinson from PolicyMap. Panelists will discuss how researchers can transform administrative records and other data into compelling maps that highlight community health disparities and lead to better policy decisions.

Save your seat today!

patrick_sullivanPATRICK SULLIVAN is a Professor of Epidemiology at Emory University’s Rollins School of Public Health, and Co-Director of the Prevention Sciences Core at Emory’s Center for AIDS Research (CFAR). Dr. Sullivan’s research focuses on HIV among men who have sex with men, including behavioral research, interventions, and surveillance. Previously, Dr. Sullivan worked as the Chief of the Behavioral and Clinical Surveillance Branch at CDC, implementing HIV research studies and surveillance systems to meet critical local, state and national HIV prevention needs. He is the PI of NIH-funded studies to determine reasons for black/white disparities in HIV among MSM, to pilot HIV prevention packages among MSM in South Africa, to evaluate distribution of at-home HIV test kits to MSM in the US, and to develop and test a comprehensive mobile prevention app for gay and bisexual men. He is also the Principal Scientist of and

arti_virkudARTI VIRKUD is a data analyst for the Population Health Team at the Bureau of the Primary Care Information Project at the New York City (NYC) Department of Health and Mental Hygiene. She works on epidemiological research using aggregate data from NYC ambulatory practices. Her research ranges from chronic disease studies on non-alcoholic fatty liver disease and falls risk in older adults to infectious disease projects on tuberculosis and HIV prevention. She has a BS in neuroscience from Massachusetts Institute of Technology and an MPH in epidemiology from Columbia University’s Mailman School of Public Health.

morgan_robinsonMORGAN ROBINSON is a data analyst at PolicyMap. She has applied and developed her skills in data processing and mapping with community-based and advocacy organizations in Detroit, Seattle, and New York. She comes to PolicyMap from Data Driven Detroit, a nonprofit data provider for Southeast Michigan, where she provided research and analysis to support local neighborhood and environmental initiatives. Through her experience, she gained an understanding of how leaders and policymakers use data to make smart and effective decisions. Morgan earned a Bachelor’s degree in Urban Studies and Political Science from Columbia University, and a Master’s degree in Community Development from the University of Detroit Mercy.

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What’s New at APDU

APDULast week, three of us from PolicyMap went to the annual APDU Conference in Washington, DC. APDU is the Association of Public Data users, so the APDU Conference is basically our Super Bowl. The conference is full of data providers (lots of Census people), users, and groups like us who are somewhere in the middle. Our own Elizabeth Nash moderated a panel on using public data alongside private sector data.

For all of you who weren’t able to attend, here are a few of the trends we saw discussed at this year’s conference:

Big Data is Here

This trend has been brewing for a while, but this year, it seems like we’ve reached the point where users of public data are looking at Big Data as a legitimate resource. What’s the difference between public data and Big Data? We’ve covered this before, but in short, public data is the sort of data you see on PolicyMap: government-collected datasets like those from the Census and BLS, which are aggregated over a geographic area (like a county). Big Data tends to come from private sources, like Google or Facebook, and often goes down to the individual level (though the public can’t access this data). It’s how Google Flu came along, where Google tracked the prevalence of the flu through user searches. (Unfortunately, Google Flu turned out to be generally inaccurate, which is a common symptom of Big Data.)

But as Big Data becomes more prevalent and available, researchers are finding that it’s an invaluable resource, because unlike public government data, it’s available in real time (how many people are Tweeting about looking for a job right now?). Georgetown University provost Robert M. Groves suggested in his keynote that “datasets” as we know them will soon be a thing of the past. Instead of a file of scientifically collected data, we’ll be turning to Twitter, Google, Facebook, and the like. But, as Google Flu taught us, we’re still finding our way.

Public Data and Private Data Can Work Together
(Since Elizabeth Nash led a panel discussion on this topic, she’s uniquely qualified to write this section)

One of the highlights of the APDU Conference this year was the emphasis on seamlessly incorporating various data sources in research projects, online tools, and advocacy work. I had the opportunity to moderate a panel of my own design on how publicly available data is being used alongside private sector information.

Elizabeth Nash, Keith Wardrip, David Norris, and Nima Nattagh, talking data

Elizabeth Nash, Keith Wardrip, David Norris, and Nima Nattagh, talking data

Our three speakers came from very different backgrounds and offered fascinating perspectives on their experiences with using proprietary, purchased data to complement free, public data. Keith Wardrip, Community Development Research Manager at the Federal Reserve Bank of Philadelphia, walked us through his research on employer demand for workers and opportunity occupations using online job posting data that the Fed purchased from Burning Glass Technologies, Occupational Employment Statistics from the BLS, Current Population Survey from the Census and BLS, and more. Nima Nattagh, Manager of Analytics at Verisk Analytics explained to us how insurance companies have taken publicly available data and made the data proprietary. And David Norris, of the Kirwan Institute at the Ohio State University, discussed their Opportunity Mapping framework, and how both publicly available data and proprietary data estimates contribute to their indices. He also provided a cautionary tale of mapping proprietary data without checking it against publicly available data, which was quite provocative and thoughtful.

A meaningful Q&A followed, which culminated into a discussion of the benefits and dangers of limiting access and charging fees for proprietary and value-added public data.

Congress Is Threatening Cuts

One thing about public government data is that it comes from, well, the government. And as you may have heard, there’s been a lot of disagreement in Washington on the role of the federal government, and its various agencies. Proposed budgets are slashing funding for agencies like Census, BLS, and others. BLS has already cut some of its data products, like Mass Layoff Statistics, and Census discontinued its released of 3-year ACS estimates (PolicyMap uses the 5-year estimates). It’s considered unlikely that these proposed budgets will make it through both houses of Congress, but the possibility exists.

Also being proposed is an effort to end mandatory responses to the ACS. Right now, if you get an ACS form in the mail, by law, you have to fill out the 28-page survey, which some consider onerous and invasive. However, without this requirement, the quality of the data decreases substantially, and it becomes more expensive to collect. Canada recently made its census voluntary, with disastrous results. Again, this effort is considered unlikely to be signed by the president, but it’s being discussed.

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Understanding FEMA Disaster Declarations

Natural disasters are “in” right now. Hurricane season is picking up, people in New Orleans and across the globe are commemorating the tenth anniversary of Hurricane Katrina, and residents of the West Coast are growing increasingly anxious about the next big earthquake. A recent feature in the New York Times visualizes the physical and economic impact of natural disasters throughout the country.

We’ve added the locations of federally-declared disaster areas to PolicyMap, and we hope this new data makes it easier to look at natural and man-made disasters in a policy context. These designations are from the Federal Emergency Management Agency (FEMA). They are represented as polygons made up of clusters of counties and American Indian/Alaska Native Areas/Hawaiian Home Lands where state governments have requested and received federal aid for a disaster. Disasters from the past five years (2010 – 2014) are included on PolicyMap in the Quality of Life menu. The map below shows floods:

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Low Income Housing Tax Credit (LIHTC) Update

The Low-Income Housing Tax Credit (LIHTC) program is a federal program that has been implemented over the last three decades to encourage the acquisition, rehabilitation, and new construction of rental housing targeted to lower-income households. Since its inception in 1986, LIHTC has contributed to the leveraging of nearly $100 billion in private investment capital, resulting in the financing of almost 2.8 million housing units. It is one of the nation’s most critical tools for creating and rehabilitating affordable housing.
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It’s a Papal Party in the USA

Philadelphia is abuzz in anticipation of Pope Francis I’s September visit to the United States. Pope Francis is visiting the city as part of a six-day trip to the United States, culminating in the World Meeting of Families in Philadelphia on September 26th-27th. In recent months the news has been about the logistical aspects of the Pope’s visit as the estimated number of religious pilgrims to visit Philadelphia is expected to exceed almost 1.5 million people.


One notable logistical point is that many of the roads going in and out of Philadelphia’s Center City and the adjoining West Philadelphia areas will be shut down to incoming vehicular traffic prior to and during the Pope’s visit. These are the areas where most of the events surrounding the Pope’s visit will take place. City officials have created a “traffic box” aimed at preventing increased congestion on the area’s main throughways.

In order to better understand the potential impact of these restrictions, we used PolicyMap’s Tables tool to evaluate the two areas affected by the Papal visit. We found that 83,021 people live in the Center City area, with 10,475 denizens in the West Philadelphia area. Center City is served by seven hospitals, while three hospitals serve West Philadelphia. With the two areas being served by 31 grocery retail locations and 85 bank branches, access to these services could be significantly affected over the weekend. To get a sense of where these resources are located within Center City and West Philadelphia, zoom in further on the map below.

Hospitals in both areas are navigating issues surrounding accessibility for expectant mothers while local markets are addressing issues regarding food deliveries to cope with the traffic ban. The restriction on travel will have both a positive and potentially negative impact on the lives of local residents, yet this once-in-a-lifetime experience will be remembered by many for years to come.

Pope Francis bobblehead courtesy of Thomas Sprott
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Congratulations and Good Luck, Katie Nelson!

I cannot believe this is Katie’s last full week with us.  I cannot believe we won’t see her smiling, intelligent face every day here at PolicyMap.  I cannot believe I actually offered to write this blog post… 

Katie Nelson – one of our earliest hires at PolicyMap – is leaving us.  Sure, she is leaving us to attend Rutgers University’s Bloustein School to earn her PhD.  Sure, she received a full scholarship.  Sure, it is an amazing path for her future.  But we can’t help ourselves.  We behave like small children when we whine “what about us?” 

Katie has been instrumental in all things related to PolicyMap –  from analyzing data, to developing new product features, to managing groundbreaking projects like, to running our NSP work with the Department of Housing and Urban Development, to managing the installation of a city wide instance of PolicyMap for the City of Philadelphia.  But even more than all of this,  she has been part of an incredible team which has grown from 3 people to 11 people and will soon become 16 people. 

And, so, while we have convinced her to stay on with us as a Fellow, working with us on projects from time-to-time, it won’t be the same. 

Who will… 

–      Be late for work because she gave her toddler the car keys while standing on top of a sewer grate;

–      Sustain a hematoma on her leg while skiing and come into work the next day insisting everything is fine (really);

–      Have her mother drive her My Little Pony collection to Philly from Washington so that she could bomb Phil Vu’s office;

–      Debate the differences among Swedish Fish (large and small), gummy bears and Fruit Roll-ups; 

–      Analyze Sunday night’s episode of the Walking Dead with us on Monday mornings.  We are really going to feel this one. OMG. It won’t be the same. 

Okay, I should stop.  We are saying good-bye, but not forever.  She is going to rock Rutgers and we wish her much success with PhD.  She deserves every minute of it and we hope she’ll be back to us as Dr. Katharine Nelson.  She is a star. 

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Color Me Curious: Why PolicyMap Maps are Purple

Data visualization is a powerful tool—colors can provide very meaningful context, but they can just as easily make for a very misleading representation of your information. There are a few things to think about when choosing colors to symbolize your data, namely, color properties, connotations, and relationships to other objects or features on the ground.


Munsell’s cylindrical arrangement of colors: the horizontal line represents chroma (saturation), the vertical line represents value (lightness) and the circle represents hue.

The technical portion of color choice deals with how colors are interpreted by the human eye, and how they look on our computer screens. Colors have three distinct properties: hue (the name of the color), value (lightness or darkness), and saturation (brightness or dullness). Because colors have these intrinsic qualities, we are able to use variations on these properties to give meaning to our data. This means that rather than using a spectral (rainbow) color scheme to represent information, we can provide color gradients to allow people to see gradual changes. Rainbow colors are not necessarily bad when used for categorical data, such as types of program eligibility, but seem nonsensical when used to represent continuous data (i.e. temperature, or crime rates).

Some colors are more difficult to see and distinguish than others (yellow, for example), while other colors might seem to make a statement about your data (red, for instance, may imply something bad). It is also important to remain aware of relationships with other map features, which is why displaying data as blue or green (colors typically used for bodies of water or parks) could make it more difficult for someone to differentiate between said features.

At PolicyMap, we use purple as the default setting for our maps. This isn’t due to branding, or to our love for singer-songwriter Prince, rather, we use purple because it is an attractive and non-deceptive way to represent a broad range of datasets. We can also use supplementary colors to strengthen our visualizations; here at PolicyMap we often use the color orange to display negative values.

Use the map below to take a look at how we represent population change in purple and orange. In this case, the saturation of each color reflects the estimated percent rise or decline of population.

There are myriad ways to display information on a map, and we hope that this brief introduction to color and visualizations has provided some helpful pointers to help you choose how best to represent your own data! For a more complete discussion, check out our Mapchat: The Art of Making Maps.


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It’s a SNAP… Affordable, Farm-Fresh Produce!

It’s National Farmers’ Market Week! To us here at PolicyMap, farmers’ markets are more than a place to pick the perfect summer tomato. As direct farm-to-consumer sales locations, farmers’ markets connect shoppers to the agricultural systems that grow our fruits, vegetables, and proteins.

Farmers MarketsIncreasingly, farmers’ markets are growing more accessible to low-income consumers. As of 2015, 27 percent of farmers’ markets accept SNAP (Supplemental Nutrition Assistance Program) benefits. Formerly known as food stamps, SNAP is a federal program that allows low-income and unemployed persons to purchase food. Though most supermarkets accept SNAP, many of the locations accepting benefits are corner stores, mini-marts, and other small locations not known for their fresh produce. In areas where food options are limited, farmers’ markets can be an important source of nutrition for low-income people. The map below shows the rate of SNAP-Authorized stores per person, with the locations of farmers markets accepting SNAP:

Farmers’ markets present many challenges to low-income shoppers. They are often open only one day per week, and some may not be transit accessible. Additionally, the cost of farm-fresh food can be high, and is sometimes out of reach for those on a tight budget. Many farmers’ markets and other food retail locations are now able provide financial incentives that increase the value of SNAP benefits, thanks to Food Insecurity Nutrition Incentive grants, a new USDA program. This program allows SNAP recipients to supplement their food budget with additional fruits and vegetables.

Data on SNAP benefits and farmers’ markets are also updated on the Healthy Food Access Portal Research Your Community interactive mapping tool, where you can learn more about how farmers’ markets fit into local food access strategies.

Market photo by flickr user Phil Roeder
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Mapchats – The Art of Maps

The Art of Maps

Data is the key to maps. But show that data in a confusing, unattractive, or misleading way, and the power of your data is lost. Normally, Mapchats focus on using good data, but this time we focus on the nuts and bolts of making good maps.

PolicyMap’s popular Mapchats series continued 7/28/15 with a panel of leaders in online mapping, including Robert Cheetham from Azavea, Jake Garcia from Foundation Center, and PolicyMap’s own Bernie Langer. The topics of discussion include picking the right colors for a map, choosing the right map for the right data, and how to make a good map show change over time.
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