Data Visualization and Map Projections

“But whatever the map, all it takes is one. Cartophilia, the love of maps, is a love at first sight. It must be predestined, written somewhere in the chromosomes.”

                                                                                  Ken Jennings - "Maphead"

Have you ever used the Bonne Projection as a Valentine’s Day card? Do you belt out “Wow, a Choropleth Map!” when you see a map of customer sentiment, or perhaps “Happiness” as you see below. If so, you and former Jeopardy conqueror Ken Jennings have something in common.

Map: Courtesy of New York Times

We’re not exactly certain when Mr. Jennings found the time to write a brilliant book about geography.  Perhaps sometime in between competing against Watson and perusing old Encyclopedia Britannica’s? But for us “Cartophiles” we are grateful he did.

“Maphead” is an exploration of human interest and passion as much as it is about geography. The book introduces us not only to Jennings early love of all things geography, but also presents us some unique characters for the world of antique map collecting, the National Geographic Spelling Bee as well as Geo-caching. Many of us are united by our love of maps and seeing data represented spatially.

The New York Times online have offered up some really cool thematic and choropleth maps over the past couple of years that we’re sure Ken Jennings has enjoyed. The appeal of the “Pursuit of Happiness” map above is that it results in questions that may never get asked if the data was not presented spatially. What does this map represent? This particular map utilized population data from the 2002 US Economic Census to be used to derive a ratio between population and arts, recreation and entertainment entities. Because the data from this census was converted from census datasets to a choropleth map, the mapmaker utilizes the human brains immense ability to process information visually.

Here are some other great Choropleth and thematic maps from the New York Times:

Geography of a Recession

Growing - Immigration Detention Centers in the US

Map of Olympic Medals

There is an excellent geography school in the Annapolis Valley in Nova Scotia called COGS (Center of Geographic Sciences). It is there that many budding GIS professionals get to hone their interest and perfect their abilities in ArcGIS, Remote Sensing or Cartography. Two of our professors: Konrad and Ela Dramowicz taught a course in GIS for Business which included a number of hands-on exercises building Choropleth maps.  Their article on Chororpleth mapping and exploratory data analysis in Directions Magazine is definitely worth a read.

Data exploration and Choropleth mapping are important to work in concert together. For variables with a more normal distribution, the standard deviation classification is most appropriate as you saw in the happiness map above.  Choropleth mapping often uses ratios to eliminate the differences in sizes between different areas on the map.

The article also delves into the use of Kolmogorov-Smirnov test for normality to determine the appropriateness of the standard deviation classification. The authors explore normality further by examining the histograms of two variables: Average Value of Dwelling % and University Degree %

Maps and spatial representation data catch our eyes. They allow us to interact with data in ways spreadsheets and data tables do not. We see patterns, we ask questions, and we want to learn more. That is the power of maps.

Ken Jennings… once again, you have the correct answer.

Creating Positive Change through Open Source GIS

Grabbing the User's Attention... Cheaply - Open Source GIS

Data visualization is all about captivating the viewer. You want the users of data visualizations to have a moment of clarity about what is presented on the screen. These moments bring forth both user adoption as well as a clearer understanding of the data. Maps provide a valuable visualization of data for a community, for researchers and for other business users to make sense of their respective environments.

Health care and social services have turned increasingly to open source GIS technologies to paint a picture of the world around us. Open source GIS tools such as Quantum GIS, PostGIS and GRASS to name a few bring affordable GIS solutions to physicians, researchers and social services. Often, health care organizations make substantial investments in enterprise shared health record systems, with little thought to how users will make sense of the vast amounts of data collected.

Maps go beyond telling us how to get to our favorite restaurants. Open source mapping brings geospatial visualization to non-profit medical facilities, social service organizations and public health organizations that traditionally do not have the budgets to find GIS initiatives.

There have been some great implementations recently:

Health care atlases have been created in Great Britain and Ireland that track mortality rates in those two countries and look at data geographically for different types of cancer, or obesity. The project was aptly titled: “The Grim Reaper’s Road Map” and this initiative provided decision makers with clear visual evidence of where improvements to health care delivery are needed.

Several medical centers in the United States have taken advantage of buffer analysis which highlights the areas that surround certain targeted geographic features. Whether or not a population falls within a defined buffer area around this point on the map can be critical in examining:

• Whether or not to pursue a facility expansion when factoring in current population data and demographic information
• Disaster relief planning activities to perform network analysis based on surrounding cities and towns and their proximities to hazardous locations on a map.

How Can You Take Advantage of Open Source GIS?

The biggest investment that is required in developing a competency in Open Source GIS tools such as GRASS and Quantum GIS (which has a plug-in for GRASS) is time. An investment in learning GIS concepts, what a spatial database typically consists of, as well as learning the open source tools themselves. Small organizations that save on the high license costs of ESRI ArcGIS or MapInfo could potentially leverage outside expertise in these open source tools to get started on the path.

Front-End: Quantum GIS

Quantum GIS is an excellent front-end GIS tool that has many convenient plug-ins (especially to GRASS and PostGIS). You can see from the example below how a small nonprofit affiliated with Cal Berkeley employed Quantum GIS to:

• To perform buffer analysis
• To provide a digital elevation model (or DEM) that provides 3-dimensional relief of the surrounding areas to show ease of travel between points
• Using county polygons to show per capita income
• Point analysis of current locations
• Points represented most beneficial locations.

You can download Quantum GIS for free at: http://www.qgis.org/

GRASS – short for Geographic Resources Analysis Support System is an open source GIS tool that can help the user modify raster or vector images as well as employ any of the hundreds of commands to perform network analysis, modify images and process satellite imagery.

The horsepower of GRASS can be combined with the front-end ease of use offered by Quantum GIS through a GRASS plug-in offered in QGIS. This is the optimal way to hide the complexity of GRASS from the user to improve the user experience. You can read more about GRASS at: http://grass.fbk.eu/intro/general.php

Non-profits, health care facilities and social services no longer have to go without geospatial analysis and visualization to provide better clarity to their data. Open source GIS technologies are helping organizations make sense of their surrounding environments and provide the public with low cost, high value visual information on important issues.

For more information on open source GIS technologies and how you can quickly leverage these, feel free to contact us.

The wonderful world of maps

"I believe in such cartography – to be marked by nature, not just label ourselves on a map like the names of rich men and women on buildings. We are communal histories, communal books. ... All I desired was to walk upon such an earth that had no maps."
— Michael Ondaatje

Reading the English Patient by brilliant Canadian writer Michael Ondaatje reminded me of an event I attended a few years ago at the Royal Geographical Society in London. This was a fair that brought together sellers of maps from all over the world. I was struck by some of the artistry of old London city maps, some dating back hundreds of years. It was also striking to see the first map constructed of the London underground. A very intriguing and sinuous design of circuits that looked quite different from the map I picked up at Victoria Station for free that day.

Maps have always told a story from the unique perspective of the map maker. Nowadays, GIS and Geospatial information are used to track diseases, global warming and social issues.

Penn State had a really interesting series of broadcasts on the role of Geospatial information in people’s lives. You can find it here.

It is amazing how far cartography has come since some of those early London city maps. You will see in some upcoming posts some cool aspects of GIS and how it can be applied in a variety of areas.

Marrying OLAP and GIS

There are numerous advantages to building upon the multidimensional data that an organization has stored away. From marketing promotions, bid-collusions detection to political constituency analysis, geography plays an important dimensional role. All of the above mentioned analysis areas required analysis by location, or political boundaries (ridings), or by pre-determined market boundaries. OLAP is critical to delivering a flexible analysis structure for this to occur.

OLAP provides a rapid method to access data at various levels of detail, while hiding the true complexity of the sources behind it. We create dimensions, including geography, to allow users to analyze data in a multitude of ways. Geographic hierarchies can be defined to give users drill down capability to explore data down to the municipal or perhaps neighborhood level.

 We ask ourselves a multitude of business questions on the job every minute of the day.

• How much construction work is contracted within my political constituency and what areas are impacted?
• Where are provincial/state job training services in most demand and are services being utilized?
• What are the demographic factors that impact use of services and how can I show this visually on a map?

These questions of where are the geographic questions that are best represented in combining OLAP and Geographic Information Systems. Traditional OLAP has focused visualization primarily on pivot tables and dynamic graphs. Drilling down to zip code is greatly enhanced if it can be shown dynamically within the map view. The extents of the map are based on the definitions of the hierarchy in OLAP.

How do we marry GIS and OLAP?

OLAP provides a great quick view of your multidimensional data. It can also provide some quick visualization of your results to answer questions. Using GIS, we can go one step further, to map measures and hierarchy values in OLAP to a shapefile. The key is in the “key”. The key in this case will map our value from OLAP to a specific layer in the shapefile.

One of the best advantages to combining with GIS is to be able to include a larger level of geographical detail, such as census or street information for greater detail. This could provide valuable information for such activities as political campaigning or marketing efforts. Through putting OLAP and GIS together, we can combine traditional OLAP measures such as services consumed, or revenue generated with attributes with a more geographic context (income, family attributes, age, and population). The two sets of attributes are set into action with data exploration by the user using a BI tool such as SAS or Cognos.

An intriguing example of GIS and OLAP was collusion detection for provincial construction contracts in Nova Scotia. I had the opportunity to work with a number of engineers and developers to pilot a project that analyzed construction bidding across the province. The results were analyzed by the 18 counties, by region, by political constituency and at the municipal level.

Some of the key business questions that drove the pilot included: 

• How much is being spent in my (insert politician here) constituency and what companies are winning the work?
• What are the discrepancies in unit prices for estimated items and how does it relate to geographic distance from quarries?
• Can we identify neglected regions or constituencies through GIS analysis?

It was an extremely interesting, albeit brief pilot that we did with the assistance of Cognos (pre-IBM). The work was convincing in demonstrating the value of enhancing the geographic dimension in OLAP to include GIS.

How do you utilize GIS in your intelligence efforts?

Using GIS to Make Intelligent Health Care Decisions

In the most recent ESRI Healthy GIS newsletter, there were a number of interesting applications of GIS in the health care sector. Two such interesting projects were based in teaching hospitals: The University of Kentucky Hospital, and Stanford University Medical Center. While used for different purposes, these application show the true power of GIS when they harness meaningful health care and demographic data.

The University of Kentucky employed a combination of AutoCAD drawings and ArcGIS server to build an application that tracks assets within its Level 1 Trauma Center. Users can edit room assets on the fly, as well as view images of the rooms and the assets contained. There could be many uses for such an application including:

• Generation of a near real-time census to track room utilization
• Tracking of potentially hazardous conditions within hospitals
• Assisting in monitoring bed changes and patient flow

Stanford University goes beyond some of the more common health care uses for GIS such as population and disease research, and emergency management. Stanford uses GIS to deal with the rising mobility of the nursing workforce. Retaining nurses is a key factor in improving patient outcomes. The application that Stanford Medical Center developed also helps to determine the optimal teams required to staff during emergency situations.

The entire San Francisco Bay Area external registered nurse population with hospital points buffered at two, four, and six miles up and down the San Francisco Peninsula, showing the ease with which nurses can establish their careers by leapfrogging from one hospital to another.

Stanford effectively combined ArcGIS with the Spatial Analyst extension to marry HR data with geographic and demographic data for planning purposes.

In the Business Intelligence world, we often go to our clients and ask them “what questions would you like to answer as a result of our efforts?” Stanford address a multitude of questions with their GIS applications.

A final usage of GIS that I had some first-hand knowledge of is Health Care GIS in the province of Nova Scotia. As a student at the College of Geographic Sciences, we were exposed to much of the work being conducted to look at demographic distribution and the availability of health care services. Some of the studies being conducted were:

• Breast Cancer mobile screening and the effectiveness of location choices
• Fixed location and analysis of health care utilization
• Demographic information combined with health care utilization

What areas of GIS and business intelligence are most intriguing?

What are some new innovative ways to use GIS in health care delivery?

These are just a few of the questions you think of when you read about how GIS is being applied for better management and improving outcomes.