Editor's Pick (1 - 4 of 8)
Leveraging Biomedical Big Data: A Hybrid Solution
Innovate Digital Services To Accelerate Business Growth and Opportunities
Data Analytics: New Edge for Success
Turning Big Data into Big Money
Finding Talent is a Challenge
Max Mortensen, CIO, Norwegian American Hospital
Leveraging the Power of the Enterprise to Streamline and Secure DoD's IT
Terry Halvorsen, CIO, US Department of Defense
Our Calling and Time
Vincent A. Marin, CIO, Sidley Austin LLP
ERP: A New Age of Innovation
William R. Dyer, CIO, Cincom Systems, Inc
The Evolving Role of GIS
By Louis Carr, CIO, Clark County
Geographic Information Systems (GIS) have been around for a long time—probably 25 to 30 years in some cases. Before Google and Bing Maps, and the Internet, many government agencies and a handful of private sector firms used GIS to conduct spatial analysis (i.e. how many businesses are within 2 miles of a particular address), basic routing of vehicles for delivery of good and services and cartography (the science and art of making maps).
Back in those days, the GIS analysts were hard core computer scientists, mathematicians and geographers. Using the tools required a steep learning curve and the software and hardware was very expensive. One typically needed at least a mini-computer to run the software and an expensive plotter to print the maps. But as most things are surrounding technology, GIS hardware and software gradually become more of a commodity and the cost of entry fell significantly in the late 1990’s with the advent and popularity of UNIX workstations (Sun, Data General, HP, etc.). The cost continued to fall in the first decade of the new millennium with the popularity of the Internet, free data from the US Census Bureau and faster and cheaper PCs. GIS software could be loaded on home computers and the price of entry level GIS software dropped to a few hundred dollars—inexpensive enough for most small business owners to afford.
With the introduction of MapQuest, Google Maps and Bing Maps, people were using GIS, but didn’t know it. I believe the future of GIS is spatially enabling apps (mobile, web and traditional desktop software) to take advantage of GIS technology without the end user having to know or learn GIS terminology and practices.
Many cities and counties have had a spatial front end system to CRM and Internet based property lookup systems for years now. People may not know they are using GIS, but they see a map, they can pan and zoom in on that map and they can click on parcels of land to display property ownership information, zoning information, political districts, links to deeds and building permits, etc.
We’ll continue to see more spatially enabled software, even if we don’t see a map
Also, aerial photography became affordable for most cities and counties to add to their internal and public facing property/parcel and street lookup systems. Most county assessors and taxing authorities have had those types of systems operational for a decade or more.
Routing and navigation systems were another milestone for GIS. Several years ago, companies like Tom Tom and Garmin made navigation devices affordable to car owner, bicycle riders and those who like to hike on trails. Even luxury automobile started adding navigation systems as standard features several years ago. These routing and navigation systems have their genesis in GIS technology. While these systems are based on GIS technology all the complexity of having to build data sets and maintain routing tables is hidden from the user through a clean, simple interface that gave turn-by-turn directions.
As we look forward towards 2017 and beyond, where do I see GIS evolving to or what do I see GIS evolving into? I believe we’ll continue to see more spatially enabled software, even if we don’t see a map. For example, some cities and counties have software powering their parks and recreation departments that use the address of the customer to identify relevant classes, courses and activities near the customer’s home address. The customer might have the option of seeing a list of recreation centers 1 mile, 3 miles or 5 miles from his home address. They might have the option of asking where the nearest swimming pool is to their house or current location. That’s done with a spatial query in the background—the user never has to see a map (although once the facility or destination is selected from the list, routing from one’s current location to that facility using google maps or something similar is typically an option). That is very useful on a mobile device where screen real estate is very limited. Another example of spatially enabled apps that do not have to use a map are the location services used by mobile apps to help us find the nearest “whatever” to our current geographic location. Whether it’s the nearest pizzeria, gas station or auto parts store, location services use GIS to identify those specific businesses.
Spatially enabling analytics is also an emerging field. We all see and hear all the noise about big data and analytics. Spatially enabling big data, Business Intelligence (BI) and analytics will immediately put that technology in the hands of the masses without having a steep learning curve as most BI solutions require. This will also allow us to visualize data in ways we could not if we only see lists of data. Density maps, distribution maps, and other thematic maps are great tools for visualization. The value of maps when using big data is users know how to use a map and don’t have to learn a new interface and new controls. We all know how to pan, zoom, turn on layers of data and turn off layers of data. The value of big data and analytics when using maps is the human mind can lock in on patterns that are not readily visible when looking at a list of information. Those software companies that can hide the complexities of big data behind a map will have a decided advantage in the market over those that cannot.
I can certainly see the next generation of GIS technology getting more powerful and more ubiquitous in the coming years. Maps have been a part of human culture for hundreds of years. Paring that with big data is a very natural way for people to finally be able to visualize the vast amounts of data we’ve been assembling and collecting over the past 40 to 50 years.