Big Data and the Big Picture
November 14, 2013
In past posts, I’ve discussed how geographical-based Big Data can be used to help companies better understand the communities in which they want to conduct business. Analysts are finding geographical-based data important for understanding a number of areas from logistics to public health. The marriage of Big Data and geographic information systems (GIS) provides a synergistic impact that enhances the insights gained from analysis. The great thing about Big Data/GIS systems is that they can be used locally, regionally, nationally, and globally. Let’s look at a few use cases.
An article written by American Sentinel University reports that GIS is being used to improve agricultural production at the farm level. [“GIS Helps Brings Tech — and Cool — to Farming,” Information Technology Blog, 22 October 2013] The article reports:
“Geographic information systems offer new ways to run machines, improve farming practices, increase yields, and make more money — to say nothing of using the cutting edge of high tech to make one of the oldest occupations in the world cool again. Yes, agricultural youth are finding that they can expand their horizons if they learn GIS. An example of GIS in the fields, so to speak, is a focus on so-called precision agriculture. … Precision agriculture is a field management practice in which farmers use data taken from their farms and combine it with scientific crop management to improve yields and increase competitiveness.”
David L. Chandler reminds us that as cities grow larger the logistics systems that support them become more complex. “As ever-larger ‘megacities’ become home to more and more of the world’s people,” he writes, “the supply chains that bring essential supplies to these crowded populations will become increasingly complex.” [“In The World: Mapping the logistics of megacities,” MIT News, 9 September 2013] To help governments and businesses come to grips with this complexity, Chandler reports, “Researchers at MIT’s Megacities Logistics Lab have gathered data — collected by 11 MIT students paired with local students around the world — on representative neighborhoods in Mexico City, Rio de Janeiro, Beijing, Santiago, Sao Paulo, Kuala Lumpur and Madrid. Now that data has been made available online, at no cost, in an open-access pool of information that’s graphically represented on city maps.” The following “screenshot shows an example of the data now available on the open-access website called km2, produced by the MIT Megacities Logistics Lab. This map shows deliveries to different types of stores (color-coded by type) in the city of Kuala Lumpur.”
When you study the so-called “last mile” challenge facing logisticians, you quickly realize that city planners often overlook logistics challenges even though it should probably be one of the first things they consider. For example, some city planners want to severely limit inner city traffic thus making cities friendlier for pedestrians. Such restrictions, however, can greatly complicate the last mile challenge and severely affect some businesses. For more on that topic, read my post entitled The Future of Urban Transportation: Moving Goods. Geographical-based Big Data research, like that being conducted at MIT, can play an important role in making cities function more effectively. Chandler explains:
“Edgar Blanco, research director at MIT’s Center for Transportation and Logistics and the initiator of the project, explains that it arose from the realization that ‘some of the things we take for granted don’t exist’ in many rapidly growing cities in the developing world. A better understanding of the supply chains needed to support those burgeoning populations was also essential, he says, for both business and regulatory planning. ‘All the models we have tried using for logistics [based on experience in the industrialized world] were not applicable,’ Blanco adds. ‘We need to learn more about the logistics in megacities, mostly because they represent the future of urbanization.’ … In many developing nations, urban centers are increasingly central to economic activity, attracting population from the surrounding towns and villages. But the infrastructure to support these growing populations often lags. ‘The cities themselves don’t know much about the logistics either, about what the city needs from a goods point of view,’ Blanco says. Planners tend to focus on essential needs such as plumbing and sewer systems, ‘but they don’t think about how goods need to move to the cities,’ Blanco says. ‘Once they reach a certain size, there can be chaos. We not only have to design better logistics systems in the cities, we need cities that are designed better for logistics,’ he adds.”
Blanco alluded to the fact that city planners “focus on essential needs such as plumbing and sewer systems.” In doing so, they often rely on Big Data and GIS. In fact, utility planning and monitoring have become some of the primary uses of Big Data/GIS systems.
Regional and National Use
Another article published by the American Sentinel University, notes that GIS systems have “become a tremendously popular technology because of [their] ability to use location and visualization to integrate many otherwise incompatible types of information.” [“GIS: Not Just for Utility Poles or Gas Lines Anymore,” Information Technology Blog, 24 October 2013] The article continues:
“GIS is often associated by lay persons with a relatively small subset of applications: utility companies tracking electrical poles, for example, or a city providing clearance for digging by construction companies that want to avoid water or gas mains. It’s a shame, because there are many more potential uses for GIS, limited only by the available data.”
The article goes on to note how useful Big Data and GIS can be in the public healthcare sector. The article reports that a variety of free databases are available for study in this area and that some of the more common types of databases include information about:
- characteristics of households
- family planning
- other proximate determinates of fertility
- fertility preferences
- early childhood mortality
- maternal and child health
- maternal and child nutrition
Andy Oram writes, “We’ve all seen cool maps of health data. … But few people think about how thoroughly geospacial data is transforming public health and changing the allocation of resources at individual hospitals.” [“Geographic data is the glue for public health and treatment,” Strata, 18 October 2013] Oram notes that more could be done, but privacy sensitivities concerning the release of personal health data makes some data difficult to obtain. He continues:
“Fine-grained targetting requires addresses, which are personally identifiable information (PII). Therefore, the health department can’t release the data to others for privacy reasons. They could fudge the addresses in order to create a deidentified data set, but it would be much less valuable. … Privacy is only one reason data is hard to get. One speaker [at the October 2013 Esri Health GIS Conference] said his facility obtained Medicare data from the Center for Medicare & Medicaid Services (CMS), but that the researchers had to sign an agreement to use the data only for specific purposes. And Medicare data is the best available in this country, he said – although other data sets are coming up to speed. [At that same conference, Bill Davenhall, Senior Health Adviser for Industry Solutions at Esri, said] that the public as well as individual health and social care providers can’t get information about clusters of low birth weight babies until long after the data has been electronically submitted (sometimes as long as 18 months after it is collected). Although the hospital staff enter the data right after birth, the data has to traverse a twisty path to the county and then to the state and then to a national center for statistical purposes. Some useful metadata is added along the way, but if a problem is developing in some area, pediatricians and policy-makers would sure like to hear about it before 18 months have passed. He thinks this is a public health information workflow that needs serious attention to improve its timely access and usefulness within the community.”
Oram concludes his article by noting “three benefits from big data in health care.” They are:
- “It can turn up issues. In Louisiana, for instance, plotting the instances of certain diseases produced a pattern over a particular waterway that they deduced to be contaminated.
- “It can identify what’s working well. If certain regions have a lower rate of unnecessary X-ray tests than others, you can investigate what the good regions are doing and try to get the practice adopted elsewhere.
- “You can allocate scarce resources more effectively. This criterion bothers me a bit because, idealistically, you would give everybody the attention they need for perfect health. Given limitations in what we can spend, we’ll help more people by looking for those clusters of low birth weights.”
Emily Northup reports that the Atmospheric Science Data Center (ASDC) at NASA Langley Research Center is using GIS to map the Earth’s climate. [“Using Big Data in Geographic Information Systems for Observing Earth’s Climate,” earthzine, 18 October 2013] Among the goals of the ASDC project is discovering “new insight into the role that clouds and atmospheric aerosols play in regulating Earth’s weather, climate, and air quality.”
The great thing about GIS’ use of Big Data is the visualization it provides. As the old adage goes, “a picture is worth a thousand words.” There are a number of start-up companies that are offering new ways to visualize Big Data analytics. They all owe a debt to the smart folks who developed GIS and who made us realize the power of visualization.