Tag Archives: big data
Updated May 31, 2014
With all the recent excitement and good hopes over the White House Climate Data Initiative, and the ongoing progress of the Group on Earth Observation System of Systems (GEOSS), there is another huge data initiative that bears mention: EarthCube.
I have used the word “initiative” for EarthCube but it has also been described as a vision, as a multi-faceted, multi-layered partnership, and also as a “virtual organization.” As such, it bears quite a bit of resemblance to the international GEOSS, but is much more US-based, having been conceived and currently funded by the US National Science Foundation (NSF). Continue reading
Last Update: July 31, 2014 In early January, we heard quite a bit about the polar vortex (not a new term, by the way) as North America struggled with some of the most frigid and dangerous temperatures seen in a … Continue reading
In an earlier post, I had mentioned Esri’s involvement in the large National Science Foundation-funded project known as CyberGIS, which aims to establish a fundamentally new software framework via a seamless integration of cyberinfrastructure, GIS, and spatial analysis/modeling capabilities, particularly … Continue reading
Updated: July 29, 2014
At Esri we are concerned with supporting basic and applied science, but we also recognize that there are many major themes of compelling interest to society that will drive scientific research for the next two decades. And thus we view science as helping us to understand much more than solely how the Earth works, but how the Earth should look (e.g., by way of geodesign), and how we should look at the Earth (i.e., by way of Earth observation in varying forms and the accompanying data science issues of analysis, modeling, developing and documenting useful datasets for science, interoperating between these datasets and between various approaches). Continue reading
Researchers today need to deal with an avalanche of data—from environmental sensor networks (both on land and at sea), social media feeds, LiDAR, and outputs from global- and regional-scale atmospheric circulation and general climate models and simulations. Because of this, “big data” is emerging as a major research theme for the academic community.
I recently had the opportunity to attend GIScience 2012, which is convened every two years and brings together leading researchers from around the world to reflect on a wide spectrum of geographic information science research areas. Attendees are normally university academics and graduate students working in the areas of geography, computer science, information science, cognitive science, mathematics, philosophy, psychology, social science, environmental sciences, and spatial statistics.
The technology tides have shifted again and, as the notion of cloud computing is becoming mainstream across most industries, a new buzzword is emerging: Big Data. Never heard of it? Simply put, the term refers to the ever-growing mountain of data, generated from myriad sources, that organizations must effectively address.
For instance, according to a recent MeriTalk survey, 96% of Federal IT professionals expect their agency’s stored data to grow in the next two years by an average of 64 percent.
Big Data is often described using the Three “V”s: Velocity, Volume, and Variety. By example, let’s take a few of the real world case studies gathered by IBM and provided by Mike Rhodin, Senior Vice President at IBM Software Solutions:
Business data is growing at such a rate that many organizations can become overwhelmed by the big data problem. A recent McKinsey, IDC, and Department of Labor Statistics analysis [PDF] of data in business found that financial/securities organizations have 3.8 petabytes per firm—that’s more than 400 million gigabytes, or about 12.5 million iPads, per company! Banking comes in a distant second with 1.9 PB. This puts big data found in financial services companies into perspective since this is even greater than most communications and media companies’ average of 1.8 PB. Continue reading