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First to explain… no, there is no time. Let me sum up: you are a scientist with complex geospatial data visualization challenges. We at Microsoft Research have a solution for you and we’re enhancing this through the release of a software library called Narwhal. (We threw in some example applications as well.) The parent project is Layerscape and the geospatial stories are told by using the WorldWide Telescope visualization engine. The release of Narwhal is in line with our philosophy of “As long as we’re going to build some tools, let’s share them and save others having to re-invent.” Inconceivable! For more: read on!
Suppose you have some data that you’d like to look at… and it is complicated data. What do I mean by complicated? Perhaps you have a model of an electrical impulse travelling through a maze of 7,000 neurons. Or you have recovered the dive trajectories for the 43 Weddell seals you tagged last summer, or you just derived the magnetic field interactions between Jupiter and Callisto, or the Jaguar supercomputer has finally finished your solution for the thermodynamic structure of the Earth. Let’s run through the two questions that occur to the data visualizer—you—at a time like this: What format should my data be in? And how do I look at it?
WorldWide Telescope visualization of data on Puget Sound water flow
Unfortunately, there is as yet no single answer to these two questions; and to be fair, you probably already know what format your data is in (be it MATLAB, Comma Separated Value, NetCDF-CF, Microsoft Excel, or whatever). But because your data is complicated, you find it difficult to render and examine on your laptop. Well, we built WorldWide Telescope (WWT) to take advantage of your PC graphics card and now you can look at 500,000 data points as they unfold in time; watch this tour to get the idea. The ability to see the data is just the beginning; we are painfully aware that even though you can see the data, there are lots of other tasks to perform before it is useful, and that is why we built both the Layerscape website (to support content sharing) and the WorldWide Telescope Add-in for Excel (to help you import your data into WWT). All of this you can learn about at Layerscape.
So far, so good; but if you are really a technical programmer, you will see more potential here—more visualization power—than you can readily access by using Excel. In fact, you may want to be able to connect directly from your software—which helps make sense of your data—to WWT where that data will appear as pixels and lines and circles and polygons and moving sidewalks and drifting balloons and neural impulses and seal-dive trajectories and magnetic fields. Enter Narwhal: software that helps you organize your data and send it to WWT. Narwhal is in its first release, so it is not the ultimate solution, but it does take big jump in that direction. To see what sorts of things Narwhal can help you do, take a look at this video.
To wrap this up: we are certain that visualization is a key to understanding data, and that humans—and specifically, researchers—are increasingly good at deluging ourselves with massive, complex, hard-to-understand datasets. At Microsoft Research we are both happy and fortunate to get to work on related tools: Layerscape, WorldWide Telescope, and the WWT Add-in for Excel… and now Narwhal. We hope that they find their way to the scientists and educators who need them—and we will continue to refine them, so watch this blog for updates.
—Rob Fatland, Senior Research Program Manager, Microsoft Research Connections
Location sensing has become ubiquitous—it’s present every time you turn on your smartphone or engage your car’s navigation system. It’s also become critical to a variety of outdoors and remote research applications, such as wildlife tracking, participatory environmental sensing, and personal health and wellness monitoring.
The Global Positioning System (GPS) is commonly used for tagging the location of data samples. But traditional GPS location fixing is a power hog; in fact, the typical smartphone battery will drain in about six hours if the phone’s GPS is constantly running, which is particularly problematic in remote locations. Moreover, a smartphone is fairly bulky—not exactly the kind of sensor you can, for example, attach to fruit bats to monitor their nocturnal flights.
Cloud-offloaded GPS may provide researchers with an energy-efficient solution for location sensing.
In a paper titled, “Energy Efficient GPS Sensing with Cloud Offloading” (PDF file, 6.13 MB), we propose a potential solution to this battery power and size dilemma. This paper describes cloud-offloaded GPS (CO-GPS), an innovative way to perform location sensing by using tiny embedded devices and the cloud to share the work of GPS signal acquisition and processing. By logging only a few milliseconds of raw GPS signals, the device can store enough information for resolving GPS-based location, and it consumes two to three orders of magnitude less energy than stand-alone or mobile phone GPS sensors. The signals are then sent to the cloud with sensor data to reconstruct the location and time that the samples are taken. In delay-tolerant, data acquisition applications—such as animal tracking, float sensor networks, participatory environmental sensing, and long-range time synchronization—CO-GPS is ideal for extending the battery life of mobile devices.
The paper received the Best Paper Award at ACM SenSys 2012—the premier conference on networked embedded sensing systems and a top forum for the sensor network research community. Many attendees consider the work to be a breakthrough in pushing continuous location sensing to extremely low power devices that can be carried by humans, animals, or recreational equipment.
We anticipate that CO-GPS will be a boon to citizen-science efforts, particularly those that rely on participatory sensing from embedded devices. For example, the CO-GPS approach is a key enabling technology in Microsoft Research Project CLEO, a participatory environmental sensing system that we are showcasing at the 2012 AGU Fall Meeting this week.
—Jie Liu, Principal Researcher and Research Manager, Microsoft Research, Sensing and Energy Research Group
—Yan Xu, Senior Research Program Manager, Microsoft Research Connections
Plant biologists in Brazil are working to develop a better understanding of tropical ecosystems—how they work and how they impact climate change, not only in the region, but worldwide. These researchers are dedicated and disciplined. They’re in the field from dawn to dusk, working through rain, wind, heat, and cold, applying all of their energy to understanding these complex ecosystems. This is intense observational work: they take copious notes and then, after grueling hours in the field, they return to their labs and flesh out their field notes in detail, striving to fully capture and make sense of what they observed. It all adds up to a long day that can take a toll on even the most committed researchers.
At the University of Campinas (better known as UNICAMP), computer science professors Ricardo Torres and Cecilia Baranauskas are exploring solutions that might help these overworked field researchers. The professors’ computer science students are creating environmental data-management apps that allow plant biologists to go to the field, observe the ecosystem, take notes by using digital devices, and then push that data to the cloud. (This work is an outgrowth of a project in e-phenology, which is supported by the Microsoft Research–FAPESP Institute for IT Research.)
Environmental data-management app for recording and sharing field observations
The environmental data-management apps should increase the precision and accuracy of the recorded data, eliminating the errors that often creep in during the transcription of handwritten notes. The ready availability of previously entered data will enable researchers in the field to easily compare new observations to past ones and to enter new information by updating a few spreadsheet cells. Moreover, by pushing the data to the cloud, it will be available to colleagues no matter where they are, enabling real-time collaboration between the researcher in the field and the team back in the lab.
With the goal of generating a variety of application ideas, the professors have split their computer science classes into multiple groups, each of which proposes a solution. Then they iterate. They talk with the plant biologists and accompany them to the field, in order to understand their needs. If all goes as planned, these students will devise applications that enable biologists to more fully record their observations in real time and preserve the record quickly, safely, and accessibly in the cloud. And what a nice convergence of high-tech computer science and shoe-leather biology that will be!
—Juliana Salles, Senior Research Program Manager, Microsoft Research Connections