Education/Visualisation (continued)

NASA WebWorldWind is a web Virtual Globe, which runs in any modern browser thanks to JavaScript and HTML5. It has only one purpose to richly visualize geospatial data, be it point, vector raster or other. Although it comes with an abundant set of APIs – application programming interface – to customize the globe. Its modular componentry architecture provides unlimited room to add and extend functionalities.

Thanks to these APIs it is possible to present any type of data, historical through time (4D), today’s weather, tomorrow’s climate, municipal infrastructure, transportation planning, and directions to the nearest coffee shop.

In this work, we present an innovative use of WebWorldWind to visualize geo-crowdsourced data (passive user-generated content). Nowadays, because of our ‘smart devices’ each of us generates a large volume of data, most of which are geospatially located and that can be interpreted for behavioral trend analyses, especially when considered collectively, i.e., to design optimum bus routes, etc.

Over the last few years, several ways of collecting, visualizing and analyzing data have been developed. For this study, we focused on telecommunication data, using data from the 2015 “BigData Challenge” of Telecom Italia.

The available data are for several cities in Italy: Bari, Milan, Naples, Palermo, Rome, Turin and Venice. This data contains telecommunication events: text messaging (SMS), phone calls and internet usage, together with ancillary geospatial data for contextualizing this information.

All entries for the telecommunication data have a timestamp expressed in milliseconds. Each represents information for a 15-minute period from that timestamp. Therefore, each entry refers to 15 minutes of events for each time interval. For SMSs and phone calls, we have information about the number of those received, those sent, and the country code of the SIM card used.

This data is represented in our application using a voxel model built with a grid sized to represent the volume of that activity for each area of origin. The availability of a fourth variable, such as time, improves the ability to model how these activities change throughout the day and week. Moreover, the available standard WMSs (Web Map Services) can also be included to enrich the context of data.

Along with the data visualization, we include summary statistics, such as minimum, maximum, average, standard deviation, range and correlation between criteria within the dataset.

This approach allows an easy and interactive way to browse the data, while maintaining the data in its actual geospatial context, simultaneous with basic statistical analysis useful for their exploration. The tool we developed is multipurpose, though in this presentation we emphasize just one example of its usability in sensing municipal activity related to telecommunication information.

The Earthquake Signal Precursors (ESP) project (a.k.a. Global Earthquake Forecast System) is a revolutionary initiative that will add to the field of earthquake science by building a coherent system monitoring earthquake precursor signals and thereby identify the increasing risk of an earthquake. The current system continually monitors earthquake precursor signals, evaluating and visualizing live data for known correlation between magnetic field anomalies that typically occur several hours to a few days prior to actual seismic event.

This monitoring system is also able to identify the focal point at depth where the increasing energy buildup that precipitates an earthquake is occurring. Continuous broadcast of this live data allows this system to provide advance warning for the increasing level of risk. The local community, major industry, transportation systems and other sensitive infrastructure, will now have the opportunity to initiate preparatory action.

Working in concert with NASA, and taking advantage of recent leading edge research in earthquake science, Alaska students, with support from NASA and NOAA personnel, have designed and built the end-to-end infrastructure to measure, communicate, store, analyze and display live earthquake precursor data. This ESP system is based entirely on free and open source software and hardware. The complete design and build of this system includes:

Sensor monitoring stations

Data transmittal

Server data acquisition

Data storage and analysis

Live data visualization

Data query and access

A World Bridge is an international enterprise for learning, technology using 21st Century Skills, and advanced pedagogy.

http://esp.trilliumlearning.com/

www.aworldbridge.com

 

This project was developed in Alaska as part of
“A World Bridge” real-time, real-world project-based learning program. 

Beyond Visualization  We all know that data visualization can be a powerful tool for understanding. But what about data sonification? Or data sculpture? Or data performance? 
The Office for Creative Research’s diverse practice has brought them from the bustling newsroom of The New York Times to a submersible in the inky depths of the Gulf of Mexico; from the gleaming white galleries of MoMA to the mine-ridden highlands of Angola. In this talk, Jer will share a variety of Open Science projects, including recent work with the Great Elephant Census, National Geographic and an ambitious citizen science project in the UK called Cloudy With a Chance of Pain. Jer will discuss The OCR's evolving practice combining data with art and science, and will propose ways for science communicators to move beyond charts and graphs.