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Networks! They are all around us. The universe is filled with systems and structures that can be organized as networks. Recently, we have seen them used to convict criminals , visualize friendships , and even to describe cereal ingredient combinations .
July 23rd 2012 - As the earth and environmental sciences evolve to be more data-intensive, discovering, integrating and analyzing massive amounts of heterogeneous information becomes critical to enable researchers to address complex questions about our environment and our role within it. DataONE, the Data Observation Network for Earth, today released technology capable of providing researchers access to globally distributed, networked data from a single point of discovery. The increasing volume of environmental and Earth science data, from historic observational field notes to recent remotely sensed data, is challenging scientists to locate and integrate pertinent data in a manner that addresses important questions for science and society. For example: How is the spread of invasive species affected by patterns of land use? What factors predict the distribution of emergent infectious diseases, and what are the associated health risks? Are climate models sufficiently predictive?
Online public relations is becoming a go-to strategy for Internet marketing as a whole.
But not before we set some ground rules... W here does your website traffic really come from and what do you need to do to get more of it? Let’s continue our not-so-basic exploration of different traffic sources and their impact on our overall website traffic generation. In the previous post, we looked into direct traffic as our first targeted website traffic source.
It’s not the data that’s the problem. It’s the people. So says a fascinating article in the winter 2011 issue of “MIT Sloan Management Review” (http://sloanreview.mit.edu/the-magazine/articles/2011/winter/52205/big-data-analytics-and-the-path-from-insights-to-value/?type=x&reprint=52205). This extensive article written by several IBM researchers explores how organizations are utilizing analytics to differentiate themselves from their competitors and to become top performers in their industries.
Buy a printable PDF in English and in French . Read the French version – Thanks to Gilles Peyroux. See a text-only version http://bit.ly/rhetological We’ve now has Rhetological translated into German , Italian and Spanish . Thanks to Klaus-Michael Lux and Iván Galarza for their great work. Leave a comment or suggestion
Adam Nieman, Science Photo Library An illustration shows the volume of all the world’s liquid water if put in the form of a sphere (green) and the volume of the atmosphere (pink) if the air were all at sea-level pressure. I recently became aware of fascinating efforts by Adam Nieman to help society appreciate environmental challenges in fresh ways by visualizing volumes that are otherwise abstractions. In 2003 he created the image above, illustrating the volume of the world’s oceans and atmosphere (if the air were all at sea-level density) by rendering them as spheres sitting next to the Earth instead of spread out over its surface. To my eye, this helps powerfully convey the finite nature of these shared global assets. In general, I think there’s great merit in conceiving and testing new ways to communicate visually on the keystone issues of this blog (energy and climate, population and consumption, the relationship between humans and other life).
Data Science DC is a non-profit professional group that meets monthly to discuss diverse topics in predictive analytics, applied machine learning, statistical modeling, open data, and data visualization. Our members are professionals, students, and others with a deep interest in these fields and related technologies. Meeting topics are varied and range from tutorials on basic concepts and their applications, to success stories from local practitioners, to discussions of tools, new technologies, and best practices. All are welcome -- to attend, to meet others, and to present their work! Data Science DC is a Program of Data Community DC, Inc. <p style="text-align:right;color:#A8A8A8"></p>
Come join us for regular technical discussion in the areas of large scale data processing and analytics. We're open to all topics related to "big data" -- distributed algorithms, machine learning, probabilistic data structures, performance and reliability. The focus will be on the practical solutions to real world big data problems rather than just a single processing or storage platform. The format will typically be two presenters with ample time for discussion and questions.