Researchers have long said that the material published on the Web amounts to a form of “collective intelligence” that can be used to spot trends and make predictions.

Using his 20% time, a Google employee discovered that during flu season, many ailing Americans enter phrases like “flu symptoms” into Google and other search engines before they call their doctors. When he mapped this data, he was able to discover where flu outbreaks would strike up to two weeks before traditional news sources were able to report them. http://www.google.org/flutrends/

This is an example of a time when merging a specific type of data to its geographical coordinates resulted in a unique insight. However, there is much more to do with data and visualization. What was found at Google is only the tip of a very large iceberg. Now that we have access to so much data on the web, we're going to see an increasing need to understand and present that data.

Agenda: This meetup will serve as an introduction to what's going on in the world of data viz. It will be freeform, so if you would like to demonstrate something you're working on, please be prepared to do so. Micah Elliott will be showing uGraph and Ed Borasky will do a GGobi demo. I'll be covering what already exists in the ecosystem and what might become useful in the future. We're dealing with a rapid communication method here. Something that, if done well, compresses the time and space it takes for us to understand something.

If you're interested in Data Visualization, please come to this event. It will be the first Portland Tech Event at WebTrends besides Web Analytics Wednesday. It's our chance to try out the space and see if it is a good fit for this group or potentially for other groups in the future.

Google Group: Ed Borasky recently started a Google group called pdx-visualization. As the name implies, it is a group for Portland-area people interested in languages and techniques for visualization of data. http://groups.google.com/group/pdx-visualization

Amber Case, @caseorganic is a Cyborg Anthropologist studying the interaction between humans and computers and how our relationship with information is changing the way we think, act, and understand the world around us.

R, also called GNU S, is a strongly functional language and environment to statistically explore data sets and make many graphical displays of data.

R is widely used for statistical software development and data analysis. R is part of the GNU project, and its source code is freely available under the GNU General Public License, and pre-compiled binary versions are provided for various operating systems. R uses a command line interface, though several graphical user interfaces are available.

Ed Borasky will provide an introduction to R this Saturday at Cubespace from 11Am-3Pm. Please come prepared with a laptop and the requisite software (link to come soon). If you have any issues installing the software, or need help before the meeting, feel free to arrive at 10:30 Am.

Software Downloads Updated to get ready for the upcoming class. There will be a few more pages coming. The first will be on installing GGobi, and the second will be on CRAN Task Views.

Click on http://groups.google.com/group/pdx-visualization/web/getting-started-with-the-r-programming-language - or copy & paste it into your browser's address bar if that doesn't work.

Here's an abbreviated "Getting Started With GGobi" guide. Please try this stuff out and let me know where it's broken. I just ran through the Windows part and the "Testing on a Social Network Dataset" part and that much of it works. :)

Click on http://groups.google.com/group/pdx-visualization/web/getting-started-with-ggobi - or copy & paste it into your browser's address bar if that doesn't work.

I added a couple of links to articles on using GGobi with social network data.

Click on http://groups.google.com/group/pdx-visualization/web/getting-started-with-ggobi - or copy & paste it into your browser's address bar if that doesn't work.

About R

R was created by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand, and is now developed by the R Development Core Team. It is named partly after the first names of the first two R authors (Robert Gentleman and Ross Ihaka), and partly as a play on the name of S. The R language has become a de facto standard among statisticians for the development of statistical software.

More information: http://www.r-project.org/

Join the Portland Data Visualization Google Group for more updates: http://groups.google.com/group/pdx-visualization?hl=en.

Presented by Charles Parker

A basic problem in computer science is binary classification, in which an algorithm applies a binary label to data based on the presence or absence of some phenomenon. Problems of this type abound in areas as diverse as computational biology, multimedia indexing, and anomaly detection. Evaluating the performance of a binary labeling algorithm is itself a complex task, often based on a domain-dependent notion of the relative cost of "false positives" versus "false negatives". As these costs are often not available to researchers or engineers, a number of methods are used to provide a cost-independent analysis of performance. In this talk, I will examine a number of these methods both theoretically and experimentally. The presented results suggest a set of best practices for evaluating binary classification algorithms, while questioning whether a cost-independent analysis is even possible.

Presented by Iulian Neamtiu.

The relative novelty and rapid evolution pace of the Android ecosystem (platform, vendor-installed apps and third-party apps) means both the platform and apps receive little scrutiny. Hence there is a need for tools that assess, monitor and verify all components of the Android ecosystem. This lack of tools and scrutiny is particularly problematic when combined with the open nature of Google Play, the main app distribution channel.

In the first part of this talk we will focus on multi-layer profiling of Android apps using ProfileDroid, a tool and framework we developed at UC Riverside. ProfileDroid is useful for a variety of Android app analyses, from performance to usability to security. ProfileDroid monitors and correlates the behavior of an app at four layers: (a) static, or app specification (b) user interaction, (c) operating system, and (d) network layer. Using ProfileDroid on 27 free and paid Android apps, we have revealed: (a) discrepancies between the app specification and app execution, (b) free versions of apps could end up costing more than their paid counterparts, due to an order of magnitude increase in traffic, (c) most network traffic is not encrypted, (d) apps communicate with many more sources than users might expect.

In the second part of the talk we will present results from our long-term permission evolution study of the Android ecosystem---platform and 237 apps---over three years. We found that the platform has increased the number of dangerous permissions and does not move towards finer-grained permissions, and that app developers do not follow the principle of least privilege. We will also briefly discuss our efforts with static information flow tracking for Android apps, as well as building a log-and-replay system for Android.

Yes, Hacks/Hackers PDX is still alive! We have two co-organizers, M. Edward (@znmeb) Borasky and Melissa (@capnleela) Chavez.

For January we’re having a 2014 kickoff round table with lightning talks. We want to hear what journalists and developers are working on and where more collaboration is needed.