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An interesting example of yet another "next generation" data analysis and presentation tool. You can see the demos at http://www.lavastorm.com/ Emphasis is on visualizing the data analytic method while doing the analysis.

What is it? A social analytics platform which contains over 1,000 days of tweets (all 70 billion of them), Facebook activity and blog posts. How is it of use to journalists? "Journalists can easily develop real-time insights into any story from Playground," PeopleBrowsr UK CEO Andrew Grill explains. Complex keyword searches can be divided by user influence, geolocation, sentiment, and virtual communities of people with shared interests and affinities. These features - and many more - let reporters and researchers easily drill down to find the people and content driving the conversation on social networks on any subject. Playground lets you use the data the way you want to use it. You can either export the graphs and tables that the site produces automatically or export the results in a CSV file to create your own visualisations, which could potentially make it the next favourite tool of data journalists. Grill added: The recent launch of our fully transparent Kred influencer platform will make it faster and easier for journalists to find key influencers in a particular community. You can give Playground a try for the first 14 days before signing up for one of their subscriptions ($19 a month for students and journalists, $149 for organisations and companies).

Europe's One-Stop Shop on Public Sector Information (PSI) Re-use Working to Stimulate PSI Re-use The aim of the ePSIplatform is to strenghthen community, stimulate action, report developments and monitor progress towards a stronger and more transparent environment for the growth of national and European PSI re-use markets. Interactive One-Stop Shop News about European and International PSI re-use Developments Emerging Good Practices Examples of New PSI Re-use Products and Services Information about Legal cases on PSI Re-use Discussion, Communication and Information Sharing across the European PSI community Expert PSI Community Meetings (two meetings per year) Guest Bloggers from the European PSI Community PSI Topic Reports - Analytical Briefings on PSI Re-use (across sectors and issues) PSI Re-use Resources What is PSI re-use? - background information - the European PSI Re-use Directive translated into 27 EU languages and European Commission Communication on Re-use of PSI Directive (language variants) (May 2009) plus other key links and resources.

A good platform to understand what is happening in the Open Data - Europe movement.

Be sure to view the video tutorial: http://www.cc.gatech.edu/gvu/ii/jigsaw/Jigsaw-tutorial.movhttp://www.cc.gatech.edu/gvu/ii/jigsaw/Jigsaw-tutorial.mov http://www.cc.gatech.edu/gvu/ii/jigsaw/views.html Jigsaw: Visual Analytics for Exploring and Understanding Document Collections System Views Jigsaw presents the individual reports in a document collection and the entities within those reports through a series of visualizations. We call these visualizations the system views. Below, we illustrate each view provided by the system and briefly describe their characteristics. Click on the individual images to see a larger version of the view. Also, a tutorial video illustrates the different views as well and the interactive behavior for each view can be seen on the video tutorial page. -tj

Also see "The Information Interfaces Group, an HCI research group in the School of Interactive Computing at Georgia Tech, develops computing technologies that help people take advantage of information to enrich their lives. " http://www.cc.gatech.edu/gvu/ii/

"ReConstitution 2012, a fun experiment by Sosolimited, processes transcripts from the presidential debates, and recreates them with animated words and charts. Part data visualization, part experimental typography, ReConstitution 2012 is a live web app linked to the US Presidential Debates. During and after the three debates, language used by the candidates generates a live graphical map of the events. Algorithms track the psychological states of Romney and Obama and compare them to past candidates. The app allows the user to get beyond the punditry and discover the hidden meaning in the words chosen by the candidates. As you let the transcript run, numbers followed by their units (like "18 months") flash on the screen, and trigger words for emotions like positivity, negativity, and rage are highlighted yellow, blue, and red, respectively. You can also see the classifications in graph form. There are a handful of less straightforward text classifications for truthy and suicidal, which are based on linguistic studies, which in turn are based on word frequencies. These estimates are more fuzzy. So, as the creators suggest, it's best not to interpret the project as an analytical tool, and more of a fun way to look back at the debate, which it is. It's pretty fun to watch. Here's a short video from Sosolimited for more on how the application works: "

Welcome to Data Science Central! Data Science Central is the industry's one stop resource for big data practitioners. From Analytics to Data Integration to Visualization, Data Science Central (DSC) provides a true community experience through social interaction, peer to peer technical support, the latest in technology, tools and trends --and even job opportunities. We look forward to hearing your feedback as we grow this community of professionals in our exciting industry during times of dramatic change.

Data-drivenjournalism:Whatistheretolearn?Apaperonthedata-drivenjournalismroundtableheldinAmsterdamon24August2010.Withadditionalmaterialondatatools,DDJinnovators,andrecommendedwebsitesandarticles.Theimmediategoalsaretoimproveaccessforinterestedjournalistsandtoidentifytrainingneedsforthefuture

VIDEO: document mining with Overview by Jonathan Stray on 10/31/2012 0 With the release of the new, web-only version of Overview that runs in your browser, we thought it was time to make a little video showing how to use it. If that doesn't answer your questions, see also the help page, and the FAQ.

ELAN description ELAN is a professional tool for the creation of complex annotations on video and audio resources. With ELAN a user can add an unlimited number of annotations to audio and/or video streams. An annotation can be a sentence, word or gloss, a comment, translation or a description of any feature observed in the media. Annotations can be created on multiple layers, called tiers. Tiers can be hierarchically interconnected. An annotation can either be time-aligned to the media or it can refer to other existing annotations. The textual content of annotations is always in Unicode and the transcription is stored in an XML format. ELAN provides several different views on the annotations, each view is connected and synchronized to the media playhead. Up to 4 video files can be associated with an annotation document. Each video can be integrated in the main document window or displayed in its own resizable window. ELAN delegates media playback to an existing media framework, like Windows Media Player, QuickTime or JMF (Java Media Framework). As a result a wide variety of audio and video formats is supported and high performance media playback can be achieved. ELAN is written in the Java programming language and the sources are available for non-commercial use. It runs on Windows, Mac OS X and Linux.

Mining of Massive Datasets The book has now been published by Cambridge University Press. A hardcopy can be obtained Here. By agreement with the publisher, you can still download it free from this page. Cambridge Press does, however, retain copyright on the work, and we expect that you will acknowledge our authorship if you republish parts or all of it. We are sorry to have to mention this point, but we have evidence that other items we have published on the Web have been appropriated and republished under other names. It is easy to detect such misuse, by the way, as you will learn in Chapter 3. --- Anand Rajaraman (@anand_raj) and Jeff Ullman Downloads Download the Complete Book (340 pages, approximately 2MB) Download chapters of the book: Preface and Table of Contents Chapter 1 Data Mining Chapter 2 Large-Scale File Systems and Map-Reduce Chapter 3 Finding Similar Items Chapter 4 Mining Data Streams Chapter 5 Link Analysis Chapter 6 Frequent Itemsets Chapter 7 Clustering Chapter 8 Advertising on the Web Chapter 9 Recommendation Systems Index

WHAT WE DO We build software that allows organizations to make sense of massive amounts of disparate data. We solve the technical problems, so they can solve the human ones. Combating terrorism. Prosecuting crimes. Fighting fraud. Eliminating waste. From Silicon Valley to your doorstep, we deploy our data fusion platforms against the hardest problems we can find, wherever we are needed most.

Statistical Reasoning 1 http://ocw.jhsph.edu/index.cfm/go/viewCourse/course/StatisticalReasoning1/coursePage/index/ Most people could probably use a bit of a refresher on statistical reasoning and its methods, and this free course from Johns Hopkins University is a great way to get started on the road back to statistical literacy. The course was originally taught by John McGready and provides "a broad overview of biostatistical methods and concepts used in the public health sciences." Users will find that the home page includes links to the course syllabus, schedule, lecture materials, readings, and additional assignments. The Lecture Materials area includes course notes from the seven modules here. The topics include "Describing Data," "An Introduction to Hypothesis Testing," and "When Time Is of Interest: The Case for Survival Analysis." Visitors can also take advantage of the assignments, which correspond to the readings and the lecture materials. The site is completed by the Other Resources area, which includes a special lecture on the software package Stata and a flowchart designed to help students learn how to choose the correct statistical procedure for the task at hand. [KMG]

Blog Learning to love…grep (let the computer search text for you) Posted by Michelle Minkoff on Aug 9, 2012 in Blog, Uncategorized | No Comments I've gotten into the habit of posting daily learnings on Twitter, but some things require a more in-depth reminder. I also haven't done as much paying as forward as I'd like (but I'm having a TON of fun! and dealing with health problems! but mostly fun!) I'd like to try to start posting more helpful tips here, partially as a notebook for myself, and partially to help others with similar issues. Today's problem: I needed to search for a few lines of text, which could be contained in any one of nine files with 100,000 lines each. Opening all of the files took a very long time on my computer, not to mention executing a search. Enter the "grep" command in Terminal, that allows you to quickly search files using the power of the computer.

An easy to use method for content analysis

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The site now has reviews of common (and some uncommon) tools that promise to help your reporting, projects for the future and soon, we hope, news of promising and interesting use of new methods for reporting.

Solving the Pie Chris Gemignani December 14, 2006 By: Chris Gemignani Last week I challenged you to reproduce this alternative to pie charts in Excel. I promised a screencast to show how it's done. http://juiceanalytics.com/writing/2006/12/square-pie-screencast/ Square Pie Eighteen people answered the call with nearly three dozen different solutions. Click here to watch the screencast showing how to accomplish the two most popular solutions; filling cells with conditional formatting and pushing the column chart to extremes. If you want to look at the source,Clint Ivy produced an excellent version of the cell filling approach.

"Software for Content Analysis: Links to external sites The list below provides links to web sites where one can find information (often including purchasing information) regarding content analysis software as well as other types of software that are often utilized by content analysts. The list was last updated in December 2008. Some links may change. You might also find Will Lowe's Review of Software for Content Analysis useful. "

"Want to help fact-check breaking news like the Malaysian airplane disaster? Here's how and where you can do it"

Visualization contests around the corner May 25, 2011 to Contests | Comments (3) The best way to learn how to visualize data is to grab a dataset and see what you can do with it. You can read as many tips and tricks as you want, but you're not going to get any better until you actually try. Contests are a fun way to do this. Participate So here are a handful of visualization contests to get your hands dirty. Hey you might even win a couple of thousand dollars. Not that money matters to you, because as well all know, learning is your reward. Hacking Education - A contest for developers and data crunchers. DonorsChoose.org has inspired $80 million in giving from 400,000 donors, helping 165,000 teachers at 43,000 schools, and the donation site has opened up this data. Can do you do something with it? Deadline: June 30, 2011. Data In Sight - A hands-on competition in San Francisco's SoMa district with surprise data sources. Some talks, lunch, dinner, and a 24-hour hackathon. Event date: June 24, 2011 (better to register your team early). Tableau Interactive Viz Contest - This one is coming up the quickest, but is the most straightforward. Plus, you get a t-shirt just for entering. Grab some business, finance, or real estate data and go to town with Tableau Public. Deadline: June 3, 2011.

Google Correlate lets you see how your data relates to search queries Posted: 25 May 2011 11:27 AM PDT Influenza search - Google Correlate A while back, Google showed how Influenza outbreaks correlated to searches for flu-related terms with Google Flu Trends. It helped researchers and policy-makers estimate flu activity much sooner than with previous methods. Google Correlate is the evolution of Flu Trends in that now you can correlate search trends with not just flu cases, but with your own data or other search queries. The above, which you already know about, matches flu cases with searches for "treatment for flu." Similarly, the search phrase that correlates highest with "Toyota for sale" is "used Hyundai," as shown below. You can also see how your data is related geographically. For example, annual rainfall (left) strongly correlates with searches for "disney vacation package." Although, it looks like distance is a strong factor in the latter, which should be a reminder that correlation is different from causation. Google is careful to point this out in their FAQ and explanation of the tool. Nevertheless, it's fun to poke around and sometimes see the non-sensical correlations. For example, the strongest correlation with "flowingdata" is "how to scan a document," because the growth rates of both seem similar. There's also a search by drawing function. You draw a time series, and Correlate finds terms that best match that trend. In the below chart, I drew a line (blue) that had steady growth, but plateaued towards present day. What weird correlations can you find? [Google Correlate]