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Visualizing Economics.


The Information Lab - Read our blog. Alteryx Tools Part 2: Filter, Sample and Date Time Three more useful Alteryx tools: Filter, Sample and Date Time.

The Information Lab - Read our blog

Read More Assessing the Market for a BI/Analytics Tool? One thing it makes good sense to do when choosing a new BI/Analytics Tool is to check out what’s happening in the market. What tool are your peer companies choosing. Read More Alteryx Tools in Focus: Fuzzy Match, Make Group and Unique Alteryx has a vast number of tools, and it’s easy to miss some functionality that might be useful, so for this new series of blog posts we’re going to take readers through three tools per blog post, detailing functionality as well as hints and tips for each tool.

Read More Radar Charts in Tableau – Part 3 I’m going to return to the concept of Radar Charts today, with part 3 of the series – you’d never imagine that we could keep talking about such a Tableau-taboo chart type, but we have! Read More Extending your options with Tableau Dual Axes Read More Radar Charts in Tableau – part 2. Clearly and Simply.

Excel charts

Eagereyes. Digital Inspiration - Technology Blog. Visualizing data. Flowing data. A visual exploration on mapping complex networks. Links. Mapping God's Bloodline. This is a genealogical map of Jesus, from the creation of Adam and Eve through Noah, the tribes of Israel, King David, and finally Joseph and Mary.

Mapping God's Bloodline

It includes everyone whose ancestry can be directly traced all the way back to Adam and Eve according to the biblical record. The map shows only father-son and father-daughter relationships, with the exception of Mary, who is shown as the spouse of Joseph and the mother of Jesus. Some relationships may also indicate a more distant ancestry than the usual father-child lineage. Red indicates the bloodline from God the Father to God the Son, Jesus Christ. Other colors show the twelve tribes of Israel (descendants of Jacob). Bibliospot. This project explores how data visualization techniques can be used to display the contents of library catalogues, creating a new way of searching for information.


The first part of this project uses The St Bride Library catalogue as a subject to develop a visual system that can be applied to any other library using a similar classification system. The final design displays the libraries classification hierarchy and the volume of information held on each subject within the classification system. The screen-based outcome of this project is a prototype of an interactive tool/website that enables users to compare library catalogues and discover which libraries hold the most items on a given subject by comparing their library spot size. Max Planck Research Networks. This multi-touch installation, on display at the Max Planck Science Gallery, explores how the various Max Planck Institutes collaborate with each other, and with their international partners.

Max Planck Research Networks

Max Planck Society for the Advancement of Science (MPG) comprises nearly 80 research institutes covering different areas, such as natural sciences, life sciences, social sciences, arts and humanities. With 32 Nobel Prizes amongst its associated scientists, MPG is one of the most respected scientific institutions in Germany and Europe. For this graph visualization, the authors analysed data from SciVerse Scopus for over 94,000 publications over the last ten years.

The dynamic network provides a high-level map of the Max Planck Institutes and their connections. The size of the institute icons represents the number of scientific publications, and the width of the connecting lines the number of jointly published papers between two institutes. Infographic Of The Day: Is "The 1%" Inevitable, Given How Networks Work? The viral protest meme known as "Occupy Wall Street" is still going strong, and according to some provocative research to be published in PLoS One, it may never have reason to run out of steam.

Infographic Of The Day: Is "The 1%" Inevitable, Given How Networks Work?

Why? Because "the 1%"--#OWS-speak for the tiny subgroup of wealthy interests that exerts outsize influence over "the 99%" comprising the rest of us--may be a mathematically inevitable consequence of the way networks self-organize. The paper, entitled "The network of global corporate control", is an attempt by complex systems theorists at the Swiss Federal Institute of Technology in Zurich to "go beyond ideology to empirically identify such a network of power," according to New Scientist. The researchers’ method: analyzing the ownership connections between 43,000 transnational corporations and seeing where the bulk of network control coalesces.

[Via New Scientist] Infographic Of The Day: China's Checkbook Diplomacy. We hear incessantly about the rise of China.

Infographic Of The Day: China's Checkbook Diplomacy

So much so that it’s all a bit too abstract: What does it mean that China’s has become a global force? And more importantly, how have they actually accomplished that? The quick answer? Through business dealings rather than military alliances, and a superb infographic from the Heritage Foundation offers a rarely seen snapshot of that.

I say rarely seen because The Heritage Foundation boasts that it possesses the only database of China’s global investments, and they’ve actually made it available for public consumption. Here are their investments around the world in energy: [Click to visit interactive version] And in metals: The more you look at this chart, the more you start seeing powerful forces at work. You could call it checkbook diplomacy, and it’s vastly different than the bedrock of our own diplomatic efforts. The one country that China is pointedly not investing much in is America. This is profoundly clever stuff. Jerome Cukier.

Change Bad Charts in the Wikipedia The Excel Charts Blog. Corporate annual reports and the Wikipedia are two great resources to find really bad charts.

Change Bad Charts in the Wikipedia The Excel Charts Blog

We can’t do much about corporate reports, but we can actually change the Wikipedia articles. So, here is an assignment for you: find a bad chart and replace it with one that actually makes sense from a data visualization point of view. Do it once a month. Here are a few examples to inspire you. If you like data visualization and don’t feel embarrassed by these charts, I don’t know what will motivate you. Kühlschifffahrt : (file) Swing (politics) : (file) Throughput Accounting : (file) Mauthausen-Gusen concentration camp : (file) Deinosuchus : (file) List of U.S. states and territories by population : (file) Petroleum : (file) Abortion in France : (file) Moon landing : (file) Health care system : (file) Immigration Act of 1924 : (file) Blackpool F.C. : (file) iPhone : (file)

Beautiful but Terrible Pyramids: Tableau Edition The Excel Charts Blog. Promising difficulties. At the recent VisWeek conference, Jessica Hullman and her coauthors presented ”Benefitting Infovis with Visual Difficulties (pdf)”, a paper that suggests that the charts which are read almost effortlessly are not necessarily the ones that readers understand or remember best.

Promising difficulties

To answer that claim, Stephen Few wrote a rather harsh critique of this paper (pdf). As I read this I felt the original paper was not always fairly represented, but more importantly, that the views develop by both parties are not at all inreconcilable. Let me explain. What is cognitive efficiency, or “say it with bar charts” For quite some time, we were told that to better communicate with data, we had to make visuals as clear as possible.

The more complicated way of saying that is talking of “cognitive efficiency”. Various charts based on the same data points. For instance: bar charts are easier to process than pie charts, because it’s easier for the human eye to compare lengths than angles. Fair enough! Agreed! Datavisualization. Travel Time and Housing Prices Map on Datavisualization. MIG Inc. teamed up with the folks at Stamen Design for a series of interactive maps for the One Bay Area project.

Travel Time and Housing Prices Map on Datavisualization

The first map in this series, the Travel Time and Housing Prices map, shows the relationship between travel time for different modes of transit, and housing prices in the bay area. Let’s say you’re looking for a place to live in the San Francisco area. First, you start by entering your office address — let’s use the Stamen studios on Mission Street as an example. Then select how you’d like to travel between your home and work place — how about to go on foot? Consequentially, the travel time doesn’t have any effect, so let’s leave it blank.

The principles behind the visualization is similar to Stamen’s work on the MySociety Travel Time Maps and a more recent project called Mapnificient by StefanWehrmeyer that is heavily inspired by the MySociety project Mapumental. Peoplemovin Visualizes Migration Flows on Datavisualization. Peoplemovin, an experimental project in data visualization by Carlo Zapponi, that shows the flows of 215,738,321 migrants as of 2010.

Peoplemovin Visualizes Migration Flows on Datavisualization

The migration data provided by The World Bank is plotted as a flow chart that connects emigration and destination countries. The chart is split in two columns, the emigration countries on the left and the destination countries on the right. The thickness of the lines connecting the countries represents the amount of immigrated people and the color code from blue to red puts the countries in comparison to the rest of the world. The visualization is built in HTML5 using the canvas element and should run fine in most modern browsers. Review of the 2011 Conference on Datavisualization. On June 24th 2011, the 2011 Conference took place at the Swiss Federal Archives in Berne. Over 150 people from politics, journalism, science and technology gathered to hear about and discuss Switzerland’s future on the Open Government Data front.

The day was filled with presentations by a diverse range of speakers, and a workshop session. The Presentations Prof. Nigel Shadbolt, Professor University of Southampton, Member Public Sector Transparency Board UK In his opening keynote Prof. He made a strong point about how freeing up government data fosters innovation, and that any restrictive license destroys the effort. “If you publish, the apps will come.” Andreas Kellerhals, Director of the Swiss Federal Archives (SFA) Mr. Jean-Philippe Amstein, Director of the Federal Office of Topography swisstopo 60 – 80 % of all political, economic and private decisions have a spatial aspect, geographic information is indispensable for a democracy.

Prof. Workshop Session Closing Keynote. Review: Designing Data Visualizations on Datavisualization. In a recent chat with Jérôme Cukier about the state of visualization related literature, he mentioned Julie Steele and Noah Iliinsky’s new book “Designing Data Visualizations” published by O’Reilly. Jérôme noted that it would be a good primer for people who are already working with data and looking for guidance about making their work more accessible. I thought of another group of people who might find themselves overwhelmed by the amount of choices they have to make while working on visualizations: designers with little knowledge about visual perception and how to apply its’ principles to their work.

After reading it from cover to cover in just a few hours I can highly agree with Jérôme’s recommendation. Julie and Noah manage to introduce the basics of visualization in a very accessible and comprehensible way. Furthermore, the slim format and of the book makes it a great read for your next flight or train ride. What the book taught me Wanna have your work featured here? How We Visualized 23 Years of Geo Bee Contests on Datavisualization. Introduction We were asked by the National Geographic Channel to visualize the history of the National Geographic Bee Contest. They provided us with a dataset containing detailed information about the finals ranging from 1989 to 2011. Our task was to make this data explorable and entertaining for their online readership. The Geo Bee Story Every year thousands of schools in the United States participate in the National Geographic Bee using materials prepared by the National Geographic Society.

Exploring the Data At the start, we analyzed the data to get a feel for the content we had available. Unfortunately the data wasn’t completely consistent (more on that later), so we looked which facts were available for the whole time period: Based on this, we started to build up the story we wanted to tell. Telling a Story Defining and knowing the story you want to tell is one of the most important steps in making a successful visualization. The final visualization consists of four views:

Review of the Visualizing Marathon Berlin 2011 on Datavisualization. Students from the greater Berlin area gathered together on Saturday morning around 10am prepared to design and code away for the next 24 hours. The team behind didn’t leave any wishes open and prepared excellent working conditions at the selected event location Urania. After a brief welcome message from GE the students learned about the data set they will try to make sense of. The data consisted of German demographics and health care statistics.

The teams were assigned with the creation of a visualization that reveals true insights from the data and communicates them in an accessible, innovative and elegant way. The Presentations Before the student started working, they had the chance to listen to two of Germany’s best visualizers Moritz Stefaner and Gregor Aisch. Moritz had prepared a packed deck of things that would have been helpful to know beforehand. Gregor followed with the presentation of his daily routine as a freelance information visualizer. The Works.

Chart porn Newborn's feeding and diaper activity. Big crime meets big data. Marc Goodman (@futurecrimes) is a former Los Angeles police officer who started that department’s first Internet crime unit in the mid-1990s. After two decades spent working with Interpol, the United Nations, and NATO, Goodman founded the Future Crimes Institute to track how criminals use technology. Malicious types of software, like viruses, worms, and trojans, are the main tools used to harvest personal data. Cyber criminals also use social engineering techniques, such as phishing emails populated with data gleaned from social networks, to trick people into providing further details. In the interview below, Goodman outlines some of the other ways organized criminals and terrorists are harnessing data for nefarious ends.

What motivates data criminals? Marc Goodman: Anything that would motivate someone to join a startup would motivate a criminal. What type of personal data is most valuable to criminals? Marc Goodman: The best value is a bank account takeover. How has cyber crime evolved? The Daily Viz. Days Members of Congress Spend in 'Session' Obama's Approval Ratings At Five-Month High. A Year In D.C. Homicides. Infosthetics.