Yesterday Visualizing.org launched version 1.0 of their Visualizing Player, a media player designed specifically for embedding and displaying infographics and data visualizations.

Perhaps its best feature is that it’s nearly agnostic of the visualization format. Right now it supports HTML5, Java, Flash, PDF, Video, Image, and whole websites. Functionality of the player adapts to each format; interactive visualizations and videos are launched via a play button, high resolution images can be zoomed and panned to explore details.

It also features a full-screen mode which launches a seperate browser window and is especially suited for interactive visualizations. It allows the user to favorite (account required), share and embed, and download a visualization. As Visualizing.org is one of the few platforms that cares for proper licensing (all content is CC-licensed), you won’t have to worry about being allowed to embed and share visualizations with the Visualizing Player.

Here’s what an embedded interactive Flash visualization looks like:

And a static infographic (with zoom and pan functionality):

As with any 1.0 release, there are still a few quirks and loose ends. Especially when displaying website and HTML content, there sometimes seem to be scaling issues and too many scrollbars appear. Some visualizations work around this by launching directly in full screen mode (like Jan Willem Tulp’s Ghost Counties). Also, when panning an image, it inadvertently sticks to the cursor when the mouse is released outside of the Player and then re-enters. But I’m sure the people at Visualizing.org are working hard to release an even better version 1.1.

Small issues aside, we’re pretty excited and think the Visualizing Player is a terrific tool for people to embed and share visualizations. It offers great features for displaying properly licensed interactive and static content, and goes beyond embedding mere screenshots and links. So what do you think? Do you have any suggestions for improvements? Share them here in the comments or directly on Visualizing.org.

For the past year or so I have been dabbling with protovis. I don’t have a heavy CS background but protovis is supposedly easy to pick up for people like me, who are vaguely aware that computers can make calculations but who need to check the manual for the most mundane programming instructions.

What I found was, while it’s reasonably easy to modify the most basic examples to make stuff happen, it is much harder to understand or adapt the more complex ones, let alone to create a fairly complex visualization. So I started documenting my struggle with data, first for my own use, and eventually realized I could share what I learned.

—Jerome Cukier

Be aware that the content is laser focused on how to deal with data instead of shiny visualization goodness. That said, if you plan to create custom visualizations with Protovis, I highly recommend to have a look at Jerome’s notes.

One aspect that the release of the Google Books Ngram Viewer last week shows really well is the power of visualization: instead of offering a huge but abstract data set like back in 2006, Google created a simple visualization tool that shows the data and makes it easily queryable. It’s not as visually appealing as what people like Chris Harrison have done with similar data, but it doesn’t have to be! The purpose of this tool is to give first insights and spawn ideas, which can then lead to a deeper analysis.

What I find most exciting about this project, is that Google enables everyone (no programming skills necessary) to ask questions and dig into a century old corpus of accumulated wisdom in over 5 million books in 6 languages.

While playing with the Ngram Viewer and looking through other peoples’ queries (click on the charts to go to the source), I noticed that there are different kinds of questions people tend to ask, so I came up with this incomplete and unscientific categorization of what the Ngram Viewer is, that I’d like to put up for discussion.

It’s About Comparing Things

A very simple but powerful use case of the Ngram Viewer is to compare ideas, products, concepts, etc. over time. People like to think in comparisons like “good” and “bad”, so this is an ideal entry point for people who don’t quite know what to do with this tool. As a case in point, I wanted to look at how the pie chart stacks up against other visualization methods, and made a first observation: these charts are always opinionated, you can (have to) leave words out, forget them, or spell them differently than others.

Another comparison I wanted to make was about what the development of communication media looks like over the years. Here, I noticed a difficulty: The Ngram Viewer is case-sensitive, so be careful how you spell “Internet”, as there will be fewer results when written in lower-case.

It’s About Patterns

Many people discover interesting patterns, like the occurrence of year numbers. Seems logical, when you see it, but did you think of this before?

It’s About Correlations

If you suspect, that one thing could have an influence on another, just go to the website,try out some terms, and see, whether they occur in literature during the same time periods. This, of course, is not a definite answer, but it’s a good start to investigate.

It’s About Phrases

The term “n-gram” describes words (or characters) that occur in a specific sequence. The Google data is available for n-grams of up to 5 words, which means that it is possible to not only search for single words, but for phrases and sayings.

It’s About Language

Because the data repository goes back to the 17th century, this tool can give us an interesting insight into the development of languages, like in the visualization below, that shows how the medial s (ſ) was superseded by the “normal” s. When looking for insights using this tool, always be aware that words may have been written differently, centuries ago, so they may not show up, if you don’t know what to look for.

It’s About History

Books reflect the history of the world, so I queried the Ngram Viewer for “guerre” (which is French for “war”), a (sadly) omnipresent event of human history. I did the query in French, because a lot of historic wars happened there, and it shows indeed: the French Revolution in 1789–1799, the Napoleonic Wars (1792–1815), the Franco-Prussian War (1870), and then, of course, the two World Wars. If you do the same query in American English, you’ll also notice a strong bump in the 1970s, the Vietnam War, which didn’t have the same impact on France as it did on the USA.

I also made a query for “baïonette” (bayonet), a tool of war, and indeed, it correlates with the wars, and we also see, when it became available, and that it’s less used today (I guess that it still shows up because it’s written about in history books).

This shows another interesting use case for the Ngram Viewer: let a teacher ask her students “what do you see?” They’ll (hopefully) know about the two World Wars, but then they’ll have to go and do some research about what those earlier spikes might mean.

It’s About Society

A last example that I want to go into, is one, that isn’t possible with the current version of the Ngram Viewer: the comparison of societal change within different language areas. I supposed, that “racism” would have  had different impacts in different regions of the world, the USA specifically. And indeed, when we superimpose queries in American English, British English, German and French using Photoshop (be sure to adjust the percentage scales correctly), we can see the bump in the late Sixties in American, but not in British literature. Also interesting is the development in France, which is strangely linear, and different from all the others.

Conclusion

I hope you had as much fun and insights as I had while researching this article. I strongly believe, that by making a visual viewer available for this huge data set, Google did a lot of people a great service, who wouldn’t otherwise have a chance to dig into this data at all.

So, go try the tool yourself and post interesting queries in the comments or to the Ngrams Tumblelog. Also be sure to read Google’s introduction to the Ngram Viewer, which has some interesting background information. And don’t forget, that you can click the links at the bottom of the charts, which will take you to the sources in the huge repository of books, that Google has digitized.

Polymaps is a free, open-source JavaScript library for making dynamic, interactive maps. It is the result of a collaboration between Stamen Design and SimpleGeo. Founded by Erik Rodenbeck, Stamen is one of the most respected data visualization studios out there. SimpleGeo is a service that provides location infrastructure that makes it easy to add geo-aware features to applications.

Description

Polymaps provides speedy display of multi-zoom datasets over maps, and supports a variety of visual presentations for tiled vector data, in addition to the usual cartography from OpenStreetMap, CloudMade, Bing, and other providers of image-based web maps.

Because Polymaps can load data at a full range of scales, it’s ideal for showing information from country level on down to states, cities, neighborhoods, and individual streets. Because Polymaps uses SVG (Scalable Vector Graphics) to display information, you can use familiar, comfortable CSS rules to define the design of your data. And because Polymaps uses the well known spherical mercator tile format for its imagery and its data, publishing information is a snap.

Examples

The provided examples give a hint about the possibilities you have with Polymaps. Here are two elegant examples for maps based on custom tiles made with CloudMade:

The following example shows different ways to display data. The used tiles are served by another great piece of code by Stamen named TileStache:

This visualization shows the pavement quality of San Francisco streets, mashing up two datasets from DataSF. Streets with high pavement quality are shown in green, while those in the worst quality are red.

Flickr Shapetiles is a slippy map of all the shapefiles that were generated from geotagged Flickr photos.

You can start using Polymaps right away by downloading the source code from Polymaps.org or checkout the latest version from the public repository on GitHub.

Together with Kim Rees from Periscopic I have reviewed the social data visualization application Swivel. Swivel is a simple to use web application that lets you visualize public or private data sets and collaborate openly or in closed user groups. My review is the first post in a series of reviews that will be published over at Information Aesthetics. Following up are reviews of the online tool Many Eyes and the desktop application Tableau Public.

Read the full review on Infosthetics.com and let me know your feedback and thoughts over there in the comments.

Humble software development released a new visualization library called HumbleFinance. It is visually and functionally inspired by the Domestic Trends visualization of Google Finance. Unlike Google’s version, which uses Flash, it is written entirely in JavaScript and uses HTML5′s canvas tag, so no Plug-In is required to display the visualization.

Although the HumbleFinance graph is especially suited to display financial time series, any two two-dimensional sets of numerical data which share an axis can be displayed.

The graph is divided in three areas: On top a section of the data sets can be compared side by side. At the bottom an overview over one data set is displayed. It also supports full interactivity, i.e. hovering over a data point in the demo shows connected points and the associated data. You can also scrub through the timeline and zoom the section of the data.

On its trail to organize the world’s information, Google has just added a new experimental product to their Lab. The Public Data Explorer makes “large datasets easy to explore, visualize and communicate”. It is designed to help people comprehend data and statistics through rich visualizations.

The Explorer uses Google’s ability of syndicating public datasets previously introduced in their search results. The visualizations are built on top of their Visualization API and the animated charts are based on the Trendalyzer technology Google acquired from the Gapminder Foundation. It has previously been available in the Motion Chart in Google Spreadsheets.

Creating a visualization is straight forward and a matter of minutes. A user can chose the data and how to visually represent it. Additional data can then be applied to different attributes of the visualization. The created views can be shared via permalink or embedded in any webpage.

The data

Google selected the data sets by analyzing anonymous search logs to find patterns in the kinds of searches people are doing. This way they can cover a majority of the demand for statistical data with a limited amount of different data providers and data sets. Here’s a list of the currently available data sets:

The World Bank, the U.S. Bureau of Labor Statistics, the U.S. Census Bureau, the Organization for Economic Co-Operation and Development (OECD), the California Department of Education, Eurostat, the U.S. Center for Disease Control, and the U.S. Bureau of Economic Analysis.

Conclusion

In my opinion Google is in a strong position to evangelize the advantages of transparency in information distribution. Let’s hope this encourages more insitutions to open acces to their data sets. I am also happy to see a user friendly addition to the solutions already available for developers to access public data programmatically. It makes it really easy to create and share visualizations based on public data. As a note: If you’re looking to display your own data, I recommend having a look at the recently launched Tableau Public.

What do you think? Are the available data sources sufficient enough to be real value to the average user? If not, what would you like to see added to the list? Please share your thoughts in the comments below.

Tableau Software today launched a new product that brings public data to life on the web. Tableau Public lets anyone who posts content to the web easily create interactive visualizations and publish them online.

How it works

Tableau Public is a freely available desktop application and can be downloaded from the Tableau.com website. The data can be visualized from multiple text or spreadsheet file formats. A visualization can be as simple as a single chart or as complex as an interactive dashboard application. I had a short introduction to the user interface and it seemed to solve some problems that its competitors struggle with. Tableau Public focuses on the data first and then suggests adequate visualization methods. Thus helping unexperienced users choose the right chart.

Bringing visualizations to the web

Everything you publish with the application is stored on the Tableau Public servers and is publicly accessible through the website. This is important to keep in mind while visualizing sensitive data. Also, there’s a 50MB online storage limit. The visualizations are composed with pure HTML, CSS and JS and can be embedded using a short JavaScript snippet.

I really enjoy the development we see with open data and the available tools to create meaningful visualizations. The approach that such a tool can be used for free as long as the created visualizations are freely accessible, is exemplary.

The Google Earth blog recently posted some examples of how well Google Earth can be used as a scientific visualization platform. The examples are posted by Thijs Damsma from the OpenEarth Initiative.

OpenEarth is the open source initiative to archive, host and disseminate Data, Models and Tools for marine & coastal scientist and engineers. It aims to remedy the above-described inefficiencies by providing a project-superseding approach.

It seems like the usage of Google Earth goes way beyond checking for your neighbours garden and with the possibilities fo KML complex data visualizations in a 3D environment are at your fingertips. OpenEarth even provides some tutorials on how to get startet with these types of visualizations.

Do you have any other examples of data visualization in Google Earth? Or are most of the data mash-ups done with Google Maps?

Torstein Hønsi from Vevstein Web has created a really impressive Javascript charting library. Highcharts allows a developer to easily include interactive charts in websites and webapplications. It currently supports line, spline, area, areaspline, column, bar, pie and scatter chart types.

The graphics are rendered using the Canvas tag or occasionally SVG & VML. The supported browsers are Safari, Firefox, Opera, Internet Explorer+ and it also runs great on the iPhone. The default skin for the visualizations does quite a good job regarding readybility and clarity. Unfortunately there are some Powerpoint-esque skins as well (please, just cut them out). One really nice feature is the zoomable timeseries, which I haven’t seen before in any Javascript library.

The library is free to use for non-commercial applications and there are commercial licenses as well. I look foreward to see some real-life examples of it but the Demo Gallery looks good so far.