One can imagine the studios are already hard at work for next year!

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Continued… see the whole scary story on Mint.com.

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The New York Times, in my opinion a leader in data visualization (both interactive and print), offers a nicely designed map that allows you to drill down by state into the details of whether the state is blue, red, or in between.

This state-by-state comparison, however, does little to show the real diversity underlying the single color applied to that state’s terrain. My home state of New Mexico, for example, may be blue-ish in the the above map, but it’s a state composed of very different voting communities (compare Santa Fe or Los Alamos to the rest of the state’s ranching communities and disadvantaged rural towns).

The Christian Science Monitor’s political map breaks out of the state-by-state mold and takes a look at just this sort of diversity. Patchwork Nation presents the nation’s voters in the context of their communities: Monied Burbs, Service Worker Centers, Military Bastions, Tractory Country, etc.

Focusing on the characteristics of each county in a state paints a much more detailed — and more complicated — picture of the American political landscape. Clearly it’s not quite so simple as red, blue, or in-between.

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Some sliders allow changes to the top and bottom of a range of values:

Movoto.com

Kayak.com

Other sliders are designed to help the user choose a value (especially useful when it’s a hard value to remember):

Yahoo! UI Library – RBG Slider Control

Some sliders even include sparklines (small data displays), a very data-rich approach:

Prisjakt.nu (via IXDA-Discuss):

Oakland CrimeSpotting

Other than the obvious cool factor, there are definite advantages to using sliders:

• instant feedback allows the user to focus on the data itself, rather than on manipulating it
• it’s much faster to modify a number of criteria at once (price, bedrooms, bathrooms) while keeping the cursor in one place (compared to a bunch of drop-down lists)
• small changes to the chosen ranges display right away, allowing for faster decision making

There’s always a downside:

• Sliders aren’t good for small adjustments or for choosing very specific values, because they require too much fine coordination (not everyone uses a mouse, and some of us have a lot of cat hair on the mouse’s infrared sensor, which makes it jump around a lot)
• People who aren’t used to seeing sliders may not even notice it’s there, and get frustrated.

Nonetheless, sliders are a very useful design element, so get going and use one! Better yet, use one on every page!

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Oakland Crimespotting

Created by Stamen Design, Oakland Crimespotting uses data from CrimeWatch, Oakland’s community mapping website. Crime reports are grouped by violent crimes, property crime, and “quality of life” crimes. Data on the map can be adjusted with a slider that is also a bar graph of recent crime reports.

A detail view (“Crime Reports”) offers more information about the nature of a crime and a close-up view of the location. You can also subscribe to an RSS feed for a specific geographic area.

The site puts crime information into the hands of the community, allowing residents to research and investigate patterns of activity, and to ask questions. As the site’s creators write, “As citizens we have a right to public information. A clear understanding of our environment is essential to an informed citizenry.”

Los Angeles Times Homicide Map

The LA Times Homicide Project by Jill Leovy combines homicide data from the LA County Coroner’s Office with original reporting. The filtering and user interface are stunning, and I can’t think of a better example of an information-rich data display.

Names and photos of the homicide victims are included next to the map. This humanizes the data in a powerful way, making it impossible to look at the map as just a warning about “dangerous” neighborhoods. There may be patterns to discover in the demographic and geographic information presented, but the tragic human side of the story makes it much more than just statistics. Sadly, new data (i.e. people) are added weekly.

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JsVis, by Kyle Sholtz, is a JavaScript framework for creating “Snowflake graphs” like this one:

There is a lot of potential for visualizing complex relationships with this sort of tool. The basic layout is best for tree structures, but a thread on the discussion board indicates that there is a non-tree display method (particle model layout) which warrants investigation.

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Timeplot is a “DHTML-based AJAXy widget for plotting time series and overlay time-based events over them (with the same data formats that Timeline supports).” Timeplot requires no software installation, server-side or client-side, and can be used with a simple comma-delimited file or with XML. The graph has a liquid layout size so it doesn’t impact your site’s design.

The example below shows an interactive look 3 factors: New Legal Permanent Residents in the U.S. (per year) vs. U.S. Population vs. U.S. History.

My example of a timeplot

Exhibit 2.0 “creates interactive data-rich web pages without ever touching a database or a web server, or doing any programming.”

Timeline “is a DHTML-based AJAXy widget for visualizing time-based events. It is like Google Maps for time-based information.”

My example of a timeline

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Example below from visualcomplexity.com.

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When the Russian chemist Dmitri Mendeleev published the first version of his Periodic Table of the Elements in 1869 he couldn’t imagine that it would become in due time one of the most outstanding information visualisations and that many fields would use it more than one century later as a visual metaphor.

… but the paradigm doesn’t transfer to other fields of information. For example, the Periodic Table of Visualization Methods falls short:

Despite the good work in classifying more than a hundred different visualisation methods, using the scheme of the periodic table and the exact shape of the same for displaying the methods is more than disputable since the paradigm the periodic table adheres to (atomic number, chemical properties, orbitals, etc) has no parallelism to the case of visualisation methods, which invalidates the visual metaphor it intends to be. Stephen Few discusses this point very cleverly in his blog Visual Business Intelligence. Hence I will not abound on this here.

The fact is that mimicking existing paradigms just because they provide a familiar lay-out doesn’t add any insight into what we are looking for, that is regularities in the methods of visualisation. Trying to map the regularities of the chemical elements into those of desserts, or visualisations, is misleading since it hampers finding true regularities and although it covers the transmission of knowledge it doesn’t contribute to pattern detection and even less to knowledge discovery, outstanding outcomes of Mendeleev work.

Building a taxonomy of visualisation methods is not a simple issue and having an equivalent of the in depth work done by Mendeleev for chemistry in Information Visualisation would be a major advance, that, in my opinion we should pursue by finding the main features of each method, building a new paradigm and representing them in original and meaningful ways in accordance with said paradigm.

See also: Periodic Table of Visualization Methods

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