Archive for the 'visualization' Category


Timetric: new time-series data visualization service

Promising new entrant in the online data visualization field: Timetric, developed by a small start-up team in the UK.

The current repository of almost 100,000 series is skewed heavily towards UK economic data sources. User can contribute additional data series, but the supported import format is currently fairly restrictive; Timetric cannot interpret and convert files that do not correspond to their specification.

Data series can also be accessed as RSS feeds, though this seems to be just an XML version of the tabular data. Data series acquired from external URLs do not appear to be “active”, there’s no apparent way to refresh the series from the source.

Charts are in Flash. I’m not a big fan of Flash, but the Timetric presentation is quite polished. HTML embedding is supported. There are also nice PNG sparklines, likewise embeddable.

Unique to Timetric is their support for data manipulation within the system: you can combine two or more existing series using an Excel-like syntax for specifying calculations.

Timetric is off to an impressive start. They’re already publishing two blogs and they are twittering. I see their biggest challenge as they same one that faces Swivel, Many Eyes and others: what’s the business model?


Still no progress on open data visualization

I wrote a year ago that visualization services are stagnating. Other than yesterday’s announcements of Wolfram Alpha and public data in Google search, has there been any progress on online analytics and data visualization?


Swivel has completely refocused on business services, but is still in beta. A new competitor, Good Data, has appeared, but has nothing new to offer. Many Eyes is now powering visualizations for the New York Times, but there have been no significant new capabilities added to the service.

Currently my hopes are pinned on Wolfram Alpha. What will the next year bring?


Public data in Google search results

Google search now returns links to Google-generated data visualizations.

Currently, there are only two datasets available through this mechanism, “unemployment rate” and “population“. It’s unclear when we’ll see additional datasets offered through this channel.

The Google capability may be useful for quick viewing, but (so far) this is a toy:

* there’s no way to download the visualization, or the raw data;
* links are provided to data source information pages (US Bureau of Labor Statistics and Census Dept), but not to the data displayed on the chart;
* no analytic capabilities.

Google’s decision to announce on the same day as the Alpha debut was a childish prank. I suspect that Nova Spivack has it right and Erick Schonfeld is off the mark – but Erick is correct that Wolfram’s service is not live yet and we can’t know for certain what has been achieved until we see it for real.


‘Shanghai, New York and Mumbai’ – GapMinder video

Another excellent GapMinder analysis by Hans Rosling.

The data for this Flash chart is hosted on a public Google spreadsheet. Sources are cited, but unfortunately no links to the source data are provided.


Mapping with GeoCommons

GeoCommons is a new data visualization service from FortiusOne, a business intelligence firm based in the Washington DC area with a focus on mapping applications for the government market. GeoCommons operates two parallel services, Finder! and Maker!.

Finder! is a repository of user-contributed data sources. Very similar to infochimps, except that GeoCommons data tables must be contributed as CSV, with either lat/long or region columns.

Maker! takes tables stored in Finder! and produces a map visualization using Flash and imagery from Google Maps. It’s quite easy to use, and the maps produced by Maker are very attractive. Unfortunately the maps are currently not accessible outside the GeoCommons environment: there are no image or PDF output options, and the Flash maps cannot be embedded into external pages.

Maker! is strong tool for the final step of producing geographic visualizations, with mapping capabilities substantially ahead of what Many Eyes or Swivel offer today. I don’t yet classify GeoCommons as either collaborative (there’s no sharing or annotation) or analytical (no manipulation of data within the system).

GeoCommons is a strong new entrant to the field. The business model is unclear, but since FortiusOne has received a couple of rounds of funding since 2005 and presumably has a solid revenue stream from services there’s reason to hope that the GeoCommons product will have the opportunity to develop further.

See also PolicyMap, operated by the non-profit TRF based in Philadelphia. PolicyMap has a richer set of visualization options than GeoCommons, but there’s no facility for user-contributed content.


Microsoft joins the fray

I wasn’t expecting Microsoft to get into the online data visualization game before Google, but here they are. Microsoft Research has launched DataDepot, “a site that lets you track, analyze, and share trend lines”. It looks like the development team has populated the site with plenty of initial datasets.

From a very quick first glance:

  • Charts are rendered using SilverLight.
  • You can embed charts via iframes.
  • DataDepot refers to each chart as a “track”. There are also “combined tracks” which seem to be overlays of multiple charts with the same Y axis.
  • Quality of the visualizations is so-so. Definitely superior to the Flash output from iCharts, but not as nice as Many Eyes or Swivel. Pointless shaded backgrounds. Bad color selection. The thumbnail image generated for the DataDepot home page is unintelligible.
  • Data can be extracted from the site in an XML format.

(via Matt Hurst’s Data Mining blog.)


Sad but true

Jon Peltier discusses the purpose of charting, with a bad pie chart as the exhibit on trial.

For an excellent explanation of why pie charts are almost universally a poor choice of visualization see Stephen Few’s Save the Pies for Dessert (PDF).

I don’t quite agree with Jon’s contention that charts are often used to make presenters look smart, conceal the facts, accentuate the positive and so on. We use the tools at hand, and we use them as quickly as possible. When the tool at hand for data visualization is Excel, and the default settings are poor, and there’s no quick & easy access to advice, then the end product is bound to be unsatisfactory — and the user might never realize that.

The solution is better tools, made pervasively available. When every analyst and presenter can reach out and grasp a superior tool for the job of information visualization — no learning curve, excellent default presentation, useful advice when needed — then we will see better analysis and better decisions.