Data visualization as interface

A recent rereading of Wired’s 2010 article “The Web is Dead” cemented a few thoughts of mine on where design in the online space might be headed. The article claims that our use of the web, meaning content delivered via the http protocol, is being eroded by apps—light-weight, low-cost, task-oriented programs. The article describes this as an effect of the natural progression of technology: as special interests start to take control of a new market it becomes fractured, producing silos that in turn allow more user friendly experiences and drive greater adoption.

The “applification” of the Internet is certainly one important factor in its evolution. There is, however, another factor that, in conjunction, could provide an even greater opportunity for design. That trend is open data. Initiatives such as Linked Data have begun to see adoption (e.g. at the New York Times), with the objective of opening up and creating relationships between databases. This presents opportunities to break down the barriers that separate individual websites and their content, creating unprecedented opportunities for the reuse and combination of different data sources. A common critique of apps has been the walled-garden approach to storing data and communicating with other apps—open data promises to change that.

As a consequence we will begin to see more apps that aggregate a multitude of sources, rather than remaining tethered to any particular set of content (though those will likely continue to exist). These will be apps designed for a particular scenario and user experience—their primary point of differentiation. They will use whatever data sources are available in order to best satisfy the goals of whatever experience or scenario is being designed.

The most common applications that aggregate content from multiple domains are search engines. Search engines present all types of content side-by-side, no matter how diverse. They aggregate data around a query or an entity (a person, place or thing), and present you with a relevant cross-section of the web for any topic. This also imbues them with the potential to become a platform for content consumption, in addition to content discovery.

Search engines generally require a high investment in order to provide relevancy of search results. The semantic layer introduced by Linked Data, however, could make parsing and ranking data more accessible, potentially lowering the cost of entry. The separation of data from the container webpage is key, and, with the ubiquity of content management systems, that foundation has already been laid. The outcome will be a greater diversity of specialized content aggregators. Microsoft’s Pivot software was essentially a visual search engine able to display a wide variety of data sources. Other recent aggregation apps are Flipboard and Qwiki. In all of these cases, user experience and presentation are key differentiators: the same content can be found elsewhere, just not in the same context and presented in the same unique way.

Navigating large datasets calls for new paradigms that extend beyond the typical techniques of finding and consuming content, while increasing both usability and engagement. We need to design systems that are adaptive and multi-layered, able to present content of all types. For that reason, I believe that the future of design in the online context is data visualization, used not for analytic purposes, but rather for content discovery. In other words, data visualization could become the interface.

This will yield a range of new views and visual paradigms suitable for displaying aggregate data from multiple sources. Applications that aggregate and visualize large datasets could well become the future of how we access and consume information online.

2 responses to “Data visualization as interface”

  1. A related article by Scott Jenson discusses a “UX of data”. Freed of silos, data can now be distributed across a variety of platforms. My interpretation of his argument is that information itself has affordances and behaviors that can translate into a particular UX, a point I can only agree with.

  2. Related: Fast Co. profile on Bloom and exploratory data visualization. Ben Cerveny talks about building “bite-sized apps that present playful, dynamic engaging metaphors for all the data you’re already immersed in.”

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