The most elegant, user-friendly data visualization program is useless without data to visualize; and, historically, those who possess data are reluctant to share it.
Massive data has been dominated by a thin layer of elites, and sophisticated data-visualization tools — such as heat maps, motion charts, time maps, and tag maps — generally have remained within the domain of those elites. This monopoly has allowed very few to decide which data were important to visualize. They’ve created some dazzling digital narratives, but it was a one-way street — very high-tech, but also very news 1.0/web 1.0.
Data Visualization For All
Happily, a movement is rising to pry data from those who hoard it. Tim Berners-Lee gave an inspiring talk at TED in 2009, challenging viewers to join him in a public drive for “Raw Data Now.” In 2010, Berners-Lee returned to TED with news of progress, while also egging the U.S. and U.K. into a competition for who could release more data, and recounting the inspiring case of global open source mapping for Haiti following the catastrophic earthquake earlier this year.
Equally exciting, some extremely powerful data-visualization tools now are available for anyone to create visualizations within a semi-controlled space: Data360, and IBM’s Many Eyes are two of the best. We at the Jefferson Institute just released betas for a set of highly abstracted Drupal data-visualization modules — including an importer — which dramatically increase the range of possibilities for using data in visual storytelling. Our aim is for Drupal users to unleash the power of these tools in their own site.
Yet, for news sites big and small, experimenting with data visualization presents a large, uncomfortable challenge: allowing users the creative freedom to play with the data behind a carefully prepared visualization — and even enable them to upload their own data, much as a reader might comment on a blog or news article. It takes courage and patience. Users might create visualizations that are ugly, misguided, or intentional misrepresentations. But you have to break some eggs to make an omelet, and this is a challenge news organizations must embrace. It will be a key component to their survival in a world of savvy consumers armed with vast quantities of data.
Sea of Data
Busting the professional monopoly on determining which data stories to tell is essential, and it becomes even more important when we consider the sea of data in which we swim today — which is only growing larger. Soon, RFID tags will be on everything, swelling the tidal surge of data to levels we hardly can fathom.
Jack Knight called for media to inform and enlighten, so the people might determine their own true interests. As we come to understand his exhortation’s new, evolving meaning, we must continually challenge ourselves to break down professional barriers in order to empower the infinite diversity of equally true interests. “Raw Data Now” should be our battle cry, and open-source data visualization modules our weaponry.
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Limited access to data also places serious limitations to the depth and breadth of scientific research by individuals, groups, even institutions.
The big reward for the kind of open/transparent user-generated visualization that Aaron speaks of would be “data visualization literacy”. It’s not until you make a visualization yourself that you internalize questions like “Where did the data come from?”, “What’s being left out?”, or “Could more have been asked of the designer?”