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Joe Lamantia, a freelance experience architect/strategy consultant has published a presentation on slideshare.com with the title ‘The Language of Discovery – A grammar for designing Big Data interactions’. The deck has a whopping total of 148 slides and covers a lot of topics, from the basics of big data to how a language can be defined that can form the basis of how interactions around Big Data need to be designed.
For example, as part of the intro of the presentation, there is a simple graph that gives an idea of where Data, and specifically Big Data can play a role in optimizing or innovating a company. It basically splits the company in four parts: R&D, Marketing, Operations and Service & Support and lists the many sources of data that are available to be analyzed.
What I found interesting is how he realizes that ultimately the information of Big Data needs to land in the lap of a person, a human being, someone who needs to take action, make a decision. I realize I’m leaving out a whole world of completely automated systems, where Big Data based triggers directly fire of other activities, such as high speed trading or safety systems, but these still seem to be a minority. When technology, and in this case Data touches humans, things quickly get very interesting: what do people expect, what do they need to do, how do they like to operate etc. This is where a user experience specialist comes into his natural element: how do people work with information?
According to Joe, there are specific ‘modes’ that people can be in when trying to discover something in data. Simply said, the ‘mode’ is the verb of a specific discovery scenario: Locate, Verify, Monitor, Compare, Comprehend, Explore, Analyze, Evaluate and Synthesize. The quest of Big Data would be to help with these: to make it easier to locate information, to better verify, to help explore etc. Putting it in that context brings light to the importance of the interface, the data experience, and how the experience needs to fit the mode the user is in. If I’m just trying to verify something, I don’t need colorful graphs with moving images. If I’m trying to analyze and perhaps spot trends or anomalies, I would value a richer, interactive environment.
Then, an argument is made how these modes are distinct, and often follow each other. For example from Analyze to Compare to Evaluate when it comes to solving a specific problem: first analyze what is going on, then compare available solutions and finally evaluate if a specific solution really meets all requirements of quality and cost. Interestingly, sometimes these activities that follow one another are done by different people, leading to more role specific information scenarios.
More in depth articles can be found on his site
