Data Visualization or Data Interaction?

… or whatever we want to call it.

Yin Shanyang writes on twitter in response to my last post on vis as bidirectional channel:

Screen Shot 2014-05-08 at 11.18.17 AM

This comment really hits a nerve on me as I have been thinking about this issue quite a lot lately. I must confess I am no longer satisfied with the word “visualization”. And I am even less satisfied by all the other paraphernalia people like to use: data visualization, interactive visualization, information visualization, visual analytics, infographics, etc.

The reason is that I think all these words do not describe well the work I and many other people do. While visualization seems to be appropriate when the main purpose is data presentation, I don’t think it captures the value of visualization when it is used as a data sensemaking tool.

When used for this purpose interaction is crucial. Analysis looks more like a continuous loop between these steps:

  1. specify to the computer what you want to see and how (the specific visual representation)
  2. detect patterns, interpret the results and generate questions
  3. ask the computer to change the data and/or the visualization to accommodate the new question(s)
  4. assess the results … repeat …

Analytical discourse is a term I saw used in the visual analytics agenda a few years back and I think it captures very well this concept. This all interplay and discourse between the machine and the human. This is what many of us are after and I am not sure the term visualization is able to express this concept in its entirety. The value of these tools is not exclusively in the visual representation; interaction plays a major role.

This became even more apparent to me while teaching my InfoVis course this semester. I teach a lot of things about visual representation but when students come down to building software for their projects, what they are really working on is a fully-fledged user interface. They have multiple linked views, search boxes, dynamic query sliders and all the rest. It’s interactive user interface design they end up doing, not visualization. And user interface design carries a lot of additional challenges that go beyond visual representation. Sure, designing the appropriate representation is still very important but many other choices impact the final results.

For instance all my students’ projects have multiple interactive views, maybe sometime just a main visualization, a list of terms and a couple of query sliders for dynamic filtering, but how do you call that? I call that visualization but in practice it’s a complex user interface. Or a “data interface” as suggested by Yin.

One last note. While thinking about this whole idea I recalled that Jeff Heer‘s lab at UW is called Interactive Data Lab and I think he’s got it right. Interaction with the data is the main thing, visualization is the medium we use to create part of this interaction.

What do you think? Too heretic? To much of a hassle?

6 thoughts on “Data Visualization or Data Interaction?

  1. Steve Haroz

    I wonder if it’d be more helpful to start standardizing terms for the “steps” or tasks involved (e.g. specifying visual representations, search, exploration, filtering, optimizing for presentation, etc).

    The differences between the overall processes (visualization, sense-making, etc.) seems to be that they involve different combinations/sequences of these component tasks. There are certainly times when a simple dataset can be loaded into Excel and graphed using default settings to look for simple pattern. That case would involve exploration and visualization but not interaction. What would you call that process? Does it need a name?

    Any overarching term is probably always going to seem too broad or too exclusive.

    Reply
    1. FILWD

      I am not in search for an overarching term and frankly I think it’s too late to introduce new terms anyway. But the concept is important! Data interaction happens anyway, the difference is who is doing it. Today, I see a lot of people doing the interaction behind the scenes and providing sensational static pictures to the world. That’s fine. But I’d like to see more tools given directly to the hands of people to do the interaction on their own. This is why Tableau is the biggest thing ever happened to vis IMO. But we need so much more than that!

      Reply
  2. miska knapek

    Well, I always enjoyed that the FH Potsdam course, where data/info visualisation is taught, is “Interface Design”, if I’m not mistaken. The key is to help people interface and experience information and the routes to this are many.

    Perhaps the question of which genre we fit in, with the genres blending is also part of the contemporary hybrid and emerging media narrative. As genres converge on computers, we end up being able to use many routes to interface information. With the world being a complex thing, it’s worth having a large palette to be able to desribe it with.

    Again, á la the FH Potsdam Interface Design route, in my experience, I think it makes sense to start thinking abstractly about what needs to be communicated and only then start narrowing down which sorts of interfaces to the message are most appropriate – whether they be a poster, book, a/v presentation, sound, static/interactive infovis. And then go and design and iteratively test your way to a good solution.

    Sure enough I enjoy information visualisation a great deal, and there’s more yet to explore there than in other other fields. But it’s just one part of a whole spectrum needed to make an effective interface to data/information/knowledge/wisdom/etc.

    One might be setting oneself up for having to learn a lot if one has to consider the many ways that might be appropriate for interfacing with information. But as the world and its information is varied, it might be better to err on the side of having slightly wider-than-needed knowledge, rather than focus too narrowly.

    A little tongue-in-cheek, I wonder if the pinnacle of information interface design isn’t game design. Game design involves putting people into abstract worlds – and that isn’t information, I don’t know what is :) – and providing interfaces for them to experience that world with. Maybe we should just all start game design courses with a focus on communicating information.

    I also enjoy the Royal Academy of Art’s approach – starting an Information Experience Design course… though maybe that’s taking a bit too broad of an approach.
    http://www.rca.ac.uk/schools/school-of-communication/ied/head-of-programme/

    Reply
    1. FILWD

      I find it interesting that when you talk about visualization you seem to talk about it as a communication tool. This is what almost everyone does and it’s exactly what does not fit with my world view. I might be totally mistaken but in my view vis is not only about communication it’s also about finding information in the first place. What do you think? That’s where it blends well with interactive functions and computational techniques. It’s a much richer picture I am advocating for.

      Reply
      1. miska knapek

        Heh, well, I think we’re on the same page, but just have slightly different senses of the term “communication”. Admittedly I was a bit general in my descriptions. Partly having a past in communications design, I suppose I tend to think of anything which makes some sort of statement as communication – even if it is a tool. Of course, as you say, if one looks a closer, there’s a difference between having more or less ‘pre-digested’ information, and/or being able to put together one’s own mix/view.

        There is definitely much value in having tools for investigating data with, to find our own way through various worlds. Thank for pushing this issue. A static visualisation can say many things, but the viewer is locked into the paradigm and hypothesis of the visualization designer. Interactive visualizations allow the viewer to further test their own hypotheses – testing their own senses of relations in data.

        We’re at a historic time where this is finally possible – thanks to cheap computers, easy programming possibilities, networked data, etc – and we can embark on a whole new knowledge building culture. I’ve been eying the digital humanities field and their interrogations of the issue. Even if there too conclusions of what the field is are agreeably open, there’s a sense there’s a big shift at hand.

        It’s been interesting to see how different fields have been converging. To make good interfaces to data one needs several fields – visualization, computer science, interaction design, humanities, and probably something else too. Whether there’ll be a unified visualization field or whether visualization will just become part of other fields, is an interesting question.

        I think one of the rather interesting sides of visualization that don’t popularly see the light of day, at least not in the popular visualzation field (with some exceptions, like Moritz election work) are various analysis methods that can be used to make sense of data.
        With clustering in machine learning, for instance, rather than try figure out which axes and parameters help define relations one is looking for – eg. success of something – one can have the clustering algorithm look for the relations that bring successful things together, and then figure out what factors define success.

        With an increasing amount of things in life becoming digital, it is a very interesting time for trying to make sense of life, through the ‘view-from-above’ that data allows. And it’d be a shame if data could only be viewed from a static perspective, rather than being able to enter it as a world and wander around it to find knowledge through one’s own arrangements. So we definitely need interactive data investigative tools – and many fields looking into interactive visual knowledge building ( << for the lack of a better term ).

        Though it might seem a bit abstract, my own experimental work has been about trying to make new tools with which to see the world with. They'd be interactive if it wasn't that it would have required more programming skills than I had when I made them.

        ( I've been using the term 'worlds' a bit often, alluding to Moritz Stefaner's comments on the matter – which I dare say I agree with. I hope I've not misunderstood/used Moritz' concepts.)

        Reply
        1. FILWD

          Yes. We are on the same page. And yes, integration of automated data analysis and visualization is the way to go in many areas. There are problems visualization cannot solve without computational power and processing. We see a lot of vis out there on trivial data sets but people in labs, companies and institutions deal with data at a crazy scale. There simply no way to visualize these data without computational analysis.

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