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The Consequences of Data Ubiquity

Faculty member Daniel Goddemeyer prepares for his spring course, “Urban Fictions,” and talks about his point of view on Small Data, data privacy, and our “digital souls.” MFA Interaction Design connects with Goddemeyer for an interview.MFA Interaction Design: Earlier this year, you taught a workshop as part of a “Data Narratives” program at the School of Visual Arts. Briefly, what was the big idea for the workshop?Daniel Goddemeyer: The main idea for the workshop was to provide an immersive, hands-on experience to encourage and stimulate students’ thinking around the increasing ways that we, as users of digital technology, create “data trails” and what some of the consequences of this impending “data ubiquity” are. We wanted to create awareness for how we deal with this production of personal data, what assumptions this may lead to, what impacts this has, but also what new opportunities this may provide.

A couple weeks prior to the workshop, we encouraged the students to install and use OpenPaths, a location tracking app from the Research and Development Lab at the New York Times Company, in order to bring their own data material into the workshop rather than handing them a non-related third party data set to work with. In the first session, we then taught Processing as a means to visualize each students’ dataset and get an understanding of their locational data and movements during the weeks before the workshop.

After gaining some initial data insights about themselves, students were asked to apply these techniques to a dataset of another participant to look at their data during the next week and create a service specifically designed just for them that helps them in their daily routine in/with the city. They were encouraged to supplement the OpenPaths information with openly available data from Facebook, Google, as well as conversations with their “one-person” usergroup.

Data Narratives Workshop

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Results of a workshop around “Small Data” that explored the impacts and opportunities of individually collected geospatial user data.

MFA IxD: What were some of the students’ first reactions in your workshop to exchanging OpenPaths data?DG: Initially, most of the students had a rather strong reluctance and skepticism against sharing their individual data sets with each other. Faced with the option of either visualizing their own data or taking part in the experiment of exchanging data sets, all of them opted into the latter after giving them time to make a decision until the next morning. For me, this was probably one of the most interesting experiences of the workshop, to witness the change in perception and thinking from the initial objection to the excitement of looking at and working with someone else’s data set.

Setting up this structure and distributing the datasets evenly among the students also meant that each student presented someone else and got presented by someone else in the final presentation, based on their locational data, supplemented with Facebook, Google, and any openly available data from the internet.

Being the subject of a presentation by someone else (who you might have just met a week ago) based on something as personal as your data created a strangely nice feeling in the final presentation, followed by a rich discussion around the impacts and opportunities of individual user data.

MFA IxD: Would you surmise that their comfort level would have differed had they been friends or colleagues beforehand? Or is this just the level of discretion we’ll need to begin designing for?DG: This workshop happened on a very interesting middle ground. If companies such as Facebook or Google collect and make use of our data, we don’t necessarily care that much due to the multiple layers of abstraction and removedness between our actions and our data. These layers have gotten so complex that it’s difficult to comprehend the cause and effect relationship between our interactions and our data we leave behind.

Also, we voluntarily use the services and very much benefit from them and in this case the benefits outweights our concerns around what actually happens with our data trails that we leave behind. On the other end of the spectrum we have become digitally very comfortable about allowing our friends a look into our“digital soul” by sharing our inner feelings and emotions through Twitter and the like.

It would be interesting to follow that thought and see how different social settings and groups deal in different ways with this “data intimacy” and how the existing social relationships influence or affect the outcomes.

MFA IxD: You’ve said yourself that “data itself doesn’t mean anything.” How do you get people — students, clients, and more — to understand the capacity and potential for what data can mean?DG: This is an interesting point since this is a common conflict in my work. Often clients tend to think that data means everything, or better, that simply looking a lot of data is the easy way to telling you everything you need to know.

I think what I referred to in the talk at EPIC was that data in itself means nothing. Knowledge comes from information and information comes from piecing the raw information pieces together in creative ways to make sense and meaning of it.

Although I am very intrigued by the potential of data, I think that we, as designers and creators, have to be careful around the potential biases and issues when working with datasets. Also, in most of the cases, the data that you get to work with, more of less represents a small sliver of the whole picture, which may be misleading or takes you down a path being too confident in what the data seems to tell you.

Given the current hype around visualizations of “Big Data” I am also skeptical about being too intrigued by the eye-candy of data visualization and am more than anything interested in seeing data visualizations as a means to a product, but not as a product in itself. What I especially liked about this workshop was that it worked with “Small Data” and encouraged a very intimate interaction with a small, but highly personal data set.

MFA IxD: “Small Data” isn’t something that gets much attention, but if this workshop is any indication, it’s the small interactions (or, “microinteractions”) that are in need of attention. Is that a fair statement?DG: I think it’s a smart combination of both. Whereas Big Data’s potential (and fascination) lies in the sheer scale, its social and geographic reach, by its nature it becomes very abstract simply by the scale it operates on and very removed from the people who’s story it’s trying to tell.

Due to my interest in uncovering and creating new opportunities that are influenced, inspired or driven by data I’m very much interested in “Small Data” as a means to uncover more intimate and interesting insights and discoveries. Obviously there has to be a bigger context to it but especially for inspiration I’m very intrigued by getting to this granularity. Also, the context that you want to supplement the data discoveries with (such as user research and interviews), becomes much more personal and inspirational due to it’s smaller scale.

What specifically interested me in this workshop as well was that mix out of granularity of the individual “data stories” and the aggregation of the participants data into a social group later on (as in the video). I think taking this even further and applying this combination to a group that was connected by socially more relevant and stronger parameters would yield quite interesting results.

MFA IxD: What’s your role in this?DG: Since I am not a trained data scientist or programmer when working with data to uncover insights and new future opportunities I work with a multidisciplinary teams to balance the data discoveries with user research, visual prototypes and interactive visualizations.

For me, this experimentation with the a multi-disciplinary process that utilizes data to the best of its abilities but creates a holistic perspective that treats the data as one part of the puzzle to uncover new opportunities is what I am mostly excited about. In my work and teaching I try to pass this on and try to make people understand that data means the most if you enrich and supplement it from multiple angles and see it in its context.

After reviewing the output of student work, what does it mean? What is it a starting point for?DG: Due to the brief timeframe of this particular workshop, the most valuable takeaway for the students was to inspire a reflective way of thinking about data and its future impacts and create a starting point for post-workshop explorations by the students themselves.

Besides getting a first technical understanding of working with locational data and longitude and latitude this seems to be the more higher level output that students took away.

In this particular case the workshop was more a first inspirational departure point for the interest in the future opportunities, impacts but also potential pitfalls to be aware and how we, as designers, can use data in responsible and reflective ways for new design opportunities and services.

On a higher level we are currently working on re-doing this workshop in a few different contexts. We aim to give the data exploration and context development a little bit more time and space and hope that this workshop format will yield interesting results, ideas and concepts in the future and serve as a platform to experiment and explore a data-driven concept opportunity discovery process and methodology.


Faculty member Daniel Goddemeyer is a researcher and strategic interaction designer who works with his studio unitedsituation at the intersection of people, technology, design, and urban space and focuses in his work on exploring their future connections, interdependencies, and interactions with each other.

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