The software industry today is in need of a new kind of designer: one proficient in the meaning, form, movement, and transformation of data. I believe this Data Designer will turn out to be the most important new creative role of the next five years.

When I began my career 25 years ago, the notion of design in the software industry was still nascent. It was an engineer’s world, in which just making software function was the consuming focus. So the qualification for this design role was quite simple: do you know anything about software? Those of us trying to apply humanistic or artistic notions to the process faced fundamental technical challenges. It was actually quite exciting, but a constant uphill battle to effect change.

#### Mark Rolston ##### About Mark Rolston is the cofounder and chief creative officer of argodesign.

Over the years, the role of the designer has improved as demand for this talent increased. The introduction of modern desktop GUIs and the web made it clear that computing needed serious and deeper design input. As the discipline grew in sophistication, delineations emerged, first between designers focused on visual concerns (Visual Design) and those focused on the logical end of the problem (Interaction Design). Later, the discipline of Design Research emerged as a response to the growing complexity of software, the growing prominence of multi-part systems, and increased expectations from consumers. More recently, Experience Design has emerged as a response to the complexity of modern systems.

That leads to where we are now: the inflection point where data emerges as a critical new medium for design. Until now, data has been used in relatively simple forms, and the designer’s role was limited to creating user interfaces that presented the data in the most clear and concise manner possible, or provided a simple means of manual data input. The data itself has not been the designer’s problem.

But that is changing—and here’s why.

Data has become a rich medium.

New systems are using rich data, and big data. This is data acquired from the larger world. It is our movement patterns, buying habits, associations, and travel routines. It comes from a network of cloud services, traffic sensors, weather sensors, social networks, public and personal cameras. It is real-time as well as historical. And it exists in volume. Massive volume.

The new design challenge is to use this data for the same humanistic outcomes that we have in mind when we shape products through the user interface or physical form. Even conceding that many interfaces are not changing much—we still use PCs, and the mobile experience still mirrors traditional PC software tropes—we can see the data that moves through these systems is becoming more interesting. Just having this data affords the possibility of exciting new products. And the kind of data we choose to acquire can begin to humanize our experiences with technology.

In fact, a simple way to look at this change is through the evolution of how we even think about data itself. For instance:

Files. At first we were concerned with the medium itself, just getting information into the system and moving it around.

Data. Once the technical medium had matured, we became concerned with pliability and transportability; unfortunately, it was still all too specific and inarticulate for outside systems to make sense of.

__Information. __ Now, finally, we are today able to sort through much of it and begin to classify the data in useful ways; it becomes better organized, but our systems still can’t independently understand it.

__Knowledge. __This is the real goal: a future in which the system actually knows the data, what data it has, where the data can be found, and what the data actually means within any number of unique contexts.

The evolution from raw data to knowledge is matched by a shift in the modern consumer experience.

Today we are creating an expanding array of experiences driven by machines that are essentially hidden from the user. They are services that run in the cloud. They are small programs that run silently on our devices, in our homes, in our offices. They feed not so much on direct user input, but on the abstracts of traffic sensors, weather sensors, social networks, public and personal cameras, and hundreds of other components gleaning our patterns of work, travel and living—these are the cues driving new invisible products in their silent toil. They work from a dataset that is rich and articulate, and the output often comes as direct action.

It can be hard to form an image of these shapeless experiences as products, but this simple framework helps: An object is known first by what it does. i.e., it is a machine that makes toasted bread. That leads to a definition of what it is. i.e., it is a toaster. Finally, having become a socially shared experience, it finds its way deeper into human value systems, with a meaning that stretches beyond its mere affordances. It is known by what it means. i.e., "I have a mid-century modern GE toaster, because I love classic kitchen style." The thing does, is, and finally means, as it takes on increasingly symbolic value beyond its literal value. This path coincides with the modern phenomenon where much of our new technology-driven experiences are invisible and ever more dependent on symbology to lend material character to their inherently ethereal nature.

The Rise of the Data Artist

The time has come for a new design discipline: one that specializes in data as the medium, with a humanistic sense of purpose.

Data is an exceedingly rich instrument that grows ever more crucial as it knits into our lives in ever more complex patterns. Data Designers can use the intent and humanism of their discipline to put this rich medium to its full purpose.

We might consider the Data Designer a hybrid of two existing disciplines. Right now, Data Analysts and Interaction Designers work at two ends of the spectrum, from technical to humanistic. Data Analysts offer the most expertise in the medium, which is a great place to start; but they are approaching the problem from a largely technical and analytical perspective, without the concentration we need in the humanistic aspects of the design problems they address. Interaction Designers today are expert in designing interfaces for devices with screens. They may encounter and even understand the data behind their interfaces; but for the most part, it’s too often left out of the design equation.

Data Designers can train a designer’s eye on the following specific opportunities:

Data modeling. Great data can drive great experiences, when we apply a humanistic lens to the questions of what data we need, and how to organize it to best use. Achieving sufficient fidelity to present knowledge, without creating overhead, is a subtle art.

Algorithm design. Defining the compositions and transformations of data, Data Designers can shape and classify the data into information, helping to ultimately create knowledge.

Manipulation of technical facets. The technical facets of data design—latency, density and size, to name a few—alter system behavior and deeply affect the user experience. Data Designers will consider and manipulate these tools of their expertise to affect quality, availability and usability.

Future computing experiences. Data Design becomes a bridge discipline to the emerging world of applications that have minimal or even non-existent visual interfaces. It’s a bridge to voice-controlled and voice-output user interface and to low-level phatic-type systems.

Cognitive systems. The Data Designer’s toolset is what’s needed when cognitive systems become more commonplace. These systems will do far more processing of data and expect to present less raw information. This processing and output will require design, not just for performance and information accuracy, but also to make systems humane.

Invisible computing. It should be an obvious goal for designers to want to make better computing experiences that require less computer-like affordances. Data Designers will drive how information is used by machines to perform tasks that don’t require human intervention.

Sociological implications. Presented with new capabilities of new technology, the design problem is to determine not just if a certain capability can be used, but how and why it should be used. When systems take in data quietly, from behind the scenes, from more parts of our lives, and shape this data in radical new ways, then we find an emerging set of implications that design does not often face, with profound sociological and safety issues to consider.

Data Design is a fascinating opportunity worthy of our attention now.

Design has been focused on the surfaces of computing, rendering pixels on screens. But now data is becoming an articulate medium of design, in its own right. Current design talent isn’t yet cut out for this. We need a new role with new skills: the Data Designer. Their medium is the shape, movement, transformation, and meaning of data. They turn data into information into knowledge. They help deliver a world where interfaces get out of the way and allow people to live more naturally, spending less time with machines and more on life itself.