Information Interaction Design – Shedroff, 1999

Data management involves the classification, storability, retrievability, share-ability, and the generation of information across multiple platforms (print, web, mobile, etc.) that represent the gist or essence of “valuable, compelling, and empowering” physical and/or digital user experiences.

In 1999, Nathan Shedroff asked: “How do we as designers create meaningful experiences and interactions for others?” (Shedroff; 1999:288). He introduced the importance of Information Interaction Design as the design of information for contextual user-centric interaction. According to Shedroff, emerging trends in information processing of designed products and experiences include: “information overload, information anxiety, media literacy, media immersion, and technological overload.” (Shedroff; 1999:267) Those, in turn, define the focus of HCI and the practice of Information Interaction Design.

[W]hat most of us deal with everyday […] is not information. It is merely data.” (Shedroff; 1999:270)

The design of data must address the in-forming condition of information; that is, how it communicates in its form by turning data into meaningful and useful content with a servicing intent and contextually thoughtful point of view.

Shedroff maps 3 disciplines as comprised in the practice of Information Interaction Design: “information design, interaction design, and sensorial design.” (Shedroff; 1999:268) Information design makes information valuable and interaction meaningful by way of organizing and framing data for its appropriate audience. Interaction design represents storytelling through interactional platforms (performance, print, digital, etc.) that identify with target user requirements. Finally, sensorial design addresses the psychographic and cognitive needs of users by understanding how design affects the senses (vision, touch, smell, sound) and how it might enrich emotional aspects of user experiences. Information Interaction design, then, seeks to provide efficient and memorable experiences for users within the boundaries of information design, interaction design, and sensorial design according to predetermined or emerging user requirements (needs, abilities, desires, and expectations).

Because the design of data informs the creation of participatory, integrated, and resourceful experiences, Information Interaction Design provides active experiences of knowledge that are interactive, persuasive, efficient, and effective. Shedroff describes wisdom as a “metalanguage”; which is to say that wisdom is an exploration of knowledge and a continuous synthesis of acquired, preconceived and experiential knowledge. The knowledge of knowing reaffirms itself in one’s ongoing rewiring of his/her thought patterns in light of newly established perceptual understandings. Design of data encourages the discovery of new knowledge through meaningful patterns and experiences.

Wisdom is a kind of metaknowledge, a blending of all the processes and relationships understood through experience.” (Shedroff; 1999:273)

Successful interactive systems are first and foremost designed to allow users to discover and learn from information, as well as to interact and control data outcomes through visual feedback. Those systems may be described as engineered to adapt, evolve, and self-sustain overtime as they enable users to populate content and provides them with the virtual freedom to co-create. In a sense, users become producers of their own interactive experiences.

Some important points to consider when designing data-driven interactive experiences:
1) How design organizes and packages information to its audience determines how information is expressed and perceived and what types of values one might assign to the overall patterns or messages.
2) Metaphoric interpretations and explanations of data may render data inaccurate in its appeal to cognitive and structural understanding of its audience.
3) Interaction design helps transform data into an interactive storytelling.
4) Systems can be tailored to allow user input and provide partial user-control.


Shedroff, Nathan. “Information Interaction Design: A Unified Field Theory of Design” Information Design. Jacobson, Robert (Ed.). MIT Press, Massachussets: 1999, pp. 267-292


Designing for Perceptual Differentiation

[T]here are unique features of individual perception that have important implications for the design of information. […] designers must search for some areas of commonality.”  (Whitehouse, 1999:103)

Oliver Sacks’ accounts of visually impaired patients demonstrate the nature of perceptual experience as essentially idiosyncratic. This “perceptual fingerprint” is identified as the difference between seeing and understanding, between vision and cognition. Roger Whitehouse categorizes perceptual processes as follows: sensory mechanisms which are defined by individual sensory receptive capabilities (i.e., retinal and eardrum functions); cognitive processing of sensory inputs which depends on individual neural wiring; and ascribed meaning to perceived sensory inputs which results from individual experience and cultural background.

As babies, we leave a womb where we receive little sensory stimulation and, with all our sensory input devices in full working order, emerge into an explosion of light, color, sound, smell, noise, movement, touch–sensations that have absolutely no meaning for us.” (Whitehouse, 1999:108)

Because we possess the ability to adapt and change in accordance to changed environments, we are in a position to perfect our physical and mental competencies. This is due in part to the fact that behavioral interventions are also metaphysical; they affect specific areas of the brain and produce physical changes. In fact, the neuroscientist Micheal Merzenich (2004) described the brain’s evolution as twofold: in childhood, the brain learns to adapt to its environment as it absorbs information directly. He calls this the ‘critical period.’ In the second period, the ‘adult plasticity,’ the brain is able not only to adapt, but also to control its behavior and change at will. The brain is then a volitional entity. By presenting the areas of the brain in the form of a geographical map, he demonstrated how the brain remodels itself in ways that are skill-specific (such as posture, movement, etc.). This also confirms Sacks’ (2009) hypothesis that there may be specific fractions in the brain responsible for specific sensorial activities such as pattern recognition. Sacks’ findings showed that patients under certain medical conditions had experienced geometrical, musical, mobile and psychotic hallucinations involving all their senses in coherent ways. Hence, every brain has its idiosyncratic geography. Merzenich noted that “the embodiment of You” is the greatest determinant of how one’s brain might look. Physical change that occurs in your performance with the world, then, occurs as well in the physical configuration and remodeling of your brain structure.

The contextual scale of information matters; that is, to design at the human scale with considerations for accessibility, readability, and reachability, that correspond to user-centric demographic and psychographic requirements. To design for user-centric perceptual processing is to coherently integrate a belief system. Whitehouse explains how belief may contribute to the ways in which information is assimilated and interpreted, thus affecting the understanding of what one sees.

Shifts in perception are borne out of our ability to adapt, learn, and change unique perceptual beliefs. Change abounds when new skills are achieved and hidden skills are discovered in the course of adapting to contextual circumstances whereby newly-made associations and patterns are established in the mental realm and henceforth shed light onto and transform every preconception and belief one might have had –often referred to as “paradigm shifts”: when one’s whole world is reconsidered and tailored again to fit a new reality. To understand and respond to users’ unique perceptual belief, design needs to shift priorities to meet user-centric design goals that allow for the generation of friction-free solutions that facilitate behavioral, sensorial, and cognitive information consumption.

To achieve effectiveness and efficiency, the design process involves: preliminary user research and observation, defining the problem that requires a design intervention, providing multiple solutions or proposals that address the problem in question, usability testing protocols (determining number of participants, duration of test, types of tests, collect responses, debriefing with users), redesigning according to test results or user responses, etc. Designing for usability methodologies lead to a comprehensive, effective and efficient design solution that responds to users’ perceptual processing needs and expectations.

By simple testing and observation, […] we became aware of some of the practical implications of individual perceptual differences. Most importantly, we began to understand how easy it is to disenfranchise individuals simply by not perceiving and correctly interpreting the most basic facts about their needs.” (Whitehouse, 1999:128)

Whitehouse encourages designers to actively include user cognitive differences by engaging in “the extraordinary value of” user research and usability testing to understanding users’ needs as well as cognitive and cultural requirements.


Merzenich, Micheal. “Exploring the Rewiring of the Brain.” Filmed February 2004.
(Access Date: December 3, 2009)

Sacks, Oliver. “Hallucinations.” The Robert B. Silvers Lecture, The New York Public Library.
Date: September 21, 2009. Source: (Access Date: December 3, 2009)

Whitehouse, Roger. “The Uniqueness of Individual Perception” Information Design. Jacobson, Robert (Ed.). MIT Press, Massachussets: 1999, pp. 103-129

The Theories of Christopher Alexander

In 1977, architect and researcher, Christopher Alexander published A Pattern Language: a guide to designing environments to enable the creation of a collectively made and more living structure or environment. Comprised of rules and guidelines that have resulted from extensive research, observation, and testing of patterns in towns, buildings, and construction, A Pattern Language addresses the unsustainable built environment we live in and encourages a bottom-up approach to architecture wherein a nurturing environment can emerge through the common understanding of patterns and the development of pattern languages (“a genetic code” to best describe their core structural properties or requirements that make the world more livable). Observation of built environments helps identify patterns that have particular impacts on the wellbeing of people. Pattern languages are, then, aggregate elements (or parts) of given systems that enable the generation of convivial physical structures that respond to humane values and a systemic conception of the global (whole) structural scale of spaces and places. The language is developed as a tool for generating coherent and whole environments (buildings, rooms, streets, parks, etc.): “more living structures.”

Not only has it made a huge impact on the ways in which architects and novel practitioners approach architecture and their environments as wholes, but it has also caused the emergent appropriation of its patterns in the world of computer science in general and software programming in particular.

In a 1996 presentation at the ACM Conference on Object-Oriented Programs, Systems, Languages and Applications, in San Jose, California, Alexander reflected on the use of his ideas in the software community that transformed object-oriented computing and how the pattern discipline brought back the systems thinking and humane perspective into the design and architecture of software.

It is Alexander’s understanding that patterns are used as “vehicles of communication” in computer science for discussing, sharing, and modifying data structures, but they are not, however, used as he originally conceived of them. For him, the uses of patterns in software science differ from those in architecture (in the 1970s) whose patterns have a moral quest, a coherent evolution, and aims at a generative whole. The architectural goal is to build a good environment and an objective and living structure “to make human life better.”

Will it actually make life better as a result of its injection into a software system?” (Alexander, 1996)

It seems, to me, that A Pattern Language helps inform the design of self-generating and adaptive computer programs. The most striking correlation between Alexander’s pattern languages and computer science is the works in what computer science often refers to as decentralized or complex adaptive systems, and its parallels to what Alexander describes as “centers” when he talks of “shared pattern languages which [enable people] to generate a complete living structure.”

If we look at systems behavior and the similarities and particularities found within decentralized systems, we see how the conception of an environment built around rules or patterns might generate parallel effects wherein environments are created at the human scale and with the equal consideration of functional and experiential coherence, while yet remaining distinct and separate entities in their particularities.

Alexander’s A Pattern Language promotes a bottom-up approach, which places users of buildings as builders of their environments through the process of co-creating a common ground with the collective consensus of a “shared pattern language”; to give users better control over the spaces they dwell in.

Prior to The Nature of Order (2003-2004), Alexander presented some ideas explored in the extension of his work on patterns: such as, to distinguish between living and non-living structures and to include both technical and experiential fluidity; that is, the integration of both functional and interactive/human behavioral relationships (hardware and software). He defined fifteen geometric properties as essential nodes to architecture that would respond to what he posited as “Do I feel myself to be more whole?” –a certain quest for self-actualization through the generative creation of livable structures. Those recursive geometric properties revealed in the emergence of buildings include the boundaries and gray areas around them as parts of the pattern language itself.

Alexander uses the term “wholeness” to mean: entities of the environment borne out of interactions existing amongst parts (or what he calls centers). He describes “wholeness” as a “field-like” center within which other centers would be interlaced or interdependent, and those in turn would hold centers within centers and so on and so forth –as closely related to self-similarity in chaos theory (Mandelbrot’s study of fractal geometry in nature) and in the behavior of natural systems in the science of fields (e.g., flock of birds). Each center represents a pattern, in theory because it has reoccurred at different times and locations and at most of those has been successful at making one feel more whole.

Essentially, Alexander attempts to identify hubs around which systems occur in the most living structures of which he extracts a pattern language (or a geometric lexicon) for architects and lay people to rely on.

According to a 2002 review in the Harvard Design Magazine, A Pattern Language seems to impose rules that are conceptually important and useful to consider as drivers of a well-informed practice, but which when combined (all 253 rules) create a chaotic and hard-to-conceive structure. In those terms, a bottom-up approach conflicts with the extensive rule set provided by Alexander’s patterns. William Saunders interprets A Pattern Language as “utopist,” “dreamy,” “fragmentary,” “additive,” “structuralist,” “authoritarian,” and even “tyrannical,” despite his respect for the “lively […] and informed intuitions” introduced in the book.

Alexander’s best ideas about town making […]: the promotion of mixed use, pedestrian convenience and zones, ample public transportation, non-exclusive zoning, cluster development, workplaces near and in homes, limited automobile access, small architectural scale, “activity nodes,” town greens, small public squares, street cafes, and so on.’ (Saunders, 2002)


Alexander, Christopher. (1996) “The Origins of Pattern Theory: The Future of the Theory, and the Generation of a Living World.” (last visited: Feb.21, 2011)

Saunders, William S. (2002) “Book Reviews: A Pattern Language.” Harvard Design Magazine, Winter/Spring 2002, Number 16. http// (last visited: Feb.18, 2011)

Foundations of ‘Information Design’

Some of the key principles that comprise information design are: the effective and persuasive communication of information, the appropriate delivery of Information as action enabler, the consideration of information as primarily context-dependent, the understanding of user cognitive processing, the practice of visual thinking and structure writing (or information mapping), and the development and the use of a comprehensive universal (e.g. iconic) visual language.

According to Robert Jacobson and Robert Horn, information design describes the emergence of a new visual language borne out of the necessity of understanding, managing, and communicating complexity. Fields stemming from the practice of information design include: “human factors in technology, educational psychology, computer interface design, performance technology, documentation design, typography research, advertising, communications, and structured writing.” (Horn; Jacobson, 1999:22) Information design is not a unified field and is termed differently in by its variety of practitioners. Tensions do exist amongst the multitude of expert fields; namely, between graphic design and technical communication, as well as between experts and novel practitioners. (Horn; Jacobson, 1999:24)

Because information design is not a unified field and because its practice is highly context dependent, it has long been a challenge for designers and researchers alike to develop a vocabulary to describe and pass over the essential ingredients necessary for effectively communicating meaningful and persuasive information.

When design is dependent on context, context is embedded in and transforms the variables within the practice information design. Attempts to create a universal language (e.g. iconic signage) have at times worked against other designers and researchers who have strived to revive and reclaim cultural and natural identity by using local and iconic visual representations. Horn introduced the term VLicons(™) which he coined to distinguish ‘visual language icons’ from words and language alone. VLicons juxtaposes both word and icon to provide a captivating, persuasive and memorable language that extracts the essence while yet communicating a meaningful visual experience. (Horn; Jacobson, 1999:24)

Research design, experience design, and cognitive science are the pillars of information design. This requires that designers of information combine various skill sets in order to provide meaningful interactions for consumers of information. Horn splits information design practitioners as such: inventors, analysts, universalists, collectors, writers, aestheticians, popularizers, and researchers. Jacobson, however, describes how information design can help one read, process, and transfer meaning. (Jacobson, 1999:10)

source: Jacobson, Robert (Ed.). Information Design. MIT Press, Massachussets: 1999

Defining ‘Entropy’

Entropy can be characterized by the term ‘randomness’ to express the phase duration in which a stable system’s state mutates due to expected or unexpected variables. Entropy is fundamentally the erratic behavior of a system caused by external disturbances that leads to a chaotic or disorganized structure of which a system may no longer function as a single unit. In system science, this effect is understood as the natural ‘force’ or movement towards disorder in Nature.

Like natural elements, every system has a life cycle. Depending on the kind of system at stake, closed or open system, and if designed to adapt, a system will survive as a decentralized system regardless of external disturbances (i.e. seemingly randomly dispersed elements of a whole system that behave according to decentralized laws –e.g. a flock of birds). An Open System would be an example of such systems that presents (after observation overtime) a pattern in its motion from order to disorder, and from disorder to order; in which case the system can be said to be stable regardless of ‘entropy’.

source: Flood, Robert L. and Ewart R. Carson. “Systems: Origin and Evolution, Terms and Concepts” Dealing with Complexity: An Introduction to the Theory and Application of Systems Science. (pp. 12-13)

Introducing ‘Systems Thinking’

According to Flood & Carson’s Dealing with Complexity, Systems Thinking –as deriving from the understanding of biological behavioral sciences and the systems that describe them –is a “framework of thought” whereby complex and seemingly unpredictable or unforeseeable object-behavior can be made understandable through the use of Systems methodologies, concepts, and principles in real-word situations (e.g. “problem solving”). Grasping these core concepts helps in the planning of complex information systems because they essentially reshape the way one reads or understands complexity and designs for complex adaptive systems. The characteristics of a system represent both “an organized whole” and an aggregate of parts (or elements) that interact with one another through flows of exchanges of “materials, information, or energy”. Understanding a system as part of a larger context (where the surrounding environment feeds back into it and affects the way the system behaves) is also a very important concept that enables us, as designers, to take context into account and consider the possible or potential futures of our proposed system whereby it might evolve, learn, change, and preferably adapt to contextual occurrences or events by identifying the extent or area of probabilistic affect (emergent property).

Systems Thinking teaches us how the design of a complex information system often needs to include mechanisms to account for “short term” and “long term” (or chronic) disturbances of flow caused by environmental changes, by dealing with the “whole” system rather than its parts. By creating systems able to adapt to environmental changes and thus to learn to sustain themselves in the face of unforeseen shifts, design can plan for more effective and efficient complex information systems. This is depicted primarily in the study of Cybernetics. Negative Feedback describes the “parameters” of a self-sustaining system; that is to say, a set of control systems within a larger given system that help enact a balance overtime of the system’s dynamics. Positive Feedback, however, describes the growing mutation of a system, often seen as an increase of disturbances and an imbalance of “elements” or component ratio that lead to a total collapse of a system when Negative Feedback no longer intervenes. A “variety” of both Negative and Positive Feedback seem to be necessary for the survival and balance of complex systems (“the law of requisite variety”(Ashby, 1956)).

According to the authors, Feedback represents the impact of an element over other elements of a given system and how this impact is then feed back into the system (Flood, 1993:8). From this inherent behavior emerge the distinctions made between closed and open systems. On the one hand, a Closed System (e.g. a machine) is identified by a system that interacts only with its subsystems and feeds back information and energy amongst itself. This kind of system discerns itself from the environment in which it lives; such as a machine will respond to its own coded rules regardless of its surrounding context. On the other hand, an Open System evolves and interacts with its environment in addition to its relationship with itself. For instance, an organism will sustain itself through both relationships within its inner biological mechanisms and its outer exchanges with the environment in which it lives, and will adapt to contextual bifurcations as it changes and evolves overtime. If an organic system were to ever be so-called closed, environmental disturbances may cause the system to become unbalanced and might have dire consequences on the state of the system by rendering it dysfunctional. An organism will appear to be unchanged overtime (as a whole) although its “information, materials, and energy” will have changed in the process of exchanging and interacting with its environment.

Homeostasis describes the condition whereby a system or organism is “open” to in/out fluxes. Homeostatic systems can be said to be self-sustaining; that is, such systems sustain themselves through equally balanced exchanges of inputs and outputs over time. As an analogy, I had an accident almost 10 years ago that injured my knee and resulted in a series of surgeries that led to subsequent procedures involved in the regeneration of the inner tissues, the superficial healing of the skin, and the rehabilitation of the muscles to walk comfortably as I used to. I understand the healing of a wound as being a Homeostasis experience. Although this may take at times longer than other times, the body regenerates its tissues in quite beautiful and surprising ways through both in/out exchanges (medication, food, physical therapy, dermatological applications, etc.). The body remains a balanced system as its inner parts fight against external events (e.g. germs) and yet requires its environment to sustain itself and grow stronger and fitter. This sub-system (here, the knee) remains seemingly unchanged whilst its materials or information are always in flux.


Flood, Robert L. and Ewart R. Carson. “Systems: Origin and Evolution, Terms and Concepts” Dealing with Complexity: An Introduction to the Theory and Application of Systems Science. 1993: pp. 1-21