Contrary to popular belief, the term “information architecture” is not synonymous with designing and structuring websites or developing an Internet-based information base. The phrase was first introduced in 1975 by Richard Saul Wurman, who is probably best known for founding TED Conferences and TEDTalks. When he introduced this concept, Wurman was thinking of information in a broad sense. He was one of the first to recognize that modern technologies were likely to produce “a stream of bytes that leaves us inundated with data but starved for the tools & patterns that give them meaning. In reality there has not been an information explosion, but rather an explosion of noninformation, or data that simply doesn’t inform” (Information Anxiety). Information architecture didn’t get its more common (but also more restrictive) meaning until the role was popularized in the book Information Architecture for the World Wide Web.
This has given the term “information architecture” a bit of an identity crisis. In my recent Cutter Business Enterprise Architecture Executive Report (“Information Architecture: Dealing with Too Much Data“), I use information architecture in its original sense to refer to the wider issues of information at large. Wurman and others have frequently referred to information architecture as “the business of understanding.”
It is useful at this point to spend a little time exploring what it takes for an enterprise to understand and make effective use of the data resources that are now available to it. For this, I refer to an excellent overview of understanding written by Nathan Shadroff (see The Business of Understanding, pp. 27-29) and summarized in Figure 1.
Figure 1 — An overview of understanding. (Adapted from Shadroff.)
We can view understanding as a continuum that starts with source data and progresses through information and knowledge to wisdom. Architecture techniques usually focus more on data and information in this continuum, while knowledge and wisdom tend to fall into the preserve of knowledge management. If information architecture is truly going to deal with concerns about information overload, then:
- It needs to include not only:
- Data architecture techniques (covering the research, creation, gathering, and discovery of source material)
- Information architecture approaches that help with the presentation and organization of information
- But it also needs to cover:
- Knowledge management techniques, such as conversation, storytelling and integration, which foster an environment for sharing ideas, insights, and innovations
- Together with:
- An enterprise culture and environment that allows time and space for contemplation, evaluation, interpretation, and retrospection
This will require new skills and team structures for many EA teams. Too often, there is a structural divide between data and information architects: one group dealing with structured data, database design, and the analysis and mining of data, while the other deals with Web structures and design. Where these teams are separate, they will need to learn to share deliverables and collaborate to achieve the right balance between production and consumption.
Architecture teams also need to embrace core knowledge management techniques into architectural practice and balance high-speed technology-based processing with smarter use of human interpretation and ideas. Much of EA practice centers around work products based on facts or structured data about technologies, applications, functions, and process. There is a danger that this pays no attention to the local knowledge of SMEs and business users. A lot of specialized knowledge is tacit or hidden, and there is huge potential for enterprise architecture to tap into overlooked experience and expertise. This means working much more closely with stakeholders who are information consumers. Architectures could also exploit existing or emerging business and management models to produce new ways to interpret and evaluate.
This overview of understanding shows diagrammatically the elements needed to converge in architectural practice. It shows the difference and overlap between the producers and consumers of understanding. It shows that there is a continuum, with additional value at each stage from data through information and knowledge to wisdom. It also shows that the context for understanding can be fairly universal or global for information, and that understanding becomes more local with knowledge, and personal with wisdom. And it shows that the transition from information to knowledge to wisdom requires experience, the stimulus to turn information into knowledge, and the understanding to extract wisdom from knowledge.