Taxonomy development

This is a continuation of last month's post: What You Need to Know to End Information Chaos.

Business makes extensive use of taxonomy and metadata in a variety of scenarios including accounting, databases and inter/intra-net based applications to provide structure and organize information.  All this is normal and straightforward.  Chaos arises, however, when a business manager or executive asks questions that cut-across systems.  When, for example, they want to be able to integrate engineering data, customer-oriented product information, customer information, and customer service complaints to identify new product-lines and solution opportunities. 

To achieve the goal of visualizing a business problem by mining information repositories in a creative way to address complex issues involving multiple data repositories, taxonomies and metadata must be aligned to establish a comprehensive "single source of truth."  The concept of a single source of truth is the mantra in the drive to put Master Data Management (MDM) into practice.  However, the effort comes with certain practical and serious challenges.  The most significant being the fact that different and well-governed information systems have different semantics and different metadata standards.  Achieving semantic interoperability is a serious challenge, especially as business systems and network service architectures develop to meet organizational needs to adapt to a rapidly changing technology environment.

So what to do?  How do organizations find ways to capture, manage, and derive understanding from a wide range of sources including its internal expertise resources and the stream of information provided by social media channels?

Card sorting is a popular technique for getting at users' understanding of content structure, relationships and terminology. I often will break out a card sorting exercise early on in a taxonomy project using terms extracted from the client's content or pre-existing taxonomies to get a sense of what kind of organizing principles are important to the users. I also find it to be a great way of socializing the project and educating people in taxonomy and information architecture.

Recently, I've been doing a lot of digital asset management (DAM) projects, where our taxonomy is meant to help organize and give access to a collection of images or other visual assets, usually through faceted search. While the typical card sorting activity is still relevant, given that we'll be using words/labels to create the taxonomy for the assets, I've found it to lack a certain something in this context.

So during my current project with a global pharmaceutical company, I decided to try a different approach: a visual card sort.

The same rules apply here as they do with traditional card sorting: you can do an open card sort (no pre-defined categories given), or a closed card sort (established set of primary categories). The only real difference being you do it with pictures, not words. And it tends to be a bit easier and fun, as many people are inherently visual.

Forget taxonomy, ontology, and psychology. Who knows why people do what they do? The point is they do it, and we can track and measure it with unprecedented fidelity. With enough data, the numbers speak for themselves." (1)

Recently Chris Anderson wrote an article for Wired magazine called the The End of Theory. The thesis of the article in a nutshell is that the impending petabyte era of data storage signals the end of the traditional scientific method of discovery. No longer are we bound to the outdated model of observation, hypothesis and measurement. Computers (developed by Google & IBM) "can throw the numbers into the biggest computing clusters the world has ever seen and let statistical algorithms find patterns where science cannot."