A case study in Wikis, Facets and KM

It has been a while since I posted on my blog. I have decided to write again to share some of the interesting topics I have come across. I recently read a very interesting write up from Pete Bell from Endeca published on KM World: Acmepedia: a case study in Wikis, Facets and KM. Pete makes some very interesting observations.

Regarding the key differences between Wikis and traditional KM:

• Wikis are an addition to KM, not a rip-and-replace. They will become yet another silo if they’re not designed to complement your existing enterprise packaged applications.
• Faceted navigation and information access can be the key to crossing different content silos.
• Although facets are part of the solution, they also introduce new requirements: how do you categorize everything so it can be found again through faceted navigation? With enhancements, tagging and folksonomy provide an answer.
• Authority and trust impose different constraints in the enterprise than in the public Wikipedia. Facets offer dramatic changes here too.

Best practices for Wikis:

• “Curated” content: Only a utopian would expect white papers, legal documents and HR forms to be produced by the proverbial million monkeys banging on a wiki. These would continue to live in a CMS, complete with version control, workflows and the like.
• Packaged applications: Data and notes from CRM, HRM and ERP packaged applications were some of our most valuable content. We would sensibly leave it where it was, but use information access to integrate it.
• Wikis and blogs: These group collaborations proved best at capturing the conversational nature of emerging topics, discussions, threads, opinions, ephemera and niches. And they required some business
process changes to align them with communities of practice.

Folksonomy and Taxonomy:

In our own experimentation, we found that the purists’ folksonomy can be amended very successfully with a pragmatic approach. It can succeed by blending elements of tops-down and bottoms-up organization. Key techniques:
• Controlled vocabulary: instead of free-form document tagging, first prompt users to select common terms from a controlled vocabulary, like names of industries, products, customers and geographies.
• Enter tags in facets: Instead of prompting for tags in a single field, offer faceted fields—again, like industries, products, etc. The name of the facet itself adds valuable structure.
• Auto-complete terms: Prevent vocabulary drift by using a type-ahead search to suggest known terms as the user types.
• Put an editor in the workflow queue: Actively prevent vocabulary drift with an expert. It takes less effort than you’d expect. You won’t catch everything, but you can add common synonyms and hesaurus
terms, and promote frequently used terms to the controlled vocabulary.
• Auto-tag: Supplement user tagging with some based on rules, like tags derived from an author’s department or LDAP profile.