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Getting rid of dead data

We have all started complex projects by taking a deep breath and having faith that our approach and objectives are valid and achievable. This is no more true than when formulating a knowledge management strategy to rationalize the many document stores (micro-silos or information silos) that any sizable organization has today.

I got to thinking about this after reading this post from Alan Pelz-Sharpe on CMS Watch. The problem is how to get from here to there, where "here" involves wikis, SharePoint document stores, content management systems, and shared and local hard drives, and "there" means a fully scrubbed repository of high-quality content that everyone can benefit from accessing.

You could:

1. Form a cleansing team that will inspect, validate, or trash the content.
2. Migrate everything into a common repository.
3. Decide whether federated search will meet your needs.
4. Build ETL-, mashup-, API- (fill in your favorite integration approach) based applications.
5. Hope the task will not be assigned to you. ;-)

But what if we used a social approach? No, I am not suggesting we let our buddies on LinkedIn or Facebook figure it out for us. I am suggesting that using the collective intelligence of the company is both an easier, quicker, and more foolproof approach.

This is where Social Knowledge Networks (SKN) can address such issues in a very specific way. Whether the SKN connects to a document store or migrates those documents directly into the SKN, the social intelligence layer of the SKN is a means of separating the good from the bad.

We know that by using ratings, tags, comments, and a host of other social technologies, good content rises to the top and bad content sinks to the bottom. To be more specific, searching and finding information within the SKN will very quickly demonstrate whether that information is useful, valid, or not.

It might be rated with one star, or have a comment that the document is out of date. One rating, in and of itself, is not grounds to trash the document. But when enough people rate and comment on it, it will become clear through reporting and usage statistics what the consensus of opinion really is.

This makes the social intelligence layer of the SKN not only a way for participants to impart their institutional knowledge, but makes it a key component to building a high-quality SKN in the first place.

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