Stored Knowledge vs. Stream Knowledge

A lot of new KM systems are built around microblog functionality. What I term streaming KM. A stream of information flows from all the people to whom you are connected in the system. Much like Twitter, you can send specific messages or mass distributed messages.

My issue with this functionality surrounds collection and long-term storage. What happens to these streamed messages? How to they get integrated into the collective knowledge (if there is such a thing) of the organization? Furthermore, how does context get applied to the meaning and content of the messages if you search?

Let me propose an example. Assume scientists at ABC company use Yammer within their large pharmaceutical company. One scientist sends a message to the group regarding the threshold level of chemical X permitted in the diffusion process for creating chemical Y. Several scientists respond with things like "it should be no more than 2"...or "research shows anything above 2.5 is ineffective..." How does this K get stored in the organization? First, the audience understands certain aspects of the message which a lay person may not. Possibly the 2 or 2.5 is micrograms per liter or whatever the amount might be. Without labels, the quantity might be useless to a search engine. Also, consider the whole stream is necessary to understand the meaning of the exchange, not just the reply. Finally, where does this information get stored so that it adds value to the company's KMS? Can the info make it's way to a database or KMS?

I really like the functionality of stream KM. I have been using Google Wave for research and for some consulting. But the lack of these modified social network systems to connect to corporate enterprise KM is a bit troubling...or might need a solution.