I recently attended a special media day at the IBM Research Labs. The point of the day was to showcase some of the new technologies being worked on at their labs both in products that are nearing releases and in new technologies that aren’t that close to showing up in products. Along with researchers from the Labs, presentations were made by IBM bigwigs such as Steve Mills, senior vice president and group executive of the IBM Software group. 
Click the thumbnails for full-sized screens
Since this Labs day took place in Cambridge, Mass., at what is essentially Lotus headquarters, the day had a very distinct Lotus focus. Among the products and technologies displayed were well-known brands such as Lotus Sametime and Lotus Notes and Domino 8.
One of the newer products that I found interesting was Lotus Connections. This has been covered as sort of IBM’s entry into Web 2.0 or Enterprise 2.0 technology and the product has plenty of the expected blog and social networking type of capabilities (and I give IBM credit for in many cases using standing open-source products to add this capability, such as their use of the open-source Roller blog platform). The most interesting part of Connections is a feature called Dogear, which is a sort of del.icio.us-like tagging structure for the enterprise. In the demo I received I was impressed with the way this feature made it easy to tag business content and even easier to find relevant content and know who did the tagging. To me this was a good example of how to properly introduce tagging into a business infrastructure.
There were also some cool non-productized technologies, including a well-implemented shared document product that went well beyond standard wiki capabilities. But probably the most interesting was a product called Many Eyes, which lets anyone upload data sets (currently only in spreadsheet form) and then perform some very cool visualizations in order to better understand the data. While sometimes visualizations can go overboard, they can also make it much easier to quickly understand data, and I can see some very cool uses for Many Eyes, especially once it can handle real-time data.
