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only some of the capabilities mentioned. Traditional blogging has many
limitations, but the most important limitation is that metadata is used
only for headline syndication in a blog. Metadata is not extensible, is
not linked to a risk-flexible data model, and is not capable of supporting
vocabulary mixing and inferencing.
The researchers, therefore, looked to the Semantic Web for a solution.
As we've discussed, the premise of the Semantic Web is that data can
be shared and reused across applications, enterprises, and community
boundaries. RSS 1.0 (web.resource.org/rss/1.0) is a Semantic Web vocab-
ulary that provides a way to express and integrate with rich information
models. The Semantic Web standard Resource Description Framework
(RDF) specifies a web-scale information-modeling format (www.w3.org/
RDF). Using these tools, they came up with a prototype for creating
what they called a Semantic Blog. The prototype has some interesting
searching capabilities. For example, snippets can be searched for either
through their own attributes (e.g., “I'm interested in snippets about HP”)
or through the attributes of their attached blog entry (e.g., “I'm inter-
ested in snippets captured by Bob”).
Virtual Worlds
Perhaps the most interesting of all social-based community software is
Linden Labs Second Life (www.secondlife.com). Though primarily used
for such fun activities as fantasy role-playing (pirates, Goths, sci-fi, and all
that), Second Life does have a serious side.
In 2008, IBM's Academy of Technology held a virtual world conference
and annual meeting in Second Life, as shown in Figure 4.11. The virtual
meeting conference space had room for breakout sessions, a library, and
various areas for community gathering. IBM estimates that the ROI for
the virtual world conference was about $320,000 and that the annual
meeting cost one-fifth that of a real-world event.
Just think of the possibilities. Project team members near and far can
use Second Life to hold virtual, but tactile, team meetings and even work
with end users.
Knowledge Management Tools
Knowledge management (KM) has been defined as the identification
and analysis of available and required knowledge—and the subsequent
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