Metadata. This is a fundamental digital
building block of the Knowledge Economy. Metadata describes knowledge
objects, and is used to support the indexing, search, discovery,
retrieval, and use of those objects. If one thinks of the analogy
of a web-based store, the metadata is analogous to the online catalog
of products and the knowledge objects are analogous to the products
Metadata adds descriptive, technical, administrative,
and structural value to data and information. Metadata assists in
clustering related information resources and in providing the capacity
for "chunking" information for easy reuse, interoperability,
transaction, archiving, and preservation. A digital object that
is not enriched with metadata cannot be used effectively in contexts
for which it was not designed.
High-value digital repositories require well-described
and organized metadata throughout the collection. Print collections
can rely on a single front-cover or catalogue descriptions of content
and context. Digital collections require extensive tagging that
enables an e-book or journal article to be segmented into modular,
durable, and independent chunks. The tradecraft of achieving metadata
chunking in a cost-effective manner will be one of the critical
emerging competencies of the e-Knowledge Industry.
Metadata is about both "how" and "what."
The initial focus of working groups defining metadata standards
such as the IMS and Dublin Core was how to describe
characteristics of information through metadata fields and related
subcategories. The what of metadata is twofold
deciding what fields among the dozens defined by these metadata
standards are necessary for a particular market or application (e.g.
Dublin Core), and how to specifically identify the subcategories
within the identified metadata fields to make sense in different
markets (e.g. postsecondary education, K-12, corporate training).
This involves a narrowing of options and providing
a sort of "pull down" menu for many categories (particularly
those related to subject area) so users can understand easily what
the descriptors mean and objects can be more easily tagged. For
example, the community of practice for physics could determine the
subcategories appropriate for learning objects in the discipline.
These would differ subtly from subcategories used in nearby disciplines
and sub disciplines. Descriptions of concept domains, like physics,
with controlled and specified vocabularies, meanings and relationships
are called ontologies.
The early focus of metadata description has focused
on technical, administrative and content-fixated description of
information. A key challenge in the development of the Knowledge
Economy will be to develop metadata standards to enable the flexible
economic exchange of information objects. Knowledge objects will
become substantially more complex, combining content, context, and
best practices and requiring complex mechanisms for recognizing
value. A sort of "matrix of economic value statements"
will emerge as an essential component of metadata. This will enable
the value webs that will develop for each market. But the most difficult
economic challenge is to drive down the cost and price of metadata
through dynamically generated knowledge objects, autotagging, and
sophisticated tradecraft. Routinely and economically creating ontologies
and metadata will be an important capability for the Knowledge Economy.
Content Management. It is now over a
decade since the first standards began to emerge in the field of
computer-supported learning. The Aviation Industry delivered the
first such specifications; whats more, theyre referenced
today in an updated form within the SCORM (Sharable Content Object
Reference Model), developed by the US Department of Defense Advanced
Distributed Learning (ADL) initiative.