Preface for the Third Edition - Read

386 B. Concepts and Theories
Sesame, KAON and Kowari. Sesame supports RDQL as well as RQL and SeRQL,
whereas most other tools only support one language. This is especially interesting
for KMS for flexibility reasons, as long as there is no clear standard yet. RDFQL
support is only available in the commercial tool RDF Gateway from Intellidimension.
A prototype implementation developed at the author’s department builds on
top of Jena and enhances the toolkit with a Web-based client for retrieval as well as
a Java-based graphical client with support for creating, storing and retrieving RDF
from the data base (Stier 2005, Maier/Peinl 2005).
Figure B-74 summarizes the most important steps for creation, i.e. annotation
and serialization, storage and retrieval of meta-data from the perspective of the
integration layer in a KMS.
original
resource
manual
annotation
automatic
annotation
meta-data standard,
e.g., DublinCore,
LOM, MPEG7
resource
description
serialization
exchangeable
resource
description
standardized
representation,
e.g., RDF/XML
FIGURE B-74. Meta-data management
storage
inline, separate file,
(relational) DBMS
accessible
resource
description
The integration layer in a KMS builds on semantic descriptions of documents to
provide functionality to the knowledge services on the upper layers, such as semantically
relating knowledge elements to each other or identifying experts based on
authorship. Thus, creation, storage, retrieval and processing of meta-data and associated
ontologies are required. With XML, RDF, OWL and RDF query languages
as well as the use of content-oriented meta-data standards, a significant part of the
required integration services can be realized.
However, the lacking standardization of RDF query languages together with
missing capabilities of the proposed standards and insufficient tool support inhibits
a broad implementation of semantic integration layers in organizations. Moreover,
despite a number of content-oriented meta-data standards that seem well-suited for
their designated domains, there is no broadly accepted standard that covers all relevant
aspects in a KMS context.
The various developments in the technology-enhanced learning community on
the standardization of learning objects, learners etc. as well as modularization that
is already designed for some standards seem to be important steps in this direction.
Probably a more flexible, modular meta-data annotation system with a few basic
attributes for all documents together with a set of document type-specific attributes
could link standards for specific domains. The meta-data should be organized in a
kind of top-level ontology according to the identified categories and the dimensions
time, topic, location, person, process and type 604 .
This already points towards the concept of ontology management. On top of
meta-data management which governs the basic services of semantic integration,
query
RDF query language,
e.g., RDQL, RDFQL,
SPARQL
resource
pointer