therefore, the quantity of information to be
processed by end-users. With this approach, citizens,
public authorities and other audiences can access
more quickly and at lover cost to the information
that they require. Moreover, this approach can be
extended to other domains of the Public
Administrations (PA’s), whose goal is focused on
the access to public information and reach of
citizens and other authorities.
The remainder of this paper is structured in the
following way. Section 2 gives an overview of
podcasting technology and Semantic Web paradigm.
Section 3 presents our content-awareness based
podcasting framework and Section 4 provides
concluding remarks and future work.
2 RELATED WORK
Podcasting is a recent and effective medium to
deliver syndicated Web content (audio/video data)
by content providers to consumer users. Interactions
between providers and consumers consist of a two-
step process. First, the content providers make
accessible audio or video files on an available
webserver, which are often referred to as one
episode of a podcast. Then, the content provider
acknowledges the existence of these files by
referencing them in another file known as the feed.
The feed is a machine-readable list of the episodes
which may be accessed. This list is usually
published in RSS format (RSS 2.0 Specification
n.d.) (Really Simple Syndication), which provides
other information, such as publish dates, titles, and
accompanying text descriptions of the series and
each of its episodes. The feed is typically limited to
a short list of the most recent episodes. Second, a
consumer user uses a software program called a
podcatcher with the purpose of determining the
location of the most recent episode and
automatically downloads it to the user's computer or
portable players. The downloaded episodes can then
be played and replayed at anytime.
Currently, the using of a subscription feed of
automatic delivery of new contents is what
distinguishes a podcast from a simple download or
real-time streaming. As a result, subscriptions to
podcasting allow users to collect programs from a
variety of sources for listening or viewing offline at
anytime and anywhere. However, no personalized
deliveries of specific contents have been included in
traditional podcasting systems. In this context,
Semantic Web (W3C: Semantic Web n.d.) paradigm
becomes a key feature for ensuring an appropriate
response to the user requests.
At present, the Semantic Web, the future of the
current Web, is an extended web of machine-
readable information and automated services that
amplify the Web far beyond current capabilities. The
explicit representation of the semantics underlying
data, pages and other Web resources will enable a
knowledge-based Web. The path to machine-
processable data is to make the data smarter.
There are four different stages from data with
minimal smarts to data embodied with enough
semantic information for machines to make
inferences about it:
• Text and databases (pre-XML): this
initial stage corresponds to applications to
proprietary applications. Thus, the smarts
are in the application and not in the data.
• XML documents for a single domain:
data, in this stage, achieves application
independence within a specific domain
using structured categories defined to
contain information about one aspect or
attribute (e.g. publisher, subjects) of an
information resource (e.g. book, document,
image). An example of this context would
be the personalized access to multi-version
XML document repositories in an
EGovernment scenario (Grandi et al, 2005,
p. 281-290).
• Taxonomies and thesauri based
resources: in this stage, data are composed
from multiple domains and accurately
classified in a hierarchically structured
controlled vocabulary of terms that are used
to describe information resources.
Relationships and cross-references can be
used to relate and thus combine data. Thus,
data is now smart enough to easily
discovered and sensibly combined with
other data. Dynamic taxonomies (Sacco,
2000, p. 468-479) have been proposed as a
tool to solve information access and
dissemination needs of e-administrations
(Sacco, 2005, p. 261-268). Intelligent
thesauri such as WordNet (Fellbaum,
1998), an online lexical reference system,
can also be used to support automatic text
analysis and artificial intelligence
applications.
• Ontologies and rules: in this stage, a
structural specification is used to express
complex relationships among concepts of a
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