NUI Galway – UL Alliance First Annual ENGINEERING AND - ARAN ...

Using the Web to Enhance Desktop Data
Laura Dragan, Renaud Delbru, Siegfried Handschuh, Stefan Decker
Digital Enterprise Research Institute, National University of Ireland, Galway
firstname.lastname@deri.org
Abstract
The Semantic Web and the Semantic Desktop provide
frameworks to structure and interlink data, using
similar stacks of technologies, but the integration of the
resulting datasets is not straightforward. We describe a
system that finds Web aliases for desktop resources and
uses them to enhance the desktop information. The
process is based on type and property mappings and
matching the values found online with the known values
from the desktop.
The Semantic Web proposes a common framework
that gives meaning to the data so that it can be
understood by machines, structured and interlinked
better. With the emergence of Linked [Open] Data, the
Semantic Web has gained momentum, and vast
amounts of structured data became available online.
The Semantic Desktop is the result of applying
Semantic Web technologies on the desktop. It promised
to bring elegant solutions to the problems of
information overload and application data silos by
using standard vocabularies and representation for the
desktop data.
The Semantic Web and the Semantic Desktop
provide solutions to interlink data in the two
environments, but we have separate islands of
knowledge, containing similar data, related to the same
topics of interest to the user, but disconnected from
each other. For instance, DBLP contains information
about publications, authors and conferences. This
information can be used to enhance the desktop
information about a fellow researcher, or about a
conference of interest. Other online data sources, like
MusicBrainz and the BBC Music Project can help
enhance the desktop information of the user's music
collection. The challenge is to find links between these
two systems and ultimately integrate them.
We describe here an approach to automatically find
semantic web aliases for Semantic Desktop resources.
An alias is a Semantic Web resource that represents the
same real-world thing as the initial desktop resource.
The type of information available about the aliases
might differ between sources - e.g. for a person, the
types of information include the email address and
telephone number, homepage, blog URL and date of
birth; for researchers, also affiliation, papers they
authored and projects they are involved in. This
information might not all be available from one source,
but spread over multiple sources, each one containing
overlapping information. Some information might only
be available online, while some could only be found on
the desktop.
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The service we propose runs on the desktop. It uses
the information available on the desktop about
resources to find Web aliases for those resources. The
process consists of three steps, as follows:
Gather local data for the current resource on
the desktop. This extends to all the values of
properties of other connected resources that might be
relevant.
Query Web sources based on the label and
type of the current resource. The Web sources can
be Semantic Web search engines like Sindice, or
accessible SPARQL endpoints like the one provided
by DBpedia.
Filter the Web results based on property
matches. For this step we use a set of mappings
between desktop and Web ontologies, and string
matching algorithms to rank the results.
The set of vocabularies used on the desktop are
different from those used on the Semantic Web,
therefore we created the mappings for some of the most
popular vocabularies, to reconcile the two systems. The
mappings between the desktop ontologies and the
vocabularies used on the Web are of two kinds: type
mappings and property mappings. The type mappings
say for each desktop resource type (e.g. pimo:Person)
what possible types can be found online (e.g.
foaf:Person, foaf:Actor, akt:Person). Property mappings
specify the correspondence between desktop and Web
properties of resources - e.g. nco:fullname corresponds
to foaf:name. Composite properties are also handled.
We process the desktop resources for which there is
a high probability of finding related information online,
like people and events. For each, the result is a list of
Web aliases and a score for each alias, to show how
exact the match was determined to be. If the score is
above a maximal threshold, the alias is saved. If the
score is below a minimal threshold, the alias is
discarded. For intermediary values, the user is asked to
decide which alias to keep.
The system is designed to be modular, more Web
sources can be plugged in at any time, and more
mappings can be added.
Finding Web aliases for desktop resources helps
enriching desktop data with new information from the
Web, and provides a way to close the gap between the
two knowledge islands.
Acknowledgments. The work presented here was
supported by Science Foundation Ireland under Grant
No. SFI/08/CE/I1380 (Líon-2).