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COLD 2010 : 1st International Workshop on Consuming Linked Data


When Nov 8, 2010 - Nov 8, 2010
Where Shanghai, China
Submission Deadline Aug 27, 2010
Notification Due Sep 17, 2010
Final Version Due Oct 7, 2010

Call For Papers

1st International Workshop on Consuming Linked Data (COLD 2010)

at the 9th International Semantic Web Conference

November 8, 2010, in Shanghai, China

The quantity of published Linked Data is increasing dramatically. However,
applications that consume this data are not yet endemic. Reasons for this may
include one or more of a number of open issues including, lack of methods for
seamless integration of Linked Data from multiple sources, dynamic discovery
of available data and data sources, provenance and information quality
assessment, application development environments, and appropriate end user
interfaces. Addressing these issues requires well-founded research, including
the development and investigation of concepts that can be applied in systems
which consume Linked Data from the Web. The workshop on consuming Linked
Data (COLD) aims to to provide a platform for discussion and work on these
open research problems. The main objective is to provide a venue for scientific
discourse (including systematic analysis and rigorous evaluation) of concepts,
algorithms and approaches for consuming Linked Data.

The term Linked Data refers to a practice to publish and interlink structured
data on the Web. Since the practice has been proposed in 2006, a grass-roots
movement started to publish and to interlink multiple open databases on the
Web following the Linked Data principles. Due to conference workshops,
tutorials, and general evangelism an increasing number of data publishers such
as the BBC, Thomson Reuters, The New York Times, the Library of Congress, and
the UK and US governments adopt this practice. This ongoing effort resulted in
bootstrapping the Web of Linked Data which, today, comprises billions of RDF
triples including millions of RDF links. The published datasets include data
about books, movies, music, radio and television programs, reviews, scientific
publications, genes, proteins, medicine, and clinical trials, geographic
locations, people, companies, statistical and census data, etc.

Access to this data presents exciting opportunities for the next generation of
Web-based applications: Data from different providers can be aggregated;
fragmentary information from multiple sources can be integrated to achieve a
more complete view. While a few applications, such as the BBC music guide have
used Linked Data to significant benefit, the deployment methodology has been to
harvest the data of interest from the Web to create a private, disconnected
repository for each specific application. This approach can only be the
beginning; new concepts to consume Linked Data are required in order to
exploit the Web of Linked Data to its full potential. The concepts, patterns,
and tools necessary are very different from situations when resource identifiers
are known a priori, local, whole-repository queries are possible, access to
the repository is reliable, and relevant data sources are known to be

Several open issues that make the development of Linked Data based
applications a challenging or still impossible task. These issues include the
lack of approaches for seamless integration of Linked Data from multiple
sources, for dynamic, on-the-fly discovery of available data, for information
quality assessment, and for appropriate end user interfaces. These open issues
can only be addressed appropriately when they are conceived as research
problems that require the development and systematic investigation of novel
approaches. The 1st International Workshop on Consuming Linked Data (COLD)
aims to provide a platform for the presentation and discussion of such
approaches. Our main objective is to receive submissions that present
scientific discussion (including systematic evaluation) of concepts and
approaches, instead of exposition of features implemented in Linked Data based
applications. For practical systems without formalization or evaluation we
refer interested participants to other offerings at ISWC, such as the Semantic
Web Challenge or the Demo Track. As such, we see our workshop as orthogonal
to these events.

Relevant topics for COLD 2010 include but are not limited to:

* Web scale data management (indexing, crawling, etc.)
* Query processing over multiple linked datasets
* Search in the Web of Linked Data
* Auto-discovery
- of URIs,
- of additional data that is not from the authoritative source of a URI,
- of relevant linked datasets in general
* Caching and replication
* Dataset dynamics
- processing change notifications,
- keeping consistency,
- temporal tracking of linked datasets
* Reasoning on Linked Data from multiple sources
* Knowledge discovery deriving insights from the Web of Linked Data
* Information quality of Linked Data
- IQ assessment,
- trustworthiness,
- provenance
* UI research for the interaction with the Web of Linked Data
- user interaction and usability,
- visualizing Linked Data,
- natural language interfaces

Paper Submission Deadline August 27, 2010, 23.50 Hawaii time
Acceptance Notification September 17, 2010
Camera Ready October 7, 2010
COLD Workshop November 8, 2010

We seek full technical research papers only with a length of up to 12 pages.
Paper submissions must be formatted in the style of the Springer Publications
format for Lecture Notes in Computer Science (LNCS), please see

Please submit your paper via EasyChair at

Submissions that do not comply with the formatting of LNCS or that exceed the
12 page limit will be rejected without review.

We note that the author list does not need to be anonymized, as we do not have
a double-blind review process in place.

Submissions will be peer reviewed by three independent reviewers. Accepted
papers have to be presented at the workshop and they will be included in the
workshop proceedings that are published online at CEUR-WS.

Olaf Hartig
Database and Information Systems Research Group
Humboldt-Universit´┐Żt zu Berlin, Germany

Andreas Harth
Institut AIFB
Karlsruhe Institute of Technology, Germany

Juan F. Sequeda
Department of Computer Sciences
University of Texas at Austin, USA


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