Appel: IJCAI-11 Workshop on Discovering Meaning On the Go in Large & Heterogeneous Data (LHD-11), July 2011, Barcelona

Thierry Hamon thierry.hamon at UNIV-PARIS13.FR
Tue May 17 19:28:45 UTC 2011

Date: Mon, 16 May 2011 18:56:38 +0100
From: Michael Chan <m.chan at>
Message-ID: <4DD16556.1000807 at>

Apologies for cross-posting

Call for Participation for LHD-11 workshop at IJCAI-11, July 2011,

Discovering Meaning On the Go in Large & Heterogeneous Data

An interdisciplinary approach is necessary to discover and match
meaning dynamically in a world of increasingly large data.  This
workshop aims to bring together practitioners from academia, industry
and government for interaction and discussion.  The workshop will

* A panel discussion representing industrial and governmental input,
  entitled "Big Society meets Big Data: Industry and Government
  Applications of Mapping Meaning".  Panel members will include:

* Peter Mika (Yahoo!)
* Representative of Google
* Tom McCutcheon (Dstl)
* Representative of ONR Global

* An invited talk from Fausto Giunchglia, discussing the relationship
  between social computing and ontology matching;

* Paper and poster presentations;

* Workshop sponsored by: Yahoo! Research, W3C and others

Workshop Description

The problem of semantic alignment - that of two systems failing to
understand one another when their representations are not identical -
occurs in a huge variety of areas: Linked Data, database integration,
e-science, multi-agent systems, information retrieval over structured
data; anywhere, in fact, where semantics or a shared structure are
necessary but centralised control over the schema of the data sources
is undesirable or impractical. Yet this is increasingly a critical
problem in the world of large scale data, particularly as more and
more of this kind of data is available over the Web.

In order to interact successfully in an open and heterogeneous
environment, being able to dynamically and adaptively integrate large
and heterogeneous data from the Web "on the go" is necessary. This may
not be a precise process but a matter of finding a good enough
integration to allow interaction to proceed successfully, even if a
complete solution is impossible.

Considerable success has already been achieved in the field of
ontology matching and merging, but the application of these techniques
- often developed for static environments - to the dynamic integration
of large-scale data has not been well studied.

Presenting the results of such dynamic integration to both end-users
and database administrators - while providing quality assurance and
provenance - is not yet a feature of many deployed systems. To make
matters more difficult, on the Web there are massive amounts of
information available online that could be integrated, but this
information is often chaotically organised, stored in a wide variety
of data-formats, and difficult to interpret.

This area has been of interest in academia for some time, and is
becoming increasingly important in industry and - thanks to open data
efforts and other initiatives - to government as well. The aim of this
workshop is to bring together practitioners from academia, industry
and government who are involved in all aspects of this field: from
those developing, curating and using Linked Data, to those focusing on
matching and merging techniques.

Topics of interest include, but are not limited to:

* Integration of large and heterogeneous data
* Machine-learning over structured data
* Ontology evolution and dynamics
* Ontology matching and alignment
* Presentation of dynamically integrated data
* Incentives and human computation over structured data and ontologies
* Ranking and search over structured and semi-structured data
* Quality assurance and data-cleansing
* Vocabulary management in Linked Data
* Schema and ontology versioning and provenance
* Background knowledge in matching
* Extensions to knowledge representation languages to better support
* Inconsistency and missing values in databases and ontologies
* Dynamic knowledge construction and exploitation
* Matching for dynamic applications (e.g., p2p, agents, streaming)
* Case studies, software tools, use cases, applications
* Open problems
* Foundational issues

Applications and evaluations on data-sources that are from the Web and
Linked Data are particularly encouraged.

Organising Committee:
Fiona McNeill (University of Edinburgh)
Harry Halpin (Yahoo! Research)
Michael Chan (University of Edinburgh)

Program committee:
Marcelo Arenas (Pontificia Universidad Catolica de Chile)
Krisztian Balog (University of Amsterdam)
Paolo Besana (University of Edinburgh)
Roi Blanco (Yahoo! Research)
Paolo Bouquet (University of Trento)
Ulf Brefeld (Yahoo! Research)
Alan Bundy (University of Edinburgh)
Ciro Cattuto (ISI Foundation)
Vinay Chaudhri (SRI)
James Cheney (University of Edinburgh)
Oscar Corcho (Universidad Politécnica de Madrid)
Shady Elbassuoni (Max-Planck-Institut für Informatik)
Jerome Euzenat (INRIA Grenoble Rhone-Alpes)
Eraldo Fernandes (Pontifícia Universidade Católica do Rio de Janeiro)
Aldo Gangemi (CNR)
Pat Hayes (IHMC)
Pascal Hitzler (Wright State University)
Ivan Herman (W3C)
Tom McCutcheon (Dstl)
Shuai Ma (Beihang University)
Ashok Malhotra (Oracle)
Martin Merry (Epimorphics)
Daniel Miranker (University of Texas-Austin)
Adam Pease (Articulate Software)
Valentina Presutti (CNR)
David Roberston (University of Edinburgh)
Juan Sequeda (University of Texas-Austin)
Pavel Shvaiko (Informatica Trentina)
Jamie Taylor (Google)
Eveylne Viegas (Microsoft Research)

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