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LRE-URLCALODRMA 2015 : Under-resourced Languages, Special Issue of the Language Resources and Evaluation Journal:Under-resourced Languages, Collaborative Approaches and Linked Open Data: Resources, Meth


When N/A
Where N/A
Submission Deadline Nov 15, 2014
Categories    NLP

Call For Papers

We are delighted to invite submissions for a Special Issue of the Language
Resources and Evaluation Journal, entitled "Under-resourced Languages,
Collaborative Approaches and Linked Open Data: Resources, Methods and

Important: More detailed information will be made available in September
2014. For more information please contact the guest editors.



Under-resourced languages are generally described as languages that suffer
from a chronic lack of available resources, from human, financial, and time
resources to linguistic ones (language data and language technology), and
often also experience the fragmentation of efforts in resource
development. This situation is exacerbated by the realization that as
technology progresses and the demand for localised languages services over
digital devices increases, the divide between adequately- and
under-resourced languages keeps widening. Given that most of the world�^�^�s
almost 7000 languages are not adequately resourced, much work needs to be
done in order to support their existence in the digital age.

Although the destiny of a language is primarily determined by its native
speakers and broader cultural context, the technological development of an
under-resourced language offers such a language a strategic opportunity to
have the same "digital dignity", "digital identity" and "digital longevity"
as large, well-developed languages on the Web.

The Linked (Open) Data framework and the emerging Linguistic Linked (Open)
Data infrastructure offer novel opportunities for under-resourced
languages. On the one hand, Linked Data offers ways of exposing existing
high quality, albeit small, language resources in the Semantic Web and, on
the other hand, allows for the development of new state-of-the-art resources
without necessarily having to rely on the availability of sophisticated
language processing support.

This special issue arises from the imperative to maintain cultural and
language diversity and from the basic right of all communities, languages,
and cultures to be "first class citizens" in an age driven by information,
knowledge and understanding. In this spirit, this special issue focuses on
three strategic approaches to augment the development of resources for
under-resourced languages to achieve a level potentially comparable to
well-resourced, technologically advanced languages, viz. a) using the crowd
and collaborative platforms; b) using technologies of interoperability with
well-developed languages; and c) using Semantic Web technologies and, more
specifically, Linked Data.

We invite original contributions, not published before and not under
consideration for publication elsewhere, that address one or more of the
following questions by means of one or more of the three approaches
mentioned above:

- How can collaborative approaches and technologies be fruitfully applied to
the accelerated development and sharing of high quality resources for
under-resourced languages?

- How can such resources be best stored, exposed and accessed by end users
and applications?

- How can small language resources be re-used efficiently and effectively,
reach larger audiences and be integrated into applications?

- How can multilingual and cross-lingual interoperability of language
resources, methods and applications be supported, also between languages
that belong to different language families?

- How can existing language resource infrastructures be scaled to thousands
of languages?

- How can research on and resource development for under-resourced languages
benefit from current advances in semantic and semantic web technologies, and
specifically the Linked Data framework?

Guest editors
Laurette Pretorius - University of South Africa, South Africa (pretol AT
unisa DOT ac DOT za)

Claudia Soria - CNR-ILC, Italy (claudia.soria AT ilc DOT cnr DOT it)

Scientific committee
Sabine Bartsch, Technische Universitat Darmstadt, Germany

Delphine Bernhard, LILPA, Strasbourg University, France

Peter Bouda, CIDLeS - Interdisciplinary Centre for Social and Language
Documentation, Portugal

Paul Buitelaar, Insight Centre for Data Analytics, NUIG, Ireland

Steve Cassidy, Macquarie University, Australia

Christian Chiarcos, Frankfurt University, Germany

Thierry Declerck, DFKI GmbH, Language Technology Lab, Germany

Mikel Forcada, University of Alicante, Spain

Dafydd Gibbon, Bielefeld University, Germany

Yoshihiko Hayashi, Graduate School of Language and Culture, Osaka
University, Japan

Sebastian Hellmann, Leipzig University, Germany

Simon Krek, Jožef Stefan Institute, Slovenia

Tobias Kuhn, ETH, Zurich, Switzerland

Joseph Mariani, LIMSI-CNRS & IMMI, France

John McCrae, Bielefeld University, Germany

Steven Moran, Universität Zürich, Switzerland

Kellen Parker, National Tsing Hua University, China

Patrick Paroubek, LIMSI-CNRS, France

Taher Pilehvar, �^�^�La Sapienza�^�^� Rome University, Italy

Maria Pilar Perea i Sabater, Universitat de Barcelona, Spain

Laurette Pretorius, University of South Africa, South Africa

Leonel Ruiz Miyares, Centro de Linguistica Aplicada (CLA), Cuba

Kevin Scannell, St. Louis University, USA

Ulrich Schäfer, Technical University of Applied Sciences Amberg-Weiden,
Bavaria, Germany

Claudia Soria, CNR-ILC, Italy

Nick Thieberger, University of Melbourne, Australia

Eveline Wandl-Vogt, Austrian Academy of Sciences, ICLTT, Austria

Michael Zock, LIF-CNRS, France

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