[Elsnet-list] Linked Data in Linguistics 2014 Data Challenge - 2nd Call for Participation
John P. McCrae
jmccrae at cit-ec.uni-bielefeld.de
Mon Feb 17 12:15:39 CET 2014
**Apologies for cross-posting**
Linked Data in Linguistics 2014 - Data Challenge
Collocated with LREC 2014
Reykjavik, Iceland, 27th May 2014
Call for Datasets
The explosion of information technology has led to a substantial growth in
quantity, diversity and complexity of linguistic data accessible on the
Web. The lack of interoperability between linguistic and language resources
represents a major challenge that needs to be addressed, in particular, if
information from different sources is to be combined, such as
machine-readable lexicons, corpus data and terminology repositories. The
Linked Data in Linguistics (LDL) workshop series provides a forum to
discuss these types of resources, strategies to address issues of
interoperability between them, protocols to distribute, access and
integrate this information and technologies and infrastructures developed
on this basis.
This year, there is a data challenge associated to the Linguistic Linked
Data Workshop. In addition to regular workshop papers, we will accept
dataset description of 4-6 pages describing linguistically or NLP-relevant
datasets published on the web as linked data published on the web as
linked data. These linguistic datasets include, but are not limited to,
lexica, terminologies, semantic networks, annotated and parallel corpora,
multimodal resources, typological resources and linguistic metadata. The
data challenge committee will review and evaluate data according to the
following criteria, with prizes of up to €700, funded by the
LIDER<http://lider-project.eu/>project, awarded to the highest scoring
Use of Linked Data and RDF.
Hosted on a publicly accessible server and be available both during
the period of the evaluation and beyond.
Use of an open license.
Quality of Resource
Represents useful linguistically or NLP-relevant information.
Reuses relevant standards and models.
Contains complex, non-trivial information, e.g., multiple levels of
Links to external resources.
Reuse of existing properties and categories.
Impact/usefulness of the resource
Relevant and likely to be reused by many researchers in NLP and wider
Uses linked data to improve the quality of and access to the resource.
Represents a type of resource or a community currently
underrepresented in (L)LOD cloud activities
Facilitates novel and unforeseen applications or use cases (as
described by the authors) enabled through Linked Data technology.
Submission & Publication
We accept dataset descriptions of 4-6 pages, which include a URL under
which the data is available. The papers of the workshop will be published
as online proceedings. All submissions can be presented as lightning talks
or posters, albeit such a presentation is optional. In addition, we aim for
a journal special issue as post-conference proceedings in which a selected
amount of papers presented at the workshop will be published. When
submitting a dataset description, authors will be asked to provide
essential information about resources (in a broad sense, i.e. also
technologies, standards, evaluation kits, etc.) that have been used for the
work described in the paper or are a new result of your research. Moreover,
ELRA encourages all LREC authors to share the described LRs (data, tools,
services, etc.), to enable their reuse, replicability of experiments,
including evaluation ones, etc. For contact data, stylesheets, up-to-date
details on submission and the workshop itself, please consult our
Specific details on dataset submissions and the challenge can be found
Submission deadline: Fri, Feb 28, 2014
Notification of acceptance: Fri, Mar 14, 2014
Camera-ready paper: Fri, Mar 28, 2014
Workshop: Tue, May 27, 2014
Please note that due to synchronization with the main conference, NO
EXTENSIONS can be given.
Christian Chiarcos (Goethe-Universität Frankfurt am Main, Germany)
John McCrae (Universität Bielefeld, Germany)
Philipp Cimiano (Universität Bielefeld, Germany)
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