[open-government] Fwd: CFP: First International Workshop on Semantic Statistics (SemStats 2013) @ ISWC 2013

Fri May 3 09:41:31 UTC 2013

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-------- Original Message --------
Subject: CFP: First International Workshop on Semantic Statistics 
(SemStats  2013) @ ISWC 2013
Resent-Date: Fri, 03 May 2013 09:29:28 +0000
Resent-From: public-lod at w3.org
Date: Fri, 03 May 2013 11:28:59 +0200
From: Raphaël Troncy <raphael.troncy at eurecom.fr>
Organization: EURECOM
To: Linked Data community <public-lod at w3.org>

============================================================================= 

First International Workshop on Semantic Statistics (SemStats 2013)

Full-Day Workshop in conjunction with ISWC 2013, the 12th International
Semantic Web Conference
21-25 October 2013, in Sydney, Australia

Workshop Web Site: http://www.datalift.org/en/event/semstats2013
EasyChair: http://www.easychair.org/conferences/?conf=semstats2013
E-mail address: semstats2013 at easychair.org
Twitter Hashtag: #semstats2013

*Important Dates*
- Deadline for paper submission: Friday, 12 July 2013, 23:59 (Hawaii time)
- Notification of acceptance/rejection: Friday, 9 August 2013
- Deadline for camera-ready version: Friday, 30 August 2013
============================================================================= 

*Workshop Summary*
The goal of this workshop is to explore and strengthen the relationship
between the Semantic Web and statistical communities, to provide better
access to the data held by statistical offices. It will focus on ways in
which statisticians can use Semantic Web technologies and standards in
order to formalize, publish, document and link their data and metadata.

The statistical community has recently shown an interest in the Semantic
Web. In particular, initiatives have been launched to develop semantic
vocabularies representing statistical classifications and discovery
metadata. Tools are also being created by statistical organizations to
support the publication of dimensional data conforming to the Data Cube
specification, now in Last Call at W3C. But statisticians see challenges
in the Semantic Web: how can data and concepts be linked in a
statistically rigorous fashion? How can we avoid fuzzy semantics leading
to wrong analyses? How can we preserve data confidentiality?

The workshop will also cover the question of how to apply statistical
methods or treatments to linked data, and how to develop new methods and
tools for this purpose. Except for visualisation techniques and tools,
this question is relatively unexplored, but the subject will obviously
grow in importance in the near future.

*Motivation*
There is a growing interest regarding linked data and the Semantic Web
in the statistical community. A large amount of statistical data from
international and national agencies has already been published on the
web of data, for example Census data from the U.S., Spain or France
amongst others. In most cases, though, this publication is done by
people exterior to the statistical office (see also
http://datahub.io/dataset/istat-immigration, http://270a.info/ or
http://eurostat.linked-statistics.org/), which raises issues such as
long-term URI persistence, institutional commitment and data maintenance.

Statistical organizations also possess an important corpus of structural
metadata such as concept schemes, thesauri, code lists and
classifications. Some of those are already available as linked data,
generally in SKOS format (e.g. FAO's Agrovoc or UN's COFOG). Semantic
web standards useful for the statisticians have now arrived at maturity.
The best examples are the W3C Data Cube, DCAT and ADMS vocabularies. The
statistical community is also working on the definition of more
specialized vocabularies, especially under the umbrella of the DDI
Alliance. For example, XKOS extends SKOS for the representation of
statistical classifications, and Disco defines a vocabulary for data
documentation and discovery; and the Visual Analytics Vocabulary is a
first step towards semantic descriptions for user interface components
developed to visualize Linked Statistical Data which can lead to
increased linked data consumption and accessibility. We are now at the
tipping point where the statistical and the Semantic Web communities
have to formally exchange in order to share experiences and tools and
think ahead regarding the upcoming challenges.

The web of data will benefit in getting rich data published by
professional and trustworthy data providers. It is also important that
metadata maintained by statistical offices like concept schemes of
economic or societal terms, statistical classifications, well-known
codes, etc., are available as linked data, because they are of good
quality, well-maintained, and they constitute a corpus to which a lot of
other data can refer to.

Statisticians have a long-going culture of data integrity, quality and
documentation. They have developed industrialized data production and
publication processes, and they care about data confidentiality and more
generally how data can be used. It seems that after a period where the
aim was to publish as many triples as possible, the focus of the
Semantic Web community is now shifting to having a better quality of
data and metadata, more coherent vocabularies (see the LOV initiative),
good and documented naming patterns, etc. This workshop aims to
contribute in these longer term problems in order to have a significant
impact.

The statistics community faces sometimes challenges when trying to adopt
Semantic Web technologies, in particular:
   * difficulty to create and publish linked data: this can be
alleviated by providing methods, tools, lessons learned and best
practices, by publicizing successful examples and by providing support.
   * difficulty to see the purpose of publishing linked data: we must
develop end-user tools leveraging statistical linked data, provide
convincing examples of real use in applications or mashups, so that the
end-user value of statistical linked data and metadata appears more clearly.
   * difficulty to use external linked data in their daily activity: it
is important do develop statistical methods and tools especially
tailored for linked data, so that statisticians can get accustomed to
using them and get convinced of their specific utility.

To conclude, statisticians know how misleading it can be to exploit
semantic connections without carefully considering and weighing
information about the quality of these connections, the validity of
inferences, etc. A challenge for them is to determine, to ensure and to
inform consumers about the quality of semantic connections which may be
used to support analysis in some circumstances but not others. The
workshop will enable participants to discuss these very important issues.

*Topics*
The workshop will address topics related to statistics and linked data.
This includes but is not limited to:

How to publish linked statistics?
   * What are the relevant vocabularies for the publication of
statistical data?
   * What are the relevant vocabularies for the publication of
statistical metadata (code lists and classifications, descriptive
metadata, provenance and quality information, etc.)?
   * What are the existing tools? Can the usual statistical software
packages (e.g. R, SAS, Stata) do the job?
   * How do we include linked data production and publication in the
data lifecycle?
   * How do we establish, document and share best practices?

How to use linked data for statistics?
   * Where and how can we find statistics data: data catalogues, dataset
descriptions, data discovery?
   * How do we assess data quality (collection methodology,
traceability, etc.)?
   * How can we perform data reconciliation, ontology matching and
instance matching with statistics data?
   * How can we apply statistical processes on linked data: data
analysis, descriptive statistics, estimation, correction, visualization,
etc.?

*Submissions*
This full-day workshop is aimed at an interdisciplinary audience of
researchers and practitioners involved or interested in Statistics and
the Semantic Web. All papers must represent original and unpublished
work that is not currently under review. Papers will be evaluated
according to their significance, originality, technical content, style,
clarity, and relevance to the workshop. At least one author of each
accepted paper is expected to attend the workshop.

Workshop participation is available to ISWC 2013 attendants at an
additional cost, see
http://iswc2013.semanticweb.org/content/registration for details.

The workshop will also feature a challenge based on Census Data
published on the web or provided by Statistical Institutes. It is
expected that data from Australia, France, Ireland, the U.S. and Spain
at least will be available. The challenge will consist in the
realization of mashups or visualizations, but also on comparisons,
alignment and enrichment of the data and concepts involved. A reward
will be attributed to the challenge winner. More details will be
available soon at http://www.datalift.org/event/semstats2013.

We welcome the following types of contributions:
   * Full research papers (up to 12 pages)
   * Short papers (up to 6 pages)
   * Challenge papers (up to 6 pages)

All submissions must be written in English and must be formatted
according to the information for LNCS Authors (see
http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0). Please,
note that (X)HTML(+RDFa) submissions are also welcome as soon as the
layout complies with the LNCS style. Authors can for example use the
template provided at https://github.com/csarven/linked-research.
Submissions are NOT anonymous. Please submit your contributions
electronically in *PDF* format at
http://www.easychair.org/conferences/?conf=semstats2013 and before July
12, 2013, 23:59 PM Hawaii Time. All accepted papers will be archived in
an electronic proceedings published by CEUR-WS.org. If you are
interested in submitting a paper but would like more preliminary
information, please contact semstats2013 at easychair.org.

*Chairs*
Franck Cotton, INSEE, France
Richard Cyganiak, DERI, Ireland
Armin Haller, CSIRO, Australia
Alistair Hamilton, ABS, Australia
Raphaël Troncy, EURECOM, France

*Program Committee*
Ghislain Atemezing, EURECOM, France
Sarven Capadisli, University of Leipzig, Germany
Ric Clarke, Australian Bureau of Statistics, Australia
Jay Devlin, Statistices New Zealand, New Zealand
Miguel Expósito, Instituto Cántabro de Estadística, Spain
Dan Gillman, U.S. Bureau of Labor Statistics, USA
Alberto González Yanes, ISTAC, Spain
Arofan Gregory, Open Data Foundation, United States
Tudor Groza, The University of Queensland, Australia
Christophe Guéret, Data Archiving and Networked Services (DANS), The
Netherlands
Andreas Harth, Karlsruhe Institute of Technology, Germany
Yves Jacques, FAO, Italy
Laurent Lefort, CSIRO, Australia
Marco Pellegrino, Eurostat, Luxembourg
Dave Reynolds, Epimorphics, UK
Monica Scannapieco, Istat, Italy
François Scharffe, LIRMM, University of Montpellier, France
Wendy Thomas, University of Minnesota, United States
Bernard Vatant, Mondeca, France
Boris Villazon-Terrazas, iSOCO, Spain
Joachim Wackerow, GESIS, Germany
Stuart Williams, Epimorphics, UK
-- 
Raphaël Troncy
EURECOM, Campus SophiaTech
Multimedia Communications Department
450 route des Chappes, 06410 Biot, France.
e-mail: raphael.troncy at eurecom.fr & raphael.troncy at gmail.com
Tel: +33 (0)4 - 9300 8242
Fax: +33 (0)4 - 9000 8200
Web: http://www.eurecom.fr/~troncy/

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