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[CfP] Second International Workshop on Semantic Statistics (SemStats 2014)

From: Sarven Capadisli <info@csarven.ca>
Date: Wed, 07 May 2014 08:20:12 +0200
Message-ID: <5369D09C.8000203@csarven.ca>
To: SW-forum <semantic-web@w3.org>
SemStats 2014 Call for Papers

Second International Workshop on Semantic Statistics (SemStats 2014)

Workshop website: http://www.datalift.org/en/event/semstats2014/cfp
Event hashtags: #SemStats #ISWC2014

in conjunction with

ISWC 2014
The 13th International Semantic Web Conference
Riva del Garda - Trentino, Italy, October 19-23, 2014

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. 
It follows the 1st Semantic Statistics workshop held at ISWC 2013 
(SemStats 2013) http://www.datalift.org/en/event/semstats2013 that was a 
big success attracting more than 50 participants all along the day.

The statistical community shows more and more 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 
W3C Recommendation. 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.


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 organisations are also interested in how Semantic Web might 
make it simpler for analysts to use well described statistical data in 
conjunction with other forms of data (eg geospatial information, 
scientific data, "big data" from various sources) which is expressed 
semantically. The ability to bring together diverse types of data in 
this way  should enable new insights on multifaceted issues.

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. 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.

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.

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.

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 to 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.


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 
* 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 
* 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, 
* How can we perform data reconciliation, ontology matching and instance 
matching with statistical data?
* How can we apply statistical processes on linked data: data analysis, 
descriptive statistics, estimation, correction?
* How to intuitively represent statistical linked data: visual 
analytics, results of data mining?


This 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 2014 attendants at an 
additional cost, see http://iswc2014.semanticweb.org/registration for 

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 and Italy 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.

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=semstats2014 and before July 
7, 2014, 23:59 PM Hawaii Time. All accepted papers will be archived in 
an electronic proceedings published by CEUR-WS.org.

See important dates and contact info on the workshop home page.

If you are interested in submitting a paper but would like more 
preliminary information, please contact semstats2014@easychair.org.


* Sarven Capadisli, University of Leipzig, Germany, and Bern University 
of Applied Sciences, Switzerland
* Franck Cotton, INSEE, France
* Armin Haller, CSIRO, Australia
* Alistair Hamilton, ABS, Australia
* Monica Scannapieco, Istat, Italy
* Raphaël Troncy, EURECOM, France

Program Committee

* Phil Archer, W3C, i-sieve, UK
* Ghislain Auguste Atemezing, Eurecom, France
* Jay Devlin, Statistics New Zealand, New Zealand
* Miguel Expósito Martín, Instituto Cántabro de Estadística, Spain
* Dan Gillman, US Bureau of Labor Statistics, USA
* Arofan Gregory, Metadata Technology NA, USA
* Tudor Groza, School of ITEE, The University of Queensland, Australia
* Christophe Guéret, Data Archiving and Networked Services (DANS), The 
* Andreas Harth, AIFB, Karlsruhe Institute of Technology, Germany
* Hak Lae Kim, Samsung Electronics
* Laurent Lefort, CSIRO ICT Centre, Australia
* Domenico Lembo, Sapienza University of Rome, Italy
* Vincenzo Patruno, Istat, Italy
* Marco Pellegrino, Eurostat, Luxembourg
* Dave Reynolds, Epimorphics, UK
* Hideaki Takeda, National Institute of Informatics, Japan
* Wendy Thomas, Minnesota Population Center, USA
* Bernard Vatant, Mondeca, France
* Boris Villazón-Terrazas, iSOCO, Intelligent Software Components, Spain
* Joachim Wackerow, GESIS - Leibniz Institute for the Social Sciences, 
* Stuart Williams, Epimorphics, UK

Received on Wednesday, 7 May 2014 06:20:41 UTC

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