*Deadline extension* for [CFP] Second International Workshop on Semantic Statistics (SemStats 2014)

On 2014-06-24 08:59, Sarven Capadisli wrote:
> SemStats 2014 Call for Papers
> =============================
>
> Second International Workshop on Semantic Statistics (SemStats 2014)
>
> Workshop website: http://semstats.org/
> Event hashtags: #SemStats #ISWC2014
>
> in conjunction with
>
> ISWC 2014
> The 13th International Semantic Web Conference
> Riva del Garda - Trentino, Italy, October 19-23, 2014
> http://iswc2014.semanticweb.org/
>
>
> 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.
>
>
> 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 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.
>
>
> 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 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?
>
>
> Submissions
> ===========
>
> 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
> 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 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.
>
>
> Chairs
> ======
>
> * 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
> Netherlands
> * 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,
> Germany
> * Stuart Williams, Epimorphics, UK


"Good news everyone",

The submission deadline is extended to 2014-07-21!

-Sarven
http://csarven.ca/#i