W3C home > Mailing lists > Public > public-semweb-lifesci@w3.org > April 2012

Fwd: Special Issue of Journal of Web Semantics on Data Linking

From: M. Scott Marshall <mscottmarshall@gmail.com>
Date: Mon, 23 Apr 2012 11:54:05 +0200
Message-ID: <CACHzV2Pm7Kyt6t13OW4g-nhsgecned3d4g=Yopa2A-s+hJDOmQ@mail.gmail.com>
To: HCLS <public-semweb-lifesci@w3.org>
FYI -Scott
---------- Forwarded message ----------
From: François Scharffe <francois.scharffe@lirmm.fr>
Date: Mon, Apr 23, 2012 at 11:05 AM
Subject: Special Issue of Journal of Web Semantics on Data Linking
To: "public-lod@w3.org" <public-lod@w3.org>


* Apologies for cross-posting *

This special issue of the Journal of Web Semantics focuses on the
problem of finding links between datasets published as linked data.

Today the web of data has become a reality. The ever increasing number
of datasets published as RDF according to the linked data principles,
the support of major search engines, e-commerce sites and social
networks give no doubt that the early scenarios of the semantic Web
vision will soon become a reality.

The power of the web lies in its networked structure, in the
connections between the resources it contains. Similarly, linked data
enable the interlinking of data resources so that databases become
interconnected and the information they contain become part of a huge
distributed database. The transformation of the Web from a “Web of
documents” into a “Web of data”, as well as the availability of large
collections of sensor generated data (“internet of things”), is
leading to a new generation of Web applications based on the
integration of both data and services. At the same time, new data are
published every day out of user generated contents and public Web
sites.

This emergence of the Web of data raises many challenges, such as the
need of comparing and matching data with the goal of resolving the
multiplicity of data references to the same real-world objects and of
finding useful and relevant similarities and correspondences among
data. The Web needs techniques and tools for the discovery of data
links, and a suitable theory for the understanding and definition of
the data links meaning.

About data links, one of the most important goals is to provide means
to ensure that the interconnection between data is effective. The
design of algorithms, methodologies, languages and tools that provide
more efficient and automated ways to link data is essential for the
growth of the Web of data rather than a set of disjoint data islands.

While the problems of entity resolution have been studied in the
database community for a long time, the Web of data environment
presents new important challenges at different levels. Large volumes
of data and the variety of repositories which have to be processed
rise the need for scalable linking techniques which require minimal
user involvement. On the other hand, in cases where user configuration
effort is required, there is a need for tools to be usable by
non-experts in the domain.

Given that published data links can be used by automatic reasoning
tools, it is important to capture the meaning of links in a precise
way. Since quality of automatically generated links can vary, their
provenance and reliability have to be modelled in an explicit way.
Finally, to capture and compare the reliability of different tools and
techniques, there is a need for evaluation methods for automatic data
linking approaches.

Challenges

• Automating the process of finding links between Web datasets
• Scaling data linking algorithms
• Representation and interpretation of links
• Providing efficient user interfaces and interaction methods
• Modeling and reasoning on links trust and provenance information

Topics of Interest

The topics of interest for this special issue include but are not
limited to the following.

• data linking tools and frameworks
• techniques for automated data linking
• data similarity measures
• similarity spreading measures
• schema-based similarity measures
• candidate dataset selection and datasets similarity measures
• statistical analysis techniques
• semi-supervised, learning-based data linking methods
• optimization methods for computing similarity
• web data sampling techniques
• identity representation and semantics
• reasoning on links, link propagation
• user interaction for link elicitation and validation
• provenance and trust models on links
• methods for link quality assessment
• innovative applications using links
• evaluation of data linking techniques and tools

Important Dates

We will review papers on a rolling basis as they are submitted and
explicitly encourage submissions well before the final deadline.

• 1 June: submission deadline
• 1 September: initial decisions and notifications
• 1 October: major/minor revisions due
• 1 November: final minor revisions due
• 1 December: final decisions and notifications
• 1 January: preprints available publication in 2013


Instructions for submission

Please see the author guidelines for detailed instructions before you
submit. Submissions should be conducted through Elsevier’s Electronic
Submission System. More details on the Journal of Web Semantics can be
found on its homepage. See the JWS Guide for Authors for details on
the submission process.


Editors

• Alfio Ferrara (Università degli Studi di Milano)
• Andriy Nikolov (Open University)
• François Scharffe (LIRMM, Université de Montpellier 2)
Received on Monday, 23 April 2012 09:54:39 GMT

This archive was generated by hypermail 2.3.1 : Tuesday, 26 March 2013 18:01:07 GMT