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

From: Michael Miller <Michael.Miller@systemsbiology.org>
Date: Mon, 23 Apr 2012 07:11:23 -0700
Message-ID: <fa4877ce9d70579e2924a283cf0b29ce@mail.gmail.com>
To: "M. Scott Marshall" <mscottmarshall@gmail.com>, HCLS <public-semweb-lifesci@w3.org>
hi all,

very interesting, this concerns one of the areas i'm curious about the
viability of semantic web technologies

> • 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

these are at the essence of one aspect of systems biology, to which i
would add significance testing, i.e. most significant differentially
expressed genes.

can our bioRDF paper be extended to show how gene sets can be created and
compared using semantic web technologies from raw gene expression data?

cheers,
michael

Michael Miller
Software Engineer
Institute for Systems Biology

> -----Original Message-----
> From: M. Scott Marshall [mailto:mscottmarshall@gmail.com]
> Sent: Monday, April 23, 2012 2:54 AM
> To: HCLS
> Subject: Fwd: Special Issue of Journal of Web Semantics on Data Linking
>
> 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 14:11:56 GMT

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