Fwd: CfP: ACM Journal of Data and Information Quality (JDIQ): Special Issue on Web Data Quality

This may inspire some of you…

Ivan

> Begin forwarded message:
> 
> From: "Christian Bizer" <chris@bizer.de>
> Subject: CfP: ACM Journal of Data and Information Quality (JDIQ): Special Issue on Web Data Quality
> Date: 17 Sep 2015 14:23:13 CEST
> To: <semantic-web@w3.org>, <public-lod@w3.org>, "W3C Vocabularies" <public-vocabs@w3.org>, <dbpedia-discussion@lists.sourceforge.net>
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> 
> Hi all,
> 
> this is the second CfP for the ACM Journal of Data and Information
> Quality (JDIQ) special issue on Web Data Quality.
> 
> The goal of the special issue is to present innovative research in the
> areas of Web Data Quality Assessment and Web Data Cleansing.
> 
> The submission deadline for the special issue is November 1st, 2015.
> 
> Please find the detailed call for papers below and at
> 
> http://jdiq.acm.org/announcements.cfm#special-issue-of-acm-jdiq-on-web-data-
> quality
> 
> Cheers,
> 
> Luna Dong, Ihab Ilyas, Maria-Esther Vidal, and Christian Bizer
> 
> 
> 
> ---------------------
> 
> Call for Papers:
> 
> ACM Journal of Data and Information Quality (JDIQ)
> 
> Special Issue on Web Data Quality
> 
> ---------------------
> 
> 
> Guest editors:
> 
> * Christian Bizer, University of Mannheim, Germany,
> chris@informatik.uni-mannheim.de
> * Luna Dong, Google, USA, lunadong@google.com
> * Ihab Ilyas, University of Waterloo, Canada, ilyas@uwaterloo.ca
> * Maria-Esther Vidal, Universidad Simon Bolivar, Venezuela,
> mvidal@umiacs.umd.edu
> 
> 
> Introduction:
> 
> The volume and variety of data that is available on the web has risen
> sharply. In addition to traditional data sources and formats such as
> CSV files, HTML tables and deep web query interfaces, new techniques
> such as Microdata, RDFa, Microformats and Linked Data have found wide
> adoption. In parallel, techniques for extracting structured data from
> web text and semi-structured web content have matured resulting in the
> creation of large-scale knowledge bases such as NELL, YAGO, DBpedia,
> and the Knowledge Vault.
> 
> Independent of the specific data source or format or information
> extraction methodology, data quality challenges persist in the context
> of the web. Applications are confronted with heterogeneous data from a
> large number of independent data sources while metadata is sparse and
> of mixed quality. In order to utilize the data, applications must
> first deal with this widely varying quality of the available data and
> metadata.
> 
> 
> Topics:
> 
> The goal of this special issue of JDIQ is to present innovative
> research in the areas of Web Data Quality Assessment and Web Data
> Cleansing. Specific topics within the scope of the call include, but
> are not limited to, the following:
> 
> WEB DATA QUALITY ASSESSMENT:
> 
> * Metrics and methods for assessing the quality of web data, including
> Linked Data, Microdata, RDFa, Microformats and tabular data.
> * Methods for uncovering distorted and biased data / data SPAM detection.
> * Methods for quality-based web data source selection.
> * Methods for copy detection.
> * Methods for assessing the quality of instance- and schema-level
> links Linked Data.
> * Ontologies and controlled vocabularies for describing the quality of
> web data sources and metadata.
> * Best practices for metadata provision.
> * Cost and benefits of web data quality assessment and benchmarks.
> 
> WEB DATA CLEANSING:
> * Methods for cleansing Web data, Linked Data, Microdata, RDFa,
> Microformats and tabular data.
> * Conflict resolution using semantic knowledge and truth discovery.
> * Human-in-the-loop and crowdsourcing for data cleansing.
> * Data quality for automated knowledge base construction.
> * Empirical evaluation of scalability and performance of data
> cleansing methods and benchmarks.
> 
> APPLICATIONS AND USE CASES IN THE LIFE SCIENCES, HEALTHCARE, MEDIA,
> SOCIAL MEDIA, GOVERNMENT AND SENSOR DATA.
> 
> 
> Important dates:
> 
> Initial submission: November 1, 2015
> First review: January 15, 2016
> Revised manuscripts: February 15, 2016
> Second review: March 30, 2016
> Publication: May 2016
> 
> 
> Submission guidelines:
> 
> http://jdiq.acm.org/authors.cfm
> 
> 
> --
> Prof. Dr. Christian Bizer
> Data and Web Science Group
> University of Mannheim, Germany
> chris@informatik.uni-mannheim.de
> http://dws.informatik.uni-mannheim.de/bizer
> 
> 
> 
> 
> 


----
Ivan Herman, W3C
Digital Publishing Lead
Home: http://www.w3.org/People/Ivan/
mobile: +31-641044153
ORCID ID: http://orcid.org/0000-0003-0782-2704