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

Hi all,

we are happy to announce that the ACM Journal of Data and Information  
Quality (JDIQ) will feature a 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

Best,

Luna Dong, Ihab Ilyas, Maria-Esther Vidal, and Christian Bizer



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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

Received on Thursday, 2 July 2015 07:59:12 UTC