Editorial: Special issue on web data quality


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



DOI: https://doi.org/10.1145/3005395
URL: http://doi.acm.org/10.1145/3005395
Additional URL: http://dl.acm.org/citation.cfm?id=3005395
Document Type: Article
Year of publication: 2016
The title of a journal, publication series: Journal of Data and Information Quality : JDIQ
Volume: 8
Issue number: 1
Page range: 1:1-1:3
Place of publication: New York, NY
Publishing house: ACM
ISSN: 1936-1955 , 1936-1963
Publication language: English
Institution: School of Business Informatics and Mathematics > Information Systems V: Web-based Systems (Bizer 2012-)
Subject: 004 Computer science, internet
Keywords (English): Web Data Quality , Information Quality , Data Cleansing , Data Profiling
Abstract: We are delighted to present this special issue of the Journal of Data and Information Quality on web data quality. This issue includes four innovative research articles covering the areas of web data profiling, web data quality assessment, and web data cleansing.Over the last few years, 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 emistructured 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. Before one can utilize the data, a potential user must first overcome the challenges of handling a wide range of quality issues in the available data and metadata.




Dieser Eintrag ist Teil der Universitätsbibliographie.




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