Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/47553

TitleForeword to the thematic track: Quality aspects in big data systems
Author(s)Santos, Maribel Yasmina
Issue date11-Jan-2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Abstract(s)[Excerpt] Recent studies have shown that poor quality data is predominant in many Big Data systems containing a variety of sources such as linked data, mobile data, social media data, Internet of Things data, and many others. The fourth "V" of big data (veracity) directly refers to uncertainty and data quality problems. With the variety of Big Data sources, new frameworks and methods are needed for quality assessment, management and improvement due to the sheer volume and velocity of data. Although significant progresses have been made, mainly in what concerns technologies for processing Big Data, several challenges still remain, including distributed and streaming discovery of data quality, crowdsourced data cleaning, and tools/data validators. In this thematic track, the focus is novel contributions for addressing Quality Aspects in Big Data Systems, ranging from conceptual frameworks to case studies, from design to implementation, from data collection to data analytics, or from data cleansing to data integration. [...]
TypeConference editorial
Description10th International Conference on the Quality of Information and Communications Technology, QUATIC 2016.
URIhttp://hdl.handle.net/1822/47553
ISBN9781509035816
DOI10.1109/QUATIC.2016.045
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:CAlg - Artigos em livros de atas/Papers in proceedings

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