Please use this identifier to cite or link to this item:

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.
AccessRestricted access (UMinho)
Appears in Collections:CAlg - Artigos em livros de atas/Papers in proceedings

Files in This Item:
File Description SizeFormat 
  Restricted access
69,72 kBAdobe PDFView/Open

Partilhe no FacebookPartilhe no TwitterPartilhe no DeliciousPartilhe no LinkedInPartilhe no DiggAdicionar ao Google BookmarksPartilhe no MySpacePartilhe no Orkut
Exporte no formato BibTex mendeley Exporte no formato Endnote Adicione ao seu ORCID