scholarly journals Data quality assessment and anomaly detection via map/reduce and linked data: A case study in the medical domain

Author(s):  
Stephen Bonner ◽  
Andrew Stephen McGough ◽  
Ibad Kureshi ◽  
John Brennan ◽  
Georgios Theodoropoulos ◽  
...  
2016 ◽  
Vol 16 (2) ◽  
pp. 93-112 ◽  
Author(s):  
João Marcelo Borovina Josko ◽  
João Eduardo Ferreira

Data quality assessment outcomes are essential to ensure useful analytical processes results. Relevant computational approaches provide assessment support, especially to data defects that present more precise rules. However, data defects that are more dependent of data context knowledge challenge the data quality assessment since the process involves human supervision. Visualization systems belong to a class of supervised tools that can make visible data defect structures. Despite their considerable design knowledge encodings, there is little support design to visual quality assessment of data defects. Therefore, this work reports a case study that has explored which and how visualization properties facilitate visual detection of data defect. Its outcomes offer a first set of implications to design visualization system to permit data quality visual assessment.


2016 ◽  
Vol 8 (1) ◽  
pp. 1-32 ◽  
Author(s):  
Jeremy Debattista ◽  
SÖren Auer ◽  
Christoph Lange

2020 ◽  
Vol 2 (4) ◽  
pp. 529-553
Author(s):  
Li Huang ◽  
Zhenzhen Liu ◽  
Fangfang Xu ◽  
Jinguang Gu

With the rapid growth of the linked data on the Web, the quality assessment of the RDF data set becomes particularly important, especially for the quality and accessibility of the linked data. In most cases, RDF data sets are shared online, leading to a high maintenance cost for the quality assessment. This also potentially pollutes Internet data. Recently blockchain technology has shown the potential in many applications. Using the blockchain storage quality assessment results can reduce the centralization of the authority, and the quality assessment results have characteristics such as non-tampering. To this end, we propose an RDF data quality assessment model in a decentralized environment, pointing out a new dimension of RDF data quality. We use the blockchain to record the data quality assessment results and design a detailed update strategy for the quality assessment results. We have implemented a system DCQA to test and verify the feasibility of the quality assessment model. The proposed method can provide users with better cost-effective results when knowledge is independently protected.


Author(s):  
Maribel Acosta ◽  
Amrapali Zaveri ◽  
Elena Simperl ◽  
Dimitris Kontokostas ◽  
Sören Auer ◽  
...  

Author(s):  
Wahyu Ari Bowo ◽  
Agus Suhanto ◽  
Meisuchi Naisuty ◽  
Syukron Ma'mun ◽  
Achmad Nizar Hidayanto ◽  
...  

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