Paper Info
Title
Using DevOps Principles to Continuously Monitor RDF Data Quality.
Abstract
One approach to continuously achieve a certain data quality level is to use an integration pipeline that continuously checks and monitors the quality of a data set according to defined metrics. This approach is inspired by Continuous Integration pipelines, that have been introduced in the area of software development and DevOps to perform continuous source code checks. By investigating in possible tools to use and discussing the specific requirements for RDF data sets, an integration pipeline is derived that joins current approaches of the areas of software-development and semantic-web as well as reuses existing tools. As these tools have not been built explicitly for CI usage, we evaluate their usability and propose possible workarounds and improvements. Furthermore, a real-world usage scenario is discussed, outlining the benefit of the usage of such a pipeline.
Year
DOI
Venue
2016
10.1145/2993318.2993351
SEMANTICS
Field
DocType
Citations 
Data integration,Data mining,Pipeline transport,Data quality,Source code,Computer science,Usability,DevOps,Database,Software development,RDF
Conference
1
PageRank 
References 
Authors
0.35
7
2
Name
Order
Citations
PageRank
Roy Meissner162.50
Kurt Junghanns251.15