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Representing Dataset Quality Metadata using Multi-Dimensional Views
[article]
2014
arXiv
pre-print
Data quality is commonly defined as fitness for use. The problem of identifying quality of data is faced by many data consumers. Data publishers often do not have the means to identify quality problems in their data. To make the task for both stakeholders easier, we have developed the Dataset Quality Ontology (daQ). daQ is a core vocabulary for representing the results of quality benchmarking of a linked dataset. It represents quality metadata as multi-dimensional and statistical observations
arXiv:1408.2468v1
fatcat:7c6ggwpvkbhzhmjrrdiixi3jxm