Profiling the Web of Data.
Anja Jentzsch · 2014
Abstract. The Web of Data contains a large number of openly-available datasets covering a wide variety of topics. In order to benefit from this massive amount of open data such external datasets must be analyzed and understood already at the basic level of data types, constraints, value patterns, etc. For Linked Datasets such meta information is currently very limited or not available at all. Data profiling techniques are needed to compute re-spective statistics and meta information. However, current state of the art approaches can either not be applied to Linked Data, or exhibit considerable performance problems. This paper presents my doctoral re-search which tackles these problems. 1 Problem Statement Over the past years, an increasingly large number of data sources has been pub-lished as part of the Web of Data1. At the time of writing the Web of Data comprised already roughly 1,000 datasets totaling more than 82 billion triples2,