Linked Data meets Data Science

As a long-term member of the Linked Data community, which has evolved from W3C's Semantic Web, the latest developments around Data Science have become more and more attractive to me due to its complementary perspectives on similar challenges. When taking a closer look to the approaches taken by those two'schools of advanced data management' one aspect becomes obvious: Both try to develop models in order to be able to'codify and to calculate the data soup'. While Linked Data technologies are built on top of knowledge models ('ontologies'), which try to describe first of all data in distributed environments like the web, are Data Science methods mainly based on statistical models. One could say: 'Causality and Reasoning over Distributed Data' meets'Correlation and Machine Learning on Big Data'. In contrast to this supposed contradiction, correlations and complementarities between those two disciplines prevail.