Tackling the Variety Dimension of Big Data - From Linked to Cognitive Data

Speaker:  Sören Auer – Leipzig, Germany
Topic(s):  Information Systems, Search, Information Retrieval, Database Systems, Data Mining, Data Science

Abstract

In recent years, we have seen an increasing attention to data. Some initiatives in this regard are open, big or smart data. The availability of large-scale datasets has unleashed an enormous potential of making computers smarter and gave rise to cognitive computing. In this talk we reflect on this development and give an overview on recent approaches in the areas of Big Data software architectures, data spaces and knowledge graphs, which all help to realize the emerging concept of hybrid AI, where large-scale, rich semantic data and knowledge tightly interacts with machine learning and analytics.

The management and analysis of large-scale datasets - described by the term Big Data - involves the three classic dimensions volume, velocity and variety. While the former two are well supported by a variety of software components, the variety dimension is still rather neglected but crucial for the integration and analysis of heterogeneous enterprise data within a company or along value chains. In this talk we discuss the principles of Enterprise Linked Data and practical approaches for their
implementation using semantic technologies such as the Industrial Data Space, Enterprise Knowledge Graphs or the Administrative Shell for Industry 4.0. We discuss some successful examples in the Supply Chain Management, Industry 4.0 and Cultural Heritage domains.

About this Lecture

Number of Slides:  20 - 90
Duration:  30 - 120 minutes
Languages Available:  English, German
Last Updated: 

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