Learning Big Data Analytics with SlideWiki

On 17-18 September 2018, the Kick-off meeting for the LAMBDA project (Learning, Applying, Multiplying Big Data Analytics) was held in Belgrade, Serbia. The project aims at developing a set of new learning materials in Big Data Analytics domain and sharing the lectures via the SlideWiki.org platform.

The SlideWiki platform has been selected based on its collaborative features that will significantly improve the collaborative work and creation and maintenance of training materials for teachers and researchers from the University of Oxford (UK), the University of Bonn (Germany), the Fraunhofer Institute for Intelligent Analysis and Information Systems (Germany) and the Institute Mihajlo Pupin (Serbia).

The following Modules will be available via the SlideWiki platform by the end of 2019:

 

Module 1 – Enterprise Knowledge Graphs: LAMBDA training materials will include formal conceptual frameworks for designing and maintaining knowledge graphs; such as strategies for the semi-automatic construction of such graphs from the combination of proprietary enterprise data and relevant public domain knowledge; opportunities and implications in terms of performance and access control.

 

Module 2 – Semantic Big Data Architectures: LAMBDA training materials will include approaches for better supporting the variety dimension of Big Data comprising RDF, RDF-Schema and OWL knowledge representation formalisms, mapping standards such as R2RML, JSON-LD and CSVW, the SPARQL query language etc. Integrating semantic and Big Data technologies can help making Big Data architectures and applications more flexible, adaptive and their implementation more efficient.

 

Module 3 – Smart Data Analytics: LAMBDA training materials will include different algorithms and tools related to Distributed Semantic Analytics, Semantic Question Answering, Structured Machine Learning, Deep Learning, Software Engineering for Data Science, Semantic Data Management, Knowledge Extraction and Validation

For more info, please check the LAMBDA Website.

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