EAN: 9783031007477

SYNTHESIS LECTURES ON DATA MANAGEMENT CLOUD-B...

Resource Description Framework (or RDF  in short) is set to deliver many of the original
semi-structured data promises: flexible structure  optional schema  and rich  flexible
Universal Resource Identifiers as a basis for information sharing. Moreover  RDF is uniquely
positioned to benefit from the efforts of scientific communities studying databases  knowledge
representation  and Web technologies. As a consequence  the RDF data model is used in a variety
of applications today for integrating knowledge and information: in open Web or government data
via the Linked Open Data initiative  in scientific domains such as bioinformatics  and more
recently in search engines and personal assistants of enterprises in the form of knowledge
graphs. Managing such large volumes of RDF data is challenging due to the sheer size 
heterogeneity  and complexity brought by RDF reasoning. To tackle the size challenge 
distributed architectures are required. Cloud computing is an emerging paradigm massively
adopted in many applications requiring distributed architectures for the scalability  fault
tolerance  and elasticity features it provides. At the same time  interest in massively
parallel processing has been renewed by the MapReduce model and many follow-up works  which aim
at simplifying the deployment of massively parallel data management tasks in a cloud
environment. In this book  we study the state-of-the-art RDF data management in cloud
environments and parallel distributed architectures that were not necessarily intended for the
cloud  but can easily be deployed therein. After providing a comprehensive background on RDF
and cloud technologies  we explore four aspects that are vital in an RDF data management
system: data storage  query processing  query optimization  and reasoning. We conclude the book
with a discussion on open problems and future directions.

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