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Modeling, Generating, and Publishing Knowledge as Linked Data Read chapter Read first chapter

2017 | OriginalPaper | Chapter

Dealing with Velocity and Variety in the Acquisition of Heterogeneous Sensor Data

Author : Luca Ferrari

Published in: Knowledge Engineering and Knowledge Management

Publisher: Springer International Publishing

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Abstract

ETL (Extraction-Transform-Load) tools, traditionally developed to operate offline, need to be enhanced to deal with various, fast, big and fresh data and be executed on the edge of the network during the acquisition process. In this dissertation we wish to develop facilities that from one side make easy, scalable and controllable the development of data acquisition plans that can be executed on the edge of the network during loading and transmission. From the other side, we wish to deal with the variety of the data and verify when the developed data acquisition plans adhere to the common semantics adopted in the Domain Ontology. These facilities are included in StreamLoader, a web application tailored for the specification and monitoring of sensor data acquisition plans.

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previous chapter Photo Archives in Linked Open Data – The Federico Zeri’s Archive Case Study
next chapter Semantic Data Integration for Industry 4.0 Standards
Footnotes
1
Apparent temperature is a value of temperature adjusted with the level of humidity.
 
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Metadata
Title
Dealing with Velocity and Variety in the Acquisition of Heterogeneous Sensor Data
Author
Luca Ferrari
Copyright Year
2017
Book
Knowledge Engineering and Knowledge Management

Print ISBN: 978-3-319-58693-9

Electronic ISBN: 978-3-319-58694-6

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-58694-6_35

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