Interoperability Effect in Big Data

The world is experiencing an explosive data growth, making big data an increasingly important field. Particularly in complex contexts such as smart cities, big data is no longer limited to analytics on large data sets. Small data produced by a large number of devices (Internet of Things) also lead t...

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Published inHandbook of Smart Cities pp. 875 - 901
Main Author Delgado, José
Format Book Chapter
LanguageEnglish
Published Cham Springer International Publishing 2021
Subjects
Online AccessGet full text
ISBN9783030696979
3030696979
DOI10.1007/978-3-030-69698-6_48

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Abstract The world is experiencing an explosive data growth, making big data an increasingly important field. Particularly in complex contexts such as smart cities, big data is no longer limited to analytics on large data sets. Small data produced by a large number of devices (Internet of Things) also lead to large data sets, with the added difficulty that most of these data can be produced, and may need to be processed, in real time. In either case, the interoperability problem (enabling several applications to interact and work together) is one of the hardest challenges to overcome. This chapter characterizes big data, with variety and variability as the most important characteristics for interoperability, and interactions between applications, distinguishing data integration from application interoperability. This chapter also presents two interoperability frameworks, one focusing on architectural issues and the other concerning different abstraction levels of application interaction. Several of the most relevant standards in this area are listed, with a discussion on their limitations and the possible evolution of interoperability, in particular, in big data contexts.
AbstractList The world is experiencing an explosive data growth, making big data an increasingly important field. Particularly in complex contexts such as smart cities, big data is no longer limited to analytics on large data sets. Small data produced by a large number of devices (Internet of Things) also lead to large data sets, with the added difficulty that most of these data can be produced, and may need to be processed, in real time. In either case, the interoperability problem (enabling several applications to interact and work together) is one of the hardest challenges to overcome. This chapter characterizes big data, with variety and variability as the most important characteristics for interoperability, and interactions between applications, distinguishing data integration from application interoperability. This chapter also presents two interoperability frameworks, one focusing on architectural issues and the other concerning different abstraction levels of application interaction. Several of the most relevant standards in this area are listed, with a discussion on their limitations and the possible evolution of interoperability, in particular, in big data contexts.
Author Delgado, José
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Snippet The world is experiencing an explosive data growth, making big data an increasingly important field. Particularly in complex contexts such as smart cities, big...
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SubjectTerms Big data
Compliance
Conformance
Coupling
Integration
Internet of Things
Interoperability
Interoperability frameworks
Schema
Variety
Title Interoperability Effect in Big Data
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