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 in | Handbook of Smart Cities pp. 875 - 901 |
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Main Author | |
Format | Book Chapter |
Language | English |
Published |
Cham
Springer International Publishing
2021
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Subjects | |
Online Access | Get full text |
ISBN | 9783030696979 3030696979 |
DOI | 10.1007/978-3-030-69698-6_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. |
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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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Copyright | Springer Nature Switzerland AG 2021 |
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DOI | 10.1007/978-3-030-69698-6_48 |
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Editor | Augusto, Juan Carlos |
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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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StartPage | 875 |
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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