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Real-time Linked Dataspaces

Overview of attention for book
Cover of 'Real-time Linked Dataspaces'

Table of Contents

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    Book Overview
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    Chapter 1 Real-time Linked Dataspaces: A Data Platform for Intelligent Systems Within Internet of Things-Based Smart Environments
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    Chapter 2 Enabling Knowledge Flows in an Intelligent Systems Data Ecosystem
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    Chapter 3 Dataspaces: Fundamentals, Principles, and Techniques
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    Chapter 4 Fundamentals of Real-time Linked Dataspaces
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    Chapter 5 Data Support Services for Real-time Linked Dataspaces
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    Chapter 6 Catalog and Entity Management Service for Internet of Things-Based Smart Environments
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    Chapter 7 Querying and Searching Heterogeneous Knowledge Graphs in Real-time Linked Dataspaces
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    Chapter 8 Enhancing the Discovery of Internet of Things-Based Data Services in Real-time Linked Dataspaces
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    Chapter 9 Human-in-the-Loop Tasks for Data Management, Citizen Sensing, and Actuation in Smart Environments
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    Chapter 10 Stream and Event Processing Services for Real-time Linked Dataspaces
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    Chapter 11 Quality of Service-Aware Complex Event Service Composition in Real-time Linked Dataspaces
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    Chapter 12 Dissemination of Internet of Things Streams in a Real-time Linked Dataspace
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    Chapter 13 Approximate Semantic Event Processing in Real-time Linked Dataspaces
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    Chapter 14 Enabling Intelligent Systems, Applications, and Analytics for Smart Environments Using Real-time Linked Dataspaces
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    Chapter 15 Autonomic Source Selection for Real-time Predictive Analytics Using the Internet of Things and Open Data
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    Chapter 16 Building Internet of Things-Enabled Digital Twins and Intelligent Applications Using a Real-time Linked Dataspace
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    Chapter 17 A Model for Internet of Things Enhanced User Experience in Smart Environments
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    Chapter 18 Future Research Directions for Dataspaces, Data Ecosystems, and Intelligent Systems
Overall attention for this book and its chapters
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Mentioned by

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14 tweeters

Citations

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9 Dimensions

Readers on

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47 Mendeley
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Title
Real-time Linked Dataspaces
Published by
Springer International Publishing, October 2019
DOI 10.1007/978-3-030-29665-0
ISBNs
978-3-03-029664-3, 978-3-03-029665-0
Authors

Curry, Edward

Twitter Demographics

The data shown below were collected from the profiles of 14 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 47 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 12 26%
Student > Bachelor 8 17%
Researcher 8 17%
Student > Ph. D. Student 5 11%
Student > Doctoral Student 4 9%
Other 4 9%
Unknown 6 13%
Readers by discipline Count As %
Computer Science 20 43%
Engineering 6 13%
Social Sciences 3 6%
Agricultural and Biological Sciences 3 6%
Business, Management and Accounting 3 6%
Other 6 13%
Unknown 6 13%