Part I: Fundamentals and Concepts
- Introduction
- Foundations
- Intelligent Systems
- Smart Environments
- Internet of Things
- Data Ecosystems
- Enabling Data Ecosystem for Intelligent Systems
- Real-time Linked Dataspaces
- Book Overview
- Summary
Chapter 2: Enabling Knowledge Flows in an Intelligent Systems Data Ecosystem
- Introduction
- Foundations
- Intelligent Systems Data Ecosystem
- System of Systems
- From Deterministic to Probabilistic Decisions in Intelligent Systems
- Digital Twins
- Knowledge Exchange between Open Intelligent Systems in Dynamic Environments
- Knowledge Value Ecosystem (KVE) Framework
- Knowledge: Transfer and Translation
- Entity-centric Data Integration
- Linked Data
- Knowledge Graphs
- Smart Environment Example
- Value: Continuous and Shared
- Value Disciplines
- Data Network Effects
- Ecosystem: Governance and Collaboration
- From Ecology and Business to Data
- The Web of Data: A Global Data Ecosystem
- Ecosystem Coordination
- Data Ecosystem Design
- Iterative Boundary Process: Pay-as-you-go
- Dataspace Incremental Data Management
- Data Platforms for Intelligent Systems within IoT-based Smart Environment
- FAIR Data Principles
- Requirements Analysis
- Summary
Chapter 3: Dataspaces: Fundamentals, Principles, and Techniques
- Introduction
- Big Data and The Long Tail of Data
- The Changing Cost of Data Management
- Approximate, Best-Effort, and “Good Enough” Information
- Fundamentals of Dataspaces
- Definition and Principles
- Comparison to Existing Approaches
- Dataspace Support Platform
- Support Services
- Life Cycle
- Implementations
- Dataspace Technical Challenges
- Query Answering
- Introspection
- Reusing Human Attention
- Dataspace Research Challenges
- Summary
Chapter 4: Real-time Linked Dataspaces: Fundamentals, Principles, and Techniques
- Introduction
- Event and Stream Processing for the Internet of Things
- Timeliness and Real-time Processing
- Fundamentals of Real-time Linked Dataspaces
- Foundations
- Definition and Principles
- Comparison of Dataspaces
- Architecture
- A Principled Approach to Pay-as-you-go Data Management
- TBL’s Five Star Data
- 5 Star Pay-as-you-go Model for Dataspace Services
- Support Platform
- Data Services
- Stream and Event Processing Services
- Suitability as a Data Platform for Intelligent Systems within IoT-based Smart Environments
- Common Data Platform Requirements
- Related Work
- Summary
Part II: Data Support Services
Chapter 5: Data Support Services for Real-time Linked Dataspaces
- Introduction
- Pay-as-you-go Data Support Services for Real-time Linked Dataspaces
- 5 Star Pay-as-you-go Levels for Data Services
- Summary
Chapter 6: Catalog and Entity Management Service for Internet of Things-based Smart Environments
- Introduction
- Working with Entity Data
- Catalog and Entity Service Requirements for Real-time Linked Dataspaces
- Real-time Linked Dataspaces
- Requirements
- Analysis of Existing Data Catalogs
- Catalog Service
- Pay-as-you-go Service Levels
- Entity Management Service
- Pay-as-you-go Service Levels
- Entity Example
- Access Control Service
- Pay-as-you-go Service Levels
- Joining the Real-time Linked Dataspace
- Summary
Chapter 7: Querying and Searching Heterogeneous Knowledge Graphs in Real-time Linked Dataspaces
- Introduction
- Querying and Searching in Real-time Linked Dataspaces
- Real-time Linked Dataspaces
- Knowledge Graphs
- Searching vs Querying
- Search and Query Service Pay-as-you-go Service Levels
- Search and Query over Heterogeneous Data
- Data Heterogeneity
- Motivational Scenario
- Core Requirements for Search and Query
- State-of-the-Art Analysis
- Information Retrieval Approaches
- Natural Language Approaches
- Discussion
- Design Features for Schema-agnostic Queries
- Summary
- Introduction
- Discovery of Data Services in Real-time Linked Dataspaces
- Real-time Linked Dataspaces
- Data Service Discovery
- Semantic Approaches for Service Discovery
- Inheritance Between OWL-S Services
- Topic Extraction and Formal Concept Analysis
- Reasoning-based Matching
- Numerical Encoding of Ontological Concepts
- Discussion
- Formal Concept Analysis for Organizing IoT Data Service Descriptions
- IoT-based Smart Environment Use Case
- Conclusions and Future Work
- Introduction
- The Wisdom of the Crowds
- Crowdsourcing Platform
- Challenges of Enabling Crowdsourcing
- Approaches to Human-in-the-Loop
- Augmented Algorithms & Operators
- Declarative Programming
- Generalised Standalone Platforms
- Comparison of Existing Approaches
- Human Task Service for Real-time Linked Dataspaces
- Real-time Linked Dataspaces
- Human Task Service
- Pay-as-you-go Service Levels
- Applications of Human Task Service
- Data Processing Pipeline
- Task Data Model for Micro-Tasks and Users
- Spatial Task Assignment in Smart Environments
- Summary
Part III: Stream and Event Processing Services
Chapter 10: Stream and Event Processing Services for Real-time Linked Dataspaces
- Introduction
- Pay-as-you-go Services for Event and Stream Processing for Real-time Linked Dataspaces
- Entity-centric Real-time Query Service
- Lambda Architecture
- Entity-centric Real-time Query Service
- Pay-as-you-go Service Levels
- Service Performance
- Summary
- Introduction
- Complex Event Processing in Real-time Linked Dataspaces
- Real-time Linked Dataspaces
- Complex Event Processing
- CEP Service Design
- Pay-as-you-go Service Levels
- Event Service Life Cycle
- QoS Model and Aggregation Schema
- QoS Properties of Event Services
- QoS Aggregation and Utility Function
- Event QoS Utility Function
- Genetic Algorithm for QoS-Aware Event Service Composition Optimisation
- Population Initialisation
- Genetic Encodings for Concrete Composition Plans
- Crossover and Mutation Operations
- Evaluation
- Part 1: Performance of the Genetic Algorithm
- Part 2: Validation of QoS Aggregation Rules
- Related Work
- QoS-aware Service Composition
- On-demand Event/Stream Processing
- Summary and Future work
Chapter 12: Dissemination of Internet of Things Streams in a Real-time Linked Dataspace
- Introduction
- Internet of Things: A Dataspace Perspective
- Real-time Linked Dataspaces
- Stream Dissemination Service
- Pay-as-you-go Service Levels
- Point-to-Point Linked Data Stream Dissemination
- TP-automata for Pattern Matching
- Linked Data Stream Dissemination via Wireless Broadcast
- The Mapping between Triples and 3D Points
- 3D Hilbert Curve Index
- Experimental Evaluation
- Evaluation of Point-to-point Linked Stream Dissemination
- Evaluation on Linked Stream Dissemination via Wireless Broadcast
- Related Work
- Matching
- Wireless Broadcast
- Summary and Future Work
Chapter 13: Approximate Semantic Event Processing in Real-time Linked Dataspaces
- Introduction
- Approximate Event Matching in Real-time Linked Dataspaces
- Real-time Linked Dataspaces
- Event Processing
- The Approximate Semantic Matching Service
- Pay-as-you-go Service Levels
- Semantic Matching Models
- Model I- The Approximate Event Matching Model
- Model II- The Thematic Event Matching Model
- Elements for Approximate Semantic Matching of Events
- Elm 1- Sub-symbolic Distributional Event Semantics
- Elm 2- Free Event Tagging
- Elm 3- Approximation
- Elements within the Event Flow Functional Model
- Instantiation
- Events
- Subscriptions
- Matching
- Evaluation and Discussion
- Evaluation of the Approximate Semantic Event Matching Model
- Evaluation of the Thematic Event Matching Model
- State-of-the-art Analysis
- Summary and Future Work
Part IV: Intelligent Systems and Applications
- Introduction
- Intelligent Energy and Water Management
- Real-time Linked Dataspaces
- Smart Environment Pilot Deployments
- Smart Airport (Linate, Milan)
- Smart Office (Galway, Ireland)
- Smart Homes (Municipality of Thermi, Greece)
- Mixed Use (Galway, Ireland)
- Smart School (Galway, Ireland)
- Target Users Groups
- Enabling Intelligent Systems, Applications, and Analytics for Smart Environments
- Summary
- Introduction
- Source Selection for Analytics in Dataspaces
- Real-time Linked Dataspaces
- Internet of Things Source Selection Challenges
- Autonomic Source Selection Service for Real-time Predictive Analytics
- Autonomic Source Selection
- Architecture
- Prediction Models
- Autonomic Source Selection Workflow
- 4 Step Workflow
- Re-selection Triggers
- Evaluation within Intelligent Systems
- Wind Farm Energy Prediction (Belgium)
- Building Energy Prediction (Galway, Ireland)
- Summary
- Introduction
- Digital Twins and Intelligent Applications with a Real-time Linked Dataspace
- Real-time Linked Dataspaces
- Digital Twins
- The OODA Loop
- Enabling OODA for Digital Twins and Intelligent Applications
- Observation
- Orientation
- Decision
- Action
- Smart Energy and Water Pilot Results
- Energy and Water Savings
- Human Task Service Evaluation
- Experiences and Lessons Learnt
- Summary
Chapter 17: A Model for Internet of Things Enhanced User Experience in Smart Environments
- Introduction
- A Model for Internet of Things Enhanced User Experience
- Digitalisation: IoT and Big Data
- Human-Computer Interaction: IoT-enhanced User Experience and Behavioural Models
- An IoT-enhanced Journey for Smart Energy and Water
- Digital: Real-time Linked Dataspace
- HCI: A User’s Journey to Sustainability using the Transtheoretical Model
- TTM Intelligent Applications
- Promotional Homepage
- Dashboard Tour
- Sense Dashboard
- User Study
- Methodology
- Impact
- Insights and Experience Gained
- Summary
Part V: Future Directions
Chapter 18: Future Research Directions for Dataspaces, Data Ecosystems, and Intelligent Systems
- Introduction
- Dataspaces: From Proof-of-concept to Widespread Adoption
- Research Directions
- Large-scale Decentralised Support Services
- Multimedia/Knowledge-Intensive Event Processing
- Trusted Data Sharing
- Ecosystem Governance and Economic Models
- Incremental Intelligent Systems Engineering: Cognitive Adaptability
- Towards Human-centric Systems
- Summary