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Introduction

In the era of big data, one of the major challenges faced by researchers and organizations is the interoperability of knowledge across different domains and systems. Linked data has emerged as a powerful tool that can address this challenge by providing a standardized way to represent and connect data on the web. By linking related data together, linked data enables users to navigate and explore information in a more efficient and effective manner.

Background of Study

The concept of linked data was first introduced by Tim Berners-Lee, the inventor of the World Wide Web, in a seminal article published in 2006. Since then, linked data has gained traction in various domains such as healthcare, government, and academia. Linked data is based on the principles of the Semantic Web, which aims to make web content more understandable to machines and humans alike.

Problem Statement

Despite the potential benefits of linked data, there are still challenges that need to be addressed in order to fully realize its potential. One of the key challenges is the lack of standardized methodologies and tools for representing and querying linked data. Additionally, there is a need for more research on the practical applications of linked data in real-world scenarios.

Objective of Study

The main objective of this thesis is to explore the use of linked data for interoperable knowledge across different domains. Specifically, the study aims to investigate how linked data can be used to facilitate the integration and sharing of knowledge in a more seamless and efficient manner.

Limitation of Study

This study is limited to a theoretical analysis of the use of linked data for interoperable knowledge. Practical implementation and evaluation of linked data systems are beyond the scope of this thesis.

Scope of Study

The study will focus on the theoretical foundations of linked data, including its principles, standards, and best practices. The research will also investigate case studies and examples of linked data applications in various domains.

Significance of Study

This study is significant as it aims to contribute to the existing body of knowledge on linked data and its potential applications in different domains. The findings of this research can help inform future research and practice in the field of linked data and interoperable knowledge.

Structure of the Thesis

Chapter 1: Introduction
1.1 Introduction
1.2 Background of study
1.3 Problem Statement
1.4 Objective of study
1.5 Limitation of study
1.6 Scope of study
1.7 Significance of study
1.8 Structure of the Thesis
1.9 Definition of Terms

Chapter 2: Literature Review
2.1 Overview of Linked Data
2.2 Principles of Linked Data
2.3 Standards for Linked Data
2.4 Linked Data and the Semantic Web
2.5 Linked Data Applications
2.6 Challenges of Linked Data
2.7 Best Practices for Linked Data
2.8 Case Studies of Linked Data
2.9 Future Trends in Linked Data
2.10 Gaps in Existing Literature

Chapter 3: System Design and Methodology
3.1 Research Design
3.2 Data Collection Methods
3.3 Data Analysis Techniques
3.4 Implementation of Linked Data System
3.5 Evaluation of Linked Data System
3.6 Methodological Framework
3.7 Case Study Selection
3.8 Ethical Considerations

Chapter 4: System Implementation
4.1 System Architecture
4.2 Data Modeling
4.3 Ontologies and Vocabularies
4.4 Data Integration Techniques
4.5 Querying Linked Data
4.6 Data Visualization
4.7 Performance Optimization
4.8 Scalability and Flexibility

Chapter 5: Conclusion and Summary
5.1 Summary of Findings
5.2 Contributions to Knowledge
5.3 Implications for Practice
5.4 Recommendations for Future Research
5.5 Conclusion

Thesis Overview: Linked Data for Interoperable Knowledge

In this thesis, the use of linked data for interoperable knowledge is explored, with a focus on its potential applications in different domains. The study examines the theoretical foundations of linked data, including its principles, standards, and best practices. Case studies and examples of linked data applications are also investigated to understand its practical implications. The findings of this research will contribute to the existing body of knowledge on linked data and inform future research and practice in the field.

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