Linked Open Data Creating Knowledge Out of Interlinked Data Results of the LOD2 Project 1st edition by Sören Auer, Volha Bryl, Sebastian Tramp ISBN 3319098454 ‎ 978-3319098456

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ISBN 10: 3319098454
ISBN 13: ‎ 978-3319098456
Author: Sören Auer, Volha Bryl, Sebastian Tramp

Linked Open Data (LOD) is a pragmatic approach for realizing the Semantic Web vision of making the Web a global, distributed, semantics-based information system. This book presents an overview on the results of the research project “LOD2 — Creating Knowledge out of Interlinked Data”. LOD2 is a large-scale integrating project co-funded by the European Commission within the FP7 Information and Communication Technologies Work Program. Commencing in September 2010, this 4-year project comprised leading Linked Open Data research groups, companies, and service providers from across 11 European countries and South Korea. The aim of this project was to advance the state-of-the-art in research and development in four key areas relevant for Linked Data, namely 1. RDF data management; 2. the extraction, creation, and enrichment of structured RDF data; 3. the interlinking and fusion of Linked Data from different sources and 4. the authoring, exploration and visualization of Linked Data.

Linked Open Data – Creating Knowledge Out of Interlinked Data Results of the LOD2 Project 1st Table of contents:

Part I: Introduction to Linked Open Data

Chapter 1: Introduction to Linked Open Data (LOD)

• Overview of Linked Open Data principles and best practices

• Historical development of LOD and key milestones

• Importance of interlinking data for open access and knowledge creation

Chapter 2: The LOD2 Project: Vision and Objectives

• Goals and outcomes of the LOD2 project

• Role of LOD2 in advancing open data research

• Stakeholders involved in the project

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Part II: Technical Foundations

Chapter 3: Linked Data Technologies

• RDF (Resource Description Framework)

• SPARQL query language

• OWL (Web Ontology Language) and reasoning mechanisms

Chapter 4: Data Modeling and Metadata for LOD

• Best practices for modeling data using RDF

• Metadata standards and interoperability

• Schema.org and other data modeling vocabularies

Chapter 5: Data Provenance and Quality in Linked Data

• Techniques for tracking data lineage and ensuring quality

• Ensuring trustworthiness in open linked datasets

• Tools for provenance tracking and validation

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Part III: Building Linked Open Data Systems

Chapter 6: Infrastructure for Linked Open Data

• Key components of LOD infrastructure (e.g., data storage, triplestore databases)

• Scalability and performance optimization for large datasets

• Design considerations for LOD platforms

Chapter 7: Tools and Technologies for LOD Publishing

• Software tools for converting datasets to Linked Data

• Publishing and sharing open data: Best practices

• Case studies of successful LOD implementations

Chapter 8: Linking Datasets Across Domains

• Approaches to linking data across different domains (e.g., government, science, business)

• Data integration challenges and solutions

• Standardization efforts (e.g., DBpedia, Wikidata)

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Part IV: Applications and Use Cases

Chapter 9: Semantic Web and Knowledge Graphs

• Connecting LOD to the broader semantic web

• Use of knowledge graphs for enhanced search, recommendations, and data insights

• Examples from industry and academia

Chapter 10: LOD in Specific Domains

• Applications of LOD in healthcare, science, government, etc.

• Domain-specific vocabularies and ontologies

• Real-world case studies and success stories

Chapter 11: Enhancing Data Accessibility and Interoperability

• Making LOD more accessible for end users

• Ensuring that datasets are reusable and understandable by non-experts

• Data visualization techniques for LOD

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Part V: Challenges and Future Directions

Chapter 12: Challenges in Implementing Linked Open Data

• Technical challenges in data interlinking and consistency

• Organizational and policy barriers to adopting LOD

• Legal and privacy issues in sharing linked data

Chapter 13: The Future of Linked Open Data

• Evolving standards and technologies in LOD

• The impact of AI and machine learning on data linking

• Potential areas for further research and development

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Appendices

• A. Glossary of Terms

• B. List of Tools and Resources

• C. Index

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