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Managing Big Data Integration in the Public Sector

Book Description

The era of rapidly progressing technology we live in generates vast amounts of data; however, the challenge exists in understanding how to aggressively monitor and make sense of this data. Without a better understanding of how to collect and manage such large data sets, it becomes increasingly difficult to successfully utilize them. Managing Big Data Integration in the Public Sector is a pivotal reference source for the latest scholarly research on the application of big data analytics in government contexts and identifies various strategies in which big data platforms can generate improvements within that sector. Highlighting issues surrounding data management, current models, and real-world applications, this book is ideally designed for professionals, government agencies, researchers, and non-profit organizations interested in the benefits of big data analytics applied in the public sphere.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Book Series
    1. Mission
    2. Coverage
  5. Dedication
  6. Foreword
  7. Preface
    1. WHY THE BOOK?
    2. BOOK AUDIENCE
    3. BOOK STRUCTURE
  8. Acknowledgment
  9. Section 1: Big Data: Issues and Models
    1. Chapter 1: The Interoperability of US Federal Government Information
      1. ABSTRACT
      2. INTRODUCTION
      3. INTEROPERABILITY
      4. INFORMATION POLICY
      5. AUTHORITY-TRACKER MODEL
      6. DATA SOURCES
      7. METHODS
      8. AN EXAMPLE: FINANCIAL CRISIS POLICY
      9. EVALUATION
      10. RESULTS
      11. DISCUSSION
      12. CONCLUSION
      13. ACKNOWLEDGMENT
      14. REFERENCES
    2. Chapter 2: A Hybrid Approach to Big Data Systems Development
      1. ABSTRACT
      2. INTRODUCTION
      3. CONCLUSION
      4. REFERENCES
    3. Chapter 3: Transparency and Enhanced Efficiency and Accountability Due to Big Data Adoption in Government Agencies and Other Enterprises
      1. ABSTRACT
      2. INTRODUCTION
      3. LITERATURE REVIEW
      4. RESEARCH METHODOLOGY
      5. DATA ANALYSIS AND FINDIGS
      6. CONCLUSION AND MANAGEMENT IMPLICATIONS
      7. FUTURE RESEARCH DIRECTIONS
      8. REFERENCES
      9. KEY TERMS AND DEFINITIONS
    4. Chapter 4: Big Data and Cloud Interoperability
      1. ABSTRACT
      2. INTRODUCTION
      3. SUMMARY
      4. REFERENCES
      5. KEY TERMS AND DEFINITIONS
  10. Section 2: Big Data: Management Issues
    1. Chapter 5: How to Engrain a Big Data Mindset into Our Managers' DNA
      1. ABSTRACT
      2. INTRODUCTION
      3. BIG DATA, BIG CHANGE, BIG SKILL SHORTAGE
      4. PRESENTATION OF THE ‘BIG DATA BETTER DECISIONS’ WORKSHOP
      5. LESSONS LEARNT AND BIG DATA INSIGHTS
      6. CONCLUSION
      7. REFERENCES
      8. KEY TERMS AND DEFINITIONS
    2. Chapter 6: Big Data from Management Perspective
      1. ABSTRACT
      2. INTRODUCTION
      3. WHAT IS BIG DATA?
      4. FOUR VS MODEL
      5. APPLICATIONS OF BIG DATA ANALYTICS
      6. BIG DATA: MANAGEMENT CHALLENGES
      7. ETHICAL PERSPECTIVE
      8. CONCLUSION
      9. REFERENCES
      10. ENDNOTES
    3. Chapter 7: Blending Technology, Human Potential, and Organizational Reality
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. MANAGING DATA POWER BY BLENDING IN PEOPLE AND ORGANISATION
      5. SOLUTIONS AND RECOMMENDATIONS
      6. FUTURE RESEARCH DIRECTIONS
      7. CONCLUSION
      8. REFERENCES
      9. KEY TERMS AND DEFINITIONS
      10. ENDNOTES
    4. Chapter 8: On Efficient Acquisition and Recovery Methods for Certain Types of Big Data
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. BIG DATA
      4. 3. EFFICIENT ACQUISITION AND RECOVERY
      5. 4. CONCLUSION
      6. REFERENCES
  11. Section 3: Big Data: Health Care Issues and Applications
    1. Chapter 9: Application of Big Data in Healthcare
      1. ABSTRACT
      2. INTRODUCTION
      3. CONCLUSION
      4. REFERENCES
      5. ENDNOTE
    2. Chapter 10: Big Data Paradigm for Healthcare Sector
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. MAIN FOCUS OF THE CHAPTER
      5. ELECTRONIC HEALTH RECORDS
      6. HEALTH DATA STREAMS
      7. SOURCES OF BIG DATA IN HEALTH CARE
      8. MHEALTH: GENERATING BIG DATA STREAMS
      9. BIG DATA PARADIGM FOR EHRs
      10. MAP-REDUCE MODELLING FOR BIG DATA WORLD
      11. QUERYING BIG DATA WORLD
      12. DATA MINING FOR EHRs
      13. PROPOSED MAP-REDUCE MODELLING FOR CLUSTERING HEALTH DATA STREAMS
      14. SOLUTIONS AND RECOMMENDATIONS
      15. FUTURE RESEARCH DIRECTIONS
      16. CONCLUSION
      17. REFERENCES
      18. KEY TERMS AND DEFINITIONS
    3. Chapter 11: Towards an Intelligent Integrated Approach for Clinical Decision Support
      1. ABSTRACT
      2. INTRODUCTION
      3. DECISION SUPPORT SYSTEM
      4. RESEARCH DIRECTION
      5. CONCLUSION
      6. REFERENCES
      7. KEY TERMS AND DEFINITIONS
  12. Section 4: Big Data: Other Application
    1. Chapter 12: Information Processing for Disaster Communications
      1. ABSTRACT
      2. INTRODUCTION
      3. TRUST ISSUES IN DISASTER COMMUNICATIONS
      4. REPORT ON OUR ACTIVITIES IN IWATE
      5. MISINFORMATION DISSEMINATION IN DISASTER COMMUNICATIONS THROUGH SNS
      6. OFFICE ENVIRONMENTS SUFFERING FROM TSUNAMI
      7. SUPPORT FOR TEMPORAL HOUSING AND RECOVERY HOUSING
      8. OBSERVING RECOVERY PROGRESS WITH LIVE CAMERA
      9. PASSING THE DISASTER THREAT INFORMATION FROM GENERATION TO GENERATION
      10. BIG DATA ISSUES
      11. CONCLUSION
      12. REFERENCES
    2. Chapter 13: Big Data and National Cyber Security Intelligence
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. BIG DATA OPPORTUNITIES FOR NATIONAL CYBER INTELLIGENCE
      4. 3. NATIONAL SECURITY ENVIRONMENT: THREATS OF BIG DATA
      5. 4. EXPLOITING BIG DATA FOR NATIONAL SECURITY - CHALLENGES
      6. 5. BIG DATA ANALYTICS FOR CRITICAL INFRASTRUCTURE PROTECTION (CIP)
      7. 6. TOOLS AND TECHNOLOGIES
      8. 7. EXISTING BIG DATA APPROACHES FOR NATIONAL SECURITY
      9. 8. CONCLUSION AND SUMMARY
      10. REFERENCES
    3. Chapter 14: Big Data Models and the Public Sector
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. BIG DATA MODELS
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
      7. REFERENCES
      8. KEY TERMS AND DEFINITIONS
  13. Section 5: Big Data: Emerging Issues
    1. Chapter 15: Emerging Role of Big Data in Public Sector
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. BIG DATA APPLICATIONS: COMPARISON OF BUSINESSES AND GOVERNMENTS
      4. 3. BIG DATA APPLICATION AREAS IN PUBLIC SECTOR
      5. 4. UNIQUE COMPUTING REQUIREMENTS OF PUBLIC SECTOR
      6. 5. BIG-DATA APPLICATIONS IN LEADING E-GOVERNMENTS
      7. 6. PRACTICAL/MANAGERIAL IMPLICATIONS AND RECOMMENDATIONS
      8. 7. CONCLUSION
      9. REFERENCES
    2. Chapter 16: Opportunities and Challenges of Big Data in Public Sector
      1. ABSTRACT
      2. BIG DATA
      3. BIG DATA DEVELOPMENT PROCESS
      4. CONCLUSION
      5. REFERENCES
  14. Compilation of References
  15. About the Contributors