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David Herron - One of the best experts on this subject based on the ideXlab platform.

  • function point analysis measurement practices for successful software projects
    2000
    Co-Authors: David Garmus, David Herron
    Abstract:

    Foreword. Preface. Introduction. Basic Counting Rules. Advanced Counting. Preparing for Certification. What's Different? Software Measurement. Function Points and the Executive. Function Point Utilization. Automation. Industry Benchmarking Data. The International Function Point Users Group. About the Authors. 1. Software Measurement. Introduction. The Need for Software Measurement. Basic Software Measurement Elements. Software Measurement Model: Quantitative and Qualitative Elements. World-Class Measurement Program. Entry Level. Basic Level. Industry Leader Level. World-Class Level. Establishing a World-Class Measurement Program. Discovery Phase. Gap Analysis Phase. Summary. 2. Executive Introduction to Function Points. Introduction. Historical Perspective. Balanced Scorecard. Return on Investment. Unit of Work. Function Points. Defining Value. Time to Market. Accountability. Summary. 3. Measuring with Function Points. Introduction. Function Points in the Lifecycle. Function Point Measures. Productivity. Quality. Financial. Maintenance. Using Function Point Measurement Data Effectively. Developing a Measurement Profile. Available Industry Comparisons. Summary. 4. Using Function Points Effectively. Introduction. Project Manager Level: Estimating Software Projects. Using Function Points. IT Management Level: Establishing Performance Benchmarks. Industry Best Practices. Organization Level: Establishing Service-Level Measures. Project and Application Outsourcing. Maintenance Outsourcing. AD/M Outsourcing. Summary. 5. Software Industry Benchmark Data. Introduction. How IT Is Using Industry Data. Benchmarking. Concerns with Industry Data. Representativeness. Consistency. Standard Definitions. What Role Do Function Points Play? Sources of Industry Data. The Gartner Group. META Group. Rubin Systems, Inc. Software Productivity Research. ISBSG. Compass America. The David Consulting Group. The Benchmarking Exchange. Hackett Benchmarking & Research. Hope for the Future. Summary. 6. Introduction to Function Point Analysis. Introduction. The Function Point Counting Process. The Process Used to Size Function Points. Types of Counts. Identifying the Counting Scope and the Application Boundary. Summary. 7. Sizing Data Functions. Introduction. Data Functions. Internal Logical Files. External Interface Files. Complexity and Contribution: ILFs and EIFs. An Example of Counting ILFs and EIFs. Summary. 8. Sizing Transactional Functions. Introduction. Transactional Functions. External Inputs. Complexity and Contribution: EIs. An Example of Counting EIs. External Outputs. Complexity and Contribution: EOs. An Example of Counting EOs. External Inquiries. Complexity and Contribution: EQs. An Example of Counting EQs. Summary. 9. GENERAL SYSTEM CHARACTERISTICS. Introduction. The Process. General System Characteristics. 1. Data Communications. 2. Distributed Data Processing. 3. Performance. 4. Heavily Used Configuration. 5. Transaction Rate. 6. Online Data Entry. 7. End User Efficiency. 8. Online Update. 9. Complex Processing. 10. Reusability. 11. Installation Ease. 12. Operational Ease. 13. Multiple Sites. 14. Facilitate Change. Value Adjustment Factor. Summary. 10. Calculating and Applying Function Points. Introduction. Final Adjusted Function Point Count. Counting a Catalog Business: An Example. Function Point Calculations and Formulas. Development Project Function Point Count. Enhancement Project Function Point Count. Application Function Point Count. Summary. 11. Case Studies in Counting. Introduction. Three Case Studies. Problem A. Problem B. Problem C. Answers to the Three Case Studies. A Short Case Study in Project Management. The Problem. Answers. A Function Point Counting Exercise in Early Definition. The Problem. Answers. 12. Counting Advanced Technologies. Introduction. Object-Oriented Analysis. Client-Server Applications. Application Boundary. Data Functions. Technical Features. Transactional Functions. Web-Based Applications. Application Boundary. Functionality of Web-Based Applications. Data Warehouse Applications. Functionality of Data Warehouse Applications. Concerns about Productivity Rates for Data Warehouse Applications. Query/Report Generators. Data Functionality. Transactional Functionality. Summary. 13. Counting a GUI Application. Introduction. Counting GUI Functionality. GUI Counting Guidelines. Exercise in Counting a GUI System. 1. Determine the Type of Function Point Count. 2. Identify the Counting Scope and the Application Boundary. 3 and 4. Identify All Data and Transactional Functions and Their Complexity. 5. Determine the Unadjusted Function Point Count. 6. Determine the Value Adjustment Factor. 7. Calculate the Final Adjusted Function Point Count. 14. Counting an Object-Oriented Application. Introduction. Functional Description of Personnel Query Service. Starting Personnel Query Service. Query. Update. Create. Delete. Add and Delete Title, Location, and Organization Records. Add and Delete an Employee's Picture. Exit. Object Model for Personnel Query Service. System Diagram for Personnel Query Service. Function Point Analysis for Personnel Query Service. 15. Tools. Introduction. Basic Tool Selection Criteria. Selecting a Function Point Repository Tool. Selecting a Project-Estimating Tool. Conducting a Proof of Concept. 1. Identification of the Current Estimating Problem. 2. Definition of the Deliverable. 3. Process and Tool Selection. 4. Project Selection. 5. Review of the Estimating Process with the Project Managers. 6. Sizing and Complexity Analysis. 7. Identification of Project Variables. 8. Analysis of the Data. 9. Review of the Estimate. 10. Assessment of the Process. Summary. 16. Preparing for the CFPs Exam. Practice Certified Function Point Specialist Exam. Part I. Part II. Part III. Answer Sheets. Answer Sheet: Part I. Answer Sheet: Part II. Answer Sheet: Part III. Appendix A: Project Profile Worksheet. Appendix B: Project Profile Worksheet Guidelines. Appendix C: Complexity Factors Project Worksheet. Appendix D: Sample Project Analysis. Appendix E: Frequently Asked Questions (FAQs). Appendix F: Answers to the CFPS Practice Exam. Answers to the CFPS Practice Exam. Bibliography. Index. 0201699443T04062001

  • function point analysis measurement practices for successful software projects
    2000
    Co-Authors: David Garmus, David Herron
    Abstract:

    Foreword. Preface. Introduction. Basic Counting Rules. Advanced Counting. Preparing for Certification. What's Different? Software Measurement. Function Points and the Executive. Function Point Utilization. Automation. Industry Benchmarking Data. The International Function Point Users Group. About the Authors. 1. Software Measurement. Introduction. The Need for Software Measurement. Basic Software Measurement Elements. Software Measurement Model: Quantitative and Qualitative Elements. World-Class Measurement Program. Entry Level. Basic Level. Industry Leader Level. World-Class Level. Establishing a World-Class Measurement Program. Discovery Phase. Gap Analysis Phase. Summary. 2. Executive Introduction to Function Points. Introduction. Historical Perspective. Balanced Scorecard. Return on Investment. Unit of Work. Function Points. Defining Value. Time to Market. Accountability. Summary. 3. Measuring with Function Points. Introduction. Function Points in the Lifecycle. Function Point Measures. Productivity. Quality. Financial. Maintenance. Using Function Point Measurement Data Effectively. Developing a Measurement Profile. Available Industry Comparisons. Summary. 4. Using Function Points Effectively. Introduction. Project Manager Level: Estimating Software Projects. Using Function Points. IT Management Level: Establishing Performance Benchmarks. Industry Best Practices. Organization Level: Establishing Service-Level Measures. Project and Application Outsourcing. Maintenance Outsourcing. AD/M Outsourcing. Summary. 5. Software Industry Benchmark Data. Introduction. How IT Is Using Industry Data. Benchmarking. Concerns with Industry Data. Representativeness. Consistency. Standard Definitions. What Role Do Function Points Play? Sources of Industry Data. The Gartner Group. META Group. Rubin Systems, Inc. Software Productivity Research. ISBSG. Compass America. The David Consulting Group. The Benchmarking Exchange. Hackett Benchmarking & Research. Hope for the Future. Summary. 6. Introduction to Function Point Analysis. Introduction. The Function Point Counting Process. The Process Used to Size Function Points. Types of Counts. Identifying the Counting Scope and the Application Boundary. Summary. 7. Sizing Data Functions. Introduction. Data Functions. Internal Logical Files. External Interface Files. Complexity and Contribution: ILFs and EIFs. An Example of Counting ILFs and EIFs. Summary. 8. Sizing Transactional Functions. Introduction. Transactional Functions. External Inputs. Complexity and Contribution: EIs. An Example of Counting EIs. External Outputs. Complexity and Contribution: EOs. An Example of Counting EOs. External Inquiries. Complexity and Contribution: EQs. An Example of Counting EQs. Summary. 9. GENERAL SYSTEM CHARACTERISTICS. Introduction. The Process. General System Characteristics. 1. Data Communications. 2. Distributed Data Processing. 3. Performance. 4. Heavily Used Configuration. 5. Transaction Rate. 6. Online Data Entry. 7. End User Efficiency. 8. Online Update. 9. Complex Processing. 10. Reusability. 11. Installation Ease. 12. Operational Ease. 13. Multiple Sites. 14. Facilitate Change. Value Adjustment Factor. Summary. 10. Calculating and Applying Function Points. Introduction. Final Adjusted Function Point Count. Counting a Catalog Business: An Example. Function Point Calculations and Formulas. Development Project Function Point Count. Enhancement Project Function Point Count. Application Function Point Count. Summary. 11. Case Studies in Counting. Introduction. Three Case Studies. Problem A. Problem B. Problem C. Answers to the Three Case Studies. A Short Case Study in Project Management. The Problem. Answers. A Function Point Counting Exercise in Early Definition. The Problem. Answers. 12. Counting Advanced Technologies. Introduction. Object-Oriented Analysis. Client-Server Applications. Application Boundary. Data Functions. Technical Features. Transactional Functions. Web-Based Applications. Application Boundary. Functionality of Web-Based Applications. Data Warehouse Applications. Functionality of Data Warehouse Applications. Concerns about Productivity Rates for Data Warehouse Applications. Query/Report Generators. Data Functionality. Transactional Functionality. Summary. 13. Counting a GUI Application. Introduction. Counting GUI Functionality. GUI Counting Guidelines. Exercise in Counting a GUI System. 1. Determine the Type of Function Point Count. 2. Identify the Counting Scope and the Application Boundary. 3 and 4. Identify All Data and Transactional Functions and Their Complexity. 5. Determine the Unadjusted Function Point Count. 6. Determine the Value Adjustment Factor. 7. Calculate the Final Adjusted Function Point Count. 14. Counting an Object-Oriented Application. Introduction. Functional Description of Personnel Query Service. Starting Personnel Query Service. Query. Update. Create. Delete. Add and Delete Title, Location, and Organization Records. Add and Delete an Employee's Picture. Exit. Object Model for Personnel Query Service. System Diagram for Personnel Query Service. Function Point Analysis for Personnel Query Service. 15. Tools. Introduction. Basic Tool Selection Criteria. Selecting a Function Point Repository Tool. Selecting a Project-Estimating Tool. Conducting a Proof of Concept. 1. Identification of the Current Estimating Problem. 2. Definition of the Deliverable. 3. Process and Tool Selection. 4. Project Selection. 5. Review of the Estimating Process with the Project Managers. 6. Sizing and Complexity Analysis. 7. Identification of Project Variables. 8. Analysis of the Data. 9. Review of the Estimate. 10. Assessment of the Process. Summary. 16. Preparing for the CFPs Exam. Practice Certified Function Point Specialist Exam. Part I. Part II. Part III. Answer Sheets. Answer Sheet: Part I. Answer Sheet: Part II. Answer Sheet: Part III. Appendix A: Project Profile Worksheet. Appendix B: Project Profile Worksheet Guidelines. Appendix C: Complexity Factors Project Worksheet. Appendix D: Sample Project Analysis. Appendix E: Frequently Asked Questions (FAQs). Appendix F: Answers to the CFPS Practice Exam. Answers to the CFPS Practice Exam. Bibliography. Index. 0201699443T04062001

David Garmus - One of the best experts on this subject based on the ideXlab platform.

  • function point analysis measurement practices for successful software projects
    2000
    Co-Authors: David Garmus, David Herron
    Abstract:

    Foreword. Preface. Introduction. Basic Counting Rules. Advanced Counting. Preparing for Certification. What's Different? Software Measurement. Function Points and the Executive. Function Point Utilization. Automation. Industry Benchmarking Data. The International Function Point Users Group. About the Authors. 1. Software Measurement. Introduction. The Need for Software Measurement. Basic Software Measurement Elements. Software Measurement Model: Quantitative and Qualitative Elements. World-Class Measurement Program. Entry Level. Basic Level. Industry Leader Level. World-Class Level. Establishing a World-Class Measurement Program. Discovery Phase. Gap Analysis Phase. Summary. 2. Executive Introduction to Function Points. Introduction. Historical Perspective. Balanced Scorecard. Return on Investment. Unit of Work. Function Points. Defining Value. Time to Market. Accountability. Summary. 3. Measuring with Function Points. Introduction. Function Points in the Lifecycle. Function Point Measures. Productivity. Quality. Financial. Maintenance. Using Function Point Measurement Data Effectively. Developing a Measurement Profile. Available Industry Comparisons. Summary. 4. Using Function Points Effectively. Introduction. Project Manager Level: Estimating Software Projects. Using Function Points. IT Management Level: Establishing Performance Benchmarks. Industry Best Practices. Organization Level: Establishing Service-Level Measures. Project and Application Outsourcing. Maintenance Outsourcing. AD/M Outsourcing. Summary. 5. Software Industry Benchmark Data. Introduction. How IT Is Using Industry Data. Benchmarking. Concerns with Industry Data. Representativeness. Consistency. Standard Definitions. What Role Do Function Points Play? Sources of Industry Data. The Gartner Group. META Group. Rubin Systems, Inc. Software Productivity Research. ISBSG. Compass America. The David Consulting Group. The Benchmarking Exchange. Hackett Benchmarking & Research. Hope for the Future. Summary. 6. Introduction to Function Point Analysis. Introduction. The Function Point Counting Process. The Process Used to Size Function Points. Types of Counts. Identifying the Counting Scope and the Application Boundary. Summary. 7. Sizing Data Functions. Introduction. Data Functions. Internal Logical Files. External Interface Files. Complexity and Contribution: ILFs and EIFs. An Example of Counting ILFs and EIFs. Summary. 8. Sizing Transactional Functions. Introduction. Transactional Functions. External Inputs. Complexity and Contribution: EIs. An Example of Counting EIs. External Outputs. Complexity and Contribution: EOs. An Example of Counting EOs. External Inquiries. Complexity and Contribution: EQs. An Example of Counting EQs. Summary. 9. GENERAL SYSTEM CHARACTERISTICS. Introduction. The Process. General System Characteristics. 1. Data Communications. 2. Distributed Data Processing. 3. Performance. 4. Heavily Used Configuration. 5. Transaction Rate. 6. Online Data Entry. 7. End User Efficiency. 8. Online Update. 9. Complex Processing. 10. Reusability. 11. Installation Ease. 12. Operational Ease. 13. Multiple Sites. 14. Facilitate Change. Value Adjustment Factor. Summary. 10. Calculating and Applying Function Points. Introduction. Final Adjusted Function Point Count. Counting a Catalog Business: An Example. Function Point Calculations and Formulas. Development Project Function Point Count. Enhancement Project Function Point Count. Application Function Point Count. Summary. 11. Case Studies in Counting. Introduction. Three Case Studies. Problem A. Problem B. Problem C. Answers to the Three Case Studies. A Short Case Study in Project Management. The Problem. Answers. A Function Point Counting Exercise in Early Definition. The Problem. Answers. 12. Counting Advanced Technologies. Introduction. Object-Oriented Analysis. Client-Server Applications. Application Boundary. Data Functions. Technical Features. Transactional Functions. Web-Based Applications. Application Boundary. Functionality of Web-Based Applications. Data Warehouse Applications. Functionality of Data Warehouse Applications. Concerns about Productivity Rates for Data Warehouse Applications. Query/Report Generators. Data Functionality. Transactional Functionality. Summary. 13. Counting a GUI Application. Introduction. Counting GUI Functionality. GUI Counting Guidelines. Exercise in Counting a GUI System. 1. Determine the Type of Function Point Count. 2. Identify the Counting Scope and the Application Boundary. 3 and 4. Identify All Data and Transactional Functions and Their Complexity. 5. Determine the Unadjusted Function Point Count. 6. Determine the Value Adjustment Factor. 7. Calculate the Final Adjusted Function Point Count. 14. Counting an Object-Oriented Application. Introduction. Functional Description of Personnel Query Service. Starting Personnel Query Service. Query. Update. Create. Delete. Add and Delete Title, Location, and Organization Records. Add and Delete an Employee's Picture. Exit. Object Model for Personnel Query Service. System Diagram for Personnel Query Service. Function Point Analysis for Personnel Query Service. 15. Tools. Introduction. Basic Tool Selection Criteria. Selecting a Function Point Repository Tool. Selecting a Project-Estimating Tool. Conducting a Proof of Concept. 1. Identification of the Current Estimating Problem. 2. Definition of the Deliverable. 3. Process and Tool Selection. 4. Project Selection. 5. Review of the Estimating Process with the Project Managers. 6. Sizing and Complexity Analysis. 7. Identification of Project Variables. 8. Analysis of the Data. 9. Review of the Estimate. 10. Assessment of the Process. Summary. 16. Preparing for the CFPs Exam. Practice Certified Function Point Specialist Exam. Part I. Part II. Part III. Answer Sheets. Answer Sheet: Part I. Answer Sheet: Part II. Answer Sheet: Part III. Appendix A: Project Profile Worksheet. Appendix B: Project Profile Worksheet Guidelines. Appendix C: Complexity Factors Project Worksheet. Appendix D: Sample Project Analysis. Appendix E: Frequently Asked Questions (FAQs). Appendix F: Answers to the CFPS Practice Exam. Answers to the CFPS Practice Exam. Bibliography. Index. 0201699443T04062001

  • function point analysis measurement practices for successful software projects
    2000
    Co-Authors: David Garmus, David Herron
    Abstract:

    Foreword. Preface. Introduction. Basic Counting Rules. Advanced Counting. Preparing for Certification. What's Different? Software Measurement. Function Points and the Executive. Function Point Utilization. Automation. Industry Benchmarking Data. The International Function Point Users Group. About the Authors. 1. Software Measurement. Introduction. The Need for Software Measurement. Basic Software Measurement Elements. Software Measurement Model: Quantitative and Qualitative Elements. World-Class Measurement Program. Entry Level. Basic Level. Industry Leader Level. World-Class Level. Establishing a World-Class Measurement Program. Discovery Phase. Gap Analysis Phase. Summary. 2. Executive Introduction to Function Points. Introduction. Historical Perspective. Balanced Scorecard. Return on Investment. Unit of Work. Function Points. Defining Value. Time to Market. Accountability. Summary. 3. Measuring with Function Points. Introduction. Function Points in the Lifecycle. Function Point Measures. Productivity. Quality. Financial. Maintenance. Using Function Point Measurement Data Effectively. Developing a Measurement Profile. Available Industry Comparisons. Summary. 4. Using Function Points Effectively. Introduction. Project Manager Level: Estimating Software Projects. Using Function Points. IT Management Level: Establishing Performance Benchmarks. Industry Best Practices. Organization Level: Establishing Service-Level Measures. Project and Application Outsourcing. Maintenance Outsourcing. AD/M Outsourcing. Summary. 5. Software Industry Benchmark Data. Introduction. How IT Is Using Industry Data. Benchmarking. Concerns with Industry Data. Representativeness. Consistency. Standard Definitions. What Role Do Function Points Play? Sources of Industry Data. The Gartner Group. META Group. Rubin Systems, Inc. Software Productivity Research. ISBSG. Compass America. The David Consulting Group. The Benchmarking Exchange. Hackett Benchmarking & Research. Hope for the Future. Summary. 6. Introduction to Function Point Analysis. Introduction. The Function Point Counting Process. The Process Used to Size Function Points. Types of Counts. Identifying the Counting Scope and the Application Boundary. Summary. 7. Sizing Data Functions. Introduction. Data Functions. Internal Logical Files. External Interface Files. Complexity and Contribution: ILFs and EIFs. An Example of Counting ILFs and EIFs. Summary. 8. Sizing Transactional Functions. Introduction. Transactional Functions. External Inputs. Complexity and Contribution: EIs. An Example of Counting EIs. External Outputs. Complexity and Contribution: EOs. An Example of Counting EOs. External Inquiries. Complexity and Contribution: EQs. An Example of Counting EQs. Summary. 9. GENERAL SYSTEM CHARACTERISTICS. Introduction. The Process. General System Characteristics. 1. Data Communications. 2. Distributed Data Processing. 3. Performance. 4. Heavily Used Configuration. 5. Transaction Rate. 6. Online Data Entry. 7. End User Efficiency. 8. Online Update. 9. Complex Processing. 10. Reusability. 11. Installation Ease. 12. Operational Ease. 13. Multiple Sites. 14. Facilitate Change. Value Adjustment Factor. Summary. 10. Calculating and Applying Function Points. Introduction. Final Adjusted Function Point Count. Counting a Catalog Business: An Example. Function Point Calculations and Formulas. Development Project Function Point Count. Enhancement Project Function Point Count. Application Function Point Count. Summary. 11. Case Studies in Counting. Introduction. Three Case Studies. Problem A. Problem B. Problem C. Answers to the Three Case Studies. A Short Case Study in Project Management. The Problem. Answers. A Function Point Counting Exercise in Early Definition. The Problem. Answers. 12. Counting Advanced Technologies. Introduction. Object-Oriented Analysis. Client-Server Applications. Application Boundary. Data Functions. Technical Features. Transactional Functions. Web-Based Applications. Application Boundary. Functionality of Web-Based Applications. Data Warehouse Applications. Functionality of Data Warehouse Applications. Concerns about Productivity Rates for Data Warehouse Applications. Query/Report Generators. Data Functionality. Transactional Functionality. Summary. 13. Counting a GUI Application. Introduction. Counting GUI Functionality. GUI Counting Guidelines. Exercise in Counting a GUI System. 1. Determine the Type of Function Point Count. 2. Identify the Counting Scope and the Application Boundary. 3 and 4. Identify All Data and Transactional Functions and Their Complexity. 5. Determine the Unadjusted Function Point Count. 6. Determine the Value Adjustment Factor. 7. Calculate the Final Adjusted Function Point Count. 14. Counting an Object-Oriented Application. Introduction. Functional Description of Personnel Query Service. Starting Personnel Query Service. Query. Update. Create. Delete. Add and Delete Title, Location, and Organization Records. Add and Delete an Employee's Picture. Exit. Object Model for Personnel Query Service. System Diagram for Personnel Query Service. Function Point Analysis for Personnel Query Service. 15. Tools. Introduction. Basic Tool Selection Criteria. Selecting a Function Point Repository Tool. Selecting a Project-Estimating Tool. Conducting a Proof of Concept. 1. Identification of the Current Estimating Problem. 2. Definition of the Deliverable. 3. Process and Tool Selection. 4. Project Selection. 5. Review of the Estimating Process with the Project Managers. 6. Sizing and Complexity Analysis. 7. Identification of Project Variables. 8. Analysis of the Data. 9. Review of the Estimate. 10. Assessment of the Process. Summary. 16. Preparing for the CFPs Exam. Practice Certified Function Point Specialist Exam. Part I. Part II. Part III. Answer Sheets. Answer Sheet: Part I. Answer Sheet: Part II. Answer Sheet: Part III. Appendix A: Project Profile Worksheet. Appendix B: Project Profile Worksheet Guidelines. Appendix C: Complexity Factors Project Worksheet. Appendix D: Sample Project Analysis. Appendix E: Frequently Asked Questions (FAQs). Appendix F: Answers to the CFPS Practice Exam. Answers to the CFPS Practice Exam. Bibliography. Index. 0201699443T04062001

Wolfgang Karl - One of the best experts on this subject based on the ideXlab platform.

  • Scientific cloud computing: Early Definition and experience
    2008
    Co-Authors: Lizhe Wang, Alvaro Canales Castellanos, Marcel Kunze, Miriam Kunze, David Kramer, Jie Tao, Wolfgang Karl
    Abstract:

    Cloud computing emerges as a new computing paradigm which aims to provide reliable, customized and QoS guaranteed computing dynamic environments for end-users. This paper reviews recent advances of Cloud computing, identifies the concepts and characters of scientific Clouds, and finally presents an example of scientific Cloud for data centers

Elena M Bennett - One of the best experts on this subject based on the ideXlab platform.

  • key features for more successful place based sustainability research on social ecological systems a programme on ecosystem change and society pecs perspective
    2017
    Co-Authors: Patricia Balvanera, Tim M Daw, Toby A Gardner, Berta Martinlopez, Albert V Norstrom, Chinwe Ifejika Speranza, Marja Spierenburg, Elena M Bennett
    Abstract:

    The emerging discipline of sustainability science is focused explicitly on the dynamic interactions between nature and society and is committed to research that spans multiple scales and can support transitions toward greater sustainability. Because a growing body of place-based social-ecological sustainability research (PBSESR) has emerged in recent decades, there is a growing need to understand better how to maximize the effectiveness of this work. The Programme on Ecosystem Change and Society (PECS) provides a unique opportunity for synthesizing insights gained from this research community on key features that may contribute to the relative success of PBSESR. We surveyed the leaders of PECS-affiliated projects using a combination of open, closed, and semistructured questions to identify which features of a research project are perceived to contribute to successful research design and implementation. We assessed six types of research features: problem orientation, research team, and contextual, conceptual, methodological, and evaluative features. We examined the desirable and undesirable aspects of each feature, the enabling factors and obstacles associated with project implementation, and asked respondents to assess the performance of their own projects in relation to these features. Responses were obtained from 25 projects working in 42 social-ecological study cases within 25 countries. Factors that contribute to the overall success of PBSESR included: explicitly addressing integrated social-ecological systems; a focus on solution- and transformation-oriented research; adaptation of studies to their local context; trusted, long-term, and frequent engagement with stakeholders and partners; and an Early Definition of the purpose and scope of research. Factors that hindered the success of PBSESR included: the complexities inherent to social-ecological systems, the imposition of particular epistemologies and methods on the wider research group, the need for long periods of time to initiate and conduct this kind of research, and power asymmetries both within the research team and among stakeholders. In the self-assessment exercise, performance relating to team and context-related features was ranked higher than performance relating to methodological, evaluation, and problem orientation features. We discuss how these insights are relevant for balancing place-based and global perspectives in sustainability science, fostering more rapid progress toward inter- and transdisciplinary integration, redefining and measuring the success of PBSESR, and facing the challenges of academic and research funding institutions. These results highlight the valuable opportunity that the PECS community provides in helping build a community of practice for PBSESR.

Chinwe Ifejika Speranza - One of the best experts on this subject based on the ideXlab platform.

  • key features for more successful place based sustainability research on social ecological systems a programme on ecosystem change and society pecs perspective
    2017
    Co-Authors: Patricia Balvanera, Tim M Daw, Toby A Gardner, Berta Martinlopez, Albert V Norstrom, Chinwe Ifejika Speranza, Marja Spierenburg, Elena M Bennett
    Abstract:

    The emerging discipline of sustainability science is focused explicitly on the dynamic interactions between nature and society and is committed to research that spans multiple scales and can support transitions toward greater sustainability. Because a growing body of place-based social-ecological sustainability research (PBSESR) has emerged in recent decades, there is a growing need to understand better how to maximize the effectiveness of this work. The Programme on Ecosystem Change and Society (PECS) provides a unique opportunity for synthesizing insights gained from this research community on key features that may contribute to the relative success of PBSESR. We surveyed the leaders of PECS-affiliated projects using a combination of open, closed, and semistructured questions to identify which features of a research project are perceived to contribute to successful research design and implementation. We assessed six types of research features: problem orientation, research team, and contextual, conceptual, methodological, and evaluative features. We examined the desirable and undesirable aspects of each feature, the enabling factors and obstacles associated with project implementation, and asked respondents to assess the performance of their own projects in relation to these features. Responses were obtained from 25 projects working in 42 social-ecological study cases within 25 countries. Factors that contribute to the overall success of PBSESR included: explicitly addressing integrated social-ecological systems; a focus on solution- and transformation-oriented research; adaptation of studies to their local context; trusted, long-term, and frequent engagement with stakeholders and partners; and an Early Definition of the purpose and scope of research. Factors that hindered the success of PBSESR included: the complexities inherent to social-ecological systems, the imposition of particular epistemologies and methods on the wider research group, the need for long periods of time to initiate and conduct this kind of research, and power asymmetries both within the research team and among stakeholders. In the self-assessment exercise, performance relating to team and context-related features was ranked higher than performance relating to methodological, evaluation, and problem orientation features. We discuss how these insights are relevant for balancing place-based and global perspectives in sustainability science, fostering more rapid progress toward inter- and transdisciplinary integration, redefining and measuring the success of PBSESR, and facing the challenges of academic and research funding institutions. These results highlight the valuable opportunity that the PECS community provides in helping build a community of practice for PBSESR.