3D Data Creation to Curation : Community Standards for 3D Data Preservation |
Autore | Moore Jennifer |
Pubbl/distr/stampa | Chicago, IL : , : Association of College & Research Libraries, , 2022 |
Descrizione fisica | 1 online resource (331 pages) |
Disciplina | 005.72 |
Altri autori (Persone) |
RountreyAdam
KettlerHannah Scates |
Soggetto topico | Data curation |
ISBN | 0-8389-3914-7 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910886172703321 |
Moore Jennifer
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Chicago, IL : , : Association of College & Research Libraries, , 2022 | ||
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Lo trovi qui: Univ. Federico II | ||
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The data librarian's handbook / / Robin Rice and John Southall [[electronic resource]] |
Autore | Rice Robin (Robin Charlotte), <1965-> |
Pubbl/distr/stampa | London : , : Facet, , 2016 |
Descrizione fisica | 1 online resource (xiii, 177 pages) : digital, PDF file(s) |
Disciplina | 025.00285 |
Soggetto topico |
Data curation
Data curation in libraries Data libraries Database management |
ISBN | 1-78330-183-X |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Data librarianship: responding to research innovation -- What is different about data? -- Supporting data literacy -- Building a data collection -- Research data management service and policy: working across your institution -- Data management plans as a calling card -- Essentials of data repositories -- Dealing with sensitive data -- Data sharing in the disciplines -- Supporting open scholarship and open science. |
Record Nr. | UNINA-9910792635703321 |
Rice Robin (Robin Charlotte), <1965->
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London : , : Facet, , 2016 | ||
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Lo trovi qui: Univ. Federico II | ||
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The data librarian's handbook / / Robin Rice and John Southall [[electronic resource]] |
Autore | Rice Robin (Robin Charlotte), <1965-> |
Pubbl/distr/stampa | London : , : Facet, , 2016 |
Descrizione fisica | 1 online resource (xiii, 177 pages) : digital, PDF file(s) |
Disciplina | 025.00285 |
Soggetto topico |
Data curation
Data curation in libraries Data libraries Database management |
ISBN | 1-78330-183-X |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Data librarianship: responding to research innovation -- What is different about data? -- Supporting data literacy -- Building a data collection -- Research data management service and policy: working across your institution -- Data management plans as a calling card -- Essentials of data repositories -- Dealing with sensitive data -- Data sharing in the disciplines -- Supporting open scholarship and open science. |
Record Nr. | UNINA-9910827549703321 |
Rice Robin (Robin Charlotte), <1965->
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London : , : Facet, , 2016 | ||
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Lo trovi qui: Univ. Federico II | ||
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Databrarianship : the academic data librarian in theory and practice / / edited by Lynda Kellam and Kristi Thompson |
Pubbl/distr/stampa | Chicago, Illinois : , : Association of College and Research Libraries, a division of the American Library Association, , 2016 |
Descrizione fisica | 1 online resource (387 p.) |
Disciplina | 027.7 |
Soggetto topico |
Academic libraries - Effect of technological innovations on
Academic librarians - Effect of technological innovations on Data curation Data libraries Database management Libraries - Special collections - Electronic information resources |
Soggetto genere / forma | Electronic books. |
ISBN | 0-8389-8800-8 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Table of Contents; Acknowledgments; Introduction; Part I. Data Support Services for Researchers and Learners; Chapter 1. A Studio Model for Academic Data Services; Chapter 2. Embedded Options: A Common Framework; Chapter 3. Data Reference: Strategies for Subject Librarians; Chapter 4. The Data Management Village: Collaboration among Research Support Providers in the Large Academic Environment; Chapter 5. The Data Librarian in the Liberal Arts College; Chapter 6. Teaching Foundational Data Skills in the Library; Chapter 7. Technical Data Skills for Reproducible Research
Chapter 8. Restricted Data Access and LibrariesPart II. Data in the Disciplines; Chapter 9. Supporting Geospatial Data; Chapter 10. From Traditional to Crowd and Cloud: Geospatial Data Services at GMU; Chapter 11. Qualitative Researchand Data Support: The Jan Brady of Social Sciences Data Services?; Chapter 12. Data in the Sciences; Part III. Data Preservation and Access; Chapter 13. Scholarly Communication and Data; Chapter 14. Data Sharing Policies in Social Sciences Academic Journals: Evolving Expectations of Data Sharing as a Form of Scholarly Communication Chapter 15. Selection and Appraisal of Digital Research DatasetsChapter 16. Local Data Success Story: The University of Calgary Library's Ten Years with the City of Calgary; Chapter 17. Metadata for Social Science Data: Collaborative Best Practices; Chapter 18. Exploring Disciplinary Metadata and Documentation Practices to Strengthen Data Archiving Services; Part IV. Data: Past, Present, and Future; Chapter 19. View from Across the Pond: A UK Perspective; Chapter 20. The Academic Data Librarian Profession in Canada: History and Future Directions Chapter 21. Data Librarianship: A Day in the Life-Science EditionChapter 22. Teaching Data Librarianship to LIS Students; Author Biographies |
Record Nr. | UNINA-9910465710503321 |
Chicago, Illinois : , : Association of College and Research Libraries, a division of the American Library Association, , 2016 | ||
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Lo trovi qui: Univ. Federico II | ||
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Databrarianship : the academic data librarian in theory and practice / / edited by Lynda Kellam and Kristi Thompson |
Pubbl/distr/stampa | Chicago, Illinois : , : Association of College and Research Libraries, a division of the American Library Association, , 2016 |
Descrizione fisica | 1 online resource (387 p.) |
Disciplina | 027.7 |
Soggetto topico |
Academic libraries - Effect of technological innovations on
Academic librarians - Effect of technological innovations on Data curation Data libraries Database management Libraries - Special collections - Electronic information resources |
ISBN | 0-8389-8800-8 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Table of Contents; Acknowledgments; Introduction; Part I. Data Support Services for Researchers and Learners; Chapter 1. A Studio Model for Academic Data Services; Chapter 2. Embedded Options: A Common Framework; Chapter 3. Data Reference: Strategies for Subject Librarians; Chapter 4. The Data Management Village: Collaboration among Research Support Providers in the Large Academic Environment; Chapter 5. The Data Librarian in the Liberal Arts College; Chapter 6. Teaching Foundational Data Skills in the Library; Chapter 7. Technical Data Skills for Reproducible Research
Chapter 8. Restricted Data Access and LibrariesPart II. Data in the Disciplines; Chapter 9. Supporting Geospatial Data; Chapter 10. From Traditional to Crowd and Cloud: Geospatial Data Services at GMU; Chapter 11. Qualitative Researchand Data Support: The Jan Brady of Social Sciences Data Services?; Chapter 12. Data in the Sciences; Part III. Data Preservation and Access; Chapter 13. Scholarly Communication and Data; Chapter 14. Data Sharing Policies in Social Sciences Academic Journals: Evolving Expectations of Data Sharing as a Form of Scholarly Communication Chapter 15. Selection and Appraisal of Digital Research DatasetsChapter 16. Local Data Success Story: The University of Calgary Library's Ten Years with the City of Calgary; Chapter 17. Metadata for Social Science Data: Collaborative Best Practices; Chapter 18. Exploring Disciplinary Metadata and Documentation Practices to Strengthen Data Archiving Services; Part IV. Data: Past, Present, and Future; Chapter 19. View from Across the Pond: A UK Perspective; Chapter 20. The Academic Data Librarian Profession in Canada: History and Future Directions Chapter 21. Data Librarianship: A Day in the Life-Science EditionChapter 22. Teaching Data Librarianship to LIS Students; Author Biographies |
Record Nr. | UNINA-9910798301903321 |
Chicago, Illinois : , : Association of College and Research Libraries, a division of the American Library Association, , 2016 | ||
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Lo trovi qui: Univ. Federico II | ||
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Databrarianship : the academic data librarian in theory and practice / / edited by Lynda Kellam and Kristi Thompson |
Pubbl/distr/stampa | Chicago, Illinois : , : Association of College and Research Libraries, a division of the American Library Association, , 2016 |
Descrizione fisica | 1 online resource (387 p.) |
Disciplina | 027.7 |
Soggetto topico |
Academic libraries - Effect of technological innovations on
Academic librarians - Effect of technological innovations on Data curation Data libraries Database management Libraries - Special collections - Electronic information resources |
ISBN | 0-8389-8800-8 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Table of Contents; Acknowledgments; Introduction; Part I. Data Support Services for Researchers and Learners; Chapter 1. A Studio Model for Academic Data Services; Chapter 2. Embedded Options: A Common Framework; Chapter 3. Data Reference: Strategies for Subject Librarians; Chapter 4. The Data Management Village: Collaboration among Research Support Providers in the Large Academic Environment; Chapter 5. The Data Librarian in the Liberal Arts College; Chapter 6. Teaching Foundational Data Skills in the Library; Chapter 7. Technical Data Skills for Reproducible Research
Chapter 8. Restricted Data Access and LibrariesPart II. Data in the Disciplines; Chapter 9. Supporting Geospatial Data; Chapter 10. From Traditional to Crowd and Cloud: Geospatial Data Services at GMU; Chapter 11. Qualitative Researchand Data Support: The Jan Brady of Social Sciences Data Services?; Chapter 12. Data in the Sciences; Part III. Data Preservation and Access; Chapter 13. Scholarly Communication and Data; Chapter 14. Data Sharing Policies in Social Sciences Academic Journals: Evolving Expectations of Data Sharing as a Form of Scholarly Communication Chapter 15. Selection and Appraisal of Digital Research DatasetsChapter 16. Local Data Success Story: The University of Calgary Library's Ten Years with the City of Calgary; Chapter 17. Metadata for Social Science Data: Collaborative Best Practices; Chapter 18. Exploring Disciplinary Metadata and Documentation Practices to Strengthen Data Archiving Services; Part IV. Data: Past, Present, and Future; Chapter 19. View from Across the Pond: A UK Perspective; Chapter 20. The Academic Data Librarian Profession in Canada: History and Future Directions Chapter 21. Data Librarianship: A Day in the Life-Science EditionChapter 22. Teaching Data Librarianship to LIS Students; Author Biographies |
Record Nr. | UNINA-9910810359503321 |
Chicago, Illinois : , : Association of College and Research Libraries, a division of the American Library Association, , 2016 | ||
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Lo trovi qui: Univ. Federico II | ||
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Development research in practice : the DIME analytics data handbook |
Autore | Bjärkefur Kristoffer |
Edizione | [1st ed.] |
Pubbl/distr/stampa | , : World Bank Publications, , 2021 |
Descrizione fisica | 1 online resource (231 pages) |
Disciplina | 658.4038 |
Altri autori (Persone) |
Cardoso de AndradeLuíza
DanielsBenjamin JonesMaria Ruth |
Soggetto topico |
Business - Data processing - Management
Data curation Economic development - Research - Methodology |
ISBN | 1-4648-1695-6 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Front Cover -- Contents -- Foreword -- Acknowledgments -- About the Authors -- Abbreviations -- Introduction -- How to read this book -- The DIME Wiki: A complementary resource -- Standardizing data work -- Standardizing coding practices -- The team behind this book -- Looking ahead -- References -- Chapter 1 Conducting reproducible, transparent, and credible research -- Developing a credible research project -- Conducting research transparently -- Analyzing data reproducibly and preparing a reproducibility package -- Looking ahead -- References -- Chapter 2 Setting the stage for effective and efficient collaboration -- Preparing a collaborative work environment -- Organizing code and data for replicable research -- Preparing to handle confidential data ethically -- Looking ahead -- References -- Chapter 3 Establishing a measurement framework -- Documenting data needs -- Translating research design to data needs -- Creating research design variables by randomization -- Looking ahead -- References -- Chapter 4 Acquiring development data -- Acquiring data ethically and reproducibly -- Collecting high-quality data using electronic surveys -- Handling data securely -- Looking ahead -- References -- Chapter 5 Cleaning and processing research data -- Making data "tidy" -- Implementing data quality checks -- Processing confidential data -- Preparing data for analysis -- Looking ahead -- References -- Chapter 6 Constructing and analyzing research data -- Creating analysis data sets -- Writing analysis code -- Creating reproducible tables and graphs -- Increasing efficiency of analysis with dynamic documents -- Looking ahead -- References -- Chapter 7 Publishing reproducible research outputs -- Publishing research papers and reports -- Preparing research data for publication -- Publishing a reproducible research package -- Looking ahead -- References. Chapter 8 Conclusion -- Bringing it all together -- Where to go from here -- Appendix A: The DIME Analytics Coding Guide -- Appendix B: DIME Analytics resource directory -- Appendix C: Research design for impact evaluation -- Boxes -- Box I.1 The Demand for Safe Spaces case study -- Box 1.1 Summary: Conducting reproducible, transparent, and credible research -- Box 1.2 Registering studies: A case study from the Demand for Safe Spaces project -- Box 1.3 Writing preanalysis plans: A case study from the Demand for Safe Spaces project -- Box 1.4 Preparing a reproducibility package: A case study from the Demand for Safe Spaces project -- Box 2.1 Summary: Setting the stage for effective and efficient collaboration -- Box 2.2 Preparing a collaborative work environment: A case study from the Demand for Safe Spaces project -- Box 2.3 Organizing files and folders: A case study from the Demand for Safe Spaces project -- Box 2.4 DIME master do-file template -- Box 2.5 Writing code that others can read: A case study from the Demand for Safe Spaces project -- Box 2.6 Writing code that others can run: A case study from the Demand for Safe Spaces project -- Box 2.7 Seeking ethical approval: An example from the Demand for Safe Spaces project -- Box 2.8 Obtaining informed consent: A case study from the Demand for Safe Spaces project -- Box 2.9 Ensuring the privacy of research subjects: An example from the Demand for Safe Spaces project -- Box 3.1 Summary: Establishing a measurement framework -- Box 3.2 Developing a data linkage table: An example from the Demand for Safe Spaces project -- Box 3.3 Creating data flowcharts: An example from the Demand for Safe Spaces project -- Box 3.4 An example of uniform-probability random sampling -- Box 3.5 An example of randomized assignment with multiple treatment arms -- Box 3.6 An example of reproducible randomization. Box 4.1 Summary: Acquiring development data -- Box 4.2 Determining data ownership: A case study from the Demand for Safe Spaces project -- Box 4.3 Piloting survey instruments: A case study from the Demand for Safe Spaces project -- Box 4.4 Checking data quality in real time: A case study from the Demand for Safe Spaces project -- Box 5.1 Summary: Cleaning and processing research data -- Box 5.2 Establishing a unique identifier: A case study from the Demand for Safe Spaces project -- Box 5.3 Tidying data: A case study from the Demand for Safe Spaces project -- Box 5.4 Assuring data quality: A case study from the Demand for Safe Spaces project -- Box 5.5 Implementing de-identification: A case study from the Demand for Safe Spaces project -- Box 5.6 Correcting data points: A case study from the Demand for Safe Spaces project -- Box 5.7 Recoding and annotating data: A case study from the Demand for Safe Spaces project -- Box 6.1 Summary: Constructing and analyzing research data -- Box 6.2 Integrating multiple data sources: A case study from the Demand for Safe Spaces project -- Box 6.3 Creating analysis variables: A case study from the Demand for Safe Spaces project -- Box 6.4 Documenting variable construction: A case study from the Demand for Safe Spaces project -- Box 6.5 Writing analysis code: A case study from the Demand for Safe Spaces project -- Box 6.6 Organizing analysis code: A case study from the Demand for Safe Spaces project -- Box 6.7 Visualizing data: A case study from the Demand for Safe Spaces project -- Box 6.8 Managing outputs: A case study from the Demand for Safe Spaces project -- Box 7.1 Summary: Publishing reproducible research outputs -- Box 7.2 Publishing research papers and reports: A case study from the Demand for Safe Spaces project -- Box 7.3 Publishing research data sets: A case study from the Demand for Safe Spaces project. Box 7.4 Releasing a reproducibility package: A case study from the Demand for Safe Spaces project -- Figures -- Figure I.1 Overview of the tasks involved in development research data work -- Figure B2.3.1 Folder structure of the Demand for Safe Spaces data work -- Figure B3.3.1 Flowchart of a project data map -- Figure B4.4.1 A sample dashboard of indicators of progress -- Figure 4.1 Data acquisition tasks and outputs -- Figure 5.1 Data-cleaning tasks and outputs -- Figure 6.1 Data analysis tasks and outputs -- Figure 7.1 Publication tasks and outputs -- Figure 8.1 Research data work outputs. |
Altri titoli varianti | Development Research in Practice |
Record Nr. | UNINA-9910794504303321 |
Bjärkefur Kristoffer
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, : World Bank Publications, , 2021 | ||
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Lo trovi qui: Univ. Federico II | ||
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Development research in practice : the DIME analytics data handbook |
Autore | Bjärkefur Kristoffer |
Edizione | [1st ed.] |
Pubbl/distr/stampa | , : World Bank Publications, , 2021 |
Descrizione fisica | 1 online resource (231 pages) |
Disciplina | 658.4038 |
Altri autori (Persone) |
Cardoso de AndradeLuíza
DanielsBenjamin JonesMaria Ruth |
Soggetto topico |
Business - Data processing - Management
Data curation Economic development - Research - Methodology |
ISBN | 1-4648-1695-6 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Front Cover -- Contents -- Foreword -- Acknowledgments -- About the Authors -- Abbreviations -- Introduction -- How to read this book -- The DIME Wiki: A complementary resource -- Standardizing data work -- Standardizing coding practices -- The team behind this book -- Looking ahead -- References -- Chapter 1 Conducting reproducible, transparent, and credible research -- Developing a credible research project -- Conducting research transparently -- Analyzing data reproducibly and preparing a reproducibility package -- Looking ahead -- References -- Chapter 2 Setting the stage for effective and efficient collaboration -- Preparing a collaborative work environment -- Organizing code and data for replicable research -- Preparing to handle confidential data ethically -- Looking ahead -- References -- Chapter 3 Establishing a measurement framework -- Documenting data needs -- Translating research design to data needs -- Creating research design variables by randomization -- Looking ahead -- References -- Chapter 4 Acquiring development data -- Acquiring data ethically and reproducibly -- Collecting high-quality data using electronic surveys -- Handling data securely -- Looking ahead -- References -- Chapter 5 Cleaning and processing research data -- Making data "tidy" -- Implementing data quality checks -- Processing confidential data -- Preparing data for analysis -- Looking ahead -- References -- Chapter 6 Constructing and analyzing research data -- Creating analysis data sets -- Writing analysis code -- Creating reproducible tables and graphs -- Increasing efficiency of analysis with dynamic documents -- Looking ahead -- References -- Chapter 7 Publishing reproducible research outputs -- Publishing research papers and reports -- Preparing research data for publication -- Publishing a reproducible research package -- Looking ahead -- References. Chapter 8 Conclusion -- Bringing it all together -- Where to go from here -- Appendix A: The DIME Analytics Coding Guide -- Appendix B: DIME Analytics resource directory -- Appendix C: Research design for impact evaluation -- Boxes -- Box I.1 The Demand for Safe Spaces case study -- Box 1.1 Summary: Conducting reproducible, transparent, and credible research -- Box 1.2 Registering studies: A case study from the Demand for Safe Spaces project -- Box 1.3 Writing preanalysis plans: A case study from the Demand for Safe Spaces project -- Box 1.4 Preparing a reproducibility package: A case study from the Demand for Safe Spaces project -- Box 2.1 Summary: Setting the stage for effective and efficient collaboration -- Box 2.2 Preparing a collaborative work environment: A case study from the Demand for Safe Spaces project -- Box 2.3 Organizing files and folders: A case study from the Demand for Safe Spaces project -- Box 2.4 DIME master do-file template -- Box 2.5 Writing code that others can read: A case study from the Demand for Safe Spaces project -- Box 2.6 Writing code that others can run: A case study from the Demand for Safe Spaces project -- Box 2.7 Seeking ethical approval: An example from the Demand for Safe Spaces project -- Box 2.8 Obtaining informed consent: A case study from the Demand for Safe Spaces project -- Box 2.9 Ensuring the privacy of research subjects: An example from the Demand for Safe Spaces project -- Box 3.1 Summary: Establishing a measurement framework -- Box 3.2 Developing a data linkage table: An example from the Demand for Safe Spaces project -- Box 3.3 Creating data flowcharts: An example from the Demand for Safe Spaces project -- Box 3.4 An example of uniform-probability random sampling -- Box 3.5 An example of randomized assignment with multiple treatment arms -- Box 3.6 An example of reproducible randomization. Box 4.1 Summary: Acquiring development data -- Box 4.2 Determining data ownership: A case study from the Demand for Safe Spaces project -- Box 4.3 Piloting survey instruments: A case study from the Demand for Safe Spaces project -- Box 4.4 Checking data quality in real time: A case study from the Demand for Safe Spaces project -- Box 5.1 Summary: Cleaning and processing research data -- Box 5.2 Establishing a unique identifier: A case study from the Demand for Safe Spaces project -- Box 5.3 Tidying data: A case study from the Demand for Safe Spaces project -- Box 5.4 Assuring data quality: A case study from the Demand for Safe Spaces project -- Box 5.5 Implementing de-identification: A case study from the Demand for Safe Spaces project -- Box 5.6 Correcting data points: A case study from the Demand for Safe Spaces project -- Box 5.7 Recoding and annotating data: A case study from the Demand for Safe Spaces project -- Box 6.1 Summary: Constructing and analyzing research data -- Box 6.2 Integrating multiple data sources: A case study from the Demand for Safe Spaces project -- Box 6.3 Creating analysis variables: A case study from the Demand for Safe Spaces project -- Box 6.4 Documenting variable construction: A case study from the Demand for Safe Spaces project -- Box 6.5 Writing analysis code: A case study from the Demand for Safe Spaces project -- Box 6.6 Organizing analysis code: A case study from the Demand for Safe Spaces project -- Box 6.7 Visualizing data: A case study from the Demand for Safe Spaces project -- Box 6.8 Managing outputs: A case study from the Demand for Safe Spaces project -- Box 7.1 Summary: Publishing reproducible research outputs -- Box 7.2 Publishing research papers and reports: A case study from the Demand for Safe Spaces project -- Box 7.3 Publishing research data sets: A case study from the Demand for Safe Spaces project. Box 7.4 Releasing a reproducibility package: A case study from the Demand for Safe Spaces project -- Figures -- Figure I.1 Overview of the tasks involved in development research data work -- Figure B2.3.1 Folder structure of the Demand for Safe Spaces data work -- Figure B3.3.1 Flowchart of a project data map -- Figure B4.4.1 A sample dashboard of indicators of progress -- Figure 4.1 Data acquisition tasks and outputs -- Figure 5.1 Data-cleaning tasks and outputs -- Figure 6.1 Data analysis tasks and outputs -- Figure 7.1 Publication tasks and outputs -- Figure 8.1 Research data work outputs. |
Altri titoli varianti | Development Research in Practice |
Record Nr. | UNINA-9910815166803321 |
Bjärkefur Kristoffer
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, : World Bank Publications, , 2021 | ||
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Lo trovi qui: Univ. Federico II | ||
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Digital library perspectives |
Pubbl/distr/stampa | Bingley, United Kingdom : , : Emerald Group Publishing Limited |
Soggetto topico |
Microcomputers
Libraries - Automation Digital libraries Institutional repositories Data curation Digital preservation |
Soggetto genere / forma | Periodicals. |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Periodico |
Lingua di pubblicazione | eng |
Altri titoli varianti | DLP |
Record Nr. | UNINA-9910149220503321 |
Bingley, United Kingdom : , : Emerald Group Publishing Limited | ||
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Lo trovi qui: Univ. Federico II | ||
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Digital library perspectives |
Pubbl/distr/stampa | Bingley, United Kingdom : , : Emerald Group Publishing Limited |
Soggetto topico |
Microcomputers
Libraries - Automation Digital libraries Institutional repositories Data curation Digital preservation |
Soggetto genere / forma | Periodicals. |
ISSN | 2059-5824 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Periodico |
Lingua di pubblicazione | eng |
Altri titoli varianti | DLP |
Record Nr. | UNISA-996398450103316 |
Bingley, United Kingdom : , : Emerald Group Publishing Limited | ||
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Lo trovi qui: Univ. di Salerno | ||
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