Development Research in Practice

Page 184

GitHub with Zenodo (https://zenodo.org) or the Open Science Framework (OSF; https://osf.io), which can link easily to and import material from GitHub and apply a permanent URL, DOI, formal citation, general license, and archival services to it. Other options include the Harvard Dataverse and ResearchGate (https://www.researchgate.net). Any of the aforementioned archival services is ­acceptable—the main requirement is that the system can handle the ­structured directory being submitted and that it can provide a stable URL for the project and report exactly what, if any, modifications have been made since initial publication. It is even possible to combine more than one tool, as long as the tools clearly reference each other. For example, code and the corresponding license can be published on GitHub, while referring to data published on the World Bank Microdata Catalog. Emerging technologies such as the “containerization” approach of CodeOcean (https://codeocean.com) offer to store both code and data in one repository and also provide an online workspace in which others can execute and modify code without having to download the tools and match the local environment used to create it. In addition to code and data, an author’s copy or preprint of the article itself could be released along with these materials, but it is important to check with the publisher before doing so; not all journals will accept material that has been publicly released before its formal publication date, although, in most development research fields, the release of working papers is a fairly common practice. This release can be done on preprint websites, many of which are topic specific. It is also possible to use GitHub or OSF and link to the PDF file directly through a personal website or whatever medium is sharing the preprint. Using file-sharing services such as Dropbox or Google Drive is not recommended for this purpose, because their access is more restrictive, and organizations often restrict access to such platforms. Finally, any reproducibility package should include an overview of its contents and instructions on how to recreate outputs. Box 7.4 describes how the Demand for Safe Spaces project released its reproducibility package. This overview is typically provided in the form of a README file. A good README file guides the reader through all of the items included in the package. Fortunately, a consortium of social science data editors offers a very good template for such documents, which can be found at https:// doi.org/10.5281/zenodo.4319999.

BOX 7.4 RELEASING A REPRODUCIBILITY PACKAGE: A CASE STUDY FROM THE DEMAND FOR SAFE SPACES PROJECT The reproducibility package for the Demand for Safe Spaces working paper was released on the World Bank’s GitHub. The reproducibility package contains all of the materials necessary for another researcher to access raw materials and reproduce all of the results included with the paper, including a README.md file with instructions for executing the code. Among other things, it provides licensing (Box continues on next page) 164

DEVELOPMENT RESEARCH IN PRACTICE: THE DIME ANALYTICS DATA HANDBOOK


Turn static files into dynamic content formats.

Create a flipbook

Articles inside

Appendix C: Research design for impact evaluation

33min
pages 215-231

Appendix A: The DIME Analytics Coding Guide

24min
pages 195-210

Appendix B: DIME Analytics resource directory

3min
pages 211-214

8.1 Research data work outputs

6min
pages 190-194

Chapter 8: Conclusion

1min
page 189

7.4 Releasing a reproducibility package: A case study from the Demand for Safe Spaces project

3min
pages 184-186

7.1 Summary: Publishing reproducible research outputs

8min
pages 172-175

7.3 Publishing research data sets: A case study from the Demand for Safe Spaces project

10min
pages 180-183

7.2 Publishing research papers and reports: A case study from the Demand for Safe Spaces project

8min
pages 176-179

Chapter 7: Publishing reproducible research outputs

1min
page 171

6.1 Data analysis tasks and outputs

3min
pages 168-170

6.8 Managing outputs: A case study from the Demand for Safe Spaces project

10min
pages 163-167

6.7 Visualizing data: A case study from the Demand for Safe Spaces project

4min
pages 161-162

6.6 Organizing analysis code: A case study from the Demand for Safe Spaces project

4min
pages 159-160

6.5 Writing analysis code: A case study from the Demand for Safe Spaces project

3min
pages 157-158

6.4 Documenting variable construction: A case study from the Demand for Safe Spaces project

4min
pages 155-156

6.3 Creating analysis variables: A case study from the Demand for Safe Spaces project

1min
page 154

6.2 Integrating multiple data sources: A case study from the Demand for Safe Spaces project

9min
pages 150-153

6.1 Summary: Constructing and analyzing research data

10min
pages 146-149

Chapter 6: Constructing and analyzing research data

1min
page 145

5.7 Recoding and annotating data: A case study from the Demand for Safe Spaces project

3min
pages 140-141

5.6 Correcting data points: A case study from the Demand for Safe Spaces project

4min
pages 138-139

5.5 Implementing de-identification: A case study from the Demand for Safe Spaces project

9min
pages 134-137

5.1 Summary: Cleaning and processing research data

7min
pages 122-124

5.4 Assuring data quality: A case study from the Demand for Safe Spaces project

7min
pages 131-133

5.3 Tidying data: A case study from the Demand for Safe Spaces project

7min
pages 128-130

5.2 Establishing a unique identifier: A case study from the Demand for Safe Spaces project

7min
pages 125-127

Chapter 5: Cleaning and processing research data

1min
page 121

B4.4.1 A sample dashboard of indicators of progress

12min
pages 113-117

4.4 Checking data quality in real time: A case study from the Demand for Safe Spaces project

2min
page 112

4.3 Piloting survey instruments: A case study from the Demand for Safe Spaces project

14min
pages 106-111

4.2 Determining data ownership: A case study from the Demand for Safe Spaces project

16min
pages 100-105

B3.3.1 Flowchart of a project data map

37min
pages 81-96

B2.3.1 Folder structure of the Demand for Safe Spaces data work

36min
pages 55-72

Chapter 4: Acquiring development data

5min
pages 97-99

Chapter 3: Establishing a measurement framework

18min
pages 73-80

Chapter 1: Conducting reproducible, transparent, and credible research

35min
pages 31-46

Chapter 2: Setting the stage for effective and efficient collaboration

18min
pages 47-54

I.1 Overview of the tasks involved in development research data work

18min
pages 22-30

Introduction

2min
page 21
Issuu converts static files into: digital portfolios, online yearbooks, online catalogs, digital photo albums and more. Sign up and create your flipbook.
Development Research in Practice by World Bank Publications - Issuu