Development Research in Practice

Page 176

offer a subscription feature with useful extensions and various sharing permissions, and some offer free-to-use versions with basic tools that are sufficient for a broad variety of applications, up to and including writing a complete academic paper with coauthors. Cloud-based implementations of LaTeX have several advantageous features for teams compared to classic desktop installations. First, because they are hosted completely online, they avoid the inevitable troubleshooting required to set up a LaTeX installation on various personal computers run by different members of a team. Second, they typically maintain a single, continuously synced copy of the document so that different writers do not create conflicted or out-of-sync copies or need to deal with Git themselves to maintain that sync. Third, they typically allow collaborators to edit documents simultaneously, although different services vary the number of collaborators and documents allowed at each subscription tier. Fourth, some implementations provide a “rich text” editor that behaves similarly to familiar tools like Word, so that collaborators can write text directly into the document without worrying too much about the underlying LaTeX coding. Cloud services usually offer a convenient selection of templates so it is easy to start a project and see results right away without knowing a lot of the code that controls document formatting. Cloud-based implementations of LaTeX also have disadvantages. Some up-front learning is still required, except when using the rich text editor. Continuous access to the internet is necessary, and updating figures and tables may require a file upload that can be tough to automate. Although some services offer ways to track changes and even to integrate a Git workflow, version control is not as straightforward as using Git locally. Finally, cloud-based services also vary dramatically in their ability to integrate with file systems that store code and code outputs, and it is necessary to practice an integrated workflow depending on what is available. Some teams adopt cloud-based tools as a permanent solution, although DIME recommends shifting eventually to local editing and compiling using tools such as TexStudio, while using Git for version control. See box 7.2 for the workflow adopted by the Demand for Safe Spaces team.

BOX 7.2 PUBLISHING RESEARCH PAPERS AND REPORTS: A CASE STUDY FROM THE DEMAND FOR SAFE SPACES PROJECT The Demand for Safe Spaces project produced a policy brief and a working paper, among other outputs. The policy brief was produced in accordance with the DIME communications protocols. For its ­production, the graphs exported by R and Stata were saved in .eps format and shared with a designer who

adapted them to fit DIME’s visual identity. The research paper was written in LaTeX through the Overleaf platform and was published as World Bank Policy Research Working Paper 9269 (Kondylis et al. 2020).

(Box continues on next page)

156

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