Development Research in Practice

Page 180

BOX 7.3 PUBLISHING RESEARCH DATA SETS: A CASE STUDY FROM THE DEMAND FOR SAFE SPACES PROJECT The final analysis data sets used in the Demand for Safe Spaces working paper were published in the World Bank’s Microdata Catalog under survey ID number BRA_2015-2016_DSS_v01_M. Three separate data sets in Stata format are present: one with the platform survey data, one with riders’ observations, and one with supplemental crowding information. The entry also contains extensive documentation, including a study description, a list of the staff involved in data collection, all questionnaires used to collect data present in the analysis data set, outputs produced using the data, survey protocols, ethics protocols, and a data dictionary. Access is licensed, so anyone who is interested in downloading the data needs to request access to them, and the data are made available only after the authors approve this request. However, even without downloading the data, users can explore the distribution of each variable. The entry includes a template citation to be used whenever the data are referenced. Finally, a clear and transparent version-control system allows viewers to see when the data were first published and when they were last modified. See the Microdata Catalog entry at https://microdatalib.worldbank​ .org/index.php/catalog/11600.

Once a platform has been chosen, it is time to determine exactly what data will be published. As mentioned earlier, there are typically two types of data releases for a research project: complete (de-identified) original data sets and derivative data sets used for specific research outputs. Whether the original data set can be published depends on data ownership and licensing agreements. If the data were acquired through a survey that was contracted by the research team, the data most likely belong to the research team, and therefore the team has publication rights to both the original and the derivative data. If data were acquired from a partner through a licensing agreement, the terms of the license will determine publication rights. These data sets should match the survey instrument or source documentation as closely as possible and should not include indicators constructed by the research team. Releasing constructed data is often more straightforward; depending on data licensing, researchers who do not have rights to publish the original data may be able to publish derivative data sets prepared by the research team. These data sets usually contain only the constructed indicators and associated documentation and should also be included in the replication package. When data are published, how they may be used and what license will be assigned to them have to be determined. It is essential to understand the rights associated with any data release and to communicate them to future users. Material without a license may never be reused. It is best to offer a license that is explicit and details whether and how specific individuals may access the data. Terms of use available in the World Bank Microdata Catalog include, in order of increasing restrictiveness: open access, direct access, and licensed access. Open access data are freely available to anyone and simply require attribution. Direct access data are available to registered users who agree to use the data for statistical and scientific research purposes only, to cite the data appropriately, and not to 160

DEVELOPMENT RESEARCH IN PRACTICE: THE DIME ANALYTICS DATA HANDBOOK


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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
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