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<onlyinclude>
The DataWork Survey Round folder is a key component of the [[DataWork Folder|DataWork folder]], DIME's standardized folder template for organizing data work in a project folder. The DataWork Survey Round folder is useful throughout all stages of a project.
This article describes the organization of a Survey Round folder inside the [[DataWork Folder|DataWork folder]] in DIME's standardized template for how to organize a the data work in project folder.
</onlyinclude>
== Subfolders in each Survey Round ==


These are the folders that [[iefolder]] creates inside the survey round folder:
==Read First==
*The Stata command <code>[[iefolder]]</code> creates the DataWork Survey Round folder as a component of the DataWork folder, which is typically housed on [https://www.box.com Box] or [https://www.dropbox.com Dropbox].
*The DataWork Survey Round folder organizes all data-related elements of the project: [[Questionnaire Design | questionnaires]], datasets, do-files, documentation of analysis, graphs, tables, survey logs, etc.
*The DataWork Survey Round folder facilitates efficiency and saves files in a manner understandable both to the current research team and to people visiting the project folder years after the project has ended.
*The DataWork Survey Round folder consists of five sub-folders: the [[DataWork_Survey_Round#DataSets Folder|DataSets folder]], the [[DataWork_Survey_Round#Dofiles Folder|Dofiles folder]], the [[DataWork_Survey_Round#Outputs Folder|Outputs folder]], the [[DataWork_Survey_Round#DataSets Folder|Documentation folder]] and the [[DataWork_Survey_Round#DataSets Folder|Questionnaire folder]].


*[[DataWork_Survey_Round#DataSets Folder|DataSets Folder]]
== Overview ==
*[[DataWork_Survey_Round#Dofiles Folder|Dofiles Folder]]
 
*[[DataWork_Survey_Round#Outputs Folder|Outputs Folder]]
The Survey Round folder contains the following sub-folders: the [[DataWork_Survey_Round#DataSets Folder|DataSets folder]], the [[DataWork_Survey_Round#Dofiles Folder|Dofiles folder]], the [[DataWork_Survey_Round#Outputs Folder|Outputs folder]], the [[DataWork_Survey_Round#DataSets Folder|Documentation folder]] and the [[DataWork_Survey_Round#DataSets Folder|Questionnaire folder]]. The remainder of this page explains each element within the folder.
*[[DataWork_Survey_Round#DataSets Folder|Documentation Folder]]
*[[DataWork_Survey_Round#DataSets Folder|Questionnaire Folder]]


==DataSets Folder ==
==DataSets Folder ==
[[File:FolderDataSets.png |thumb|300px|Image 1. Example of a DataSets folder. (Click to enlarge.)]]
[[File:FolderDataSets.png |thumb|300px|Image 1. Example of a DataSets folder. (Click to enlarge.)]]


The DataSets folder contains three sub-folders: Deidentified, Intermediate and Final (Image 1).   
The DataSets folder contains three sub-folders in which datasets are stored: Deidentified, Intermediate and Final (Image 1).   


Note that it is not recommended to create a folder for raw data in the DataSets folder: raw data almost always includes identifying information and the DataSets folder is not in the [[Encryption | encrypted]] branch of the DataWork folder. Instead, save raw data in the DataWork [[DataWork_Folder#Contents#Survey_Encrypted_Data | Survey Encrypted Data]] folder. The [[DataWork_Survey_Round#Raw_Data|Raw Data]] section describes best practices for raw data in more detail.  
It is not recommended to create a folder for raw datasets in the DataSets folder: raw data almost always includes identifying information and the DataSets folder is not in the [[Encryption | encrypted]] branch of the DataWork folder. Instead, save raw data in the DataWork [[DataWork_Folder#Contents#Survey_Encrypted_Data | Survey Encrypted Data]] folder. The [[DataWork_Survey_Round#Raw_Data|Raw Data]] section describes in more detail best practices for raw data.


=== De-identified Folder ===  
=== De-identified Folder ===  
Once the raw data is [[De-identification|de-identified]], it can be saved in the De-identified folder. Working with the raw, de-identified data rather than raw, encrypted data will make the work flow easier for the entire research team.
The De-identified folder houses [[De-identification|de-identified]] raw data. Working with the raw, de-identified data rather than raw, encrypted data makes the work flow easier and smoother for the entire research team.


=== Intermediate Folder ===  
=== Intermediate Folder ===  
The Intermediate folder is a work-in-progress folder containing all datasets that belong neither in the Raw nor Final folder. Raw datasets on which simple changes have been made belong in the Intermediate folder. There are no specific rules how this folder should be organized. However, it is a good idea to keep it organized in sub-folders and to name files according to efficient [[Naming Conventions|naming conventions]].
The Intermediate folder is a work-in-progress folder containing all datasets that belong neither in the Raw nor Final folder. Raw datasets on which simple changes have been made belong in the Intermediate folder. There are no specific rules how this folder should be organized. However, it is a good idea to keep it organized in sub-folders and to name files according to [[Naming Conventions|naming conventions]].


=== Final Folder ===  
=== Final Folder ===  
The Final folder contains the clean datasets with final variables constructed. This folder should only contain one version of each dataset. If your project has various datasets for different [[Unit of Observation | units of observation]], (i.e. student dataset, school dataset, teacher dataset), then the Final folder should contain a sub-folder for each dataset. The Final folder is the folder most likely to be visited several years after the project has ended by someone with very little knowledge of the project. This folder should therefore be one of the folders organized to the most level of detail.
The Final folder contains the clean datasets with final variables constructed. This folder should only contain one version of each dataset. If your project has various datasets for different [[Unit of Observation | units of observation]], (i.e. student dataset, school dataset, teacher dataset), then the Final folder should contain a sub-folder for each dataset.  
 
The Final folder is the folder most likely to be visited several years after the project has ended by someone with very little knowledge of the project. This folder should therefore be one of the folders organized to the most level of detail.


==Dofiles Folder==
==Dofiles Folder==
[[File:FolderDofiles.png |thumb|300px|Image 2. Example of a DataSets folder. (Click to enlarge.)]]
[[File:FolderDofiles.png |thumb|300px|Image 2. Example of a DataSets folder. (Click to enlarge.)]]
Each Survey Round folder contains a Dofiles folder. The top level of this folder should only contain a [[Master Do-files | master do-file]] and sub-folders. The master do-file maps out all do-files and datasets relevant to this survey round.  
Each Survey Round folder contains a Dofiles folder. The top level of this folder should contain only a [[Master Do-files | master do-file]] and sub-folders. The master do-file maps out all do-files and datasets relevant to this survey round.  


The sub-folders in the Dofiles folder should be organized according to task. For example, ''import'', ''cleaning'', ''analysis''. All do-files related to each of these tasks should be saved in those folders. Make sure to use [[Naming Conventions|naming conventions and version control]] rather than having multiple versions of the same dofile. Each sub-folder should have a task level master do-file.  
The sub-folders in the Dofiles folder should be organized according to task (i.e. ''import'', ''cleaning'', ''analysis''), with the relevant do-files saved within its respective task folder. Each sub-folder should have a task level master do-file. Make sure to use [[Naming Conventions|naming conventions and version control]] when creating and updating these files and folders.  


Task-level do-files have very little technical purpose as the do-files can technically be called from the round master do-file. However, the task-level master do-files are critical for documentation for data work and make it significantly easier for someone unfamiliar with the code to follow the data work.
Task-level master do-files have little technical purpose as the round master do-file can technically call each individual do-file. However, the task-level master do-files document data work and make it significantly easier for someone unfamiliar with the code to understand the process.


== Outputs Folder ==
== Outputs Folder ==


The Outputs folder should also be organized in sub-folders. The necessary sub-folders depend on the output and the method used to output. If, for example, both tables and graphs are outputted, then create Table and Graph sub-folders. Each sub-folder should contain Raw and Formatted folders (i.e. if the tables are exported in .csv format and the data is used as input in the formatted file or if single graphs are outputted to disk and later combined to one graph file with multiple graphs). See best practices of [[Exporting_Analysis|exporting analysis]] for many more relevant recommendations.
The Outputs folder houses the survey round outputs. It consists of sub-folders. The exact sub-folders depend on the output and the method used to create outputs. If, for example, both tables and graphs are outputted, then create Table and Graph sub-folders. Each sub-folder should contain Raw and Formatted folders. For example, if single graphs are outputted to disk and later combined to one cumulative graph file, save the former as Raw and the latter as Formatted. See best practices of [[Exporting_Analysis|exporting analysis]] for additional recommendations.


The Outputs folder is one of the few places where it may be good practice to save multiple versions of the same file: it is common to compare different versions of the analysis, and it is convenient to do so without any version control software or regeneration of an old output. If you save multiple versions of the same file, do not use the naming convention of table_v1, table_v2, etc. Instead, name files by date (i.e. table_Apr30, table_Jun6). If the outputted file size is significant in terms of disk space, do not save multiple versions of the same file. This will soon take up a lot of space on the disk and will make it difficult for people with slow internet connection to access the folder via syncing services like [https://www.dropbox.com| DropBox].
The Outputs folder is one of the few places where it may be good practice to save multiple versions of the same file, since it is common to compare different versions of the analysis. If you save multiple versions of the same file, do not use the naming convention of table_v1, table_v2, etc. Instead, name files by date (i.e. table_Apr30, table_Jun6). If the outputted file size is significant in terms of disk space, do not save multiple versions of the same file: this will make it difficult for people with slow internet connection to access the folder via syncing services like [https://www.dropbox.com| DropBox].


==Documentation Folder==
==Documentation Folder==


This Documentation folder will contain the documentation for the analysis including any duplicate reports, survey logs, etc. While there is no strict format for this folder, it is good practice to save any documentation for this survey round in this folder. This could be include anything from formal documentation to email conversations. You never know what you and your project team will need to know about this round in the future.
This Documentation folder contains documentation for the analysis including any duplicate reports, survey logs, etc. While there is no strict format for this folder, it is good practice to save any documentation for this survey round in this folder. This could include anything from formal documentation to email conversations. You never know what you and your project team will need to know about this round in the future.


== Questionnaire Folder ==
== Questionnaire Folder ==


All documentation related to the [[Primary Data Collection | data collection]] should be gathered in this folder. The most important thing to document is the [[Questionnaire Design | questionnaire]], hence the name of the folder, but it is also important to save any other material that documents the survey, including material from the [[Enumerator Training | enumerator training]], survey manuals used in the field, [[Survey Firm TOR | contract]] with [[Survey Firm | survey firm]], and anything else that provides the project team with a better qualitative understanding of their quantitative data.
The Questionnaire folder contains all documentation related to the [[Primary Data Collection | data collection]]. While [[Questionnaire Design | questionnaire]] is the most important document to include in this folder, it is also important to save any other material that documents the survey. This includes material from the [[Enumerator Training | enumerator training]], survey manuals used in the field, the [[Survey Firm TOR | survey firm TOR]], and anything else that provides the project team with a better qualitative understanding of the data.


== Encrypted Round Folder ==
== Encrypted Round Folder ==
[[File:FolderEncryptedRound.png |thumb|300px|Image 3. Example of a DataSets folder. (Click to enlarge.)]]
[[File:FolderEncryptedRound.png |thumb|300px|Image 3. Example of a DataSets folder. (Click to enlarge.)]]


The Encrypted Round folders are created by [[iefolder]] at the same time as a round folder is created, but they are created in the [[DataWork Folder#Contents#Survey Encrypted Data | encrypted branch]] of DataWork instead of inside the round folder. The [[Encryption | encrypted]] round folders are separated from the other round folders as they are likely to include identifying data.
The Encrypted Round folders are created by [[iefolder]] at the same time as a round folder is created, but they are created in the [[DataWork Folder#Contents#Survey Encrypted Data | encrypted branch]] of DataWork instead of inside the round folder. The [[Encryption | encrypted]] round folders are separated from the other round folders as they likely include identifying data.


===Raw Data===
===Raw Data===
Any data downloaded from the server used to collect data should be saved in the Raw Identified Data folder. This includes data downloaded from the internet, data received from [[Primary Data Collection | data collection]], and data received from other projects.  
Any data downloaded from the server used to collect data should be saved in the Raw Identified Data folder. This includes data downloaded from the internet, data received from [[Primary Data Collection | data collection]], and data received from other projects.  


The data in this folder should be exactly as you got it and absolutely no changes should be made to it. Even simple changes like correcting known errors, changing variable names, changing format, or changing file name changes should never be done to any files in this folder. The only exception to this rule is if the file name needs to be changed to be imported.
The data in this folder should be exactly as you got it: absolutely no changes should be made to it. Even simple changes like correcting known errors, changing variable names, changing format, or changing file names should never be done to any files in this folder. The only exception to this rule is if the file name needs to be changed in order to be imported.


If there are known errors in your raw datasets, import the raw data set, write a do-file that corrects the errors and save the corrected data in the Intermediate folder. The data set in the Raw folder with known errors should remain unaltered. If corrections to the datasets are not [[Reproducible Research | documented]], then the research team will not fully understand the quality of the data nor the quality of our research.
If there are known errors in your raw datasets, import the raw data set, write a do-file that corrects the errors and save the corrected data in the Intermediate folder. The datset in the Raw folder with known errors should remain unaltered. If corrections to the datasets are not properly [[Reproducible Research | documented]], then the research team will not fully understand the quality of neither the data nor the research.


===Import Dofiles===
===Import Dofiles===
The do-files used to import, edit and [[De-identification | de-identify]] the raw data are likely to include identifying information. Therefore, need to keep those files in the Encrypted folder as well.
The do-files used to import, edit and [[De-identification | de-identify]] the raw data likely include identifying information. Therefore, they should be housed in the Encrypted folder as well.


Running these files should import the data, address any immediate issues such as missing [[ID Variable Properties | IDs]] or [[Duplicates and Survey Logs | duplicates]], de-identify it and save the data set in the Intermediate folder, which is nested in the DataSets folder in the unencrypted branch of the DataWork.
Running these do-files files should import the data, address any immediate issues such as missing [[ID Variable Properties | IDs]] or [[Duplicates and Survey Logs | duplicates]], de-identify it and save the data set in the Intermediate folder, which is nested in the DataSets folder in the unencrypted branch of the DataWork.


== Back to Parent ==
== Back to Parent ==

Revision as of 15:02, 15 April 2019

The DataWork Survey Round folder is a key component of the DataWork folder, DIME's standardized folder template for organizing data work in a project folder. The DataWork Survey Round folder is useful throughout all stages of a project.

Read First

  • The Stata command iefolder creates the DataWork Survey Round folder as a component of the DataWork folder, which is typically housed on Box or Dropbox.
  • The DataWork Survey Round folder organizes all data-related elements of the project: questionnaires, datasets, do-files, documentation of analysis, graphs, tables, survey logs, etc.
  • The DataWork Survey Round folder facilitates efficiency and saves files in a manner understandable both to the current research team and to people visiting the project folder years after the project has ended.
  • The DataWork Survey Round folder consists of five sub-folders: the DataSets folder, the Dofiles folder, the Outputs folder, the Documentation folder and the Questionnaire folder.

Overview

The Survey Round folder contains the following sub-folders: the DataSets folder, the Dofiles folder, the Outputs folder, the Documentation folder and the Questionnaire folder. The remainder of this page explains each element within the folder.

DataSets Folder

Image 1. Example of a DataSets folder. (Click to enlarge.)

The DataSets folder contains three sub-folders in which datasets are stored: Deidentified, Intermediate and Final (Image 1).

It is not recommended to create a folder for raw datasets in the DataSets folder: raw data almost always includes identifying information and the DataSets folder is not in the encrypted branch of the DataWork folder. Instead, save raw data in the DataWork Survey Encrypted Data folder. The Raw Data section describes in more detail best practices for raw data.

De-identified Folder

The De-identified folder houses de-identified raw data. Working with the raw, de-identified data rather than raw, encrypted data makes the work flow easier and smoother for the entire research team.

Intermediate Folder

The Intermediate folder is a work-in-progress folder containing all datasets that belong neither in the Raw nor Final folder. Raw datasets on which simple changes have been made belong in the Intermediate folder. There are no specific rules how this folder should be organized. However, it is a good idea to keep it organized in sub-folders and to name files according to naming conventions.

Final Folder

The Final folder contains the clean datasets with final variables constructed. This folder should only contain one version of each dataset. If your project has various datasets for different units of observation, (i.e. student dataset, school dataset, teacher dataset), then the Final folder should contain a sub-folder for each dataset.

The Final folder is the folder most likely to be visited several years after the project has ended by someone with very little knowledge of the project. This folder should therefore be one of the folders organized to the most level of detail.

Dofiles Folder

Image 2. Example of a DataSets folder. (Click to enlarge.)

Each Survey Round folder contains a Dofiles folder. The top level of this folder should contain only a master do-file and sub-folders. The master do-file maps out all do-files and datasets relevant to this survey round.

The sub-folders in the Dofiles folder should be organized according to task (i.e. import, cleaning, analysis), with the relevant do-files saved within its respective task folder. Each sub-folder should have a task level master do-file. Make sure to use naming conventions and version control when creating and updating these files and folders.

Task-level master do-files have little technical purpose as the round master do-file can technically call each individual do-file. However, the task-level master do-files document data work and make it significantly easier for someone unfamiliar with the code to understand the process.

Outputs Folder

The Outputs folder houses the survey round outputs. It consists of sub-folders. The exact sub-folders depend on the output and the method used to create outputs. If, for example, both tables and graphs are outputted, then create Table and Graph sub-folders. Each sub-folder should contain Raw and Formatted folders. For example, if single graphs are outputted to disk and later combined to one cumulative graph file, save the former as Raw and the latter as Formatted. See best practices of exporting analysis for additional recommendations.

The Outputs folder is one of the few places where it may be good practice to save multiple versions of the same file, since it is common to compare different versions of the analysis. If you save multiple versions of the same file, do not use the naming convention of table_v1, table_v2, etc. Instead, name files by date (i.e. table_Apr30, table_Jun6). If the outputted file size is significant in terms of disk space, do not save multiple versions of the same file: this will make it difficult for people with slow internet connection to access the folder via syncing services like DropBox.

Documentation Folder

This Documentation folder contains documentation for the analysis including any duplicate reports, survey logs, etc. While there is no strict format for this folder, it is good practice to save any documentation for this survey round in this folder. This could include anything from formal documentation to email conversations. You never know what you and your project team will need to know about this round in the future.

Questionnaire Folder

The Questionnaire folder contains all documentation related to the data collection. While questionnaire is the most important document to include in this folder, it is also important to save any other material that documents the survey. This includes material from the enumerator training, survey manuals used in the field, the survey firm TOR, and anything else that provides the project team with a better qualitative understanding of the data.

Encrypted Round Folder

Image 3. Example of a DataSets folder. (Click to enlarge.)

The Encrypted Round folders are created by iefolder at the same time as a round folder is created, but they are created in the encrypted branch of DataWork instead of inside the round folder. The encrypted round folders are separated from the other round folders as they likely include identifying data.

Raw Data

Any data downloaded from the server used to collect data should be saved in the Raw Identified Data folder. This includes data downloaded from the internet, data received from data collection, and data received from other projects.

The data in this folder should be exactly as you got it: absolutely no changes should be made to it. Even simple changes like correcting known errors, changing variable names, changing format, or changing file names should never be done to any files in this folder. The only exception to this rule is if the file name needs to be changed in order to be imported.

If there are known errors in your raw datasets, import the raw data set, write a do-file that corrects the errors and save the corrected data in the Intermediate folder. The datset in the Raw folder with known errors should remain unaltered. If corrections to the datasets are not properly documented, then the research team will not fully understand the quality of neither the data nor the research.

Import Dofiles

The do-files used to import, edit and de-identify the raw data likely include identifying information. Therefore, they should be housed in the Encrypted folder as well.

Running these do-files files should import the data, address any immediate issues such as missing IDs or duplicates, de-identify it and save the data set in the Intermediate folder, which is nested in the DataSets folder in the unencrypted branch of the DataWork.

Back to Parent

This article is part of the topic DataWork Folder.