<Help text is included in angle brackets and should be deleted before saving. Note that data/dataset is here used as a cover term for data, code, software and other types of material. We recommend you to add "00_" in front of the ReadMe file name (e.g. “00_README.txt”), which will make the file appear on the top of the file overview.>

<DataverseNO README File Template --- Software Code --- Version: 2.1 (2023-04-14)>

This README file was generated on [YYYY-MM-DD] (YYYY-MM-DD) by [NAME].
Last updated: [YYYY-MM-DD].


-------------------
GENERAL INFORMATION
-------------------
// Title of Dataset: 
// Contact Information
<The person to be contacted for questions about the dataset>
     // Name: 
     // Institution: 
     // Email: 
     // ORCID: 
     // Code repository URL: <e.g. GitHub, GitLab> 

<The following information must be registered in the metadata schema of DataverseNO in the fields/sections referred to below. Do not change text below.>
// Contributors: See metadata field Contributor.
// Data Type: See metadata field Data Type.
// Date of data production: See metadata field Production Date     .
// Geographic location: See metadata section Geographic Coverage.
<If applicable.>
// Funding sources: See metadata section Grant Information.
<If applicable.>

// Short description of what the dataset is about, including reference to related project(s) and publication(s), if applicable.: 
<For example: goals/what problem(s) it solves; key concepts; most useful/innovative/noteworthy features; development status. This information should be added below as well as in the metadata field Description.>


--------------------------
SHARING/ACCESS INFORMATION
--------------------------
(See metadata record for dataset.)
<The following information must be registered in the metadata schema of DataverseNO in the fields/sections referred to below. Do not change text below.>
// Licenses/Restrictions: See Terms section.
// Links to publications that cite or use the data: See metadata field Related Publication.
// Links/relationships to related data sets: See metadata field Related Datasets.
// Data sources: See metadata field Data Sources.
// Recommended citation: See citation generated by repository.


--------------------
DATA & FILE OVERVIEW
--------------------
// File List: 
<List all files (or folders, as appropriate for dataset organization) contained in the dataset. Where appropriate, a file overview may be provided by explaining file naming conventions, instead of listing individual files. For each file (or folder), provide a brief description of what data it contains, and of the file format (e.g. plain text) if not obvious from file extension (e.g. .txt). If necessary, also include system and hardware requirements needed to open and read the file.>

// Relationship between files, if important: 

// Is this a new version of a previously published dataset? yes/no
<If yes, repeat the following information for each file that was updated.> 
     File name: 
     Why was the file updated?: 
     When was the file updated (YYYY-MM-DD)?:

----------------------
HOW TO USE THE DATASET
----------------------
<Include links or references to publications or other documentation (e.g. GitHub pages or project main pages). Note! If the documentation referred to is not openly available through a persistent URL, it must be added here or uploaded as a file to the dataset.>

// Getting Started: 
<Provide instructions on how to get a copy of the project up and running on a local machine for development and testing purposes. More information about how to deploy the project on a live system can be provided in the deployment section below.>
a. Prerequisites
<What is needed to install the software and how to install the required resources.>
b. Installing
<A step by step series of examples that explain how to get a development environment running. If appropriate, provide an example of getting some data out of the system or using it for a little demo.>

// Running the tests
<Explain how to run the automated tests for this system.>
a. Break down into end to end tests
<Explain what these tests test and why.>
b. Coding style tests
<Explain what these tests test and why.>

// Deployment
<Additional notes about how to deploy this on a live system.>

----------------------------------
CODE DOCUMENTATION FOR: [FILENAME] 
----------------------------------
<Repeat this section for each dataset, folder or file, as appropriate. Recurring items may also be explained in a common initial section.>
<Document your code, including coding conventions, such as file organization, comments, naming conventions, programming practices, etc.>


<
Acknowledgements. This README file template is adapted from the following documents/resources:

AJPS. ‘American Journal of Political Science Qualitative Data Verification Checklist’. Wiley, 11 March 2016. https://ajps.org/wp-content/uploads/2019/01/ajps-qualdata-checklist-ver-1-0.pdf.

Berkeley Library, University of California. How to Write a Good Documentation. Available at: http://guides.lib.berkeley.edu/how-to-write-good-documentation

Cornell University. Guide to writing readme style metadata. Available at: https://data.research.cornell.edu/content/readme#bestpractices

Corti, Louise, Veerle Van den Eynden, Libby Bishop, Matthew Woollard, Maureen Haaker, and Scott Summers. Managing and Sharing Research Data: A Guide to Good Practice. 2nd edition. Los Angeles: SAGE, 2019.

Dryad. Best practices for creating reusable data publications. Available at: https://datadryad.org/stash/best_practices#describe

PurpleBooth. A template to make good README.md. Available at: https://gist.github.com/PurpleBooth/109311bb0361f32d87a2

University of Bath. Working with data: Data Documentation and Metadata. Available at: https://library.bath.ac.uk/research-data/working-with-data/data-documentation-metadata

Zalando. Zalando's README Template. Available at: https://github.com/zalando/zalando-howto-open-source/blob/master/READMEtemplate.md#readme
>
