Readme

Where do I start?

You can load this project in RStudio by opening the file called 'veni_forest.Rproj'.

Project structure

File | Description | Usage
------------------------- | -------------------------------- | -------------- README.md | Description of project | Human editable veniforest.Rproj | Project file | Loads project LICENSE | User permissions | Read only
.worcs | WORCS metadata YAML | Read only
preregistration.rmd | Preregistered hypotheses | Human editable preparedata.R | Script to process raw data | Human editable manuscript/manuscript.rmd | Source code for paper | Human editable manuscript/references.bib | BibTex references for manuscript | Human editable renv.lock | Reproducible R environment | Read only

Reproducibility

This project uses the Workflow for Open Reproducible Code in Science (WORCS) to ensure transparency and reproducibility. The workflow is designed to meet the principles of Open Science throughout a research project.

• To learn how WORCS helps researchers meet the TOP-guidelines and FAIR principles, read the preprint at https://osf.io/zcvbs/
• To get started with worcs, see the setup vignette
• For detailed information about the steps of the WORCS workflow, see the workflow vignette
• For a brief overview of the steps of the WORCS workflow, see below.

WORCS: Steps to follow for a project

Phase 1: Study design

1. Create a (Public or Private) remote repository on a 'Git' hosting service
2. When using R, initialize a new RStudio project using the WORCS template. Otherwise, clone the remote repository to your local project folder.
3. Add a README.md file, explaining how users should interact with the project, and a LICENSE to explain users' rights and limit your liability. The worcs project template does this automatically.
4. Optional: Preregister your analysis by committing a plain-text preregistration and tagging the commit as "preregistration".
5. Optional: Upload the preregistration to a dedicated preregistration server
6. Optional: Add study Materials to the repository

Phase 2: Writing and analysis

1. Create an executable script documenting the code required to load the raw data into a tabular format, and de-identify human subjects if applicable
2. Save the data into a plain-text tabular format like .csv. When using open data, commit this file to 'Git'. When using closed data, commit a checksum of the file, and a synthetic copy of the data.
3. Write the manuscript using a dynamic document generation format, with code chunks to perform the analyses.
4. Commit every small change to the 'Git' repository
5. Cite essential references with @, and non-essential references with @@

Phase 3: Submission and publication

1. Use dependency management to make the computational environment fully reproducible
2. Optional: Add a WORCS-badge to your project's README file
3. Make a Private 'Git' remote repository Public
4. Optional: Create a project page on the Open Science Framework
5. Connect your 'OSF' project page to the 'Git' remote repository
6. Add an open science statement to the Abstract or Author notes, which links to the 'Git' remote repository or 'OSF' page
7. Render the dynamic document to PDF
8. Optional: Publish the PDF as a preprint, and add it to the OSF project
9. Submit the paper, and tag the release of the submitted paper, as in Step 3.

Notes for cautious researchers

Some researchers might want to share their work only once the paper is accepted for publication. In this case, we recommend creating a "Private" repository in Step 1, and completing Steps 13-18 upon acceptance.

Access to data

Some of the data used in this project are not publically available. Synthetic data with similar characteristics to the original data have been provided. Using the function loaddata() will load these synthetic data when the original data are unavailable. Note that these synthetic data cannot be used to reproduce the original results. However, it does allow users to run the code and, optionally, generate valid code that can be evaluated using the original data by the project authors. Synthetic data with similar characteristics to the original data have been provided. Using the function loaddata() will load these synthetic data when the original data are unavailable. Note that these synthetic data cannot be used to reproduce the original results. However, it does allow users to run the code and, optionally, generate valid code that can be evaluated using the original data by the project authors. Synthetic data with similar characteristics to the original data have been provided. Using the function load_data() will load these synthetic data when the original data are unavailable. Note that these synthetic data cannot be used to reproduce the original results. However, it does allow users to run the code and, optionally, generate valid code that can be evaluated using the original data by the project authors. To request access to the original data, open a GitHub issue.

Access to data

Some of the data used in this project are not publically available. To request access to the original data, open a GitHub issue.

Access to data

Some of the data used in this project are not publically available. To request access to the original data, open a GitHub issue.

Access to data

Some of the data used in this project are not publically available. To request access to the original data, open a GitHub issue.

Access to data

Some of the data used in this project are not publically available. To request access to the original data, open a GitHub issue.

Access to data

Some of the data used in this project are not publically available. To request access to the original data, open a GitHub issue.

Access to data

Some of the data used in this project are not publically available. To request access to the original data, open a GitHub issue.

Access to data

Some of the data used in this project are not publically available. To request access to the original data, open a GitHub issue.

Access to data

Some of the data used in this project are not publically available. To request access to the original data, open a GitHub issue.

Access to data

Some of the data used in this project are not publically available. To request access to the original data, open a GitHub issue.

Access to data

Some of the data used in this project are not publically available. To request access to the original data, open a GitHub issue.