Collaboration among a research team is a critical part of nearly all impact evaluations. With the general availability of low-cost cloud collaboration tools, it is important to use tools that effectively achieve the goals of sharing access to data and content, while protecting the privacy, integrity, and history of that content and imposing as low of a learning cost on other collaborators as possible.
Collaboration tools for data analysis
GitHub allows for multiple data analysts to work on the same project simultaneously, by keeping a local copy of all analysis code, and merging final versions together in a centralized repository. GitHub also preserves every version history of code and outputs, making it easy to recover old code snippets after deleting them from the main production branch, as well as making them publicly accessible for others to review analyses that did not appear in the final publication.
Cloud Sync Tools
Cloud Sync tools, such as Dropbox, are commonly used to share code, data, and outputs with collaborators. Unlike GitHub, sync tools have limited version histories and typically do not allow multiple collaborators to work simultaneously on the same file without version conflicts arising. However, they bear more similarity to traditional filesystem structures, meaning the learning curve is nearly zero for working on files in sync tools.
Collaboration tools for paper writing
Overleaf is a web-based LaTeX collaboration tool that allows multiple authors to simultaneously edit documents. It maintains a folder structure containing a main document, a bibliography document, and images and other resources. It supports limited integrations with Git and Dropbox, and is currently under active redevelopment following a merger with ShareLaTex, a similar service.
While Overleaf is based on a LaTeX structure, it now offers a "Google-Docs-like" editor and limited comments and version histories, making it easier to collaborate with coauthors who are more comfortable with WYSIWYG editors like Word.
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