Welcome to Issue 11 of the RDM Weekly Newsletter!
If you are new to RDM Weekly, the content of this newsletter is divided into 3 categories:
☑️ What’s New in RDM?
These are resources that have come out within the last year or so
☑️ Oldies but Goodies
These are resources that came out over a year ago but continue to be excellent ones to refer to as needed
☑️ Just for Fun
A data management meme or other funny data management content
What’s New in RDM?
Resources from the past year
1. STAPLE: Infrastructure for Open, Transparent, and Collaborative Science — Webinar
Modern research is increasingly collaborative, interdisciplinary, and global but the tools researchers use to manage their projects often lag behind. STAPLE (Science Tracking Across the Project Lifespan) is an open-source platform designed to support transparent, well-documented, and reusable research workflows. In this Center for Open Science webinar happening on Sep 17, 2025 10am CST, the presenters will introduce the vision behind STAPLE and demonstrate how it supports the full research lifecycle. They will also provide a hands-on walkthrough: how to create a project, assign tasks and roles, and track contributions over time.
2. surveydown: An Open-Source, Markdown-Based Platform for Programmable and Reproducible Surveys
This paper introduces the surveydown survey platform. With surveydown, researchers can create surveys that are programmable and reproducible using markdown and R code, leveraging the Quarto publication system and R Shiny web framework. While most survey platforms rely on graphical interfaces or spreadsheets to define survey content, surveydown uses plain text, enabling version control and collaboration via tools like GitHub. The package renders surveys as interactive Shiny web applications, allowing for complex features like conditional skip logic, dynamic question display, and complex randomization. As an open-source platform, surveydown provides researchers full control over their survey implementation, including the survey application as well as where and how the resulting response data are stored. Workflows are entirely reproducible and integrate seamlessly with existing workflows for data collection and analysis in R.
3. Anonymous GitHub
Anonymous Github allows you to anonymize your Github repository. Several anonymization options are available to ensure that you do not break the double-anonymize such as removing links, images or specific terms. You still keep control of your repository, and define an expiration date to make your repository unavailable after the review.
4. TADA! Simple Guidelines to Improve Code Sharing
Code sharing is important for transparency and facilitates computational reproducibility of published research. However, even as the number of journals that encourage or mandate code sharing continues to increase, the prevalence of open code remains low. Furthermore, even when shared, code is often non-functional, which hinders computational reproducibility. To improve code sharing, there is an urgent need for clear and simple guidance on how to prepare functional and reproducible code for sharing. To address this, the authors provide simple code sharing guidelines: TADA (Transferable, Accessible, Documented and Annotated). TADA details the minimum requirements necessary for a researcher to produce functional and reproducible code for sharing that directly supports open science best practices and the FAIR (Findable, Accessible, Interoperable, Reusable) principles for code. TADA aims to streamline the process of depositing and sharing functional code for researchers with all levels of coding experience, with the ultimate goal of increasing the transparency, reproducibility, and reliability of research results across ecology and evolution, and more broadly.
5. Easily Download Files from the Open Science Framework with Papercheck
Researchers increasingly use the Open Science Framework (OSF) to share files, such as data and code underlying scientific publications, or presentations and materials for scientific workshops. However, downloading all files related to a project can be surprisingly effortful. To make things easier, Lisa DeBruine and Daniel Lakens have added a new function to their R package {papercheck} that will download all files and folders in an OSF repository, saving all files by recreating the folder structure from the OSF in your download folder.
6. Air, An Extremely Fast R Formatter
Air is an R code formatter that can be used into an IDE such as RStudio, VS Code, or Positron. A formatter is in charge of the layout of your R code. Formatters do not change the meaning of code; instead they ensure that whitespace, newlines, and other punctuation conform to a set of rules and standards. Using a formatter has many benefits including having more legible code (without having to think about it) and reducing friction when working on a team (collaborators no longer have to discuss styling and layout issues).
Oldies but Goodies
Older resources that are still helpful
1. Good Enough Practices in Scientific Computing
In 2014, a group of researchers involved in Software Carpentry and Data Carpentry wrote a paper called "Best Practices for Scientific Computing". That paper provided recommendations for people who were already doing significant amounts of computation in their research. However, as computing has become an essential part of science for all researchers, there is a larger group of people new to scientific computing, and the question then becomes, "where to start?" This 2017 paper focuses on these first accessible skills and perspectives—the "good enough" practices—for scientific computing: a minimum set of tools and techniques that the authors believe every researcher can and should consider adopting.
2. The TRUST Principles for Digital Repositories
As information and communication technology has become pervasive in our society, we are increasingly dependent on both digital data and repositories that provide access to and enable the use of such resources. Repositories must earn the trust of the communities they intend to serve and demonstrate that they are reliable and capable of appropriately managing the data they hold. Following a year-long public discussion and building on existing community consensus, several stakeholders, representing various segments of the digital repository community, collaboratively developed and endorsed a set of guiding principles to demonstrate digital repository trustworthiness. Transparency, Responsibility, User focus, Sustainability and Technology: the TRUST Principles provide a common framework to facilitate discussion and implementation of best practice in digital preservation by all stakeholders.
3. Awesome-Python
This GitHub Repo README contains an opinionated list of awesome Python frameworks, libraries, software and resources. The list is organized by functionality. Thanks to Miranda Cooper for recently sharing this resource!
4. Example Project for Data Sharing
This project, which contains fictitious data, provides an example of the data products a researcher may choose to publicly share at the end of a research project to allow for reuse and reproducibility. The files a researcher shares and how they share them will depend on their specific project and requirements (e.g., funder requirements, data reuse considerations). However, this repository provides just one example of how education researchers, in particular, may consider organizing data products in a public repository.
Just for Fun
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