Streamlining Data Sharing: Simplifying Repository Selection with GREI's Flowchart and Comparison Chart

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Authors: Matthew B. Carson, Traci Snowden
Cited by: 0
References: 4

Abstract

This presentation is part of a three-part webinar series hosted by the Generalist Repository Ecosystem Initiative (GREI), designed to assist scientific researchers in navigating data management and sharing requirements The series provides an introduction to GREI-developed resources that streamline the data-sharing lifecycle, from planning to submission, helping researchers maximize the impact of their work. In this specific session, "Simplifying Repository Selection with GREI’s Flowchart and Comparison Chart," presenters Matt Carson (Zenodo) and Traci Snowden (Mendeley Data) introduce the Generalist Repository Selection Flowchart and the Generalist Repository Comparison Chart as essential tools for navigating decision points in the repository selection process. The slides provide a walkthrough of these resources alongside practical user stories that demonstrate real-world applications. Specifically, the presentation features case studies from Rogan Grant (Northwestern University) and Liz Mallott (Washington University in St. Louis), offering perspectives on how researchers successfully manage, share, and reuse data within their respective fields, including such insights as: Sharing reusable code and pipelines on Zenodo boosts reproducibility and transparency. Data reuse through meta-analysis can uncover new and critical scientific insights. Combining datasets requires effort to re-code and standardize data from different labs. Reaching out to original authors for data often leads to successful, fruitful collaborations. Generalist repositories support diverse data types and facilitate discovery for reuse. The session recording is available here: https://youtu.be/jmhO9F0P-ts?si=UzAXiEyretnWIeLb

Fields of Study & Subjects

Research Data Management Practices Data Analysis and Archiving Scientific Computing and Data Management

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
28 January 2026