The biological sciences community is increasingly recognizing the value of open, reproducible, and transparent research practices for science and society at large. Despite this recognition, many researchers remain reluctant to share their data and code publicly. This hesitation may arise from knowledge barriers about how to archive data and code, concerns about its re-use, and misaligned career incentives. Here, we define, categorise, and discuss barriers to data and code sharing that are relevant to many research fields. We explore how real and perceived barriers might be overcome or reframed in light of the benefits relative to costs. By elucidating these barriers and the contexts in which they arise, we can take steps to mitigate them and align our actions with the goals of open science, both as individual scientists and as a scientific community.
Professor at George Washington University
I am a Professor with Human-Technology Collaboration and Educational Technology programs at George Washington University in Washington DC. I have written 12 books and more than 100 articles, and I co-host of the Parsing Science podcast where scientists tell the stories behind their research. I am also the developer of the WeShareScience.com online platform for sharing research videos, and SciencePods.com where researchers can create free podcasts about their science. My research interests include human interactions with intelligent machines, needs, needs assessments, and instructional design.
Latest posts by Ryan Watkins (see all)
- Exploring Student Behaviors and Motivations using AI TAs with Optional Guardrails - April 16, 2025
- AI-University: An LLM-based platform for instructional alignment to scientific classrooms - April 15, 2025
- Interaction-Required Suggestions for Control, Ownership, and Awareness in Human-AI Co-Writing - April 14, 2025