Ten Simple Rules for Researchers Who Want to Develop Web Apps

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: http://doi.org/10.1371/journal.pcbi.1009663. This is version 1 of this Preprint.

Add a Comment

You must log in to post a comment.


There are no comments or no comments have been made public for this article.


Download Preprint


Sheila M. Saia, Natalie G. Nelson , Sierra N. Young , Stanton Parham , Micah Vandegrift 


Growing interest in data-driven, decision-support tools across the life sciences and physical sciences has motivated development of web applications, also known as web apps. Web apps can help disseminate research findings and present research outputs in ways that are more accessible and meaningful to the general public--from individuals, to governments, to companies. Specifically, web apps enable exploration of scenario testing and policy analysis (i.e., to answer “what if?”) as well as co-evolution of scientific and public knowledge. However, the majority of researchers developing web apps receive little formal training or technical guidance on how to develop and evaluate the effectiveness of their web-based decision support tools. Take some of us for example. We (Saia and Nelson) are agricultural and environmental engineers with little experience in web app development, but we are interested in creating web apps to support sustainable aquaculture production in the Southeast. We had user (i.e., shellfish growers) interest, a goal in mind (i.e., develop a new forecast product and decision-support tool for shellfish aquaculturalists), and received funding to support this work. Yet, we experienced several unexpected hurdles from the start of our project that ended up being fairly common hiccups to the seasoned web app developers among us (Young, Parham). As a result, we share the following Ten Simple Rules, which highlight take home messages, including lessons learned and practical tips, of our experience as burgeoning web app developers. We hope researchers interested in developing web apps draw insights from our (in)experience as they set out on their decision support tool development journey.




Agricultural Science, Agriculture, Applied Statistics, Artificial Intelligence and Robotics, Bioresource and Agricultural Engineering, Computer Sciences, Databases and Information Systems, Environmental Monitoring, Graphics and Human Computer Interfaces, Natural Resources and Conservation, Software Engineering, Terrestrial and Aquatic Ecology, Water Resource Management


web applications, web tools, decision support tools, task-centered design


Published: 2021-07-18 07:57

Last Updated: 2021-07-18 14:57


CC BY Attribution 4.0 International

Additional Metadata

Conflict of interest statement: