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Most commonly, a trained or experienced web developer will specialize in one particular component however, some web developers may specialize in the full stack, which refers to the front end and back end of the web app combined.įig 1. The back end typically includes (1) scripts (i.e., computer code) written in a back end language (e.g., Java and Python) to support the front end appearance and back end functionality of the web app (i.e., how periodic updates are made to the front end) (2) databases (e.g., MySQL) to store data for the web app and its users and (3) web services (e.g., Google Cloud Platform, ) to present the updated web app to users and connect the user’s front end experience with the back end tasks via the web app ( Fig 1C–1E). The front end represents everything the user sees on their device screen ( Fig 1B, 1F), while the back end represents parts of the web app that only the web developers see ( Fig 1C, 1D).

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These can usually be hosted on free third-party services such as GitHub Pages. For example, some web apps are front end only and require no dedicated back end (e.g., single-page applications like ). There are some exceptions to this design. Web developers often separate web apps into two main components: the front end and the back end ( Fig 1). Here, we further define web apps as dynamic tools that allow users to perform a task, although we acknowledge that others may define web apps differently. Web apps provide interactive services that can be accessed by web browsers. We focus on web apps, rather than mobile phone applications, because advances in web app coding frameworks make it possible to seamlessly scale web apps across multiple devices (e.g., phones, computers, and tablets). 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. As a result, we share the following 10 simple rules, which highlight take-home messages, including lessons learned and practical tips, of our experience as burgeoning web app developers. 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 (Parham).

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. 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.

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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. Specifically, web apps enable exploration of scenario testing and policy analysis (i.e., to answer “what if?”) as well as coevolution of scientific and public knowledge. Web apps help disseminate research findings and present research outputs in ways that are accessible and meaningful to the general public-from individuals, to governments, to companies. Web applications, also known as web apps, are increasingly common in the research communication portfolios of those working in the life sciences (e.g., ) and physical sciences (e.g., ).

The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ĭompeting interests: The authors have declared that no competing interests exist. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.įunding: This work was supported in part by the North Carolina Sea Grant R/20-SFA-4 (NGN, SMS, SP), United States Department of Agriculture (USDA) Food and Agriculture Cyberinformatics Tools (FACT) project 2019-67021-29936 (NGN, SMS), and USDA National Institute of Food and Agriculture (NIFA) Hatch projects 1021499 (SNY) and 1016068 (NGN). PLoS Comput Biol 18(1):Įditor: Scott Markel, Dassault Systemes BIOVIA, UNITED STATESĬopyright: © 2022 Saia et al. Citation: Saia SM, Nelson NG, Young SN, Parham S, Vandegrift M (2022) Ten simple rules for researchers who want to develop web apps.