Workshop Announcement: Shinyscholar – Reproducible Analytic Apps in R

Join our workshop on Shinyscholar – a template for producing reproducible analytic apps in R, which is a part of our workshops for Ukraine series! 

Here’s some more info: 

Title: Shinyscholar – a template for producing reproducible analytic apps in R

Date: Thursday, June 5th, 18:00 – 20:00 CEST (Rome, Berlin, Paris timezone)

Speaker: Simon Smart is a software developer in the Department of Population Health Sciences at the University of Leicester, UK. He has a background in plant and agricultural science and began developing Shiny apps in 2018, originally for forecasting yield in tomato and potato crops. He developed the shinyscholar package for creating reproducible apps and has applied it to create Disagapp for epidemiological modelling and refactor MetaInsight for evidence synthesis. He strives to create flexible, robust and reproducible apps using modern workflows that break down barriers for performing complex analyses.

Description: Shiny is an increasingly popular method for researchers to develop apps but they are typically not reproducible and a lack of training in software development results in substandard coding practices that make apps hard to maintain. The shinyscholar package addresses these problems by providing a template for producing apps that enable complex reproducible analyses, without having to learn best practices from scratch. In the workshop you will learn how to create a new application and the steps in developing shinyscholar modules, including prototyping, creating functions, checking for valid inputs, generating outputs, enabling reproducibility and automated testing.

Minimal registration fee: 20 euro (or 20 USD or 800 UAH)

Please note that the registration confirmation is sent 1 day before the workshop to all registered participants rather than immediately after registration

How can I register?

• Go to https://bit.ly/3wvwMA6 or https://bit.ly/4aD5LMC  or  https://bit.ly/3PFxtNA and donate at least 20 euro. Feel free to donate more if you can, all proceeds go directly to support Ukraine.

• Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)

• Fill in the registration form, attaching a screenshot of a donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after donation).

If you are not personally interested in attending, you can also contribute by sponsoring a participation of a student, who will then be able to participate for free. If you choose to sponsor a student, all proceeds will also go directly to organisations working in Ukraine. You can either sponsor a particular student or you can leave it up to us so that we can allocate the sponsored place to students who have signed up for the waiting list.

How can I sponsor a student?

• Go to https://bit.ly/3wvwMA6 or https://bit.ly/4aD5LMC  or https://bit.ly/3PFxtNA and donate at least 20 euro (or 17 GBP or 20 USD or 800 UAH). Feel free to donate more if you can, all proceeds go to support Ukraine!

• Save your donation receipt (after the donation is processed, there is an option to enter your email address on the website to which the donation receipt is sent)

• Fill in the sponsorship form, attaching the screenshot of the donation receipt (please attach the screenshot of the donation receipt that was emailed to you rather than the page you see after the donation). You can indicate whether you want to sponsor a particular student or we can allocate this spot ourselves to the students from the waiting list. You can also indicate whether you prefer us to prioritize students from developing countries when assigning place(s) that you sponsored.

If you are a university student and cannot afford the registration fee, you can also sign up for the waiting list here. (Note that you are not guaranteed to participate by signing up for the waiting list).

You can also find more information about this workshop series,  a schedule of our future workshops as well as a list of our past workshops which you can get the recordings & materials here.

Looking forward to seeing you during the workshop!

Continue reading: Shinyscholar – a template for producing reproducible analytic apps in R workshop

Long-term Implications and Possible Future Developments

The increasing popularity of the coding language, R, and the shift toward data-driven decision making in various fields underscores the relevance of training programs such as the Shinyscholar workshop. Herein lies the long-term implications and possible future developments based on the workshop’s details explicitly outlined in the text above.

Shinyscholar, the focal point of the workshop, is a package for producing reproducible analytic apps in R. Its growing use indicates a significant long-term effect on how researchers, software developers, and data scientists appraise and process data, leaning more towards reproducible analyses.

Standardization of Practices

By teaching and promoting sophisticated coding practices, Shinyscholar aids the creation of clean and robust applications. This development may drive a long-term transition towards a more standardized and efficient data processing paradigm, mitigating the issues associated with poor code quality and hard-to-maintain apps.

Future Adoption

Lessons gleaned from the workshop such as prototyping, creating functions, checking for valid inputs, enabling reproducibility, and automated testing indicates a widespread future adoption of Shiny apps, particularly in research fields requiring substantial data analysis.

Increased Accessibility

The provision to sponsor a student and the low registration fee hints at a commitment to accessibility. With sufficient support and funding, these workshops can become more universal, providing valuable coding and data analysis skills to a broader audience.

Actionable Response

Given these insights, consider the following actionable advice:

1. Get Involved: Attend the Shinyscholar workshop or similar training programs to acquire skills that would remain relevant in the long term. These skills offer potential opportunities in research, data science, and software development.
2. Sponsor a Student: If personally attending these events is not an option, consider sponsoring a student’s participation. This act not only facilitates the spread of essential coding skills but also supports local charities.
3. Advocate for Accessibility: Promote these events within your network or organization to raise awareness. If you are part of an institution, consider collaborating with these workshop organizers to sponsor a series of sessions for students or staff.
4. Apply for Waiting Lists: If you are a student or financially constrained, sign up for waiting lists. These workshops might be tissue-tight but present a cost-effective way of learning crucial programming skills that will be sought after in the future.

In conclusion, the adoption and promotion of reproducible analytics apps in R, such as Shinyscholar, will undoubtedly have a profound impact on the way researchers and data scientists process and generate information. The increased accessibility and affordability of workshops like these indicate a promising shift towards widespread data literacy.

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