Uploaded April 2023 | Updated September 2026, 2 weeks ago
About the talk:
We are often involved in many projects as researchers in academia. Ensuring that we have the bigger picture of the project tasks can be challenging if not well documented. Recently, our line manager asked us to create a Gantt chart to present all current tasks and how far we are from completing them. R Markdown came to mind at first, and we created beautiful Gantt charts which can be shared as an HTML file. Since the projects are evolving, new tasks are assigned to us. Therefore, to present the updated Gantt chat, we ought to rerun the R Markdown file. A question came to mind. Instead of rerunning the R Markdown file to update the Gantt Chart, could Shiny Apps be used to automate this process? The answer is yes! We created an R Shiny App that can automate and update Gantt Charts. This results in improving the efficiency of project management in academia. In this presentation, we will point out some of the awesome features of R shiny and demonstrate how our R Shiny App can easily automate Gantt charts and track the progress of tasks.
Speaker's bio:
My name is Lucy Njoki Njuki. I hold the position of Research Assistant at the Centre for Epidemiology VS Arthritis at the University of Manchester while being a part-time second-year student at Hasselt University, studying MSc in Statistics and Data Science (Biostatistics) through a distance learning program. I am an active member of the R community and serve as an organiser of R-Ladies Nairobi. I rely on R for most of my tasks, including healthcare data wrangling and processing, plus conducting statistical analysis for my project assignments. Hello! My name is Yuanyuan Zhang. I am currently a research associate at the Center for Digital Trust and Society in the University of Manchester. My research background is in the general area of statistical modelling, distribution theory and data science with applications to finance. I use R to perform statistical/machine learning models, develop new R software packages, build awesome Data Visualizations tools and interactive dashboards (such as Shiny Apps on medical science & Financial data).
About the talk:
We are often involved in many projects as researchers in academia. Ensuring that we have the bigger picture of the project tasks can be challenging if not well documented. Recently, our line manager asked us to create a Gantt chart to present all current tasks and how far we are from completing them. R Markdown came to mind at first, and we created beautiful Gantt charts which can be shared as an HTML file. Since the projects are evolving, new tasks are assigned to us. Therefore, to present the updated Gantt chat, we ought to rerun the R Markdown file. A question came to mind. Instead of rerunning the R Markdown file to update the Gantt Chart, could Shiny Apps be used to automate this process? The answer is yes! We created an R Shiny App that can automate and update Gantt Charts. This results in improving the efficiency of project management in academia. In this presentation, we will point out some of the awesome features of R shiny and demonstrate how our R Shiny App can easily automate Gantt charts and track the progress of tasks.
Speaker's bio:
My name is Lucy Njoki Njuki. I hold the position of Research Assistant at the Centre for Epidemiology VS Arthritis at the University of Manchester while being a part-time second-year student at Hasselt University, studying MSc in Statistics and Data Science (Biostatistics) through a distance learning program. I am an active member of the R community and serve as an organiser of R-Ladies Nairobi. I rely on R for most of my tasks, including healthcare data wrangling and processing, plus conducting statistical analysis for my project assignments. Hello! My name is Yuanyuan Zhang. I am currently a research associate at the Center for Digital Trust and Society in the University of Manchester. My research background is in the general area of statistical modelling, distribution theory and data science with applications to finance. I use R to perform statistical/machine learning models, develop new R software packages, build awesome Data Visualizations tools and interactive dashboards (such as Shiny Apps on medical science & Financial data).
