Program > Invited speakers

Data science without the data

As data scientists, we sometimes find ourselves faced with the daunting task of writing code without actually seeing the data we are working with. Whether it's due to data privacy concerns, limited access, or simply data that has not yet been collected, we often have to rely on incomplete or synthetic data to develop and test our code.

In a recent project, we worked on patient-level data. As such, the controls around the data and analysis (were rightfully) tightly controlled. We'll share how we used dummy data and mock-ups to inform code development, maintaining flexibility and adaptability in the face of changing data requirements. We'll also discuss the importance of and collaboration between developers and subject experts to ensure that code is developed with a deep understanding of the data domain

By understanding these challenges and developing effective strategies for overcoming them, we can ensure that our code is robust, reliable, and effective, even in the absence of direct data access.

Spatial Ecosystem in R

R language has long been used to process spatial data. Several fairly recent packages (sf, terra, stars, etc.) have renewed the base allowing the implementation of spatial data processing.

Most of the current developments are forming a robust ecosystem which offers users most of the functionalities formerly reserved for Geographic Information Systems. During this presentation we will show a panorama of the spatial ecosystem of R.

We will illustrate this panorama through a series of examples mobilizing data of different natures (vector data and raster or raster data) from the free geographical database OpenStreetMap.

We will address in particular the acquisition, manipulation and mapping of geographic data, traditional geoprocessing operations as well as more advanced spatial analysis processing.

R in the Dataviz Universe

With a vast array of tools, use cases, and plot types available, it can be difficult to navigate the world of data visualization (dataviz). In this presentation, we'll explore how dataviz is used by various professions: research, data journalism, business intelligence, and others. We'll look at the different tools available, with a focus on R.

Although each tool has its strengths and weaknesses, R has become a popular choice among data scientists and analysts. We will explore R's position in the dataviz ecosystem, highlighting its advantages and limitations. We'll also look at d3.js, a popular JavaScript library for creating graphics, and compare it to R in terms of its capabilities and limitations.

Whether you are new to data visualization or an experienced practitioner, this presentation will provide you with valuable insights into the world of dataviz and equip you with the knowledge to choose the right tool for your needs.

Pastels, glitter and packages to support research with r

For the last 12 years, I work as a research support engineer in a geography laboratory.

To support my fellow researchers, teachers, students in their research and help them in their data analysis with R, I use various tools. The first and the one that benefits the greatest number consists in creating and offering educational materials (the pastels): blog, online tutorials, illustrations, and a regular internal training offer for the members of my laboratory. In certain specific cases, when the level of technicality required by an analysis is too high or when the need to explore the data in a user-friendly way is strong, I prefer to offer more "turnkey" tools such as shiny apps (glitter). Finally, in other cases, my contact is a more confirmed R user with a specific need and I analyze this need with him to develop a certain number of dedicated functions (packages).

I will explain what my job consists of on a daily basis, by presenting my personal background and enameling it with examples of collaborations.

Tips pour combattre le syndrome de l'imposteur

Who has not once said the sentence: I feel like an impostor? I don't feel entitled to do this or do that?

Some people are convinced that they do not deserve their success, despite the efforts they make to succeed. They often convince themselves that their success is not linked to their work, their personal accomplishment, but simply to luck or the work of others. In fact, they live permanently with a feeling of deception and constantly fear that someone will unmask them from one day to another.

In this talk we will return to what the impostor syndrome is, how it is reflected on a daily basis and we will see that it is not inevitable, on the contrary, that there are tips and tricks for the fight, overcome and improve.