From data to paper: science communication to peers
BIO-707 / 1 crédit
Enseignant(s): Friskes Anoek, Garcia Arcos Juan Manuel
Langue: Anglais
Remark: Learn to turn your research data into clear figures, a coherent scientific story and an effective presentation through practical exercises and structured peer feedback
Frequency
Every year
Summary
Across three half-day sessions and a final poster session, participants analyse published examples, work on their own research and revise their outputs through feedback.
Content
General aim
The course trains participants to transform research data into clear, rigorous and publishable scientific outputs. It provides adaptable methods for selecting evidence, structuring information, communicating uncertainty and revising scientific work.
Course structure
- From data to figures: Participants learn to select evidence, design clear figures and identify weak or misleading representations. Basic statistical, reporting, open-science and data-transparency principles are also introduced.
- From figures to a scientific argument: Participants identify their main contribution, organise results logically and develop a coherent Results narrative. They learn to distinguish evidence from interpretation and communicate limitations clearly.
- From a scientific argument to a poster: Participants use poster design to test and communicate their scientific story. They learn to create a clear visual hierarchy and present their work concisely.
Teaching methods
Less than 20% of course time is devoted to teacher presentations. Activities include paper analysis, self- and peer assessment, small-group work, role-playing and guided revision.
Participants work on their own research material whenever possible. Each activity follows a production-feedback-revision cycle.
Note
An additional edition may be offered depending on demand.
LEARNING OUTCOMES
By the end of the course, students will be able to:
- Select evidence and build publication-quality figures.
- Apply visual-design, statistical, reporting and data-transparency principles.
- Identify unclear or potentially misleading data representations.
- Organise figures and results into a coherent scientific argument.
- Communicate the main contribution, evidence, uncertainty and limitations of their work.
- Design and present a clear scientific poster.
- Give constructive feedback and revise their work accordingly.
TRANSVERSAL SKILLS
Participants will develop their ability to:
- Communicate clearly with peer scientific audiences.
- Structure complex information concisely.
- Represent data rigorously and ethically.
- Give, receive and integrate feedback.
- Assess their skills and identify learning goals.
- Work effectively in groups and within available resources.
- Reflect on the impact of how scientific evidence is presented.
ASSESSMENT
Assessment is based on individual written and oral work. In each session, participants will submit a revised communication artefact, such as a figure or storyline, contributing to a final scientific poster. They will briefly present and discuss their poster during the final session. Assessment criteria will be shared in advance.
PRACTICAL INFORMATION
Attendance at all four sessions is required.
The course is limited to 16 participants and is intended primarily for doctoral students currently producing or analysing research data.
To apply, email juan.garciaarcos@epfl.ch with a brief description of your current communication challenges and the stage of your research project. Applications will be assessed for fit. Eligible applicants will be accepted in the order their applications are received.
Keywords
Scientific communication, evidence selection, data visualisation, figure design, scientific writing, Results section, scientific storytelling, uncertainty, poster design, oral presentation, peer feedback, open science, data transparency, research-based learning, transversal skills.
Learning Prerequisites
Required courses
No specific course is required.
Participants should be working on a research project and have data, figures or preliminary results to use during the course.
Assessment methods
Written & oral
Resources
Bibliography
Resources will be provided before or during the course, including:
- Guidance on figure design, statistics and reporting standards.
- Published papers and examples for analysis.
- Feedback templates for figures, storylines and posters.
- Resources on open science and ethical data representation.
- A workbook containing course activities and assessment criteria.
Moodle Link
Dans les plans d'études
- Nombre de places: 16
- Forme de l'examen: Ecrit & Oral (session libre)
- Matière examinée: From data to paper: science communication to peers
- Cours: 12 Heure(s)
- Type: optionnel