Data Science for Forestry Sciences
The tools and concepts developed enable progressive and applied learning of data science and visualisation for forestry sciences.
Duration: July 2022 – December 2022
Status: Completed
Educational Level: Tertiary Level
Topic: Data Science for Education
Keywords: Data Science
Initial Situation
Teaching data science and data visualization to learners without a strong background in applied mathematics or computer science poses a significant didactic challenge. Traditional, abstract approaches are often not suitable for students and professionals in applied fields such as forest sciences. To address this, there is a need for adapted tools and educational concepts that make these topics more accessible and practice-oriented. The project leverages the martelage.sylvotheque.ch (MSC) platform, which hosts data from over 130 managed forest plots and is already in use for both basic education and continuing professional training in forestry.
Objectives
The project team aimed to develop a suite of tools and innovative didactic concepts for data science and visualization, tailored to learners in forestry. These tools were intended to support progressive, hands-on learning and be adaptable for use beyond formal sciences.
Method
The BFH-TI developed a dashboard editor for the web platform martelage.sylvotheque.ch, while the BFH-HAFL designed the underlying forestry concept. In parallel, a technical interface (API) was programmed to enable data retrieval from the platform. The BFH-HAFL also produced manuals and example dashboards for data visualisation using Power BI, which can be adapted by students and practitioners. In addition, didactic concepts were developed for the use of these tools in forestry education and continuing training.
Results
The team developed three main tools with increasing levels of complexity and flexibility:
- a dashboard editor integrated into the MSC platform for basic data visualization;
- a ready-to-use project template in Power BI allowing flexible workflow definition and dashboard creation without coding;
- a web API enabling easy data export from MSC for use in R or Python projects.
Alongside these tools, didactic concepts were created to support their integration into both undergraduate and professional education.
Implemented Translation
The tools were designed for immediate use in educational settings. The dashboard editor is accessible to Bachelor students from their first year. Power BI allows students to define and adapt data workflows without programming, while the API supports more advanced, coding-based data science projects. These resources enable students to engage with real data progressively, from simple visualization to complex analysis. The project enables the teaching of data science and data visualisation to learners without advanced knowledge of computer science or mathematics. The three tools developed, with graduated levels of complexity – ranging from the integrated dashboard editor to Power BI templates and the web API – support step-by-step, practice-oriented learning and accommodate different levels of prior knowledge. The didactic concepts and tools are used in basic and continuing forestry education, making data science competencies accessible to applied fields. The approach can be transferred to other disciplines and serves as a model for fostering digital competencies in non-technical study programmes.
