Open Access

Khem Raj Regmi

• This thesis will study the creation of an interactive data visualization tool for environmental dataset that concentrates specifically on Nitrate concentrations in groundwater. This project is intended to create a tool for exploratory/experiential learning - one that allows learners to investigate regional data and pursue genuine learning opportunities. The plan is to use regional data in a specific user journey to create this interactive learning experience. The project uses open environmental data: Hygris dataset of LANUV(Landesamt für Natur, Umwelt und Verbraucherschutz) related to the regions Kleve and Wesel in Germany, and realizes this with help of python programming language and python streamlit framework, web development tools and data visualization libraries (pandas , plotly.express, streamlite.components.v1). This study explores tailored visualization strategies that address key challenges such as the inherent complexity of environmental datasets and the need for more engaging and comprehensible educational tools. These strategies include deploying interactive visualizations that allow hands-on data exploration, and temporal visualizations. The role of user feedback in refining educational tools for teaching environmental data is examined, particularly in designing effective visualization techniques like line char, bar chart, bubble chart, pie chart, scatter plot and intensity graph for representing groundwater nitrate concentrations. The impact of different visualization techniques on the understanding and interpretation of open environmental data among educators and students is analyzed, with an emphasis on the spatial distribution of groundwater nitrate concentrations over time. This approach aims to increase user engagement and deepen understanding of environmental data, facilitating a more profound embedding of information within learners' cognitive processes.