An interactive relationship map that speeds up scientific literature analysis

The goal was to design a tool that:

• Lets users search collections of scientific publications for specific variables.
• Visualizes relationships between variables as an interactive map.
• Presents statistical data in a clear, understandable way.
• Gives quick access to the data source (the scientific articles).

The main challenge was presenting complex statistical relationships between research variables in a way that is clear and intuitive. It was also important to allow analysis of large datasets without any loss of performance.

Our team built the application on the following technologies:

• Frontend: React CRA + Material-UI - a clean, modern interface with ready-to-use components.
• Forms: react-use-form - for building multi-step forms with validation.
• Data visualization: React-Flow - an advanced library used to create dynamic graphs and diagrams.

• A map of connections between research variables, visualizing statistical relationships.
• A table of statistical analysis results with links to specific articles.
• A multi-step data analysis process that makes it easy to upload PDF files, choose variables and filter publications.

• A working prototype of an application that supports researchers' work.
• Highly readable and easy to use, even when analyzing large, complex datasets.
• A much faster research process thanks to intuitive visualization and quick access to sources.

Working closely with the client, the Boring Owl team developed a prototype application that supports scientific data analysis. By combining advanced visualization, well-thought-out UX and flexible analytical tools, it helps researchers better understand the relationships between variables and draw conclusions from the scientific literature faster.