Information Visualisation and Information Systems

Making complex scientific data accessible, interpretable and impactful

We transform complex datasets into clear, meaningful visual representations that support understanding and decision-making. Through advanced information systems and visualisation tools, we enable researchers and organisations to explore, interpret and communicate large-scale scientific data effectively.

Modern biology is generating and increasing amount of data from heterogenous data sources which is often difficult to collect, store, visualise and analyse. Solutions are therefore needed to aid this process.  

One of the main benefits of information visualization is its ability to reveal patterns and trends that might be hidden within raw data. By visually representing data, researchers can quickly identify correlations, outliers and anomalies that would normally be difficult to detect. This can lead to new insights and discoveries and help researchers gain a deeper understanding of their data.  

Visualization also contributes towards the effective communication of scientific findings and results. Visual representations, such as charts, graphs and maps convey complex information more clearly and concisely than written descriptions thus increasing understanding This is particularly important when communicating with non-specialists, policymakers and the general public.  

We have a demonstratable track history in the development of complex information systems covering tools relating to plant breeding, pre-breeding, genetics and ecological sciences and work on a number large international projects developing widely used visualisation tools. 

We have a demonstratable track history in the development of complex information systems covering tools relating to plant breeding, pre-breeding, genetics and ecological sciences and work on a number large international projects developing widely used visualization tools. 

Paul Shaw, Bioinformatician ICS
Software like GridScore help field staff collect data quickly and efficiently, removing errors and allowing data to be quickly uploaded into trials databases. 
Providing tools to allow researchers to interactively plot data can bring a deeper understanding of datasets and identify interesting results. In this case 20 years of strawberry trials data from Italy is visualized using the tools offered by Germinate
Visualisation tools like Helium allow visual interactive representations of complex plant pedigrees. In the example above 1500 UK Elite barley cultivars and their genetic relationships are shown.

What is information visualisation in scientific research?

Information visualisation involves presenting complex data in visual formats such as charts, maps and interactive dashboards. Collaborations involving James Hutton Institute Scientific Services help transform large scientific datasets into clear visual insights.

Why is data visualisation important for research?

Data visualisation helps scientists, policymakers and industry partners understand complex datasets more easily. By presenting information visually, researchers can communicate results more effectively and support evidence-based decision-making.

What types of information systems are used in research projects?

Information systems can include databases, digital platforms and analytical tools designed to store, manage and interpret large volumes of scientific data. These systems support collaborative research and knowledge sharing.

Contact for more information

Senior Research Scientist
Based in Dundee
T: +44 (0)1382 568864
Paul focuses on software development for plant genetic resources, genetics and plant breeding. He leads several projects where his research contributes towards making experimental data including plant passport, pedigree, phenotypic and genotypic data available to collaborators, research and breeding communities using a suite of database and visualization tools that his team develops. He is particularly interested in biological visualization and how data can be effectively presented, explored and accessed in logical, digestible chunks in order to gain maximum impact and insight. He is also interested in how biological entities, such as plant accessions in pedigrees, and samples in plant breeding and genetics experiments, can be visualized and modelled using graphs.