You can process, clean, organise, transform, analyse, interpret and visualise your research data using software or computational methods.

Prepare data

Preparing data for analysis can involve identifying and fixing errors or inconsistencies, removing duplicates, reformatting, combining, splitting and other cleaning and wrangling activities.

These tools will help prepare data:

Analyse data

Analyse data with these tools:

  • Gale Digital Scholar Lab— analyse text from historical primary source collections
  • ArcGIS—geographic information and mapping
  • Leximancer—textual analysis and visualisation
  • Ansys—engineering simulation and 3D design
  • Nvivo—qualitative analysis of texts
  • Ttext and data miningableau—analytics and business intelligence
  • MATLAB —mathematics and technical computing
  • STATA—statistics and data science.

Find these and other tools via the Software catalogue.

Analyse large datasets with the power of Griffith's High Performance Computing (HPC).

Learn from the Programming Historian how to use digital tools, techniques and workflows that help facilitate research in any discipline.

Explore tutorials

Find tools and tutorials on the GLAM Workbench, to work with data from galleries, libraries, archives, and museums.

Get started

Visualise data

Visualising data can help you communicate the meaning of your research.

Use these open source tools to visualise data:

  • Voyant tools—reading and analysis for digital texts
  • RawGraphs—create visualisations for complex data
  • Gephi—network analysis and visualisations
  • Cytoscape—complex network analysis and visualisations
  • R or Python.

Work through this tutorial to start using MS Excel, Voyant tools, and RAWGraphs for visualising data.

Data visualisation basics (Griffith login required)

Find a graph for your data, and the code to build it.

Explore Data to Viz


Attend a workshop that is targeted to support you through every stage of the research lifecycle.

Explore workshops

Bring your laptop to Hacky Hour for hands-on support in analysis languages including R, Python, ArcGIS and more.

Hacky Hour

View training offered by Queensland Cyber Infrastructure Foundation.

Learn more

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Find us in the libraries or contact us by phone or online.