Data Visualisation
Data visualisation at North-West University (NWU) involves using visual representations to explore, analyse, and communicate data for various research and educational purposes. Data visualisation provides a powerful way to share data-driven findings, motivate analyses, and detect flaws. A data visualisation workflow outlines the steps to create meaningful and effective visualisations from raw data. This process ensures that data is translated into visual representations that can be easily understood and provide insights.
Data Visualisation Workflow
Student Projects:
We encourage students to incorporate data visualisation into their coursework and research projects. This helps build skills and creates a portfolio of work.
Data Collection and Preparation
- Gather the raw data from various sources.
- Clean and preprocess the data by handling missing values, outliers, and formatting issues.
- Perform data transformation and aggregation if necessary.
| Type of Data | Format |
|---|---|
| Images | PNG and SVG |
| Web Pages | HTML |
| Tabular Data | XML, CSV and JSON |
Data Exploration and Analysis
- Conduct exploratory data analysis (EDA) to gain a deeper understanding of the dataset.
- Identify patterns, trends, and relationships within the data.
| Type of Analysis | Data Visualisation Tools |
|---|---|
| Statistical Analysis | Graphs and Infographics |
| Text Analysis | World Cloud, Word Tree, Collocation Graph |
| Geospatial analysis | Map, Network Graph |
Select Visualisation Types
- Choose the appropriate visualisation types based on the nature of the data and the objectives.
- Common visualisation types include bar charts, line graphs, scatter plots, pie charts, heat maps, and more.
Design Layout and Structure
- Plan the visualisation layout, including the arrangement of charts and graphs on the page.
- Decide on the colour scheme, fonts, and other visual elements.
Create Visualisations
- Use data visualisation tools or programming libraries (e.g., D3.js, Matplotlib, Tableau, Excel) to create the visualisations.
- Ensure that the visualisations accurately represent the data.
Interactivity (if applicable)
- Add interactive elements to allow users to explore the data further. This can include tooltips, filters, and drill-down options.
Labelling and Annotations
- Provide clear labels for axes, data points, and legends.
- Add annotations and captions to explain key insights or trends.
Testing and Iteration
- Test the visualisations with potential users or stakeholders to gather feedback.
- Iterate and make improvements based on feedback.
Optimize for Performance
- Optimize the performance of the visualisation, especially for large datasets.
- Ensure that the visualisation loads quickly and is responsive.
Data Storytelling
- Create a narrative or story around the visualisation to explain the insights and findings.
- Ensure that the visualisation supports the narrative.
Sharing and Distribution
- Decide on the platform or medium for sharing the visualisation, such as a web page, report, or presentation.
- Publish or distribute the visualisation to the intended audience on Dayta Ya Rona.
Training and Workshops
We offer training sessions and workshops to students, faculty, and staff on data visualisation techniques and tools. These include basic visualisation principles, software-specific training, and advanced visualisation methods.
Collaboration
The NWU encourages interdisciplinary collaboration among departments and research groups. Data visualisation can often benefit from expertise across multiple domains.
Data Repository
Researchers can access and share datasets for visualisation and analysis on the data repository or portal Dayta Ya Rona.
Data Ethics and Privacy
Ensure that data privacy and ethical considerations are followed, especially when dealing with sensitive or private data.
Public Engagement
Use data visualisation to engage with the broader public. Public lectures, workshops, and infographics can help disseminate research findings to a broader audience.
Service
- Contact us for bookings to use our visualisation wall.
- Mahikeng Campus, Ground floor, Room G15
CONTACT
Songezo Mpikashe
Senior Librarian: Institutional Repositories and
Digital Scholarship
+27 (0)18 389 2352