How do you create a transportation data visualization project?

1 Define your goals and audience

The first step is to define what you want to achieve with your data visualization project and who you want to reach. Do you want to inform, persuade, or inspire your audience? Do you want to show trends, patterns, relationships, or comparisons? Do you want to focus on a specific location, mode, or time period? Your goals and audience will guide your data selection, design, and presentation choices.

2 Collect and clean your data

The next step is to collect and clean your data sources. You can use various types of transportation data, such as geospatial, temporal, categorical, or numerical. You can also combine different data sources, such as public, private, or open data. However, you need to make sure that your data is accurate, consistent, and relevant for your goals and audience. You may need to filter, aggregate, or transform your data to make it ready for visualization.

3 Choose your tools and methods

The third step is to choose your tools and methods for creating and displaying your data visualization. You can use various software, platforms, or libraries, such as Tableau, Power BI, QGIS, or D3.js. You can also use different methods, such as charts, maps, dashboards, or interactive elements. You need to consider the advantages and limitations of each tool and method, as well as the compatibility and accessibility of your data visualization.

4 Design your data visualization

The fourth step is to design your data visualization according to the principles of visual perception, aesthetics, and storytelling. You need to select the appropriate visual elements, such as colors, shapes, sizes, or symbols, to represent your data and highlight the key insights. You also need to arrange the visual elements in a logical and intuitive way, using labels, legends, titles, or annotations, to guide your audience and convey your message.

5 Test and refine your data visualization

The fifth step is to test and refine your data visualization before you share it with your audience. You need to check the accuracy, clarity, and effectiveness of your data visualization, as well as the usability and functionality of your tools and methods. You can use various techniques, such as feedback, evaluation, or iteration, to identify and fix any errors, gaps, or improvements in your data visualization.

6 Share and present your data visualization

The final step is to share and present your data visualization with your audience. You need to choose the appropriate format and channel for your data visualization, such as online, print, or live. You also need to consider the context and expectations of your audience, such as their background, interests, or questions. You can use various strategies, such as narration, animation, or interaction, to engage your audience and communicate your data visualization effectively.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?