Our Data Visualisation Competition is back!

The Data Lab Community’s Data Visualisation Competition returns for 2025!

Whether you are a seasoned data visualisation pro, or you’re earlier in your journey and looking to learn about data viz whilst working on an interesting project, this competition is for you!

Taking part in the competition provides the ideal opportunity to hone your skills, demonstrate your abilities and raise your profile to a global community of data and AI professionals, students and enthusiasts.

Top 3 finalists will be invited to DataFest 2026, with a top prize worth over £500 up for grabs!

Don’t forget to register your interest if you think you’ve got what it takes to be crowned the winner!

You can submit your data visualisation from 26th November 2025 – 16th January 2026.

What is the data visualisation competition?

To take part in the competition you will be tasked with creating a data visualisation that tells a compelling story using real-world data. Participants design and submit their projects, which are judged on clarity and communication, creativity and design, and data analysis, understanding and accuracy.

Shortlisted entries will be showcased at DataFest 2026, with prizes awarded to the top projects. The competition is open to everyone – from students and beginners to experienced data professionals. You can enter as an individual or a team.

The Challenge: Communicate the co-benefits of climate action

For this year’s competition, we’re going to explore one of the biggest challenges facing humankind today – climate change.

Climate action aimed at addressing climate change is often talked about in terms of costs, trade-offs, or distant impacts that can be hard to quantify, and are often difficult for the average person to appreciate in their daily lives.

The UK Co-benefits Atlas reveals something different: the positive and often hidden benefits that climate action can bring to our health, communities, economy, and environment.

Your challenge is to uncover and visualise a story from the data that has the potential to shift perspectives and influence beliefs.

You are tasked with choosing one or more of the 11 co-benefits modelled in the data, and using the data to create a compelling, persuasive argument that highlights the benefits of climate action to a specific audience of your choice (e.g. a local council, a business leader, a community group).

You should consider:

• Who is your audience? – For example, a local community group, a business leader, a friend.
• What’s the story? – What insights can you glean from the data? What message are you trying to communicate with your visualisation?
• How will you tell your story? – What visualisation tools and techniques will you employ to get your point across? – E.g. maps, infographics, interactive tools, or something else?

The goal of the challenge isn’t just to show the data; your objective is to use data to tell a story that helps communicate the benefits of climate action to your chosen audience.

For example, you could decide to create a visualisation that helps:

• A local community group trying to decide if climate projects matter
• A business executive unsure about their green investments
• A local council who is unsure whether climate action will benefit their community
• A friend who needs convinced of the benefits of climate action
• A climate skeptic who thinks climate action is an expensive waste of money

What dataset should I use?

Provided by the team at Edinburgh Climate Change Institute (ECCI), you will be given access to the primary dataset that is used to power The UK Co-Benefits Atlas – an interactive visual interface for communicating the co-benefits of reaching net zero across the UK.

Climate actions are designed to lower greenhouse gas (GHG) emissions but the gains for society reach further. The actions we need to undertake to reduce fossil fuel emissions often have significant and positive impacts on health, economy and society, as well as the environment. The team at ECCI have been modelling these wider benefits (‘co-benefits’) to make the positive case for climate action.

These values are estimates of these wider socio-economic impacts from the UK reaching net zero by 2050. The data are monetised figures, representing the value to individuals and society across 11 co-benefit types from following the actions set out by the UK Climate Change Committee. They represent improved quality of life, reduced air pollution, better health outcomes and safer, more comfortable homes. They have been modelled at the local level to include local context, for example rurality, wealth and demographics.

The data is provided at 3 different resolutions to allow you to choose the depth and granularity that you are most comfortable with. If you are confident with data visualisation you may wish to use the full, detailed dataset. If you are just starting out with data viz, one of the smaller, less detailed datasets may be more suitable for you.

Can I use other data?

In addition to the provided dataset, you are also welcome and encouraged to link other existing datasets to your project. For example, you may wish to include insights from data related to health, poverty, environment and examine any overlaps or patterns to help tell your story.

Some excellent repositories of Open Data include find.data.gov.scot, Open Data Scotland, UK Data Service, The World Bank, Data.Gov.

How will the competition be judged?

Judges will evaluate the data visualisations based on three main criteria:

1. Clarity and communication  
Does the visualisation clearly communicate the key insights from the data?

Entries should be clear, concise engaging and impactful. Judges should assess the storytelling’s impact and how well the visualisation guides the viewer to understand the message.

2. Creativity & Design 
The design of the visualisation should be visually appealing, easy to read and interpret, and should incorporate appropriate colours, fonts, and visual elements. It should also be relevant to the content and should be designed with accessibility in mind.

Judges will consider innovative approaches, thoughtful and accessible use of colour, as well as creativity in layout and design.

3. Data Analysis, understanding and accuracy 
Is the data analysed appropriately and accurately?

Judges should assess where the data analysis demonstrates a solid understanding of the dataset and whether the data is represented truthfully and ethically.

Entrants must appropriately credit their data sources and should use reliable sources. You are responsible for ensuring you have the appropriate permissions to use the data.

All entries will be judged on the above criteria by our panel of industry experts with years of experience in data analysis, visualisation, and accessibility. 

How do I enter?

Step 1

Complete this form to register your interest in the competition.

Step 2

Download the data and start creating your data visualisation. You can access the data via this Google Drive folder.

Step 3

Once you have completed your Data Visualisation project, you must complete the Project Submission Form. In this form, you should provide your submission details, including the dataset(s) you have used and answer some additional questions. For this form, you will need the following:

• Name
• Contact details
• Details of your data visualisation project
• Your completed visualisation
• Agreement to our terms and conditions

Submit your data visualisation project either as a PDF (static visualisations) or a public link (interactive visualisations). It is your responsibility to ensure interactive visualisations can be viewed/accessed by the judging panel.

The Project Submission Form will be available from the 26th November 2025 – 16th January 2026.

Step 4

Our team will review all entries and a shortlist will be invited to the final round where you will have the opportunity to present your data visualisation to the judging panel during an online session on Zoom.

This session will take place  on Thurs 29th January from 09:30-13:00 GMT.

Step 5

The top 3 finalists will be invited to DataFest in Edinburgh on the 27-28th May 2026.

Terms and Conditions of Entry

Terms and Conditions of Entry:

• Entries are open to members of The Data Lab Community. If you are not a member, it’s easy and free to join. Sign up here.
• The competition will close at 23:59 on Friday 16th January 2026, any entries received after this time will not be accepted.
• Groups are permitted to enter; however, any prizes will be awarded to the lead submitter. It is then up to your group how any prize is shared. Groups must be made up of individuals and cannot be an organisation.
• You must use the provided dataset. Any additional datasets used must be cited.
• All work submitted to The Data Lab must be your own and must not breach the rights of any third party, including intellectual property rights and data protection.
• By entering you give The Data Lab the non-exclusive right to publish your work and/or excerpts of it (e.g., social media, website, emails etc.). You agree that The Data Lab may, but is not required to, make your entry available on its social media, websites or other media in connection with the competition.
• The decision of The Data Lab as to who has won the competition is final.
• The Data Lab reserves the right to hold void, suspend, cancel or amend the competition where it becomes necessary to do so.

Competition Privacy Statement:

• The Data Lab will process your name and contact details for the purpose of enabling you to enter the competition and communicate about it with you.
• The Data Lab may make public your name in connection with your work and / or in relation to announcing you as the winner. This is on the basis of our legitimate interests, those interests being that we wish to publicise this competition and give credit to entrants / the winner. Please contact The Data Lab Community by email to community@thedatalab.com if you would not like your name to be announced / published.
• For further information as to how personal data is processed in connection with The Data Lab Community, please see the privacy notice: here.