Doughnut Data Portraits: Visualiser & Data Hub

Version 1.0 (December 2025)

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Overview

Welcome to Doughnut Economics Action Lab’s (DEAL’s) Doughnut Data Portraits Visualiser & Data Hub, an online and interactive tool that allows users to create their own place-based Doughnut diagrams, based on locally relevant, data-led information.

Access the Doughnut Data Portraits Visualiser & Data Hub

In this first version of the Visualiser & Data Hub, users can add indicators that they have collected following the Doughnut Data Portrait methodology, which offers an approach to compile place-based targets and indicators within 44 dimensions grouped across four crucial ‘lenses’ that arise from combining two domains (social and ecological) and two scales (local and global).

The data entered by users is visualised in a basic Doughnut diagram, which can be saved as an image or as an editable graphic. Users can also explore the indicators and Doughnut diagrams of other public Portrait initiatives on the platform, and, crucially, choose to make their own work visible for others to learn from.

Why use this tool?

The primary aim for DEAL in creating this online Visualiser & Data Hub is to provide a light and flexible Doughnut visualisation tool that supports prospective analysts and practitioners in the process of creating their own Data Portrait. 

By lightening the process of creating place-based Doughnut visualisations that are consistent with the Portrait methodology, and making visible the data selection choices of other initiatives, DEAL envisions this tool will be particularly useful in two related ways, especially during the initial stages of creating a Data Portrait. 

First, the data entry process provides a structure for practitioners to compile indicators both within individual Doughnut dimensions, such as food and climate change, and across the local and global scales of the Doughnut Portrait framework. This structure clarifies the scope and amount of information required for visualising a Portrait during the early stages of data exploration. 

Second, the basic Doughnut diagrams created by this tool with local data can help inform internal conversations that develop a collective understanding and 'buy-in' for the Doughnut Portrait among practitioners and stakeholders. DEAL imagines the initial visual outputs could also serve to identify preliminary gaps in knowledge and/or data, which can inform the purpose and feasibility of creating a Data Portrait by the project team as well as the process of identifying who should be involved.

NOTE: Although DEAL does not expect the basic Doughnut diagrams to serve as publication-quality figures, the ability to download as an editable vector graphic can be a useful data-led input to creating such figures (e.g. by manually adding additional elements, labels, and other finishing touches using graphic design software, such as Inkscape or Adobe Illustrator).

Finally, DEAL is excited to explore the possibilities opened up by this new online Visualiser & Data Hub. An obvious next step is to make the existing Portrait initiatives, currently compiled in the Doughnut Data Portraits Indicator Library, visible on the Hub. Another idea is to use the online platform as a tool within applied Doughnut Data training sessions and courses, or even place-based Doughnut Portrait 'hackathons'. Or we can imagine expanding the scope of the platform to provide a 'one-stop-shop' for all Doughnut metrics, such as those available at national scale and at global scale. Of course, the current version of the online platform is a first pass that is far from perfect -- DEAL looks forward to hearing feedback and suggestions for further improvement in subsequent versions.

How to use this tool

( NOTE: DEAL is currently preparing an explainer video and that provides step-by-step instructions on how to use this tool, which will be available soon.)

The Doughnut Portrait Visualiser & Data Hub is an online platform hosted at https://doughnut-visualiser.doughnuteconomics.org/.

Anyone with access to the internet can navigate to this website and explore any publicly available Doughnut Portraits. In order to input your own data to compile and visualise a Doughnut Portrait (which can be private/in-progress or public), there are three main steps:

1. Create a user account

To create a Portrait, you need to create a (free) account and be logged in. For technical reasons, user profiles on the Visualiser & Data Hub are managed separately from membership on the primary DEAL platform (i.e. you have to create a new account even if you are already a member of the DEAL Community at https://doughnuteconomics.org).

In addition to DEAL's Terms of Use, Privacy notice, and Principles & guidelines, there are some additional boundaries we ask you to respect when using the Doughnut Portrait Visualiser & Data Hub, shown in the image below. Once you have agreed to the Terms and Conditions, your user account request will be reviewed by an administrator.

 

2. Create a Portrait

Once your account has been approved, you can start creating your own Doughnut Data Portrait by clicking 'Add New Portrait' on the Portrait page. Creating a Portrait on the Visualiser & Data Hub involves two steps:

Portrait Information. On this page, you input basic information, including the Portrait name, location (linked to the map), a nice photo of your place, a contact email, brief description (including relevant links to external websites), and visibility status (private or public). All of this portrait information can be updated at any time.

Data Entry. This is the core page where users input their locally relevant indicators by adding rows linked to specific Doughnut dimensions, following the broad structure of the four lenses Doughnut Portrait methodology. This is the data-led information that is visualised in a Doughnut.

IMPORTANT NOTE: The online Visualiser & Data Hub tool assumes practitioners are fairly familiar with the Doughnut Portraits methodology, especially the descriptions and terminology used in the Doughnut Data Portraits: A Methodological Guide tool. A decent amount of background research, data exploration, and documentation will be required before analysts are ready to input meaningful indicators at the Data Entry stage.

There are separate data entry tabs for each of the four lenses (i.e. local-social, local-ecological, global-social, and global-ecological).

Within each lens-specific data table, users can add individual observations (rows) that include five variables (columns):

• Dimension. The Dimension variable includes:
  •  a dropdown menu to select the lens-specific dimension, as labelled in DEAL’s current Doughnut Portrait guidance
  • an optional 'custom label' field, which allows users to input a custom label that will be visualised instead of the default DEAL dimension label in English.
• Indicator. The Indicator variable is an open field for users to input a concise description of their locally relevant indicator. There is at least one illustrative indicator description that appears when this input field is clicked, but this is just to provide a bit of dimension-specific guidance. 
• Value. The Value variable is an open field for users to input the current value of the chosen indicator, expressed numerically. 
• Target. The Target variable is an open field for users to input the desired value of the chosen indicator, expressed numerically. 
• Ratio. The Ratio variable is a normalised metric of the indicator's current value with respect to its target value, expressed numerically. The Ratio variable contains the numerical values that are used to visualise wedges in the Doughnut diagram, so it is important to note some technical conditions:
  • The Ratio field will be automatically filled by taking a simple ratio of the value and target fields, if these have been inputted (i.e. Ratio = Value / Target). However, the user can override this automated value by inputting a different value in the field.
  • For the social lenses, the visualiser expects a Ratio value that ranges from a minimum of zero to a maximum of one, where zero represents total deprivation and one represents the target social boundary. Depending on the indicator, analysts may need to apply some numerical transformations of indicator Value and Target in order to calculate Ratio values in the format expected by the Visualiser. For example, an indicator value of 20% population experiencing food insecurity (with a target of 0%) would have to be transformed 80% not experiencing food insecurity (with a target of 100%) for normalisation purposes (i.e. Ratio = 80 / 100 = 0.8). 
  • For the ecological lenses, the visualiser expects a Ratio value that ranges from a minimum of zero to no upper bound, where zero represents no ecological pressure, one represents the target ecological boundary, and values greater than one represent increasing extent of ecological overshoot. Similar to indicators in the social lens, some numerical transformations of Value and Target may be needed to calculate Ratio values in the format expected by the Visualiser.
  • Notably, DEAL emphasises that framing the Ratio values as described in the points above is solely related to the technical requirements of visualising wedges as expected by the Visualiser. Users are free to express the indicator descriptions, values, and targets in the frames and units desired. In fact, DEAL recommends framing indicators in deprivation-based terms for social indicators, and overshoot-based terms for ecological indicators.

3. View Portrait

From within the Portrait Editor pages (i.e. 'Portrait Information' or 'Data Entry'), save any relevant changes, and click 'View Portrait' to see the resulting Doughnut diagram and data record.   

This page is also the public-facing Portrait profile that other users will land on if visibility is set to 'Public'. If you are viewing a Portrait that you created, there will be a blue 'Edit Portrait' button that takes you into the Portrait Editor.

 

The Portrait Viewer includes the title and brief description along with an option to toggle between two view options:

Show Doughnut. The default view, which shows the Doughnut Portrait diagram rendered by the Visualiser with wedge lengths corresponding to the Ratio data inputted. Users can zoom in/out and download the diagram as either an image file (.png) or as an editable vector file (.svg). 

Some important points on how the Doughnut Visualiser renders data across the four lenses:

• Local-social. Indicators for the local-social dimensions are shown in light red under the Social Foundation ring of the Doughnut. To render the local-social lens with no missing data, there must be at least 12 local-social indicators. Three additional local-social dimensions - mobility, community, and culture - can be selected (and renamed) during Data Entry to yield a maximum number of 15 local-social dimensions.
• Local-ecological. Indicators for the local-ecological dimensions are shown in light red around the bottom half of the Ecological Ceiling ring. To render the local-ecological lens with no missing data, all eight of the local-ecological dimensions must include indicators.
• Global-social. Indicators for the global-social dimensions are shown in dark red under the Social Foundation ring of the Doughnut. Even if no global-social indicators are included, the Visualiser does not show 'missing data' wedges for this lens. Relatively few Portrait initiatives quantify this lens at all, so DEAL encourages the inclusion of even a single global-social metric as a step in the right direction towards normalising the practice of making impacts on the wellbeing of workers and communities abroad visible. Three additional global-social dimensions - supply chains, social footprints, and lifestyle patterns - can be selected (and renamed) during Data Entry to yield a maximum number of 15 global-social dimensions.
• Global-ecological. Indicators for the global-ecological dimensions are shown in dark red around the upper half of the Ecological Ceiling ring. To render the local-ecological lens with no missing data, all nine of the global-ecological dimensions (i.e. planetary boundaries) must include indicators.   
• Shared social dimensions across local and global scales. In order to optimise space within the social foundation, if any indicators are inputted with a shared dimension across the local-social lens and the global-social lens, then they are shown side-by-side (i.e. by using half of the wedge area in light red for local and half in dark red for global). In contrast, the ecological lenses do not have shared dimensions across the local and global scales within DEAL's current guidance, so this feature is not applied for the ecological indicators. 

 

Show Data Table. This view shows a table of all the indicators that have been added to the Portrait, including their respective lens, dimensions (as per DEAL's default labels), custom labels (if any), values, targets, and normalised ratios. Users can click on individual indicator descriptions to see the whole text, in case it is not visible due to space constraints. The data table can also be downloaded as a speadsheet file (.csv).

DEAL notes that this table can serve as a minimal record of data inputs, but it does not include sufficient information to replicate the analysis, notably due to a lack of data sources. Analysts should maintain a separate document that describes indicator-specific details, such as selection criteria, methods, and data sources. Such additional information, along with any other relevant outputs, can be posted separately and included as a link in the Portrait description. Examples of indicator-specific documentation can be found here and here.
 

Where to go next

DEAL notes that the results underpinning Data Portrait visualisations usually form part of a broader report or a set of written materials that often provide valuable place-based context, rich justifications for locally relevant targets & indicators, participatory methods, and inspiring ideas for transformative action.

Other relevant tools to explore include:

• Downscaling the Doughnut: Data Portraits in Action tool, which serves as a portal for the Doughnut Data Portrait methodology tools and resources, and as a repository for data-led case studies and practice.
• Doughnut Data Portraits: A Methodological Guide, which provides guidelines and approaches to select targets and indicators across the four lenses.
• Doughnut Data Portraits: Indicator Library, which is a harmonised database of 30+ existing Doughnut Data Portraits worldwide with thousands of indicators and targets structured according to the four lenses methodology.
• What is a Doughnut Portrait?, a tool for planning the broader process of making a holistic Doughnut Portrait for your place.

Acknowledgements

The online Doughnut Portraits Visualiser & Data Hub is an ongoing collaboration between Doughnut Economics Action Lab (DEAL) and InceptionU, a web-development learning organisation co-founded by DEAL Community member Greg Hart.

This version of the Doughnut Portraits Visualiser & Data Hub has been co-created by Andrew Fanning at DEAL, lead developer Tony Enerson at InceptionU, and early-career developers Nardos Tesfalem, Mohamed Afilal, Jenna Kersch, Michelle Loewen, Naiara Lopes, and Sarfraz Qazi at InceptionU, with valuable comments and contributions from Leonora Grcheva, Rob Shorter, Karn Spydar Lee Bianco, Greg Hart, and Kate Raworth.

Please do let us know if you have any comments, suggestions, or additional sources that we should add to the backlog of the Visualiser & Data Hub by sending a message via the contact page and select 'Research & Data Analysis' from the category options. We hope this tool is useful for you, and look forward to your feedback.