Doughnut Data Portraits: Indicator Library

Version 1.0 (October 2025)

Overview

Welcome to Doughnut Economics Action Lab’s (DEAL’s) Doughnut Data Portraits Indicator Library, a spreadsheet-based tool that compiles and harmonises data-led information from existing Doughnut Portrait diagrams and infographics.

The Indicator Library currently includes information published by more than 30 separate initiatives worldwide (and counting!). It assembles locally relevant indicators, targets, and other relevant place-based insights from each of these Doughnut Data Portraits into a single database (currently 2,000+ entries).

In this first version of the Indicator Library, the database is currently hosted on Google Sheets (also available as a Microsoft Excel spreadsheet below, although DEAL suggests using the Google Sheets version for full compatibility/formatting).

Access the Doughnut Data Portraits Indicator Library (via Google Sheets)

The Indicator Library is organised by place and structured following the Doughnut Data Portrait methodology, which collects 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).

Why use this tool?

The primary aim for DEAL in compiling this Indicator Library is to provide a tool that supports prospective analysts and practitioners in the process of creating their own Data Portrait by seeing what other initiatives have done. The database will be updated on an ongoing basis.

This is useful because the Data Portrait methodology invites analysts to select indicators and targets for each dimension that are as locally relevant as possible (rather than prescribing a specific set), but it can be helpful to understand and learn from the choices of earlier initiatives. 

The Indicator Library makes this process of understanding and learning from others easier by providing a ‘one-stop-shop’ of harmonised information, which can be filtered by individual place, or lens, or dimension (or all three!). There are also links to each of the published sources that underpin the database, for analysts that want to dive deeper into Portrait-specific details.

An additional aim of this tool is to be able to synthesise insights from the indicator selection choices applied by existing initiatives. Such stock-taking is useful for DEAL to have an overview of existing practice and to inform future iterations of our data-led methodological guidance. It may also be useful as an input for research-led analyses by others – there is a wealth of insights to be gathered from the database.

The Indicator Library should be seen as a global compendium or repository of indicators; please note the quantitative results are not directly comparable across places.

How to use this tool?

The Indicator Library database has been ‘harmonised’ by ensuring that all dimension labels, such as 'food', 'health', 'cycle water', or 'climate change', are consistent with the 44 labels used in DEAL’s current Doughnut Portrait guidance. This harmonisation process enables users to filter and sort information included within 30+ existing Portraits coherently, e.g. by place, lens, and/or dimension (all sources are listed within the 'Overview’ tab of the spreadsheet-based tool).

The information in the Indicator Library spreadsheet groups five ‘tabs’ into two sections:

1. Indicator Library

This section includes the main database as well as interactive and dynamic charts that visualise summary information. There are two tabs in this section:

• Database. This tab contains the core database of indicators and targets, structured according to the ‘four lenses’ methodology, and including more than 30 existing Doughnut Data Portraits. The database has more than 2,000 rows and it has been organised to be used with 'filters' which allow users to search the database by column headings, such as by place, by lens, and/or by dimension. For example, users can filter the data to explore indicators related to a specific dimension across places, such as food or climate change, and/or to zoom in to an individual place, such as Grenoble or Melbourne, among other possibilities (NOTE: instructions on how to enable filters are provided below).

• Charts. This tab contains dynamic visualisations of the indicator-specific information that has been filtered by users in the Database tab. These charts are updated whenever the information selected in the Database filters changes. Other charts, such as maps of geographical spread by city and country are also available.

📢 IMPORTANT: HOW TO USE FILTERS. The settings on the Google Sheet are set to 'View only' to protect the content from accidental editing and to avoid the filter settings of one user from affecting other users. 

To easily filter the database in view-only mode, click the 'Filter views' button on the 'Database' tab (between the 'Print' button and the ‘Zoom’ button in the Menu bar at the top of the tab), and select 'Create filter view'. This will create a temporary filter for you that will not affect other users. Note that the visualisations in the 'Charts' tab are dynamic -- they provide summary information for the information selected in your filters. 

Alternatively, you can also download the Microsoft Excel version and work offline. If you are unfamiliar with filters in spreadsheet-based applications, there are many resources and explainer videos available on the internet, such as this one for Google Sheets, or this one for Microsoft Excel.

2. Supplementary Materials 

This section includes additional materials that are relevant to using the database along with a template for ‘downscaling’ planetary boundaries to sub-national levels using an income-based approach. There are three tabs in this section:

• Column descriptions. This tab provides a description and an illustrative example for each of the column headings included in the Indicator Library (i.e. ‘Database’ tab).

• Concordance tables and charts. This tab provides a record of the Portrait-specific harmonisation and concordance process that was used to rename any applicable dimension labels in existing Portraits to ensure consistency with the dimension labels used in DEAL's guidance. Labels that were harmonised are indicated by coloured cells (red for the non-matching labels used in source publications and green for the renamed labels following DEAL’s dimension names). Additional summary charts and concordance information by dimension are also included. 

• Global-ecological template. This tab provides a quantitative template for the global-ecological lens that includes the main calculations used to downscale national environmental footprints and planetary boundaries using an income-based approach, with Amsterdam's data shown as an example. Although this template is not directly related to the Indicator Library, it is included as a tool that practitioners creating their own Data Portraits may find useful to adapt in order to estimate consumption-based footprints (with respect to downscaled per capita boundaries) for their places.

Access the Doughnut Data Portraits Indicator Library (via Google Sheets)

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, and inspiring ideas for transformative action.

For additional details on Portrait-specific information, the source publications of all Doughnut Data Portraits included in the Indicator Library are listed on the ‘Overview’ tab of the spreadsheet-based tool (with external links).

Other tools that may be relevant to explore include:

• Downscaling the Doughnut: Data Portraits in Action tool, for more data-led examples and practice
• What is a Doughnut Portrait?, a tool for planning the broader process of making a holistic Doughnut Portrait for your place

Acknowledgements

The Doughnut Data Portraits Indicator Library was compiled by Joel Petterson and Andrew Fanning, with valuable comments from Leonora Grcheva, Rob Shorter, and participants of cities gatherings in Bad Nauheim (2024) and Tomelilla (2025).

Suggested citation: Petterson, J and Fanning, AL (2025). Doughnut Data Portraits: Indicator Library (v1.0). Doughnut Economics Action Lab, Oxford. https://doi.org/10.64981/BOSY3928

Please do let us know if you have any comments, suggestions, or additional sources that we should add to the Indicator Library 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.