Causal Loop? Do It Yourself! (CL-DIY): An open-source and browser-based editor to share causal loop diagrams
Causal loop diagrams (CLDs) are a qualitative system dynamics method. They show the variables in a system, the causal links between them and the polarity of each link, and they make reinforcing and balancing feedback loops visible. CLDs are often built together with stakeholders in group model building and other participatory settings. There, the diagram is a shared object that people reorganise, annotate and argue over. However, after a participatory session, the CLD usually ends up in specialist modelling software that participants cannot easily open, let alone change. We therefore developed CL-DIY (Causal Loop? Do It Yourself!), an open-source, browser-based editor for building, exploring and refining CLDs. It lets a group revisit its diagram after the session: walk through it loop by loop, correct it themselves, and keep it as a record of what they decided and why. CL-DIY does this with a single file that anyone can open in a web browser, with no installation, no account and no server, so the data stays with its owners. In that file, participants can edit the diagram group variables, trace and label feedback loops, and note the reason for each change. The result can be shared, edited further, archived alongside a publication and exchanged with other system dynamics tools. The most recent version of CL-DIY can always be found on GitHub.
Authors
- Spencer Moore (ORCID: https://orcid.org/0000-0002-1229-9578)
- Ciska Ulug (ORCID: https://orcid.org/0000-0003-4764-6143)
- Kristina Thompson (ORCID: https://orcid.org/0000-0002-2570-3365)
- Jiri Kaan (ORCID: https://orcid.org/0000-0003-2668-5303)
- Annemarie Wagemakers (ORCID: https://orcid.org/0000-0002-1212-6888)
Institutions
- Wageningen University & Research (NL)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-10-28
- DOI
- https://doi.org/10.5281/zenodo.23733353
- Primary Topic
- Complex Systems and Decision Making
- Type
- preprint
Funders
- ZonMw