Colandr 2.0: reflections on a near-decade of free and open evidence synthesis tooling development, management, and use

The exponential growth of scientific literature—doubling roughly every nine years—has made it increasingly difficult for researchers and decision-makers to locate, assess, and synthesize the evidence needed for sound policy and practice. Systematic maps and systematic reviews offer robust, unbiased ways to answer “what works?” but today they depend on manual search and screening workflows that are slow, costly, and vulnerable to human error. The result is a bottleneck: high-quality, up-to-date evidence syntheses are often too labor-intensive to produce at the pace conservation challenges demand.

This talk and demo presents an open, community-driven approach to lowering that bottleneck using human-in-the-loop machine learning and transparent evidence-management tooling. In 2018, DataKind and the the Science for Nature and People Partnership, built two free and open-access, web-based workflows for computer-assisted paper screening and evidence management, integrated into a single collaborative application (colandrapp.com). The platform combines active-learning prioritization, reproducible labeling, and interactive visualization to help teams rapidly identify relevant studies from tens of thousands of documents, extract key metadata, and generate portable, shareable review outputs. All components are designed to support open research practices: auditable decision trails, exportable datasets, and interoperability with downstream synthesis and visualization tools. Now, in 2026, we are releasing a significant update to Colandr that ensures the tool continues to be functional and sustainable. Colandr is supported by a global community of researchers and volunteers (colandrcommunity.com) and this session will highlight the additional open source solutions that have been built on top of the Colandr stack in addition to the Colandr product updates.

We aim to engage the FOSDEM community around a concrete open research challenge: building trustworthy, extensible tools that keep evidence synthesis fast, reproducible, and accessible. Participants will leave with a clear view of the platform’s capabilities, the design decisions behind it, and a set of well-scoped technical and research directions where open-source contributors can meaningfully push the state of practice forward.