There were several early projects starting our work on what has later become the Hi Knowledge initiative. In March 2010, we organised the workshop “Tackling the emerging crisis of invasion biology: How can ecological theory, experiments, and field studies be combined to achieve major progress?” in Benediktbeuern, Germany, in the context of the specialist group “Theory in Ecology” of the Ecological Society of Germany, Austria and Switzerland (GfÖ; see Heger et al. 2013). The idea of the hierarchy-of-hypotheses (HoH) approach emerged from fruitful discussions during this workshop and our parallel work on the study “Support for major hypotheses in invasion biology is uneven and declining” (Jeschke et al. 2012), with the main funder Deutsche Forschungsgemeinschaft (DFG) as part of the project “Combining bottom-up and top-down analyses to test fundamental concepts in invasion biology”.

A DFG Heisenberg grant from from 2014 to 2019 allowed us to develop and apply network analysis and web-based approaches to synthesize hypotheses and data in invasion biology and related disciplines. During this time period, we worked on the book “Invasion Biology: Hypotheses and Evidence” (Jeschke & Heger 2018). We thought it would be cool to have an interactive website complementing the book, and we decided to call this website “Hi Knowledge”. In parallel, we worked on “Dark Knowledge” (Jeschke et al. 2019), and Martin Enders had started his doctoral thesis “Creating and evaluating hypothesis networks in invasion biology” funded by the Foundation of German Business (sdw) and the BMBF in the context of the project Bridging in Biodiversity Science. Martin Enders and collaborators explored and evaluated different approaches to create hypothesis networks, using invasion biology as an example. Two of these hypothesis networks can be interactively explored in our Hi Knowledge website: (i) Enders & Jeschke (2018), which was published in the first version of the Hi Knowledge website to complement the above-mentioned book, and (ii) Enders et al. (2020).

In 2017 and 2018, we organised a series of three symposia in Hanover, Germany, funded by the VolkswagenStiftung with a focus on the HoH approach. We had inspiring discussions in these symposia with researchers from different fields as well as artists and designers. Several ideas emerged from these discussions, which also allowed us to further improve the HoH approach (Heger et al. 2021).

In the enKORE project (Jeschke et al. 2021), we took the Hi Knowledge initiative to the next level by developing a range of interactive tools that allow users to (i) find papers and data in invasion science, (ii) explore the field, (iii) analyse and synthesize and (iv) contribute and curate data and information. These tools can now be explored and used on our website. While the enKORE project focused on invasion science, we also started to develop tools for other fields, in particular urban ecology (Lokatis et al. 2023) and restoration ecology (Heger et al. 2024). In a workshop in late 2023, we additionally explored opportunities to use the Hi Knowledge approach for meta-ecology theory. Please get in touch if you’d like to join our initiative and perhaps apply such an approach in other fields, so that we can jointly build an open, zoomable atlas across research fields.

In the INAS project (https://inas-argumentation.github.io/; Heger et al. 2022), which is part of the Robust Argumentation Machines program by the DFG, we investigate basic questions related to knowledge synthesis in invasion biology. In an interdisciplinary team, we combine methods from natural language processing, knowledge representation and the semantic web to explore how to: (i) represent concrete and more abstract knowledge on hypotheses and their underlying concepts; (ii) automatically compute semantic relations between hypotheses made in scientific publications, and between hypotheses and datasets; and (iii) interactively support users in developing their own hypothesis based on these resources.

Recent advances in data science and AI technology may offer novel ways of dealing with complexity in ecology and may allow the development of knowledge synthesis tools that can manage context dependence. Especially promising seems the idea to bring together advanced AI-based technologies with conceptual causal models, because this may allow moving beyond pure pattern recognition towards causal inference. In an interdisciplinary setting including ecologists, data scientists, computational linguists and philosophers, the Resident Group at the Center for Interdisciplinary Research (ZiF) in Bielefeld titled “Mapping Evidence to Theory in Ecology: Addressing the Challenges of Generalization and Causality” explores ways for combining ecological theory represented in the form of causal network graphs with evidence found in scientific papers. The vision is that complex, multifactorial hypotheses about ecological mechanisms would become the basis of a digital atlas of knowledge, and in this atlas the available empirical evidence would be mapped on these hypotheses to allow for case-specific explanations and predictions.