This repo contains materials related to a presentation given on 30 September 2026 at the conference Integrative Social-Ecological Knowledge Systems: Conceptual and Computational Foundations for Ecological Synthesis in Jena, Germany. Title Navigating research diversity in ecological synthesis: the role of openness and machine actionability Abstract Multiple research fields from a range of disciplines contribute - each in their own ways - to the study of ecological systems and their internal and external interactions. Attempts at synthesizing the various contributions within and across fields into a coherent body of knowledge thus have to take into account the diversity of ways in which these fields perform, organize and share research. In this presentation, we will explore how openness and machine actionability can assist in the process. Specifically, we will consider four contexts in which openness and machine actionability can and do affect evidence synthesis in ecology: (i) the Diamond Open Access literature, (ii) nanopublications, (iii) research software, (iv) Wikimedia projects. Within each of these contexts, we will consider examples of ecological research questions and highlight challenges and opportunities that these contexts present in terms of evidence synthesis within and across fields.

This repo hosts materials related to the Nanopublications tutorial on 15 September 2026 as part of the SEMANTiCS 2026 conference taking place in Ghent on 15-17 September 2026. Practical information about the conference - including its entire schedule - has also been represented via nanopublications. The abstract for the session: Nanopublications are small, structured, semantically rich knowledge units built entirely on Semantic Web standards and based on RDF. Published to a decentralized peer-to-peer network, they enable FAIR, machine-actionable knowledge sharing. This hands-on tutorial introduces participants to the full nanopublication lifecycle: understanding the conceptual model, creating and publishing nanopublications via the Nanodash web interface and programmatic libraries, querying the network with SPARQL through Nanopub Query, building custom templates, and understanding the trust and community layer. The tutorial builds on a successful first edition held at ESWC 2025 and incorporates major developments in the nanopublication ecosystem since then, including the second-generation Nanopub Registry and Nanopub Query services. Participants will leave with practical skills they can readily apply to their own research and data management workflows.

This repo hosts materials related to a talk given at the Grassroots of Digital Europe (GRADE) Conference Paris on 22 August 2026.

This repo hosts materials related to a presentation given on 25 June 2026 at the Beilstein Dialogues Symposium 2026 "Representation and Reality: Rethinking Scientific Models" at the Jagdschloss Niederwald near Rüdesheim, Germany. For some granular notes on the event, see https://w3id.org/spaces/BeilsteinDialogues2026. Title: How granular formalization transforms modeling into a social machine Abstract Traditionally, scientific models have been seen as coherent representations of natural systems – idealized in some ways but still mirrors of reality. Yet contemporary research practices are eroding this picture from multiple directions. Distributed computation, large-scale collaboration, and machine-readable infrastructures now allow knowledge to be continuously revised, recombined, and verified across disciplinary boundaries. This shift is changing not only how models are constructed, but the very nature of what a scientific model is.This transformation is driven by the growing formalization of knowledge into discrete, addressable and increasingly interoperable units. This granularity is becoming visible across diverse fields. For instance, in chemistry, reaction databases are organized as machine-readable graphs, where each unit of chemical interest is individually addressable. In biology, modular and version-controlled models of signaling pathways can be independently validated and recombined. In mathematics, proofs are formally verified, and each lemma used on the way is a stand-alone, executable object. In computer science, computational notebooks can blend narrative, code and data in complex and even interactive ways, turning scientific reasoning into a distributed, executable artifact.In all these cases, scientific claims – whether about parameters, observations, or logical assertions – no longer serve merely as supporting material for a final representation. Instead, they become composable, machine-actionable components of shared epistemic infrastructures. Such components can be linked, validated, reused, and extended within evolving research workflows, often across disciplinary boundaries.This development forces a fundamental philosophical reorientation. A model is no longer evaluated solely by its explanatory adequacy or empirical fit. It is also judged by additional characteristics like its interoperability, verifiability, its environmental impact and its participatory potential within a distributed network of human and machine agents. In this emerging landscape, modeling the world and modeling the knowledge process are converging, and modeling becomes a form of social machine building that I am looking forward to discuss with the other participants of the symposium.

The extraction and liberation of biodiversity knowledge from scientific literature increasingly depends on both automated and community-driven workflows. The Wikimedia ecosystem comprised of Wikipedia, Wikidata, Wikimedia Commons, Wikisource, Wikispecies and related projects has become a large, open, multilingual environment consistently ranked amongst the world’s top 10 websites. It reflects many of the challenges and opportunities outlined in the Disentis Roadmap. This contribution presents Wikimedia projects as complementary infrastructures for literature-based biodiversity evidence synthesis and examines how scientific publications enter and are transformed within this ecosystem. Biodiversity literature reaches Wikimedia through several pathways, including (1) papers cited from encyclopedic entries related to biodiversity and beyond, (2) suitably licensed digital publications or digitized out-of-copyright publications hosted in Wikisource, (3) images and other media extracted from the literature and deposited in Wikimedia Commons, (4) structured bibliographic, taxonomic and methodological metadata represented in Wikidata through both automated imports (e.g., WikiCite workflows) and community editing, and (5) taxonomic concepts curated in Wikispecies. Entities named in the literature can further propagate across Wikimedia projects, creating a rich network of linked context. We examine how these distributed contributions together form a community-maintained pipeline that captures, structures, and redistributes biodiversity knowledge from the scientific literature to the large, diverse, global and multilingual audience of Wikimedia projects. We outline how taxonomic groups, geographic regions, habitat types and publication types are represented across Wikimedia platforms, how media extraction compares to the volume of available literature, how community editing patterns introduce or mitigate various types of biases, and how these facets change over time. We also discuss Wikidata’s increasing integration with research biodiversity infrastructures like BHL, Bionomia or GBIF, and we explore the strengths and limitations of query-based evidence synthesis using Wikidata-related tools like Scholia. By situating Wikimedia workflows within the broader goals of the Disentis Roadmap, we highlight how community curation, open licensing, and machine-readable knowledge graphs can complement large-scale digitization and text-mining pipelines. Finally, we outline pathways for integrating Wikimedia-derived biodiversity information further with infrastructures such as GBIF and Biodiversity PMC, thereby enhancing the accessibility, reusability, and interoperability of literature-based biodiversity evidence. The abstract has the DOI 10.5194/wbf2026-845.

This is a presentation given at the Vom Beweis zum Bibliotheksregal 2026 workshop in Leipzig on 17 March 2026.Abstract: The FAIR principles are reshaping the curation and reuse of mathematical research data, software and publications, both within initiatives like MaRDI and far beyond. To fully leverage their potential, however, the specific challenges of mathematical communication - ranging from rendering and indexing complex notation to interlinking with research software - require equally robust publishing solutions. This talk argues that Diamond Open Access, where neither authors nor readers pay for literature access, is not merely an economic alternative but a fundamental component of addressing these challenges at the intersection of mathematical content and technology. We will explore how community-governed Diamond models (e.g., university presses, overlay journals) are uniquely positioned to let mathematical needs drive technical solutions. Unlike commercial workflows, these platforms can prioritize the integrity of mathematical content, e.g. by preserving the semantic fidelity of formulas throughout publishing workflows, enabling support for LEAN-style formalizations and more actively facilitating software discovery. Drawing on developments from zbMATH Open as well as the SeDOA and find.software projects, this session outlines actionable strategies for librarians to cultivate and integrate these Diamond ecosystems into their workflows. We conclude with a practical outlook on how Diamond infrastructures can and do serve as a key vehicle for seamlessly connecting publications with FAIR data, ensuring that the “math” in the metadata remains as usable and discoverable as the article itself.

Personal reflections on a legendary scientist, leader, builder, and mentor

This repo contains the materials for the nanopublication hackathon at the "Perspectives on Scientific Error 2026" on 13 February 2026 in Leiden, The Netherlands. Abstract Communicating and reusing estimations of uncertainty and error is critical for interpreting scientifically relevant observations but currently hampered by poor consistency and documentation. These errors arise from diverse sources, including linguistic ambiguity, computational bugs, systematic biases, unstable measurements and missing data. Despite its central role in quality control, data integration, and decision-making, uncertainty is often underreported or informally expressed. Nanopublications offer an ideal, structured, and machine-actionable framework to address this challenge by providing a scalable solution that transcends traditional, narrative-based methods. Their design combines precise assertions with rich provenance, allowing researchers to clearly state an observation or claim (e.g., regarding an error or uncertain measurement) while simultaneously linking to its full supporting history and context. Expressed as interoperable RDF triples, nanopublications are openly published on a decentralized network as FAIR Digital Objects, making this essential information easily discoverable, integratable, and processable by automated systems across various scientific domains. The Metabolomics and Analytics Center (MAC) at Leiden Academic Center for Drug Research is developing a nanopublication-based reporting framework to capture three critical uncertainty types inherent in high-throughput mass spectrometry data: those related to detection limits/sensitivity, physical/chemical instabilities (such as evaporation or oxidation), and ambiguities from structural isomers. This hackathon will leverage the MAC's developments to explore nanopublications as a universal, scalable, and machine-actionable mechanism for communicating errors, uncertainty, and related concepts across scientific domains, using metabolomics as a core case study. Participants will be introduced to nanopublication principles and decentralized publication infrastructures through hands-on experience with user-friendly interfaces and templates. To lower barriers to participation, no technical prerequisites are assumed; participants only need to authenticate via ORCID in a browser [so come prepared with your ORCID credentials at hand!]. We'll show metabolomics examples from MAC that include uncertainty and error reporting. Participants are encouraged to bring their own examples of errors, uncertainties, and data quality issues from any scholarly domain. By the end of the hackathon, participants will have created and published nanopublications describing real error and uncertainty scenarios and gained practical experience with FAIR, machine-actionable error communication.