Meetings

Recent preprints

• Aug 9, 2026

  Variant representation in RDF

  During the International SWAT4HCLS conference held on 24-27th February 2025 in Barcelona (Spain), we detected an emerging number of novel RDF models to represent variant information in genomic datasets potentially hindering data reuse. We tackled the question how semantic representations can enhance the interoperability of variant data for clinical applications. Here we report our initial results on genomic variant schema alignment. less than 1 minute read
• Aug 9, 2026

  Variant annotation in RDF for clinical trials matching

  Precision oncology depends on semantic, interoperable representations of genomic variants (GV) - particularly structural variants (SVs) - to match patients with clinical trials. In this exploratory project, we investigated the use of RDF and the GA4GH VRS Schema to standardize variant annotations and integrate them with clinical trial data. Our work, developed in collaboration with the Pangenome Graphs and Platform for Precision Medicine groups, prototypes an RDF-based data harmonization that paves the way for improved semantic interoperability in precision medicine, especially for cancer research and AI-driven discovery. less than 1 minute read
• Jul 29, 2026

  Schema-Driven Generation of Synthetic HL7 FHIR RDF Data from Shape Expressions (ShEx)

  We describe how synthetic HL7 FHIR data in RDF was produced directly from Shape Expressions (ShEx), using the authoritative FHIR R4 ShEx schema as the sole source of domain structure. Rather than encoding clinical knowledge in a domain-specific simulator, we drive generation from the published shapes: a schema-driven generator (rudof generate) consumes them, and a small configuration file controls scale, cardinalities, and value generation. This note reports the method - schema selection, a minimal schema preparation step, the generator configuration, and the invocation - so that the process is reproducible. less than 1 minute read
• Jul 26, 2026

  Measure before you rewrite: ablation-driven redesign of LLM-facing RDF schema documentation in TogoMCP

  MIE files are per-database YAML documents that TogoMCP supplies to a large language model at query time so it can compose SPARQL against the DBCLS RDF Portal. Ours had grown to eleven sections, semi-automatically generated for each of 36 databases and reviewed by hand. Each section had been introduced in response to a systematic query failure observed in use — sound practice, but it left open whether any section still earned its tokens once the other ten were present. We measured that, in eighteen ablation conditions across four families: is a section necessary, is a functional group necessary, is the whole document worth anything, and is any one group sufficient alone. No single section and no single group is necessary. Removing the entire document costs 0.9 points out of 20, and the query-construction group alone recovers 99% of that — the whole is worth roughly 2.7 times the sum of its parts, the signature of heavy redundancy. We rebuilt the format around that evidence, making the verified executable example the atomic unit: 36 files, 303 examples, each 29–65% smaller than the file it replaces. A pre-registered equivalence run over 100 benchmark questions finds v3 statistically indistinguishable from v2 in answer quality (+0.29/20, 95% CI [-0.09, +0.68]) while using 15% fewer input tokens, costing 15% less and running 6% faster, with the factoid-question score up a full point. We also report eight measurement traps that faked or destroyed signal, and one budgeting error worth more than the results: we spent the most on the least informative experiment, and say what we would do instead. 1 minute read
• Jul 8, 2026

  Maintaining and refining the Tidyomics ecosystem: enhancing core packages and interoperability for EuroBioc2026

  The Tidyomics ecosystem facilitates the manipulation of computational omics data structures by bringing the intuitive and consistent syntax of the tidy paradigm to R. During the EuroBioc2026 Tidyomics Hackathon, five bioinformatics researchers collaborated to strengthen this ecosystem across four areas. First, we introduce tidyAnnData, a new package that expands interoperability between the tidyverse and AnnData objects. Second, we updated and harmonized the accessibility of information across the core packages that form the current Tidyomics backbone. Third, we improved the stability of core packages by resolving critical bugs through targeted pull requests and implementing functional enhancements to the DFplyr and tidybulk packages. Fourth, we enhanced the documentation by producing a comprehensive and stable vignette for tidySingleCellExperiment covering typical single-cell analysis workflows. Together, these contributions lower the barrier to entry for new users, promote reproducibility, and support the continued transition from disparate scripts toward robust, unified omics workflows driven by community development. less than 1 minute read
• Jun 19, 2026

  BiocExecute: Make package functions or workflows executable from the command line

  Bioconductor (Huber et al., 2015) is a collection of more than 2,400 open-source software packages, together accounting for about a million downloads per year (Bioconductor, 2026). The packages are thoroughly maintained and documented, and their quality is enforced through BiocCheck. Their reach, however, largely stops at the R console. The R and Bioconductor paradigm of interactivity through a responsive, informative REPL has served academic users well for a long time. But computational biology has grown more interdisciplinary, and increasingly runs on high-performance and high-throughput compute, large-scale experimentation, and the cloud. In these settings analyses are assembled from command-line tools and run under workflow managers, where an interactive R session does not fit. For Bioconductor and the work built on it to stay relevant, its tooling must be portable and scriptable as well as interactive. Some of this ground is already covered: R2G2 integrates R with Galaxy, and Rapp (r-lib,2024) lets an R script run as if it were a command-line program. What is missing is a path from a Bioconductor package to such tools that follows the project’s own packaging conventions. BiocExecute fills that gap. It is a package that wraps Rapp so that the functions and workflows inside any Bioconductor package can be called from the command line, with these command-line entry points declared and bundled as part of the package itself. Both users and developers gain from this. Users can run Bioconductor tools outside of Rscripts, combine them as modules with other command-line tools, and reuse them in workflows under any workflow manager; developers reach a wider range of users. More broadly, making Bioconductor packages executable improves their FAIRness (Barker et al., 2022; Wilkinson et al., 2016) and gives Bioconductor software visibility among a larger community of bioinformaticians. Longer term, the goal is to lay the groundwork for programmatic generation of command-line tooling from within Bioconductor packages, so that this tooling can be slotted into modern workflow management systems or interactive platforms such as Galaxy (Goecks et al., 2010). 1 minute read
• Jun 16, 2026

  Rendering SSSOM ontology mappings as RDF named graphs and RDF 1.2 triple terms

  SSSOM shares ontology mappings as a TSV+YAML file usually consumed as a dataframe. At the GOBLIN hackathon we explored rendering it as RDF with the individual mapping as first-class object, via two complementary serializations: named graphs (TriG, modelling sssom:MappingSet) and RDF 1.2 triple terms (Turtle 1.2, modelling sssom:Mapping). We compare the design trade-offs and show they compose rather than compete. As proof of concept we rendered all EBI OLS extracts (271 sets, ~6.2M mappings) into both forms and built an in-browser Oxigraph + Comunica demo. Wikidata extraction is ongoing. An early proposal to start discussion. less than 1 minute read