Enhancing RDM in Galaxy by integrating RO-Crate

We introduce how the Galaxy research environment (Jalili et al. 2020) integrates with RO-Crate as an implementation of Findable Accessible Interoperable Reproducible Digital Objects (FAIR / FDO) (Wilkinson 2016, Schultes and Wittenburg 2018) using exchange mechanism workflows their execution history helps integrate wider ecosystem ELIXIR (Harrow 2021) European Open Science Cloud (EOSC-Life) to enable FAIR reproducible data analysis. (Soiland-Reyes 2022) is a generic packaging format containing datasets description standards for Linked Data. The based on schema.org (Guha 2016) annotations in JSON-LD, which allows rich metadata representation. effort aims make best-practice formal accessible practical use variety situations, from individual researcher working folder data, large data-intensive computational environments. community brings together practitioners very different backgrounds, motivations cases. Among core target users are: researchers engaged computation data-intensive, workflow-driven analysis; digital repository managers infrastructure providers; looking straightforward tool or how-to guide “FAIRify” data; stewards supporting projects creating curating datasets. Given wide applicability lack implementations FDOs, co-opted this initiative project define common entries. Thus, during last year it’s been implemented range services, such as: WorkflowHub (Goble (a registry describing, sharing publishing scientific workflows) uses RO-Crates improve reproducibility that follow Workflow profile (Bacall 2022); LifeMonitor (Leo service support sustainability being developed part EOSC-Life project) describing test suites associated workflows. Tools have towards aiding previously mentioned cases increasing general usability by providing user-friendly (programmatic) interface consumption production through programmatic libraries consuming/producing (ro-crate-py De Geest 2022, ro-crate-ruby Bacall Whitwell ro-crate-js Lynch 2021). provides analysis management functionalities multi user platform, aiming biology scientists do not computer programming systems administration experience. As such, it stores just related but also complete analytical workflow, including its metadata. internal model involves entity, all steps performed specific analysis, workflow defining structure pipeline. From start, analyses capabilities export (and import) details way. daily management. continuously improving adding features, integration Object principles natural next step this. To be able these leverages Python client library (De multiple entry points import objects representing entities These include: definition, used share/publish pipeline, graph tools need executed, about types required files collection compressed archive entire used, versions, parameters chosen, invocation metadata, inputs, outputs, license, author, CWLProv (Khan 2019) contextual references form Identifiers (DOIs), ‘EMBRACE Data And Methods’ ontology (EDAM) terms (Ison 2013), etc. adoption RO-crate standardised FDOs other platforms ecosystem, LifeMonitor. Integrating deeply into offering options various Research increased standardisation, improved Management (RDM) functionalities, smoother experience (UX) well interoperability systems. platform biologists intensive facilitates publication invocations skill levels democratises ability perform Science.