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Luca Pireddu

Publications and source records attributed to Luca Pireddu.

4 recordsLinked to original sources

An Ecosystem of Services for FAIR Computational Workflows

Computational workflows represent major investments of effort and expertise. As first-class, publishable research objects of their own, they are key to sharing methodological know-how for reuse, reproducibility, and transparency. Thus, the application of the FAIR Principles to workflows is inevitable to enable them to be Findable, Accessible, Interoperable, and Reusable. Making workflows FAIR reduces duplication of effort, assists in the reuse of best practice approaches and community-supported standards, and ensures that workflows as digital objects can support reproducible, robust science. FAIR workflows draw from both FAIR data and software principles, and they help ensure and support data FAIRification. The FAIR Principles emphasize the association of persistent identifiers and machine-actionable metadata with workflows. Implementing the Principles requires a framework with appropriate programmatic protocols and an accompanying ecosystem of services, tools, policies, and best practices, as well the buy-in of existing workflow systems. The European EOSC-Life Workflow Collaboratory is an example of such a digital infrastructure for the Biosciences. It includes a metadata standards framework for describing workflows that is managed and used by dedicated new FAIR workflow services and programmatic APIs for interoperability and metadata access. It includes the WorkflowHub registry and LifeMonitor workflow testing service, and it incorporates existing workflow systems and packaging solutions. Here, we introduce the FAIR Principles for workflows and connect FAIR workflows with the FAIR ecosystems they inhabit with the EOSC-Life Collaboratory as a concrete example. We also introduce other community efforts that are easing the ways that workflows are shared and reused by others, and we discuss how the variations in different workflow settings impact their FAIR perspectives.

cs.DC

WorkflowHub: a registry for computational workflows

The rising popularity of computational workflows is driven by the need for repetitive and scalable data processing, sharing of processing know-how, and transparent methods. As both combined records of analysis and descriptions of processing steps, workflows should be reproducible, reusable, adaptable, and available. Workflow sharing presents opportunities to reduce unnecessary reinvention, promote reuse, increase access to best practice analyses for non-experts, and increase productivity. In reality, workflows are scattered and difficult to find, in part due to the diversity of available workflow engines and ecosystems, and because workflow sharing is not yet part of research practice. WorkflowHub provides a unified registry for all computational workflows that links to community repositories, and supports both the workflow lifecycle and making workflows findable, accessible, interoperable, and reusable (FAIR). By interoperating with diverse platforms, services, and external registries, WorkflowHub adds value by supporting workflow sharing, explicitly assigning credit, enhancing FAIRness, and promoting workflows as scholarly artefacts. The registry has a global reach, with hundreds of research organisations involved, and more than 700 workflows registered.

cs.DL

Recording provenance of workflow runs with RO-Crate

Recording the provenance of scientific computation results is key to the support of traceability, reproducibility and quality assessment of data products. Several data models have been explored to address this need, providing representations of workflow plans and their executions as well as means of packaging the resulting information for archiving and sharing. However, existing approaches tend to lack interoperable adoption across workflow management systems. In this work we present Workflow Run RO-Crate, an extension of RO-Crate (Research Object Crate) and Schema.org to capture the provenance of the execution of computational workflows at different levels of granularity and bundle together all their associated objects (inputs, outputs, code, etc.). The model is supported by a diverse, open community that runs regular meetings, discussing development, maintenance and adoption aspects. Workflow Run RO-Crate is already implemented by several workflow management systems, allowing interoperable comparisons between workflow runs from heterogeneous systems. We describe the model, its alignment to standards such as W3C PROV, and its implementation in six workflow systems. Finally, we illustrate the application of Workflow Run RO-Crate in two use cases of machine learning in the digital image analysis domain. A corresponding RO-Crate for this article is at https://w3id.org/ro/doi/10.5281/zenodo.10368989

cs.DL

EOSC-LIFE WP4 TOOLBOX: Toolbox for sharing of sensitive data -- a concept description

The Horizon 2020 project EOSC-Life brings together the 13 Life Science 'ESFRI' research infrastructures to create an open, digital and collaborative space for biological and medical research. Sharing sensitive data is a specific challenge within EOSC-Life. For that reason, a toolbox is being developed, providing information to researchers who wish to share and/or use sensitive data in a cloud environment in general, and the European Open Science Cloud in particular. The sensitivity of the data may arise from its personal nature but can also be caused by intellectual property considerations, biohazard concerns, or the Nagoya protocol. The toolbox will not create new content, instead, it will allow researchers to find existing resources that are relevant for sharing sensitive data across all participating research infrastructures (F in FAIR). The toolbox will provide links to recommendations, procedures, and best practices, as well as to software (tools) to support data sharing and reuse. It will be based upon a tagging (categorisation) system, allowing consistent labelling and categorisation of resources. The current design document provides an outline for the anticipated toolbox, as well as its basic principles regarding content and sustainability.

q-bio.OT