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Bioinformatics workflows connect software packages into multi-step processes that are used to transform raw data into a form that can be analysed and interpreted to answer a variety of research questions in life science. Some examples include workflows for genome assembly, variant calling, metagenomics and proteome quantitation. Each workflow represents intellectual property, with significant time and effort required during development, configuration and maintenance. To support FAIR principles, workflows should be 1) published, 2) discoverable, 3) reusable and 4) citable, as this allows for sharing of best practice approaches, accelerated science, reduced duplication of effort, and recognition for bioinformaticians. To facilitate this ideal, the Australian BioCommons has established a presence on the WorkflowHub registry. Now, workflows tested on Australian national computational infrastructures (i.e. National Computational Infrastructure (NCI), Pawsey Supercomputing Centre, QRISCloud, Galaxy Australia) are registered on WorkflowHub, improving reusability and findability respectively. Using WorkflowHub also aligns with community requirements for integration with git development repositories and the ability to mint digital object identifiers (DOIs). Since March 2021, 31 workflows have been registered. In total, the workflows have been viewed >16,000 times, downloaded >250 times and are now being cited in publications. Together, these observations demonstrate growing interest in reusable workflows. The BioCommons is working with our communities to further expand their use of registries, and that these registries align well with research processes in the life sciences.
WorkflowHub, workflows, bioinformatics, registry, FAIR
WorkflowHub, workflows, bioinformatics, registry, FAIR
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
views | 3 | |
downloads | 4 |