Galaxy:A Decade of Realising CWFR Concepts

Despite recent encouragement to follow the FAIR principles,the day-to-day research practices have not changed substantially.Due to new developments and the increasing pressure to apply best practices,initiatives to improve the efficiency and reproducibility of scientific workflows are becoming more prevalent.In this article,we discuss the importance of well-annotated tools and the specific requirements to ensure reproducible research with FAIR outputs.We detail how Galaxy,an open-source workflow management system with a web-based interface,has implemented the concepts that are put forward by the Canonical Workflow Framework for Research(CWFR),whilst minimising changes to the practices of scientific communities.Although we showcase concrete applications from two different domains,this approach is generalisable to any domain and particularly useful in interdisciplinary research and science-based applications.

Pilot Study on the Intercalibration of a Categorisation System for FAlRer Digital Objects Related to Sensitive Data in the Life Sciences

Sharing sensitive data is a specific challenge for research infrastructures in the field of life sciences.For that reason a toolbox has been developed,providing resources for researchers who wish to share and use sensitive data,to support the workflows for handling these kinds of digital objects.Common and community approved annotations are required to be compliant with FAIR principles(Findability,Accessibility,Interoperability,Reusability).The toolbox makes use of a tagging(categorisation)system,allowing consistent labelling and categorisation of digital objects,in terms relevant to data sharing tasks and activities.A pilot study was performed within the Horizon 2020 project EOSC-Life,in which 2 experts from 6 life sciences research infrastructures were recruited to independently assign tags to the same set of 10 to 25 resources related to sensitive data management and data sharing(in total 110).Summary statistics of agreement and observer variation per research infrastructure are provided.The pilot study has shown that experts were able to attribute tags but in most cases with a considerable observer variation between experts.In the context of CWFR(Canonical Workflow Frameworks for Research),this indicates the necessity for careful definition,evaluation and validation of parameters and processes related to workflow descriptions.The results from this pilot study were used to tackle this issue by revising the categorisation system and providing an updated version.

From a Dynamic Image Annotation Process within the Humanitiesto a Canonical Workflow

One idea of the Canonical Workflow Framework for Research(CWFR)is to improve the reusability and automation in research.In this paper,we aim to deliver a concrete view on the application of CWFRs to a use case of the arts and humanities to enrich further discussions on the practical realization of canonical workflows and the benefits that come with it.This use case involves context dependent data transformation and feature extraction,ingests into multiple repositories as well as a"human-in-the-loop"workflow step,which introduces a certain complexity into the mapping to a canonical workflow.

Enabling Canonical Analysis Workflows Documented Data Harmonization on Global AirQuality Data

Data harmonization and documentation of the data processing are essential prerequisites for enabling Canonical Analysis Workflows.The recently revised Terabyte-scale air quality database system,which the Tropospheric Ozone Assessment Report(TOAR)created,contains one of the world's largest collections of near-surface air quality measurements and considers FAIR data principles as an integral part.A special feature of our data service is the on-demand processing and product generation of several air quality metrics directly from the underlying database.In this paper,we show that the necessary data harmonization for establishing such online analysis services goes much deeper than the obvious issues of common data formats,variable names,and measurement units,and we explore how the generation of FAIR Digital Objects(FDO)in combination with automatically generateddocumentation may support Canonical Analysis Workflows for airquality and related data.

Realising Data-Centric Scientific Workflows with Provenance-Capturing on Data Lakes

Since their introduction by James Dixon in 2010,data lakes get more and more attention,driven by the promise of high reusability of the stored data due to the schema-on-read semantics.Building on this idea,several additional requirements were discussed in literature to improve the general usability of the concept,like a central metadata catalog including all provenance information,an overarching data governance,or the integration with(high-performance)processing capabilities.Although the necessity for a logical and a physical organisation of data lakes in order to meet those requirements is widely recognized,no concrete guidelines are yet provided.The most common architecture implementing this conceptual organisation is the zone architecture,where data is assigned to a certain zone depending on the degree of processing.This paper discusses how FAIR Digital Objects can be used in a novel approach to organize a data lake based on data types instead of zones,how they can be used to abstract the physical implementation,and how they empower generic and portable processing capabilities based on a provenance-based approach.

A Semantic Approach to Workflow Management and Reuse for Research Problem Solving

The investigation proposes the application of an ontological semantic approach to describing workflow control patterns,research workflow step patterns,and the meaning of the workflows in terms of domain knowledge.The approach can provide wide opportunities for semantic refinement,reuse,and composition of workflows.Automatic reasoning allows verifying those compositions and implementations and provides machine-actionable workflow manipulation and problem-solving using workflows.The described approach can take into account the implementation of workflows in different workflow management systems,the organization of workflows collections in data infrastructures and the search for them,the semantic approach to the selection of workflows and resources in the research domain,the creation of research step patterns and their implementation reusing fragments of existing workflows,the possibility of automation of problemsolving based on the reuse of workflows.The application of the approach to CWFR conceptions is proposed.

Making Canonical Workflow Building Blocks Interoperable across Workflow Languages

We introduce the concept of Canonical Workflow Building Blocks(CWBB),a methodology of describing and wrapping computational tools,in order for them to be utilised in a reproducible manner from multiple workflow languages and execution platforms.The concept is implemented and demonstrated with the BioExcel Building Blocks library(BioBB),a collection of tool wrappers in the field of computational biomolecular simulation.Interoperability across different workflow languages is showcased through a protein Molecular Dynamics setup transversal workflow,built using this library and run with 5 different Workflow Manager Systems(WfMS).We argue such practice is a necessary requirement for FAIR Computational Workflows and an element of Canonical Workflow Frameworks for Research(CWFR)in order to improve widespread adoption and reuse of computational methods across workflow language barriers.