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 im...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.展开更多
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 ...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.展开更多
基金supported by the European Union's Horizon 2020 programme(No.857652,EOSCNordic,and No.101017501,RELIANCE)supported by BMBF grants 031 A538A/A538C(de.NBI-RBC),NFDI7/1-42077441(DataPLANT)and 031L0101C(de.NBI-epi)+2 种基金supported by Research Foundation-Flanders(FWO)for ELIXIR Belgium(I002819N)the European Union's Horizon 2020 programme(No.824087,EOSC-Life)partially supported by the Research Council of Norway's grant 270068 for ELIXIR Norway.
文摘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.
文摘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.
