FAIR Computational Workflows

作     者：Carole Goble Sarah Cohen-Boulakia Stian Soiland-Reyes Daniel Garijo Yolanda Gil Michael R.Crusoe Kristian Peters Daniel Schober Carole Goble;Sarah Cohen-Boulakia;Stian Soiland-Reyes;Daniel Garijo;Yolanda Gil;Michael R.Crusoe;Kristian Peters;Daniel Schober

作者机构：Department of Computer ScienceThe University of ManchesterOxford RoadManchester M139PLUK Laboratoire de Recherche en InformatiqueCNRSUniversitéParis-SaclayBatiment 650UniversitéParis-Sud91405 ORSAY CedexFrance Information Sciences InstituteUniversity of Southern CaliforniaMarina Del Rey CA 90292USA Common Workflow Language projectSoftware Freedom ConservancyInc.137 Montague St STE 380NY 11201-3548USA Leibniz Institute of Plant Biochemistry(IPB Halle)Department of Biochemistry of Plant InteractionsWeinberg 306120 Halle(Saale)Germany 

出 版 物：《Data Intelligence》 (数据智能（英文）)

年 卷 期：2020年第2卷第1期

页      面：108-121,307,308,309页

核心收录：

学科分类：08[工学] 081203[工学-计算机应用技术] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Carole Goble acknowledges funding by BioExcel2(H2020823830) IBISBA1.0(H2020730976)and EOSCLife(H2020824087) Daniel Schober’s work was financed by Phenomenal(H2020654241)at the initiation-phase of this effort,current work in kind contribution Kristian Peters is funded by the German Network for Bioinformatics Infrastructure(de.NBI)and acknowledges BMBF funding under grant number 031L0107 Stian Soiland-Reyes is funded by BioExcel2(H2020823830) Daniel Garijo,Yolanda Gil,gratefully acknowledge support from DARPA award W911NF-18-1-0027,NIH award 1R01AG059874-01,and NSF award ICER-1740683. 

主　　题：Computational workflow Reproducibility Software FAIR data Provenance 

摘      要：Computational workflows describe the complex multi-step methods that are used for data collection,data preparation,analytics,predictive modelling,and simulation that lead to new data products.They can inherently contribute to the FAIR data principles:by processing data according to established metadata;by creating metadata themselves during the processing of data;and by tracking and recording data provenance.These properties aid data quality assessment and contribute to secondary data usage.Moreover,workflows are digital objects in their own right.This paper argues that FAIR principles for workflows need to address their specific nature in terms of their composition of executable software steps,their provenance,and their development.