*** Provenance-aware and Reproducible Workspaces

作     者：Alessandro Spinuso Mats Veldhuizen Daniele Bailo Valerio Vinciarelli Tor Langeland 

作者机构：Koninkljk Nederlands Meteorologisch InstituutDe BiltUtrecht 3731GAThe Netherlands Istituto Nazionale Geofisica e VulcanologiaRomeLazio 00143Italy NORCE Norwegian Research Centre ASBergenHordaland NO-5838Norway 

出 版 物：《Data Intelligence》 (数据智能（英文）)

年 卷 期：2022年第4卷第2期

页      面：243-258页

核心收录：

学科分类：08[工学] 080402[工学-测试计量技术及仪器] 0804[工学-仪器科学与技术] 

基　　金：supported by the EU H2020 project ENVRIFair(No.824068) ISENES3(No.824084) 

主　　题：Productivity Data-analysis Reproducibility Provenance Cloud-computing 

摘      要：Modern interactive tools for data analysis and visualisation are designed to expose their functionalities as a service through the *** present in this paper a Web API(SWIRRL)that allows Virtual Research Environments(VREs)to easily integrate such tools in their websites and re-purpose them to their *** APl deals,on behalf of the clients,with the underlying complexity of allocating and managing resources within a target cloud *** combining storage and containerised services,offering analysis notebooks and other visualisation software,the APl creates dedicated working sessions on-demand,which can be accessed *** to the API s support for workflow execution,SWIRRL workspaces can be automatically populated with data of interest collected from external data *** system keeps track of updates and changes affecting the data and the tools by adopting versioning and standard provenance *** are provided with interactive controls enabling traceabilityand recovery actions,including the possibility of creating executable snapshots of their *** is built in cooperation with two research infrastructures in the field of solid earth science and climate data *** report on the particularadoptions and use cases.