分类： 计算机科学 >> 计算机科学的集成理论 提交时间： 2022-11-28 合作期刊: 《数据智能（英文）》
摘要： Modern interactive tools for data analysis and visualisation are designed to expose their functionalities as a service through the Web. We 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 users. The API deals, on behalf of the clients, with the underlying complexity of allocating and managing resources within a target cloud platform. By combining storage and containerised services, offering analysis notebooks and other visualisation software, the API creates dedicated working sessions on-demand, which can be accessed collaboratively. Thanks to the APIs support for workflow execution, SWIRRL workspaces can be automatically populated with data of interest collected from external data providers. The system keeps track of updates and changes affecting the data and the tools by adopting versioning and standard provenance technologies. Users are provided with interactive controls enabling traceability and recovery actions, including the possibility of creating executable snapshots of their environments. SWIRRL is built in cooperation with two research infrastructures in the field of solid earth science and climate data modeling. We report on the particular adoptions and use cases.
分类： 计算机科学 >> 计算机科学的集成理论 提交时间： 2022-11-28 合作期刊: 《数据智能（英文）》
摘要： We present a set of configurable Web service and interactive tools, s-ProvFlow, for managing and exploiting records tracking data lineage during workflow runs. It facilitates detailed analysis of single executions. It helps users manage complex tasks by exposing the relationships between data, people, equipment and workflow runs intended to combine productively. Its logical model extends the PROV standard to precisely record parallel data-streaming applications. Its metadata handling encourages users to capture the application context by specifying how application attributes, often using standard vocabularies, should be added. These metadata records immediately help productivity as the interactive tools support their use in selection and bulk operations. Users rapidly appreciate the power of the encoded semantics as they reap the benefits. This improves the quality of provenance for users and management. Which in turn facilitates analysis of collections of runs, enabling users to manage results and validate procedures. It fosters reuse of data and methods and facilitates diagnostic investigations and optimisations. We present S-ProvFlows use by scientists, research engineers and managers as part of the DARE hyper-platform as they create, validate and use their data-driven scientific workflows.
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