文章基本信息

标题：Lightweight Distributed Provenance Model for Complex Real–world Environments
本地全文：下载
作者：Rudolf Wittner ; Cecilia Mascia ; Matej Gallo 等
期刊名称：Scientific Data
电子版ISSN：2052-4463
出版年度：2022
卷号：9
期号：1
页码：1-19
DOI：10.1038/s41597-022-01537-6
语种：English
出版社：Nature Publishing Group
摘要：Provenance is information describing the lineage of an object, such as a dataset or biological material . Since these objects can be passed between organizations, each organization can document only parts of the objects life cycle . As a result, interconnection of distributed provenance parts forms distributed provenance chains . Dependant on the actual provenance content, complete provenance chains can provide traceability and contribute to reproducibility and FAIRness of research objects . In this paper, we defne a lightweight provenance model based on W3C PROV that enables generation of distributed provenance chains in complex, multi-organizational environments . The application of the model is demonstrated with a use case spanning several steps of a real-world research pipeline — starting with the acquisition of a specimen, its processing and storage, histological examination, and the generation/ collection of associated data (images, annotations, clinical data), ending with training an AI model for the detection of tumor in the images . The proposed model has become an open conceptual foundation of the currently developed ISO 23494 standard on provenance for biotechnology domain .