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Integrating Provenance Capture and UML With UML2PROV: Principles and Experience by Carlos Saenz-Adan; Beatriz Perez; Francisco J. Garcia-Izquierdo; Luc Moreau is a Computer Science article available to read on EtoBox.

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In response to the increasing calls for algorithmic accountability, UML2PROV is a novel approach to address the existing gap between application design, where models are described by UML diagrams, and provenance design, where generated provenance is meant to describe an application's flows of data, processes and responsibility, enabling greater accountability of this application. The originality of UML2PROV is that designers are allowed to follow their preferred software engineering methodology to create the UML Diagrams for their application, while UML2PROV takes the UML diagrams as a starting point to automatically generate: (1) the design of the provenance to be generated (expressed as PROV templates); and (2) the software library for collecting runtime values of interest (encoded as variable-value associations known as bindings), which can be deployed in the application without developer intervention. At runtime, the PROV templates combined with the bindings are used to generate high-quality provenance suitable for subsequent consumption. UML2PROV is rigorously defined by an extensive set of 17 patterns mapping UML diagrams to provenance templates, and is accompanied by a refer

Who reads Integrating Provenance Capture and UML With UML2PROV: Principles and Experience?

Author

Carlos Saenz-Adan; Beatriz Perez; Francisco J. Garcia-Izquierdo; Luc Moreau

Publisher

IEEE; Institute of Electrical and Electronics Engineers; Institute of Electrical and Electronics Engineers (IEEE) (ISSN 0098-5589)

Published

2022

Language

EN

Field

Computer Science (Physical Sciences)