Carlos Sáenz-Adán
University of La Rioja
7 Papers
12 Citations
Carlos Sáenz-Adán is an academic researcher from University of La Rioja. The author has contributed to research in topics: Unified Modeling Language & Computer science. The author has an hindex of 3, co-authored 7 publications.
Chat about Author
Papers
A systematic review of provenance systems
TL;DR: A six-dimensional taxonomy of provenance characteristics attending to: general aspects, data capture, data access, subject, storage, and non-functional aspects is defined and pinpoints future directions.
67
UML2PROV: Automating Provenance Capture in Software Engineering
Carlos Sáenz-Adán,Beatriz Pérez,Trung Dong Huynh,Luc Moreau +3 more
- 29 Jan 2018
TL;DR: UML2PROV is an approach addressing the gap between application design, through UML diagrams, and provenance design, using PROV-Template, a declarative approach that enables software engineers to develop programs that generate provenance following the PROV standard.
Integrating Provenance Capture and UML with UML2PROV: Principles and Experience
TL;DR: As the UML design drives both the design and capture of provenance, this work discusses how the levels of detail in UML designs affect aspects such as provenance design generation, application instrumentation, provenance capability maintenance, storage and run-time overhead, and quality of the generated provenance.
Using the Provenance from Astronomical Workflows to Increase Processing Efficiency
Michael A. C. Johnson,Luc Moreau,Adriane Chapman,Poshak Gandhi,Carlos Sáenz-Adán +4 more
- 09 Jul 2018
TL;DR: It is deduced that provenance has the potential to produce a net increase in this efficiency if more uses cases are to be considered and is highlighted in this work.
A tool for management of knowledge dispersed throughout multiple references
Carlos Sáenz-Adán,Francisco J. García-Izquierdo,Ángel Luis Rubio,Eduardo Saenz-de-Cabezon Irigaray,Emilio Rodriguez-Priego,Oscar Díaz +5 more
- 20 Jul 2015
TL;DR: This paper presents the main features of RCMTool, a tool for creating References-enriched Concept Maps (RCM), based on the development of an RCM metamodel and the inclusion of a natural language processing engine.
2