Skip to Main content Skip to Navigation
New interface
Reports (Research report)

PORTOLAN: a Model-Driven Cartography Framework

Vincent Mahe 1 Salvador Martinez Perez 1 Guillaume Doux 1 Hugo Bruneliere 1 Jordi Cabot 1 
1 ATLANMOD - Modeling Technologies for Software Production, Operation, and Evolution
LINA - Laboratoire d'Informatique de Nantes Atlantique, Département informatique - EMN, Inria Rennes – Bretagne Atlantique
Abstract : Processing large amounts of data to extract useful information is an essential task within companies. To help in this task, visualization techniques have been commonly used due to their capacity to present data in synthesized views, easier to understand and manage. However, achieving the right visualization display for a data set is a complex cartography process that involves several transformation steps to adapt the (domain) data to the (visualization) data format expected by visualization tools. To maximize the benefits of visualization we propose Portolan, a generic model-driven cartography framework that facilitates the discovery of the data to visualize, the specification of view definitions for that data and the transformations to bridge the gap with the visualization tools. Our approach has been implemented on top of the Eclipse EMF modeling framework and validated on three different use cases.
Document type :
Reports (Research report)
Complete list of metadata

Cited literature [25 references]  Display  Hide  Download
Contributor : Vincent Mahe Connect in order to contact the contributor
Submitted on : Tuesday, February 22, 2011 - 5:56:34 PM
Last modification on : Thursday, October 27, 2022 - 4:02:38 AM
Long-term archiving on: : Monday, May 23, 2011 - 3:28:08 AM


Files produced by the author(s)


  • HAL Id : inria-00568186, version 1
  • ARXIV : 1102.4684


Vincent Mahe, Salvador Martinez Perez, Guillaume Doux, Hugo Bruneliere, Jordi Cabot. PORTOLAN: a Model-Driven Cartography Framework. [Research Report] RR-7542, INRIA. 2011, pp.27. ⟨inria-00568186⟩



Record views


Files downloads