Dag Hovland

TL;DR: This work has developed a deployment module to create ontologies and mappings from relational databases in a semi-automatic fashion; a query processing module to perform and optimise the process of translating ontological queries into data queries and their execution over either a single DB of federated DBs; and a query formulation module to support query construction for engineers with a limited IT background.

TL;DR: In this article, the authors present data access challenges in the data-intensive petroleum company Statoil and their experience in addressing these challenges with OBDA technology, and develop a deployment module to create ontologies and mappings from relational databases in a semi-automatic fashion, and a query processing module to perform and optimize the process of translating ontological queries into data queries and their execution.

TL;DR: This work presents OptiqueVQS, a query formulation tool designed based on the experience with OBDA applications in Statoil and Siemens and on best HCI practices for interdisciplinary engineering environments, which implements a number of unique techniques distinguishing it from analogous query formulation systems.

TL;DR: The problem of bootstrapping and maintenance of ontologies and mappings is discussed, and examples of different kinds of error are presented, and the preliminary view on their debugging is given.

TL;DR: This paper tackles the problem of answering SPARQL queries over virtually integrated databases, and formally treats several fundamental questions in this context: how links over database identifiers can be represented in terms of owl:sameAs statements, how to recover rewritability of SParQL into SQL lost because of owl:(sameAs), and how to check consistency.