Intensional and Extensional Views in DL-Lite Ontologies

Authors: Marco Console, Giuseppe De Giacomo, Maurizio Lenzerini, Manuel Namici

IJCAI 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical In this work, we study views in Ontology-Based Data Access (OBDA) systems. OBDA is a powerful paradigm for accessing data through an ontology, i.e., a conceptual specification of the domain of interest written using logical axioms. Intuitively, users of an OBDA system interact with the data only through the ontology s conceptual lens. We present a novel framework to express natural and sophisticated forms of views in OBDA systems and introduce fundamental reasoning tasks for these views. We study the computational complexity of these tasks and present classes of views for which these tasks are tractable or at least decidable.
Researcher Affiliation Academia Marco Console1 , Giuseppe De Giacomo1 , Maurizio Lenzerini1 and Manuel Namici1 1University of Rome, La Sapienza , Italy {console,degiacomo,lenzerini,namici}@diag.uniroma1.it
Pseudocode No The paper describes logical formalisms and provides examples of formulas and TBox/ABox structures, but it does not include any pseudocode or algorithm blocks.
Open Source Code No The paper does not mention or provide any links to open-source code for the described methodology.
Open Datasets No The paper uses abstract examples (e.g., 'HR data' in Example 1) to illustrate its theoretical framework but does not refer to or provide access information for any specific publicly available datasets.
Dataset Splits No The paper is theoretical and does not involve empirical experiments with dataset splits. Therefore, it does not provide any information regarding training, validation, or test splits.
Hardware Specification No The paper describes a theoretical framework and does not report on any empirical experiments that would require specific hardware specifications.
Software Dependencies No The paper focuses on theoretical aspects of views in DL-Lite ontologies and does not mention any specific software dependencies with version numbers.
Experiment Setup No The paper describes a theoretical framework and analyzes its computational properties; it does not detail any experimental setup, hyperparameters, or training configurations.