RT Journal Article
T1 NORA: Scalable OWL reasoner based on NoSQL databases and Apache Spark.
A1 Benítez-Hidalgo, Antonio
A1 Navas-Delgado, Ismael
A1 Roldán-García, María del Mar
K1 Ontologías (Recuperación de la información)
K1 Lenguajes de marcas
K1 Representación del conocimiento (Teoría de la información)
AB Reasoning is the process of inferring new knowledge and identifying inconsistencies within ontologies. Traditional techniques often prove inadequate when reasoning over large Knowledge Bases containing millions or billions of facts. This article introduces NORA, a persistent and scalable OWL reasoner built on top of Apache Spark, designed to address the challenges of reasoning over extensive and complex ontologies. NORA exploits the scalability of NoSQL databases to effectively apply inference rules to Big Data ontologies with large ABoxes. To facilitate scalable reasoning,OWL data, including class and property hierarchies and instances, are materialized in the Apache Cassandra database. Spark programs are then evaluated iteratively, uncovering new implicit knowledge from the dataset and leading to enhanced performance and more efficient reasoning over large-scale ontologies. NORA has undergone a thorough evaluation with different benchmarking ontologies of varying sizes to assess the scalability of the developed solution.
PB Wiley
YR 2023
FD 2023-09-04
LK https://hdl.handle.net/10630/30623
UL https://hdl.handle.net/10630/30623
LA eng
NO Benítez-Hidalgo A, Navas-Delgado I, Roldán-García MM. NORA: Scalable OWL reasoner based on NoSQL databases and Apache Spark. Softw Pract Exper. 2023; 53(12): 2377–2392. doi: 10.1002/spe.3258
NO MCIN/AEI/10.13039/501100011033/: PID2020-112540RB-C41. Spanish Ministry of Science, Innovation and Universities: PRE2018-084280. Funding for open access charge: Universidad de Málaga / CBUA.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026