Beyond OWL 2 QL in OBDA: Rewritings and Approximations
Authors: Elena Botoeva, Diego Calvanese, Valerio Santarelli, Domenico Savo, Alessandro Solimando, Guohui Xiao
AAAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We have implemented our techniques in the prototype system ONTOPROX, making use of the state-of-the-art OBDA system ONTOP and the query answering system CLIPPER, and we have shown their feasibility and effectiveness with experiments on synthetic and real-world data. |
| Researcher Affiliation | Academia | 1 KRDB Research Centre for Knowledge and Data, Free University of Bozen-Bolzano, Italy, lastname@inf.unibz.it 2 Dip. di Ing. Informatica Automatica e Gestionale, Sapienza Universit a di Roma, Italy, lastname@dis.uniroma1.it 3 DIBRIS, University of Genova, Italy, alessandro.solimando@unige.it |
| Pseudocode | No | While Figure 1 describes an algorithm (Rew Obda), its steps are presented as a numbered list of high-level procedures rather than structured pseudocode or an algorithm block with code-like formatting. |
| Open Source Code | Yes | We have implemented our techniques in a prototype system called ONTOPROX6 and evaluated it over synthetic and real OBDA instances. (Footnote 6: https://github.com/ontop/ontoprox/) |
| Open Datasets | Yes | UOBM. The university ontology benchmark (UOBM) (Ma et al. 2006) comes with a SHOIN ontology (with 69 concepts, 35 roles, 9 attributes, and 204 TBox axioms), and an ABox generator. (Footnote 11: https://github.com/ontop/ontop-examples/tree/master/aaai2016-ontoprox/uobm) |
| Dataset Splits | No | The paper does not provide specific training/validation/test dataset splits or mention how the datasets were partitioned for these purposes. |
| Hardware Specification | No | The paper does not specify any hardware details (e.g., CPU/GPU models, memory) used for running the experiments. |
| Software Dependencies | No | Our system relies on the OBDA reasoner ONTOP7 and the complete Horn-SHIQ CQ-answering system CLIPPER8, used as Java libraries. ONTOPROX also relies on a standard Prolog engine (SWIPROLOG9) and on an OWL 2 reasoner (HERMIT10). (No specific version numbers are provided for these dependencies, other than ONTOP v1.15 in a comparison context.) |
| Experiment Setup | No | The paper describes five different setups for comparison (ONTOP, LSA, GSA, ONTOPROX, CLIPPER), but it does not provide specific experimental setup details such as hyperparameters or system-level training settings for these setups. |