Epistemic Integrity Constraints for Ontology-Based Data Management
Authors: Marco Console, Maurizio Lenzerini2790-2797
AAAI 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, we establish a novel framework for integrity constraints in the OBDM scenarios, based on the notion of knowledge state of the information system. For integrity constraints in this framework, we define a language based on epistemic logic, and study decidability and complexity of both checking satisfaction and performing different forms of static analysis on them. |
| Researcher Affiliation | Academia | Marco Console,1 Maurizio Lenzerini2 1University of Edinburgh 2Sapienza, University of Rome |
| Pseudocode | No | The paper focuses on theoretical frameworks, formal languages, and complexity analysis. It does not include any pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any information or links regarding open-source code for the described methodology. It is a theoretical paper. |
| Open Datasets | No | The paper is theoretical and does not conduct experiments involving datasets, training, or public data availability. Example 1 is provided for illustrative purposes only, not as a dataset for experimentation. |
| Dataset Splits | No | The paper is theoretical and does not describe experiments requiring data splits for training, validation, or testing. |
| Hardware Specification | No | The paper is theoretical and does not describe any experiments that would require hardware specifications. Therefore, no hardware details are mentioned. |
| Software Dependencies | No | The paper focuses on theoretical formalisms (e.g., Description Logics, DL-Lite A, epistemic logic) and does not specify any software dependencies with version numbers that would be required to reproduce experimental results. |
| Experiment Setup | No | The paper is theoretical and does not describe an experimental setup, hyperparameters, or training configurations. |