Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Epistemic Integrity Constraints for Ontology-Based Data Management
Authors: Marco Console, Maurizio Lenzerini2790-2797
AAAI 2020 | Venue PDF | 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 deο¬ne 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. |