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..
Managing Change in Graph-Structured Data Using Description Logics
Authors: Shqiponja Ahmetaj, Diego Calvanese, Magdalena Ortiz, Mantas Simkus
AAAI 2014 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We study different reasoning problems, which range from ensuring the satisfaction of a given set of integrity constraints after a given sequence of updates, to deciding the (non-)existence of a sequence of actions that would take the data to an (un)desirable state, starting either from a specific data instance or from an incomplete description of it. We provide algorithms and tight complexity bounds for the formalized problems, both for an expressive DL and for a variant of DL-Lite. |
| Researcher Affiliation | Academia | Shqiponja Ahmetaj Institute of Information Systems Vienna Univ. of Technology, Austria Diego Calvanese KRDB Research Centre Free Univ. of Bozen-Bolzano, Italy Magdalena Ortiz Mantas Šimkus Institute of Information Systems Vienna Univ. of Technology, Austria |
| Pseudocode | No | The paper formally defines the action language and transformations but does not provide pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any statement or link regarding the availability of open-source code for the described methodology. |
| Open Datasets | No | The paper is theoretical and does not involve datasets or training. |
| Dataset Splits | No | The paper is theoretical and does not involve datasets or validation splits. |
| Hardware Specification | No | The paper is theoretical and does not involve experimental hardware specifications. |
| Software Dependencies | No | The paper is theoretical and does not specify software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe an experimental setup or hyperparameters. |