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..
Mapping Repair in Ontology-based Data Access Evolving Systems
Authors: Domenico Lembo, Riccardo Rosati, Valerio Santarelli, Domenico Fabio Savo, Evgenij Thorstensen
IJCAI 2017 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We then present a set of results on the complexity of query answering in the above framework, when the ontology is expressed in DL-Lite R. In these settings we provide a number of complexity results on the entailment of conjunctive queries. |
| Researcher Affiliation | Academia | 1 Sapienza Universit a di Roma 2 University of Oslo |
| Pseudocode | Yes | Algorithm 1: Check DMR-QE (M, T , S , D, q) |
| Open Source Code | No | The paper does not provide any specific links or explicit statements about the release of open-source code for the described methodology. The paper is theoretical in nature. |
| Open Datasets | No | The paper presents theoretical concepts and complexity analysis, and does not refer to the use of any specific publicly available or open dataset for training. |
| Dataset Splits | No | As the paper focuses on theoretical analysis and does not describe empirical experiments, no training/test/validation dataset splits are provided. |
| Hardware Specification | No | The paper is theoretical in nature and does not describe any specific hardware used for experiments. |
| Software Dependencies | No | The paper focuses on theoretical analysis and does not provide any specific software dependencies with version numbers. |
| Experiment Setup | No | The paper describes theoretical frameworks and algorithms, but does not provide details on experimental setup, hyperparameters, or training configurations. |