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..
Ontology-Mediated Queries for NOSQL Databases
Authors: Marie-Laure Mugnier, Marie-Christine Rousset, Federico Ulliana
AAAI 2016 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, we study the problem of answering ontology-mediated queries on top of key-value stores. We formalize the data model and core queries of these systems, and introduce a rule language to express lightweight ontologies on top of data. We study the decidability and data complexity of query answering in this setting. |
| Researcher Affiliation | Academia | Marie-Laure Mugnier Universit e de Montpellier CNRS, LIRMM Grahp IK Team, INRIA EMAIL Marie-Christine Rousset Univ. Grenoble Alpes CNRS, LIG IUF (Institut Universitaire de France) EMAIL Federico Ulliana Universit e de Montpellier CNRS, LIRMM Grahp IK Team, INRIA EMAIL |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described. |
| Open Datasets | No | The paper focuses on theoretical aspects and does not mention using any public or open datasets for training. |
| Dataset Splits | No | The paper focuses on theoretical aspects and does not mention any training/test/validation dataset splits. |
| Hardware Specification | No | The paper does not provide specific hardware details used for running experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details with version numbers. |
| Experiment Setup | No | The paper focuses on theoretical aspects and does not provide specific experimental setup details like hyperparameters or training configurations. |