Enriching Ontology-based Data Access with Provenance (Extended Version)
June 01, 2019 ยท Declared Dead ยท ๐ International Joint Conference on Artificial Intelligence
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Diego Calvanese, Davide Lanti, Ana Ozaki, Rafael Penaloza, Guohui Xiao
arXiv ID
1906.00179
Category
cs.DB: Databases
Cross-listed
cs.AI
Citations
30
Venue
International Joint Conference on Artificial Intelligence
Last Checked
3 months ago
Abstract
Ontology-based data access (OBDA) is a popular paradigm for querying heterogeneous data sources by connecting them through mappings to an ontology. In OBDA, it is often difficult to reconstruct why a tuple occurs in the answer of a query. We address this challenge by enriching OBDA with provenance semirings, taking inspiration from database theory. In particular, we investigate the problems of (i) deciding whether a provenance annotated OBDA instance entails a provenance annotated conjunctive query, and (ii) computing a polynomial representing the provenance of a query entailed by a provenance annotated OBDA instance. Differently from pure databases, in our case these polynomials may be infinite. To regain finiteness, we consider idempotent semirings, and study the complexity in the case of DL-Lite ontologies. We implement Task (ii) in a state-of-the-art OBDA system and show the practical feasibility of the approach through an extensive evaluation against two popular benchmarks.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ Databases
R.I.P.
๐ป
Ghosted
R.I.P.
๐ป
Ghosted
The Case for Learned Index Structures
R.I.P.
๐ป
Ghosted
Untangling Blockchain: A Data Processing View of Blockchain Systems
R.I.P.
๐ป
Ghosted
Converting Static Image Datasets to Spiking Neuromorphic Datasets Using Saccades
R.I.P.
๐ป
Ghosted
BLOCKBENCH: A Framework for Analyzing Private Blockchains
R.I.P.
๐ป
Ghosted
Data Synthesis based on Generative Adversarial Networks
Died the same way โ ๐ป Ghosted
R.I.P.
๐ป
Ghosted
Language Models are Few-Shot Learners
R.I.P.
๐ป
Ghosted
PyTorch: An Imperative Style, High-Performance Deep Learning Library
R.I.P.
๐ป
Ghosted
XGBoost: A Scalable Tree Boosting System
R.I.P.
๐ป
Ghosted