Demo Data from EDBT 2026 / reviewers in the wild / expert
Valerio Santarelli
dblp:127/6417
· DBLP profile ↗
7ranked-venue papers
0as first author
0since 2021 · last 2017
0009-0009-9689-438XORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 4Databases, data management, data science and information retrieval · 3Graphics, computer vision, multimedia, augmented reality and games · 3Theory of computation · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Artificial intelligence
3 papers |
Knowledge representation and reasoning · 100% | |
| Databases, data mining, and information retrieval
3 papers |
Database theory · 48% Data integration and cleaning · 38% Data models and query languages · 7% | |
| Theoretical computer science
1 paper |
Automated reasoning and model checking · 100% |
Topics — the 16 heaviest of 16, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Knowledge, reasoning and agents › Knowledge representation and reasoning
ontology |
0.5 | 2 | 2016 | Easy OWL Drawing with the Graphol Visual Ontology Language · KR 2016 Eddy: A Graphical Editor for OWL 2 Ontologies · IJCAI 2016 |
Data integration and cleaning
ontology-based data access |
0.5 | 2 | 2017 | Mapping Repair in Ontology-based Data Access Evolving Systems · IJCAI 2017 MASTRO STUDIO: Managing Ontology-Based Data Access applications · Proc. VLDB Endow. 2013 |
Database theory
query answering |
0.3 | 1 | 2017 | Mapping Repair in Ontology-based Data Access Evolving Systems · IJCAI 2017 |
Database theory
query complexity |
0.3 | 1 | 2017 | Mapping Repair in Ontology-based Data Access Evolving Systems · IJCAI 2017 |
Knowledge, reasoning and agents › Knowledge representation and reasoning
description logic |
0.2 | 1 | 2016 | Beyond OWL 2 QL in OBDA: Rewritings and Approximations · AAAI 2016 |
Knowledge, reasoning and agents › Knowledge representation and reasoning › description logic
DL-Lite |
0.2 | 1 | 2016 | Beyond OWL 2 QL in OBDA: Rewritings and Approximations · AAAI 2016 |
Knowledge, reasoning and agents › Knowledge representation and reasoning
ontology-based query answering |
0.2 | 1 | 2016 | Beyond OWL 2 QL in OBDA: Rewritings and Approximations · AAAI 2016 |
Knowledge, reasoning and agents › Knowledge representation and reasoning › ontology
ontology engineering |
0.2 | 1 | 2016 | Eddy: A Graphical Editor for OWL 2 Ontologies · IJCAI 2016 |
Knowledge, reasoning and agents › Knowledge representation and reasoning › ontology › ontology engineering
ontology visualization |
0.2 | 1 | 2016 | Easy OWL Drawing with the Graphol Visual Ontology Language · KR 2016 |
Knowledge, reasoning and agents › Knowledge representation and reasoning › ontology
OWL ontology |
0.2 | 1 | 2016 | Eddy: A Graphical Editor for OWL 2 Ontologies · IJCAI 2016 |
Knowledge, reasoning and agents › Knowledge representation and reasoning › ontology-based query answering
query rewriting |
0.2 | 1 | 2016 | Beyond OWL 2 QL in OBDA: Rewritings and Approximations · AAAI 2016 |
Automated reasoning and model checking › automated reasoning
ontology reasoning |
0.2 | 1 | 2013 | MASTRO STUDIO: Managing Ontology-Based Data Access applications · Proc. VLDB Endow. 2013 |
Data models and query languages
description logics |
0.1 | 1 | 2017 | Mapping Repair in Ontology-based Data Access Evolving Systems · IJCAI 2017 |
Knowledge, reasoning and agents › Knowledge representation and reasoning
open-world learning |
0.1 | 1 | 2016 | Easy OWL Drawing with the Graphol Visual Ontology Language · KR 2016 |
Query processing and optimization › semantic query processing
ontology-based query answering |
0.1 | 1 | 2016 | Beyond OWL 2 QL in OBDA: Rewritings and Approximations · AAAI 2016 |
User interface design and tools › interactive design tools
graphics editor |
0.1 | 1 | 2016 | Eddy: A Graphical Editor for OWL 2 Ontologies · IJCAI 2016 |
Methods — techniques the papers use, named apart from their topics
graphical editing · 0.5conservative rewriting · 0.5approximation · 0.5OWL 2 · 0.5ontology evolution · 0.3minimal change · 0.3graphol visual ontology language · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | Mapping Repair in Ontology-based Data Access Evolving SystemsabstractIn this paper we study the evolution of ontology-based data access (OBDA) specifications, and focus on the case in which the ontology and/or the data source schema change, which may require a modification to the mapping between them to preserve both consistency and knowledge. Our approach is based on the idea of repairing the mapping according to the usual principle of minimal change and on a recent, mapping-based notion of consistency of the specification. We define and analyze two notions of mapping repair under ontology and source schema update. We then present a set of results on the complexity of query answering in the above framework, when the ontology is expressed in DL-LiteR. Domenico Lembo, Riccardo Rosati 0001, Valerio Santarelli, Domenico Fabio Savo, Evgenij Thorstensen |
IJCAI | 3 |
| 2016 | Beyond OWL 2 QL in OBDA: Rewritings and ApproximationsabstractOntology-based data access (OBDA) is a novel paradigm facilitating access to relational data, realized by linking data sources to an ontology by means of declarative mappings. DL-Lite_R, which is the logic underpinning the W3C ontology language OWL 2 QL and the current language of choice for OBDA, has been designed with the goal of delegating query answering to the underlying database engine, and thus is restricted in expressive power. E.g., it does not allow one to express disjunctive information, and any form of recursion on the data. The aim of this paper is to overcome these limitations of DL-Lite_R, and extend OBDA to more expressive ontology languages, while still leveraging the underlying relational technology for query answering. We achieve this by relying on two well-known mechanisms, namely conservative rewriting and approximation, but significantly extend their practical impact by bringing into the picture the mapping, an essential component of OBDA. Specifically, we develop techniques to rewrite OBDA specifications with an expressive ontology to "equivalent" ones with a DL-Lite_R ontology, if possible, and to approximate them otherwise. We do so by exploiting the high expressive power of the mapping layer to capture part of the domain semantics of rich ontology languages. We have implemented our techniques in the prototype system OntoProx, making use of the state-of-the-art OBDA system Ontop and the query answering system Clipper, and we have shown their feasibility and effectiveness with experiments on synthetic and real-world data. Elena Botoeva, Diego Calvanese, Valerio Santarelli, Domenico Fabio Savo, Alessandro Solimando, Guohui Xiao 0001 |
AAAI | 3 |
| 2016 | Eddy: A Graphical Editor for OWL 2 Ontologies
Domenico Lembo, Daniele Pantaleone, Valerio Santarelli, Domenico Fabio Savo |
IJCAI | 3 |
| 2016 | Easy OWL Drawing with the Graphol Visual Ontology Language
Domenico Lembo, Daniele Pantaleone, Valerio Santarelli, Domenico Fabio Savo |
KR | 3 |
| 2014 | Effective Computation of Maximal Sound Approximations of Description Logic Ontologies
Marco Console, Jose Mora, Riccardo Rosati 0001, Valerio Santarelli, Domenico Fabio Savo |
ISWC (2) | 4 |
| 2013 | Graph-Based Ontology Classification in OWL 2 QL
Domenico Lembo, Valerio Santarelli, Domenico Fabio Savo |
ESWC | 2 |
| 2013 | MASTRO STUDIO: Managing Ontology-Based Data Access applicationsabstractOntology-based data access (OBDA) is a novel paradigm for accessing large data repositories through an ontology, that is a formal description of a domain of interest. Supporting the management of OBDA applications poses new challenges, as it requires to provide effective tools for (i) allowing both expert and non-expert users to analyze the OBDA specification, (ii) collaboratively documenting the ontology, (iii) exploiting OBDA services, such as query answering and automated reasoning over ontologies, e.g., to support data quality check, and (iv) tuning the OBDA application towards optimized performances. To fulfill these challenges, we have built a novel system, called MASTRO STUDIO, based on a tool for automated reasoning over ontologies, enhanced with a suite of tools and optimization facilities for managing OBDA applications. To show the effectiveness of MASTRO STUDIO, we demonstrate its usage in one OBDA application developed in collaboration with the Italian Ministry of Economy and Finance. Cristina Civili, Marco Console, Giuseppe De Giacomo, Domenico Lembo, Maurizio Lenzerini, Lorenzo Lepore, Riccardo Mancini, Antonella Poggi, Riccardo Rosati 0001, Marco Ruzzi, Valerio Santarelli, Domenico Fabio Savo |
Proc. VLDB Endow. | 11 |