Ontology-Based Data Access: A Survey

Xiao, Guohui; Calvanese, Diego; Kontchakov, Roman; Lembo, Domenico; Poggi, Antonella; Rosati, Riccardo; Zakharyaschev, Michael

doi:10.24963/ijcai.2018/777

Cited by 222 publications

(139 citation statements)

References 44 publications

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“…Data complexity may also be investigated, as well as algorithmic aspects, in particular FO-rewritability, i.e. the possibility to rewrite a query over a KB into a query over its ABox only, which is a key property for OMQA/OBDA [16]. Other DLs and/or fragments of sparql may also be considered.…”

Section: Discussionmentioning

confidence: 99%

Certain Answers to a sparql Query over a Knowledge Base

Corman

Xiao

2020

Semantic Technology

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Ontology-Mediated Query Answering (OMQA) is a wellestablished framework to answer queries over an rdfs or owl Knowledge Base (KB). OMQA was originally designed for unions of conjunctive queries (UCQs), and based on certain answers. More recently, OMQA has been extended to sparql queries, but to our knowledge, none of the efforts made in this direction (either in the literature, or the so-called sparql entailment regimes) is able to capture both certain answers for UCQs and the standard interpretation of sparql over a plain graph. We formalize these as requirements to be met by any semantics aiming at conciliating certain answers and sparql answers, and define three additional requirements, which generalize to KBs some basic properties of sparql answers. Then we show that a semantics can be defined that satisfies all requirements for sparql queries with SELECT, UNION, and OPTIONAL, and for DLs with the canonical model property. We also investigate combined complexity for query answering under such a semantics over DL-LiteR KBs. In particular, we show for different fragments of sparql that known upper-bounds for query answering over a plain graph are matched.

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Section: Discussionmentioning

confidence: 99%

Certain Answers to a sparql Query over a Knowledge Base

Corman

Xiao

2020

Semantic Technology

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“…Ontology-based data access (OBDA) is about accessing data from underlying sources through an ontology, most typically via queries expressed in the language of the ontology, which has access to the data through mappings [55]. The combination of extensional database (EDB) and the ontology may become inconsistent and has to be repaired.…”

Section: Beyond Relational Dbs: Ontology-based Data Accessmentioning

confidence: 99%

Repair-Based Degrees of Database Inconsistency

Bertossi¹

2019

Lecture Notes in Computer Science

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We propose a generic numerical measure of the inconsistency of a database with respect to a set of integrity constraints. It is based on an abstract repair semantics. In particular, an inconsistency measure associated to cardinalityrepairs is investigated in detail. More specifically, it is shown that it can be computed via answer-set programs, but sometimes its computation can be intractable in data complexity. However, polynomial-time deterministic and randomized approximations are exhibited. The behavior of this measure under small updates is analyzed, obtaining fixed-parameter tractability results. Furthermore, alternative inconsistency measures are proposed and discussed.

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“…The central aspect of this family of semantic portals (including SmartGround) is the help offered to a community of users, each one contributing to the global knowledge base while also consuming the common enriched knowledge. See [27] for a survey of relevant semantic technologies.…”

Section: Related Workmentioning

confidence: 99%

Crowd Sourced Semantic Enrichment (CroSSE) for knowledge driven querying of digital resources

Cavallo¹,

Mauro²,

Pasteris³

et al. 2019

J Intell Inf Syst

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Today, most information sources provide factual, objective knowledge, but they fail to capture personalized contextual knowledge which could be used to enrich the available factual data and contribute to their interpretation, in the context of the knowledge of the user who queries the system. This would require a knowledge framework which can accommodate both objective data and semantic enrichments that capture user provided knowledge associated to the factual data in the database. Unfortunately, most conventional DBMSs lack the flexibilities necessary (a) to prevent the data and metadata, evolve quickly with changing application requirements and (b) to capture user-provided and/or crowdsourced data and knowledge for more effective decision support. In this paper, we present CrowdSourced Semantic Enrichment (CroSSE) knowledge framework which allows traditional databases and semantic enrichment modules to coexist. CroSSE provides a novel Semantically Enriched SQL (SESQL) language to enrich SQL queries with information from a knowledge base containing semantic annotations. We describe CroSSE and SESQL with examples taken from our SmartGround EU project.

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Ontology-Based Data Access: A Survey

Cited by 222 publications

References 44 publications

Certain Answers to a sparql Query over a Knowledge Base

Certain Answers to a sparql Query over a Knowledge Base

Repair-Based Degrees of Database Inconsistency

Crowd Sourced Semantic Enrichment (CroSSE) for knowledge driven querying of digital resources

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