Queries with Negation and Inequalities over Lightweight Ontologies

Abstract

While the problem of answering positive existential queries, in particular, conjunctive queries (CQs) and unions of CQs, over description logic ontologies has been studied extensively, there have been few attempts to analyse queries with negated atoms. Our aim is to sharpen the complexity landscape of the problem of answering CQs with negation and inequalities in lightweight description logics of the DL-Lite and EL families. We begin by considering queries with safe negation and show that there is a surprisingly significant increase in the complexity from AC 0 to undecidability (even if the ontology and query are fixed and only the data is regarded as input). We also investigate the problem of answering queries with inequalities and show that answering a single CQ with one inequality over DL-Lite with role inclusions is undecidable. In the light of our undecidability results, we explore syntactic restrictions to attain efficient query answering with negated atoms. In particular, we identify a novel class of local CQs with inequalities, for which query answering over DL-Lite is decidable.

Domain and Schema Independent Semantic Model Verbalization: A Conceptual Overview

“…To quickly revise, firstly the complexity associated with comprehension of the schematics, as without properly knowing the schematics of the ontology, writing appropriate queries for the knowledge retrieval would be infeasible [10] [11] [13]. Secondly, even after the hurdle of comprehending schema is achieved as the next step, writing of accurate SPARQL or SQWRL queries to achieve the knowledge retrieval demands [22] [23] [24] will become a critical challenge. Users should have a sound knowledge about triple concepts of the ontologies and the relevant syntaxes as well as RDF and OWL axiom related concepts to properly write a query to fulfil knowledge requirements.…”

“…www.ijacsa.thesai.org Because without properly understanding the schema of the ontology, queries cannot be written to fulfil appropriate knowledge requirements. Secondly, writing of SPARQL or SQWRL queries to prorogate knowledge retrieval could be mostly an infeasible and unfair task to be expected from a nontechnical specialist [22] [23] [24]. Therefore, as already conversed, these two issues will act as critical bottlenecks hindering the effective usage of semantic technologies within and outside of the computing domain.…”

“…One of the potential solutions to overcome this technical barrier is to introduce ontology verbalizers. Verbalizers are capable of extracting knowledge represented in an OWL or RDF knowledge model and presenting it in a human understandable natural language [24].…”

Managing Data Through the Lens of an Ontology

“…As for the query language, we note that going beyond unions of CQs is problematic from the point of view of tractability, or even decidability. For instance, adding negation to CQs causes query answering to become undecidable (Gutiérrez-Basulto et al 2015).…”

Using Ontologies for Semantic Data Integration

“…As for the query language, we note that going beyond unions of CQs is problematic from the point of view of tractability, or even decidability. For instance, adding negation to CQs causes query answering to become undecidable [28].…”