An Argumentation Workflow for Reasoning in Ontology Based Data Access

In this paper we demonstrate how to benefit from structured argumenta-tion frameworks and their implementations to provide for reasoning capabilities of Ontology Based Data Access systems under inconsistency tolerant semantics. More precisely, given an inconsistent Datalog ± knowledge base we instantiate it using the ASPIC + framework and show that the reasoning provided by ASPIC + is equivalent to the main inconsistent tolerant semantics in the literature. We provide a workflow that shows the practical interoperability of the logic based frameworks handling Datalog ± and ASPIC + .

[1]  Guillermo Ricardo Simari,et al.  Inconsistency-Tolerant Reasoning in Datalog ^± ± Ontologies via an Argumentative Semantics , 2014, IBERAMIA.

[2]  Madalina Croitoru,et al.  Introducing Preference-Based Argumentation to Inconsistent Ontological Knowledge Bases , 2015, PRIMA.

[3]  Meghyn Bienvenu,et al.  On the Complexity of Consistent Query Answering in the Presence of Simple Ontologies , 2012, AAAI.

[4]  Abdallah Arioua,et al.  Dialectical Characterization of Consistent Query Explanation with Existential Rules , 2016, FLAIRS Conference.

[5]  Philippe Besnard,et al.  Bridging the Gap between Abstract Argumentation Systems and Logic , 2009, SUM.

[6]  François Goasdoué,et al.  Querying Inconsistent Description Logic Knowledge Bases under Preferred Repair Semantics , 2014, Description Logics.

[7]  Andrea Calì,et al.  A general Datalog-based framework for tractable query answering over ontologies , 2012, J. Web Semant..

[8]  Jean-François Baget,et al.  On rules with existential variables: Walking the decidability line , 2011, Artif. Intell..

[9]  Phan Minh Dung,et al.  On the Acceptability of Arguments and its Fundamental Role in Nonmonotonic Reasoning, Logic Programming and n-Person Games , 1995, Artif. Intell..

[10]  Franz Baader,et al.  Pushing the EL Envelope , 2005, IJCAI.

[11]  Sebastian Rudolph,et al.  Walking the Complexity Lines for Generalized Guarded Existential Rules , 2011, IJCAI.

[12]  Abdallah Arioua,et al.  A Dialectical Proof Theory for Universal Acceptance in Coherent Logic-Based Argumentation Frameworks , 2016, ECAI.

[13]  Diego Calvanese,et al.  Linking Data to Ontologies , 2008, J. Data Semant..

[14]  Jean-François Baget,et al.  Revisiting Chase Termination for Existential Rules and their Extension to Nonmonotonic Negation , 2014, NMR 2014.

[15]  Leila Amgoud Five Weaknesses of ASPIC + , 2012, IPMU.

[16]  Marie-Laure Mugnier,et al.  Graph-based Knowledge Representation - Computational Foundations of Conceptual Graphs , 2008, Advanced Information and Knowledge Processing.

[17]  Henry Prakken,et al.  The ASPIC+ framework for structured argumentation: a tutorial , 2014, Argument Comput..

[18]  Diego Calvanese,et al.  Tractable Reasoning and Efficient Query Answering in Description Logics: The DL-Lite Family , 2007, Journal of Automated Reasoning.

[19]  Riccardo Rosati,et al.  Tractable Approximations of Consistent Query Answering for Robust Ontology-based Data Access , 2013, IJCAI.

[20]  Maurizio Lenzerini,et al.  Inconsistency-Tolerant Semantics for Description Logics , 2010, RR.

[21]  Andrea Calì,et al.  A general datalog-based framework for tractable query answering over ontologies , 2009, SEBD.

[22]  Georg Gottlob,et al.  Datalog±: a unified approach to ontologies and integrity constraints , 2009, ICDT '09.

[23]  Madalina Croitoru,et al.  What Can Argumentation Do for Inconsistent Ontology Query Answering? , 2013, SUM.

[24]  Marie-Laure Mugnier Ontological Query Answering with Existential Rules , 2011, RR.