On the Ostensibly Silent ‘W’ in OWL 2 RL

Hogan, Aidan; Decker, Stefan

doi:10.1007/978-3-642-05082-4_9

“…For the purposes of this paper, we chose to focus on a materialization approach, although supporting resolution-based reasoning is considered future work. We note that many Semantic Web rule-based reasoners, including DLEJena [36], SAOR [23], OwlOntDb [16] and RuQAR [5], also follow a materialization approach.…”

Section: Reasoning Tasksmentioning

confidence: 99%

Benchmarking semantic reasoning on mobile platforms: Towards optimization using OWL2 RL

Woensel

¹

2019

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Mobile hardware has advanced to a point where apps may consume the Semantic Web of Data, as exemplified in domains such as mobile context-awareness, m-Health, m-Tourism and augmented reality. However, recent work shows that the performance of ontology-based reasoning, an essential Semantic Web building block, still leaves much to be desired on mobile platforms. This presents a clear need to provide developers with the ability to benchmark mobile reasoning performance, based on their particular application scenarios, i.e., including reasoning tasks, process flows and datasets, to establish the feasibility of mobile deployment. In this regard, we present a mobile benchmark framework called MobiBench to help developers to benchmark semantic reasoners on mobile platforms. To realize efficient mobile, ontology-based reasoning, OWL2 RL is a promising solution since it (a) trades expressivity for scalability, which is important on resource-constrained platforms; and (b) provides unique opportunities for optimization due to its rule-based axiomatization. In this vein, we propose selections of OWL2 RL rule subsets for optimization purposes, based on several orthogonal dimensions. We extended MobiBench to support OWL2 RL and the proposed ruleset selections, and benchmarked multiple OWL2 RL-enabled rule engines and OWL reasoners on a mobile platform. Our results show significant performance improvements by applying OWL2 RL rule subsets, allowing performant reasoning for small datasets on mobile systems.

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“…: OWL 2 RL [51]. In [73], we presented discussion on the new ruleset from the perspective of application over Web data, and showed that the ruleset is not immediately amenable to the requirements outlined, and still needs amendment for our purposes.…”

Section: High-level Approachmentioning

confidence: 99%

“…Herein, we follow on from discussion in [73] and implement a fragment of OWL 2 RL/RDF: we present our ruleset in Appendix B and now briefly discuss how we tailored the standard ruleset [51] for our purposes. 37 Firstly, we do not apply rules which specifically infer what we term as "tautological statements", which refer to syntactic RDFS and OWL statements such as rdf:type rdfs:Resource statements, and reflexive owl:sameAs statements -statements which apply to every term in the graph.…”

Section: High-level Approachmentioning

confidence: 99%

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Searching and browsing Linked Data with SWSE: The Semantic Web Search Engine

Hogan

¹

,

Harth

²

,

Umbrich

³

et al. 2011

Journal of Web Semantics

Self Cite

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In this paper, we discuss the architecture and implementation of the Semantic Web Search Engine (SWSE). Following traditional search engine architecture, SWSE consists of crawling, data enhancing, indexing and a user interface for search, browsing and retrieval of information; unlike traditional search engines, SWSE operates over RDF Web dataloosely also known as Linked Data -which implies unique challenges for the system design, architecture, algorithms, implementation and user interface. In particular, many challenges exist in adopting Semantic Web technologies for Web data: the unique challenges of the Web -in terms of scale, unreliability, inconsistency and noise -are largely overlooked by the current Semantic Web standards. Herein, we describe the current SWSE system, initially detailing the architecture and later elaborating upon the function, design, implementation and performance of each individual component. In so doing, we also give an insight into how current Semantic Web standards can be tailored, in a besteffort manner, for use on Web data. Throughout, we offer evaluation and complementary argumentation to support our design choices, and also offer discussion on future directions and open research questions. Later, we also provide candid discussion relating to the difficulties currently faced in bringing such a search engine into the mainstream, and lessons learnt from roughly six years working on the Semantic Web Search Engine project.

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“…37 Please note that we do not consider rules which infer an inconsistent (have a false consequent), and consider equality reasoning separately in the consolidation component: thus we do not support any of the rules in rule group R2 as defined in [73] -also of note, we co-incidently do not supported any rules which use the new OWL 2 constructs, since they require A-Box joins which -as we will justify herein -our system currently does not support. 38 For example, we consider the triples mo:wikipedia rdfs:subPropertyOf foaf:page .…”

Section: High-level Approachmentioning

confidence: 99%

Searching and Browsing Linked Data with SWSE: The Semantic Web Search Engine

Hogan

¹

,

Harth

²

,

Umbrich

³

et al. 2011

Self Cite

View full text Add to dashboard Cite

In this paper, we discuss the architecture and implementation of the Semantic Web Search Engine (SWSE). Following traditional search engine architecture, SWSE consists of crawling, data enhancing, indexing and a user interface for search, browsing and retrieval of information; unlike traditional search engines, SWSE operates over RDF Web dataloosely also known as Linked Data -which implies unique challenges for the system design, architecture, algorithms, implementation and user interface. In particular, many challenges exist in adopting Semantic Web technologies for Web data: the unique challenges of the Web -in terms of scale, unreliability, inconsistency and noise -are largely overlooked by the current Semantic Web standards. Herein, we describe the current SWSE system, initially detailing the architecture and later elaborating upon the function, design, implementation and performance of each individual component. In so doing, we also give an insight into how current Semantic Web standards can be tailored, in a besteffort manner, for use on Web data. Throughout, we offer evaluation and complementary argumentation to support our design choices, and also offer discussion on future directions and open research questions. Later, we also provide candid discussion relating to the difficulties currently faced in bringing such a search engine into the mainstream, and lessons learnt from roughly six years working on the Semantic Web Search Engine project.

show abstract

On the Ostensibly Silent ‘W’ in OWL 2 RL

Cited by 11 publications

References 11 publications

Benchmarking semantic reasoning on mobile platforms: Towards optimization using OWL2 RL

Benchmarking semantic reasoning on mobile platforms: Towards optimization using OWL2 RL

Searching and browsing Linked Data with SWSE: The Semantic Web Search Engine

Searching and Browsing Linked Data with SWSE: The Semantic Web Search Engine

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