Query Answering for OWL-DL with rules

Motik, Boris; Sattler, Ulrike; Studer, Rudi

doi:10.1016/j.websem.2005.05.001

Cited by 346 publications

(161 citation statements)

References 9 publications

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“…One of the first attempts to overcome the limitations of OWL for representing cycles was DL-safe rules [51]. The extension of OWL ontologies with DL-safe rules allowed certain reasoning tasks to be performed over non-tree-like structures while preserving decidability.…”

Section: Resultsmentioning

confidence: 99%

Structure-based classification and ontology in chemistry

et al. 2012

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BackgroundRecent years have seen an explosion in the availability of data in the chemistry domain. With this information explosion, however, retrieving relevant results from the available information, and organising those results, become even harder problems. Computational processing is essential to filter and organise the available resources so as to better facilitate the work of scientists. Ontologies encode expert domain knowledge in a hierarchically organised machine-processable format. One such ontology for the chemical domain is ChEBI. ChEBI provides a classification of chemicals based on their structural features and a role or activity-based classification. An example of a structure-based class is 'pentacyclic compound' (compounds containing five-ring structures), while an example of a role-based class is 'analgesic', since many different chemicals can act as analgesics without sharing structural features. Structure-based classification in chemistry exploits elegant regularities and symmetries in the underlying chemical domain. As yet, there has been neither a systematic analysis of the types of structural classification in use in chemistry nor a comparison to the capabilities of available technologies.ResultsWe analyze the different categories of structural classes in chemistry, presenting a list of patterns for features found in class definitions. We compare these patterns of class definition to tools which allow for automation of hierarchy construction within cheminformatics and within logic-based ontology technology, going into detail in the latter case with respect to the expressive capabilities of the Web Ontology Language and recent extensions for modelling structured objects. Finally we discuss the relationships and interactions between cheminformatics approaches and logic-based approaches.ConclusionSystems that perform intelligent reasoning tasks on chemistry data require a diverse set of underlying computational utilities including algorithmic, statistical and logic-based tools. For the task of automatic structure-based classification of chemical entities, essential to managing the vast swathes of chemical data being brought online, systems which are capable of hybrid reasoning combining several different approaches are crucial. We provide a thorough review of the available tools and methodologies, and identify areas of open research.

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Section: Resultsmentioning

confidence: 99%

Structure-based classification and ontology in chemistry

et al. 2012

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“…Pellet) because of the DL-safe restriction of the reasoners. DL-safe restriction assumes that all instances of rules, both in conditions and in conclusions, should be available at the knowledge base [17]. Unfortunately, however, the rules for the event extraction generate new instances of events and event attributes in the conclusions.…”

Section: Methodsmentioning

confidence: 99%

Improving the extraction of complex regulatory events from scientific text by using ontology-based inference

Kim¹,

Rebholz‐Schuhmann²

2011

J Biomed Sem

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BackgroundThe extraction of complex events from biomedical text is a challenging task and requires in-depth semantic analysis. Previous approaches associate lexical and syntactic resources with ontologies for the semantic analysis, but fall short in testing the benefits from the use of domain knowledge.ResultsWe developed a system that deduces implicit events from explicitly expressed events by using inference rules that encode domain knowledge. We evaluated the system with the inference module on three tasks: First, when tested against a corpus with manually annotated events, the inference module of our system contributes 53.2% of correct extractions, but does not cause any incorrect results. Second, the system overall reproduces 33.1% of the transcription regulatory events contained in RegulonDB (up to 85.0% precision) and the inference module is required for 93.8% of the reproduced events. Third, we applied the system with minimum adaptations to the identification of cell activity regulation events, confirming that the inference improves the performance of the system also on this task.ConclusionsOur research shows that the inference based on domain knowledge plays a significant role in extracting complex events from text. This approach has great potential in recognizing the complex concepts of such biomedical ontologies as Gene Ontology in the literature.

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“…Besides that, SWRL might lead to undecidable implementation models. Nevertheless, this issue may be overcome by restricting the use of rules for handling only those which are DL-safe [20].…”

Section: Configuration Management Implementation Modelmentioning

confidence: 99%

Implementation and application of a well-founded configuration management ontology

Baioco

Garcia

2010

2010 IEEE/IFIP Network Operations and Management Symposium Workshops

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Information technology (IT) is becoming essential for organizations. In this context, IT management has evolved to include IT service management and governance, towards business driven IT management paradigms. Thus, the alignment between IT and business has been regarded as one of the leading factors to the effectiveness of such paradigms. Furthermore, contributions from management activities automation are mentioned. Following these evolution, configuration management plays a key role by providing accurate IT information to all related to management. However, due to this closed relationship among all management agents, interoperability between these agents has been characterized as one of the main research challenges in network and service management. This paper extends the contributions of [13], designing and implementing the conceptual models in implementation models. Thus, the main goal of this paper is to show how concepts modeled by ontologies can be implemented and applied in a computational system, allowing the conception of automated and semantically interoperable management solutions.

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Query Answering for OWL-DL with rules

Cited by 346 publications

References 9 publications

Structure-based classification and ontology in chemistry

Structure-based classification and ontology in chemistry

Improving the extraction of complex regulatory events from scientific text by using ontology-based inference

Implementation and application of a well-founded configuration management ontology

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