STOWL: An OWL Extension for Facilitating the Definition of Taxonomies in Spatio-temporal Ontologies

Salguero, Alberto; Delgado, Cecilia; Araque, Francisco

doi:10.1007/978-3-642-04754-1_35

Cited by 3 publications

(3 citation statements)

References 7 publications

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“…Salguero et al define a STOWL language to build data sources schemes associated with temporal and spatial information. In other work by Salguero et al, the authors extend the OWL to describe the spatio‐temporal ontology so as to support the definition of taxonomies in a spatio‐temporal ontology. Batsakis and Petrakis propose an ontology model SOWL for dealing with quantitative and qualitative temporal and spatial information in ontologies.…”

Section: Related Workmentioning

confidence: 99%

“…With the development of the Semantic Web, a large amount of fuzzy spatio‐temporal knowledge and many related applications are incorporated into the Semantic Web . Currently, some authors have already investigated some spatio‐temporal extensions of ontology and OWL (Web Ontology Language) for modeling spatio‐temporal information such as STOWL, SOWL ontology, sensor ontology, Internet of Things ontology (IoT‐O), and logic‐based spatio‐temporal ontology . In addition, description logics (DLs), as a logical basis of OWL language, play an important role in the Semantic Web, especially in the design of ontologies.…”

Section: Introductionmentioning

confidence: 99%

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Fuzzy spatio‐temporal ontologies and formal construction based on fuzzy Petri nets

Cheng

et al. 2019

Computational Intelligence

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Fuzzy spatio‐temporal knowledge is required in a wide range of application fields, including GIS, spatio‐temporal database, and artificial intelligence. Ontology, as a formal method of knowledge representation, plays a key role in the Semantic Web. Therefore, how to extend ontologies to represent fuzzy spatio‐temporal knowledge needs to be solved. In this paper, we propose an approach for representing fuzzy spatio‐temporal knowledge with ontologies and investigate a formal construction of fuzzy spatio‐temporal ontologies based on fuzzy Petri nets. First, we propose a formal definition of fuzzy spatio‐temporal ontologies. In addition, based on fuzzy description logic, a description logic named the fuzzy spatio‐temporal description logic, which provides a logical basis for the fuzzy spatio‐temporal ontologies, is presented. Furthermore, a fuzzy spatio‐temporal web ontology language, which is fuzzy and spatio‐temporal extension of standard ontology language OWL, is proposed to make the fuzzy spatio‐temporal ontologies easy to use and support efficient reasoning. On the basis of fuzzy spatio‐temporal ontologies, we investigate a formal approach for constructing fuzzy spatio‐temporal ontologies from fuzzy spatio‐temporal Petri nets, ie, transforming fuzzy spatio‐temporal Petri nets (including Petri net model and Petri net instance) into fuzzy spatio‐temporal ontologies at both structure and instance levels. Finally, we prove the correctness of the transformation and provide a detailed transformation example.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fuzzy spatio‐temporal ontologies and formal construction based on fuzzy Petri nets

Cheng

et al. 2019

Computational Intelligence

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“…Since the model is semantic, i.e., based on an ontology, all system-defined relationships have formally-defined properties, and any application-defined property can also be described formally. There are related efforts by Salguero et al [2009] and Batsakis and Petrakis [2010] who extend the OWL ontology language to present spatiotemporal relationships and their properties. We also draw from basic concepts in the DOLCE upper ontology [Gangemi et al, 2002] and the work of Perry [2008] that develops an RDF-based data model to represent spatial, temporal and thematic relationships between data objects.…”

Section: E* -A Graph-based Event Model Using Rdf and Ontologiesmentioning

confidence: 99%

Managing Event Information: Modeling, Retrieval, and Applications

Gupta¹,

Jain²

2011

Synthesis Lectures on Data Management

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All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means-electronic, mechanical, photocopy, recording, or any other except for brief quotations in printed reviews, without the prior permission of the publisher. Managing Event Information: Modeling, Retrieval, and Applications ABSTRACTWith the proliferation of citizen reporting, smart mobile devices, and social media, an increasing number of people are beginning generate information about events they observe and participate in. A significant fraction of this information contain multimedia data to share the experience with their audience. A systematic information modeling and management framework is necessary to capture this widely heterogeneous, schemaless, potentially humongous information produced by many different people. This book is an attempt to examine the modeling, storage, querying, and applications of such an event management system in a holistic manner. It uses a semantic-web style graph-based view of events, and shows how this event model, together with its query facility, can be used toward emerging applications like semi-automated storytelling.

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MRQUTER : A Parallel Qualitative Temporal Reasoner Using MapReduce Framework

Kim

Kim²

2016

KIPS Transactions on Software and Data Engineering

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In order to meet rapid changes of Web information, it is necessary to extend the current Web technologies to represent both the valid time and location of each fact and knowledge, and reason their relationships. Until recently, many researches on qualitative temporal reasoning have been conducted in laboratory-scale, dealing with small knowledge bases. However, in this paper, we propose the design and implementation of a parallel qualitative temporal reasoner, MRQUTER, which can make reasoning over Web-scale large knowledge bases. This parallel temporal reasoner was built on a Hadoop cluster system using the MapReduce parallel programming framework. It decomposes the entire qualitative temporal reasoning process into several MapReduce jobs such as the encoding and decoding job, the inverse and equal reasoning job, the transitive reasoning job, the refining job, and applies some optimization techniques into each component reasoning job implemented with a pair of Map and Reduce functions. Through experiments using large benchmarking temporal knowledge bases, MRQUTER shows high reasoning performance and scalability.

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STOWL: An OWL Extension for Facilitating the Definition of Taxonomies in Spatio-temporal Ontologies

Cited by 3 publications

References 7 publications

Fuzzy spatio‐temporal ontologies and formal construction based on fuzzy Petri nets

Fuzzy spatio‐temporal ontologies and formal construction based on fuzzy Petri nets

Managing Event Information: Modeling, Retrieval, and Applications

MRQUTER : A Parallel Qualitative Temporal Reasoner Using MapReduce Framework

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