摘要 :
Evolution and reactivity in the Semantic Web address the vision and concrete need for an active Web, where data sources evolve autonomously and perceive and react to events. In 2004, when the Rewerse project started, regarding wor...
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Evolution and reactivity in the Semantic Web address the vision and concrete need for an active Web, where data sources evolve autonomously and perceive and react to events. In 2004, when the Rewerse project started, regarding work on Evolution and Reactivity in the Semantic Web there wasn't much more than a vision of such an active Web.
Materialising this vision requires the definition of a model, architecture, and also prototypical implementations capable of dealing with reactivity in the Semantic Web, including an ontology-based description of all concepts. This resulted in a general framework for reactive Event-Condition-Action rules in the Semantic Web over heterogeneous component languages.
Inasmuch as heterogeneity of languages is, in our view, an important aspect to take into consideration for dealing with the heterogeneity of sources and behaviour of the Semantic Web, concrete homogeneous languages targeting the specificity of reactive rules are of course also needed. This is especially the case for languages that can cope with the challenges posed by dealing with composite structures of events, or executing composite actions over Web data.
In this chapter we report on the advances made on this front, namely by describing the above-mentioned general heterogeneous framework, and by describing the concrete homogeneous language XChange.
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摘要 :
The Web and the Semantic Web, as we see it, can be understood as a "living organism" combining autonomously evolving data sources, each of them possibly reacting to events it perceives. Rather than a Web of data sources, we envisa...
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The Web and the Semantic Web, as we see it, can be understood as a "living organism" combining autonomously evolving data sources, each of them possibly reacting to events it perceives. Rather than a Web of data sources, we envisage a Web of Information Systems, where each such system, besides being capable of gathering information (querying persistent data, as well as "listening" to volatile data such as occurring events), is capable of updating persistent data, communicating the changes, requesting changes of persistent data in other systems, and being able to react to requests from other systems. The dynamic character of such a Web requires declarative languages and mechanisms for specifying the evolution of the data. In this course we will talk about foundations of evolution and reactive languages in general, and will then concentrate on some specific issues posed by evolution and reactivity in the Web and in the Semantic Web.
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摘要 :
The Web and the Semantic Web, as we see it, can be understood as a "living organism" combining autonomously evolving data sources, each of them possibly reacting to events it perceives. Rather than a Web of data sources, we envisa...
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The Web and the Semantic Web, as we see it, can be understood as a "living organism" combining autonomously evolving data sources, each of them possibly reacting to events it perceives. Rather than a Web of data sources, we envisage a Web of Information Systems, where each such system, besides being capable of gathering information (querying persistent data, as well as "listening" to volatile data such as occurring events), is capable of updating persistent data, communicating the changes, requesting changes of persistent data in other systems, and being able to react to requests from other systems. The dynamic character of such a Web requires declarative languages and mechanisms for specifying the evolution of the data. In this course we will talk about foundations of evolution and reactive languages in general, and will then concentrate on some specific issues posed by evolution and reactivity in the Web and in the Semantic Web.
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摘要 :
An important branch of investigation in the field of agents has been the definition of high level languages for representing effects of actions, the programs written in such languages being usually called action programs. Logic pr...
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An important branch of investigation in the field of agents has been the definition of high level languages for representing effects of actions, the programs written in such languages being usually called action programs. Logic programming is an important area in the field of knowledge representation and some languages for specifying updates of Logic Programs had been defined. Starting from the update language Evolp, in this work we propose a new paradigm for reasoning about actions called Evolp action programs. We provide translations of some of the most known action description languages into Evolp action programs, and underline some peculiar features of this newly defined paradigm. One such feature is that Evolp action programs can easily express changes in the rules of the domains, including rules describing changes.
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摘要 :
An important branch of investigation in the field of agents has been the definition of high level languages for representing effects of actions, the programs written in such languages being usually called action programs. Logic pr...
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An important branch of investigation in the field of agents has been the definition of high level languages for representing effects of actions, the programs written in such languages being usually called action programs. Logic programming is an important area in the field of knowledge representation and some languages for specifying updates of Logic Programs had been defined. Starting from the update language Evolp, in this work we propose a new paradigm for reasoning about actions called Evolp action programs. We provide translations of some of the most known action description languages into Evolp action programs, and underline some peculiar features of this newly defined paradigm. One such feature is that Evolp action programs can easily express changes in the rules of the domains, including rules describing changes.
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摘要 :
Logic Programming Update Languages have been proposed as extensions of logic programming that allow specifying and reasoning about knowledge bases where both extensional knowledge (facts) as well as intentional knowledge (rules) m...
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Logic Programming Update Languages have been proposed as extensions of logic programming that allow specifying and reasoning about knowledge bases where both extensional knowledge (facts) as well as intentional knowledge (rules) may change over time as a result of updates.Despite their generality, these languages are limited in that they do not provide a means to directly access past states of the evolving knowledge. They only allow for so-called Markovian change, i.e. change which is entirely determined by the current state of the knowledge base.After motivating the need for non-Markovian change, we extend the language EVOLP - a Logic Programming Update Language - with Linear Temporal Logic-like operators, which allow referring to the history of an evolving knowledge base. We then show that it is in fact possible to embed the extended EVOLP into the original one, thus demonstrating that EVOLP itself is expressive enough to encode non-Markovian dynamic knowledge bases. This embedding additionally sheds light on the relationship between Logic Programming Update Languages and Modal Temporal Logics. The embedding is also the starting point of our implementation.
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摘要 :
Logic Programming Update Languages have been proposed as extensions of logic programming that allow specifying and reasoning about knowledge bases where both extensional knowledge (facts) as well as intentional knowledge (rules) m...
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Logic Programming Update Languages have been proposed as extensions of logic programming that allow specifying and reasoning about knowledge bases where both extensional knowledge (facts) as well as intentional knowledge (rules) may change over time as a result of updates.Despite their generality, these languages are limited in that they do not provide a means to directly access past states of the evolving knowledge. They only allow for so-called Markovian change, i.e. change which is entirely determined by the current state of the knowledge base.After motivating the need for non-Markovian change, we extend the language EVOLP - a Logic Programming Update Language - with Linear Temporal Logic-like operators, which allow referring to the history of an evolving knowledge base. We then show that it is in fact possible to embed the extended EVOLP into the original one, thus demonstrating that EVOLP itself is expressive enough to encode non-Markovian dynamic knowledge bases. This embedding additionally sheds light on the relationship between Logic Programming Update Languages and Modal Temporal Logics. The embedding is also the starting point of our implementation.
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In this paper we present the r{sup}3 ontology, a foundational ontology for reactive rules, aiming at coping with language heterogeneity at the rule (component) level. This (OWL-DL) ontology is at a low (structural) abstraction lev...
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In this paper we present the r{sup}3 ontology, a foundational ontology for reactive rules, aiming at coping with language heterogeneity at the rule (component) level. This (OWL-DL) ontology is at a low (structural) abstraction level thus fostering its extension. Although focusing on reactive rules (reactive derivation rules not excluded), the r{sup}3 ontology defines a vocabulary that allows also for the definition of rule (component) languages to model other types of rules like production, integrity, or logical derivation rules.
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In this paper we present the r~3 ontology, a foundational ontology for reactive rules, aiming at coping with language heterogeneity at the rule (component) level. This (OWL-DL) ontology is at a low (structural) abstraction level t...
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In this paper we present the r~3 ontology, a foundational ontology for reactive rules, aiming at coping with language heterogeneity at the rule (component) level. This (OWL-DL) ontology is at a low (structural) abstraction level thus fostering its extension. Although focusing on reactive rules (reactive derivation rules not excluded), the r~3 ontology defines a vocabulary that allows also for the definition of rule (component) languages to model other types of rules like production, integrity, or logical derivation rules.
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The Web of today can be seen as an active and heterogeneous infrastructure of autonomous systems, where reactivity, evolution and propagation of information and changes play a central role. In the same way as the main driving forc...
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The Web of today can be seen as an active and heterogeneous infrastructure of autonomous systems, where reactivity, evolution and propagation of information and changes play a central role. In the same way as the main driving force for XML and the Semantic Web idea was the heterogeneity of the underlying data, the heterogeneity of concepts for expressing behavior calls for an appropriate handling on the semantic level. We present an ontology-based approach for specifying behavior in the Semantic Web by Event-Condition-Action (ECA) rules that models rules as well as their event, condition, and action components, and languages as resources. The necessary information about semantics and suitable processors is then associated with the language resources. The approach makes use of the data integration facilities by URIs that allow for a seamless integration of information and services physically located at different places. Additionally, that point of view allows for sharing and reuse of these resources throughout the Semantic Web.
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