32 research outputs found

    Reason Maintenance - State of the Art

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    This paper describes state of the art in reason maintenance with a focus on its future usage in the KiWi project. To give a bigger picture of the field, it also mentions closely related issues such as non-monotonic logic and paraconsistency. The paper is organized as follows: first, two motivating scenarios referring to semantic wikis are presented which are then used to introduce the different reason maintenance techniques

    Reason Maintenance - Conceptual Framework

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    This paper describes the conceptual framework for reason maintenance developed as part of WP2

    Constructive Reasoning for Semantic Wikis

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    One of the main design goals of social software, such as wikis, is to support and facilitate interaction and collaboration. This dissertation explores challenges that arise from extending social software with advanced facilities such as reasoning and semantic annotations and presents tools in form of a conceptual model, structured tags, a rule language, and a set of novel forward chaining and reason maintenance methods for processing such rules that help to overcome the challenges. Wikis and semantic wikis were usually developed in an ad-hoc manner, without much thought about the underlying concepts. A conceptual model suitable for a semantic wiki that takes advanced features such as annotations and reasoning into account is proposed. Moreover, so called structured tags are proposed as a semi-formal knowledge representation step between informal and formal annotations. The focus of rule languages for the Semantic Web has been predominantly on expert users and on the interplay of rule languages and ontologies. KWRL, the KiWi Rule Language, is proposed as a rule language for a semantic wiki that is easily understandable for users as it is aware of the conceptual model of a wiki and as it is inconsistency-tolerant, and that can be efficiently evaluated as it builds upon Datalog concepts. The requirement for fast response times of interactive software translates in our work to bottom-up evaluation (materialization) of rules (views) ahead of time – that is when rules or data change, not when they are queried. Materialized views have to be updated when data or rules change. While incremental view maintenance was intensively studied in the past and literature on the subject is abundant, the existing methods have surprisingly many disadvantages – they do not provide all information desirable for explanation of derived information, they require evaluation of possibly substantially larger Datalog programs with negation, they recompute the whole extension of a predicate even if only a small part of it is affected by a change, they require adaptation for handling general rule changes. A particular contribution of this dissertation consists in a set of forward chaining and reason maintenance methods with a simple declarative description that are efficient and derive and maintain information necessary for reason maintenance and explanation. The reasoning methods and most of the reason maintenance methods are described in terms of a set of extended immediate consequence operators the properties of which are proven in the classical logical programming framework. In contrast to existing methods, the reason maintenance methods in this dissertation work by evaluating the original Datalog program – they do not introduce negation if it is not present in the input program – and only the affected part of a predicate’s extension is recomputed. Moreover, our methods directly handle changes in both data and rules; a rule change does not need to be handled as a special case. A framework of support graphs, a data structure inspired by justification graphs of classical reason maintenance, is proposed. Support graphs enable a unified description and a formal comparison of the various reasoning and reason maintenance methods and define a notion of a derivation such that the number of derivations of an atom is always finite even in the recursive Datalog case. A practical approach to implementing reasoning, reason maintenance, and explanation in the KiWi semantic platform is also investigated. It is shown how an implementation may benefit from using a graph database instead of or along with a relational database

    A Perfect Match for Reasoning, Explanation, and Reason Maintenance

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    Path query languages have been previously shown to com- plement RDF rule languages in a natural way and have been used as a means to implement the RDFS derivation rules. RPL is a novel path query language specifically designed to be incorporated with RDF rules and comes in three avors: Node-, edge- and path- avored expressions allow to express conditional regular expressions over the nodes, edges, or nodes and edges appearing on paths within RDF graphs. Providing reg- ular string expressions and negation, RPL is more expressive than other RDF path languages that have been proposed. We give a compositional semantics for RPL and show that it can be evaluated efficiently, while several possible extensions of it cannot

    A Potpourri of Reason Maintenance Methods

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    We present novel methods to compute changes to materialized views in logic databases like those used by rule-based reasoners. Such reasoners have to address the problem of changing axioms in the presence of materializations of derived atoms. Existing approaches have drawbacks: some require to generate and evaluate large transformed programs that are in Datalog - while the source program is in Datalog and significantly smaller; some recompute the whole extension of a predicate even if only a small part of this extension is affected by the change. The methods presented in this article overcome these drawbacks and derive additional information useful also for explanation, at the price of an adaptation of the semi-naive forward chaining

    Dependency Updates and Reasoning in KiWi

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    KiWi is a framework for semantic social software applica- tions that combines the Wiki philosophy with Semantic Web technolo- gies. Applications based on KiWi can therefore leverage i.a. reasoning and versioning to follow both aspects and even go beyond existing tech- nologies. For example, KiWi allows composition of content items, which poses a challenge to the versioning system. In this paper we discuss ver- sioning of composed content items and challenges related to reasoning in collaborative social software, as both topics are concerned with updates on the application state

    A Perfect Match for Reasoning, Explanation, and Reason Maintenance

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    Path query languages have been previously shown to com- plement RDF rule languages in a natural way and have been used as a means to implement the RDFS derivation rules. RPL is a novel path query language specifically designed to be incorporated with RDF rules and comes in three avors: Node-, edge- and path- avored expressions allow to express conditional regular expressions over the nodes, edges, or nodes and edges appearing on paths within RDF graphs. Providing reg- ular string expressions and negation, RPL is more expressive than other RDF path languages that have been proposed. We give a compositional semantics for RPL and show that it can be evaluated efficiently, while several possible extensions of it cannot

    Magma mixing and exsolution phenomena in peralkaline rhyolites: insights from the Gold Flat Tuff, Nevada

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    The distribution and compositions of chevkinite-group minerals (CGMs) in the pantelleritic Gold Flat Tuff, Nevada, USA, are used to examine three aspects of the evolution of the tuff, which we feel are of general significance in peralkaline magmatism. First, both chevkinite-(Ce) and perrierite-(Ce) occur in certain facies, although normally these phases almost invariably occur in different igneous lithologies. Their co-occurrence in the tuff is due to the mixing of pantelleritic and intermediate magmas. Second, the tuff is the first recorded occurrence of a CGM in a pantellerite eruptive, with possible implications for the crystallization conditions. In particular, low values of aSiO2{{a}}\mathrm{SiO}_{2} may have stabilized ilmenite + chevkinite rather than aenigmatite, although the unusually high LREE contents (\sum La–Sm {\le } 1517 ppm) in the pantellerite may have played a role. Third, an unusual lamellar texture in the CGM is revealed by Atomic Force Microscopy to be formed by a rutile-like phase. The lamellae may have formed by exsolution from a rutile-like layer in the crystal structure. An electron back-scattered diffraction study of a single crystal showed a structural dislocation not apparent optically or by electron back-scattered imaging. This may have wider implications in mineralogical studies
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