1,373 research outputs found
A Potpourri of Reason Maintenance Methods
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
Pengines: Web Logic Programming Made Easy
When developing a (web) interface for a deductive database, functionality
required by the client is provided by means of HTTP handlers that wrap the
logical data access predicates. These handlers are responsible for converting
between client and server data representations and typically include options
for paginating results. Designing the web accessible API is difficult because
it is hard to predict the exact requirements of clients. Pengines changes this
picture. The client provides a Prolog program that selects the required data by
accessing the logical API of the server. The pengine infrastructure provides
general mechanisms for converting Prolog data and handling Prolog
non-determinism. The Pengines library is small (2000 lines Prolog, 150 lines
JavaScript). It greatly simplifies defining an AJAX based client for a Prolog
program and provides non-deterministic RPC between Prolog processes as well as
interaction with Prolog engines similar to Paul Tarau's engines. Pengines are
available as a standard package for SWI-Prolog 7.Comment: To appear in Theory and Practice of Logic Programmin
A General Framework for Representing, Reasoning and Querying with Annotated Semantic Web Data
We describe a generic framework for representing and reasoning with annotated
Semantic Web data, a task becoming more important with the recent increased
amount of inconsistent and non-reliable meta-data on the web. We formalise the
annotated language, the corresponding deductive system and address the query
answering problem. Previous contributions on specific RDF annotation domains
are encompassed by our unified reasoning formalism as we show by instantiating
it on (i) temporal, (ii) fuzzy, and (iii) provenance annotations. Moreover, we
provide a generic method for combining multiple annotation domains allowing to
represent, e.g. temporally-annotated fuzzy RDF. Furthermore, we address the
development of a query language -- AnQL -- that is inspired by SPARQL,
including several features of SPARQL 1.1 (subqueries, aggregates, assignment,
solution modifiers) along with the formal definitions of their semantics
Taming Existence in RDF Querying
We introduce the recursive, rule-based RDF query language
RDFLog. RDFLog extends previous RDF query languages by arbitrary
quantifier alternation: blank nodes may occur in the scope of all, some,
or none of the universal variables of a rule. In addition RDFLog is aware
of important RDF features such as the distinction between blank nodes,
literals and URIs or the RDFS vocabulary. The semantics of RDFLog is
closed (every answer is an RDF graph), but lifts RDF’s restrictions on
literal and blank node occurrences for intermediary data. We show how
to define a sound and complete operational semantics that can be implemented
using existing logic programming techniques. Using RDFLog
we classify previous approaches to RDF querying along their support for
blank node construction and show equivalence between languages with
full quantifier alternation and languages with only ∀∃ rules
Reason Maintenance - State of the Art
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
A Provenance Tracking Model for Data Updates
For data-centric systems, provenance tracking is particularly important when
the system is open and decentralised, such as the Web of Linked Data. In this
paper, a concise but expressive calculus which models data updates is
presented. The calculus is used to provide an operational semantics for a
system where data and updates interact concurrently. The operational semantics
of the calculus also tracks the provenance of data with respect to updates.
This provides a new formal semantics extending provenance diagrams which takes
into account the execution of processes in a concurrent setting. Moreover, a
sound and complete model for the calculus based on ideals of series-parallel
DAGs is provided. The notion of provenance introduced can be used as a
subjective indicator of the quality of data in concurrent interacting systems.Comment: In Proceedings FOCLASA 2012, arXiv:1208.432
Reason Maintenance - Conceptual Framework
This paper describes the conceptual framework for reason maintenance developed as part of
WP2
Developing an ontology of mathematical logic
An ontology provides a mechanism to formally represent a body of knowledge. Ontologies are one of the key technologies supporting the Semantic Web and the desire to add meaning to the information available on the World Wide Web. They provide the mechanism to describe a set of concepts, their properties and their relations to give a shared representation of knowledge. The MALog project are developing an ontology to support the development of high-quality learning materials in the general area of mathematical logic. This ontology of mathematical logic will form the basis of the semantic architecture allowing us to relate different learning objects and recommend appropriate learning paths. This paper reviews the technologies used to construct the ontology, the use of the ontology to support learning object development and explores the potential future use of the ontology
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