140 research outputs found
XQOWL: An Extension of XQuery for OWL Querying and Reasoning
One of the main aims of the so-called Web of Data is to be able to handle
heterogeneous resources where data can be expressed in either XML or RDF. The
design of programming languages able to handle both XML and RDF data is a key
target in this context. In this paper we present a framework called XQOWL that
makes possible to handle XML and RDF/OWL data with XQuery. XQOWL can be
considered as an extension of the XQuery language that connects XQuery with
SPARQL and OWL reasoners. XQOWL embeds SPARQL queries (via Jena SPARQL engine)
in XQuery and enables to make calls to OWL reasoners (HermiT, Pellet and
FaCT++) from XQuery. It permits to combine queries against XML and RDF/OWL
resources as well as to reason with RDF/OWL data. Therefore input data can be
either XML or RDF/OWL and output data can be formatted in XML (also using
RDF/OWL XML serialization).Comment: In Proceedings PROLE 2014, arXiv:1501.0169
Survey over Existing Query and Transformation Languages
A widely acknowledged obstacle for realizing the vision of the Semantic Web is the inability
of many current Semantic Web approaches to cope with data available in such diverging
representation formalisms as XML, RDF, or Topic Maps. A common query language is the first
step to allow transparent access to data in any of these formats. To further the understanding
of the requirements and approaches proposed for query languages in the conventional as well
as the Semantic Web, this report surveys a large number of query languages for accessing
XML, RDF, or Topic Maps. This is the first systematic survey to consider query languages from
all these areas. From the detailed survey of these query languages, a common classification
scheme is derived that is useful for understanding and differentiating languages within and
among all three areas
Web and Semantic Web Query Languages
A number of techniques have been developed to facilitate
powerful data retrieval on the Web and Semantic Web. Three categories
of Web query languages can be distinguished, according to the format
of the data they can retrieve: XML, RDF and Topic Maps. This article
introduces the spectrum of languages falling into these categories
and summarises their salient aspects. The languages are introduced using
common sample data and query types. Key aspects of the query
languages considered are stressed in a conclusion
Use-cases on evolution
This report presents a set of use cases for evolution and reactivity for data in the Web and
Semantic Web. This set is organized around three different case study scenarios, each of them
is related to one of the three different areas of application within Rewerse. Namely, the scenarios
are: “The Rewerse Information System and Portal”, closely related to the work of A3
– Personalised Information Systems; “Organizing Travels”, that may be related to the work
of A1 – Events, Time, and Locations; “Updates and evolution in bioinformatics data sources”
related to the work of A2 – Towards a Bioinformatics Web
Identification of Design Principles
This report identifies those design principles for a (possibly new) query and transformation
language for the Web supporting inference that are considered essential. Based upon these
design principles an initial strawman is selected. Scenarios for querying the Semantic Web
illustrate the design principles and their reflection in the initial strawman, i.e., a first draft of
the query language to be designed and implemented by the REWERSE working group I4
Methods for Semantic Interoperability in AutomationML-based Engineering
Industrial engineering is an interdisciplinary activity that involves human experts from various technical backgrounds working with different engineering tools. In the era of digitization, the engineering process generates a vast amount of data. To store and exchange such data, dedicated international standards are developed, including the XML-based data format AutomationML (AML). While AML provides a harmonized syntax among engineering tools, the semantics of engineering data remains highly heterogeneous. More specifically, the AML models of the same domain or entity can vary dramatically among different tools that give rise to the so-called semantic interoperability problem. In practice, manual implementation is often required for the correct data interpretation, which is usually limited in reusability.
Efforts have been made for tackling the semantic interoperability problem. One mainstream research direction has been focused on the semantic lifting of engineering data using Semantic Web technologies. However, current results in this field lack the study of building complex domain knowledge that requires a profound understanding of the domain and sufficient skills in ontology building. This thesis contributes to this research field in two aspects. First, machine learning algorithms are developed for deriving complex ontological concepts from engineering data. The induced concepts encode the relations between primitive ones and bridge the semantic gap between engineering tools. Second, to involve domain experts more tightly into the process of ontology building, this thesis proposes the AML concept model (ACM) for representing ontological concepts in a native AML syntax, i.e., providing an AML-frontend for the formal ontological semantics. ACM supports the bidirectional information flow between the user and the learner, based on which the interactive machine learning framework AMLLEARNER is developed.
Another rapidly growing research field devotes to develop methods and systems for facilitating data access and exchange based on database theories and techniques. In particular, the so-called Query By Example (QBE) allows the user to construct queries using data examples. This thesis adopts the idea of QBE in AML-based engineering by introducing the AML Query Template (AQT). The design of AQT has been focused on a native AML syntax, which allows constructing queries with conventional AML tools. This thesis studies the theoretical foundation of AQT and presents algorithms for the automated generation of query programs. Comprehensive requirement analysis shows that the proposed approach can solve the problem of semantic interoperability in AutomationML-based engineering to a great extent
Querying and reasoning with RDF(S)/OWL in XQuery
Abstract. In this paper we investigate how to use the XQuery language for querying and reasoning with RDF(S)/OWL-style ontologies. Our proposal allows the handling of RDF(S)/OWL triples by means of a XQuery library for the Semantic Web, and it encodes RDF(S)/OWL reasoning by means of XQuery functions. We have tested and implemented the approach
State-of-the-art on evolution and reactivity
This report starts by, in Chapter 1, outlining aspects of querying and updating resources on
the Web and on the Semantic Web, including the development of query and update languages
to be carried out within the Rewerse project.
From this outline, it becomes clear that several existing research areas and topics are of
interest for this work in Rewerse. In the remainder of this report we further present state of
the art surveys in a selection of such areas and topics. More precisely: in Chapter 2 we give
an overview of logics for reasoning about state change and updates; Chapter 3 is devoted to briefly describing existing update languages for the Web, and also for updating logic programs;
in Chapter 4 event-condition-action rules, both in the context of active database systems and
in the context of semistructured data, are surveyed; in Chapter 5 we give an overview of some relevant rule-based agents frameworks
Four Lessons in Versatility or How Query Languages Adapt to the Web
Exposing not only human-centered information, but machine-processable data on the Web is one of the commonalities of recent Web trends. It has enabled a new kind of applications and businesses where the data is used in ways not foreseen by the data providers. Yet this exposition has fractured the Web into islands of data, each in different Web formats: Some providers choose XML, others RDF, again others JSON or OWL, for their data, even in similar domains. This fracturing stifles innovation as application builders have to cope not only with one Web stack (e.g., XML technology) but with several ones, each of considerable complexity. With Xcerpt we have developed a rule- and pattern based query language that aims to give shield application builders from much of this complexity: In a single query language XML and RDF data can be accessed, processed, combined, and re-published. Though the need for combined access to XML and RDF data has been recognized in previous work (including the W3C’s GRDDL), our approach differs in four main aspects: (1) We provide a single language (rather than two separate or embedded languages), thus minimizing the conceptual overhead of dealing with disparate data formats. (2) Both the declarative (logic-based) and the operational semantics are unified in that they apply for querying XML and RDF in the same way. (3) We show that the resulting query language can be implemented reusing traditional database technology, if desirable. Nevertheless, we also give a unified evaluation approach based on interval labelings of graphs that is at least as fast as existing approaches for tree-shaped XML data, yet provides linear time and space querying also for many RDF graphs. We believe that Web query languages are the right tool for declarative data access in Web applications and that Xcerpt is a significant step towards a more convenient, yet highly efficient data access in a “Web of Data”
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