13,930 research outputs found
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
An infrastructure for building semantic web portals
In this paper, we present our KMi semantic web portal infrastructure, which supports two important tasks of semantic web portals, namely metadata extraction and data querying. Central to our infrastructure are three components: i) an automated metadata extraction tool, ASDI, which supports the extraction of high quality metadata from heterogeneous sources, ii) an ontology-driven question answering tool, AquaLog, which makes use of the domain specific ontology and the semantic metadata extracted by ASDI to answers questions in natural language format, and iii) a semantic search engine, which enhances traditional
text-based searching by making use of the underlying ontologies and the extracted metadata. A semantic web portal application has been built, which illustrates the usage of this infrastructure
Effective and Efficient Data Access in the Versatile Web Query Language Xcerpt
Access to Web data has become an integral part of many applications
and services. In the past, such data has usually been accessed
through human-tailoredHTMLinterfaces.Nowadays, rich client interfaces
in desktop applications or, increasingly, in browser-based clients ease data
access and allow more complex client processing based on XML or RDF
data retrieved throughWeb service interfaces. Convenient specifications of
the data processing on the client and flexible, expressive service interfaces
for data access become essential in this context.Web query languages such
as XQuery, XSLT, SPARQL, or Xcerpt have been tailored specifically for
such a setting: declarative and efficient access and processing ofWeb data.
Xcerpt stands apart among these languages by its versatility, i.e., its ability
to access not just oneWeb format but many. In this demonstration, two aspects
of Xcerpt are illustrated in detail: The first part of the demonstration
focuses on Xcerpt’s pattern matching constructs and rules to enable effective
and versatile data access. It uses a concrete practical use case from
bibliography management to illustrate these language features. Xcerpt’s
visual companion language visXcerpt is used to provide an intuitive interface
to both data and queries. The second part of the demonstration shows
recent advancements in Xcerpt’s implementation focusing on experimental
evaluation of recent complexity results and optimization techniques, as
well as scalability over a number of usage scenarios and input sizes
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
RDF Querying
Reactive Web systems, Web services, and Web-based publish/
subscribe systems communicate events as XML messages, and in
many cases require composite event detection: it is not sufficient to react
to single event messages, but events have to be considered in relation to
other events that are received over time.
Emphasizing language design and formal semantics, we describe the
rule-based query language XChangeEQ for detecting composite events.
XChangeEQ is designed to completely cover and integrate the four complementary
querying dimensions: event data, event composition, temporal
relationships, and event accumulation. Semantics are provided as
model and fixpoint theories; while this is an established approach for rule
languages, it has not been applied for event queries before
Data integration through service-based mediation for web-enabled information systems
The Web and its underlying platform technologies have often been used to integrate existing software and information systems. Traditional techniques for data representation and transformations between documents are not sufficient to support a flexible and maintainable data integration solution that meets the requirements of modern complex Web-enabled software and information systems. The difficulty
arises from the high degree of complexity of data structures, for example in business and technology applications, and from the constant change of data and its
representation. In the Web context, where the Web platform is used to integrate different organisations or software systems, additionally the problem of heterogeneity
arises. We introduce a specific data integration solution for Web applications such as Web-enabled information systems. Our contribution is an integration technology
framework for Web-enabled information systems comprising, firstly, a data integration technique based on the declarative specification of transformation rules and the construction of connectors that handle the integration and, secondly, a mediator architecture based on information services and the constructed connectors to handle the integration process
Reasoning & Querying – State of the Art
Various query languages for Web and Semantic Web data, both for practical use and as an area of research in the scientific community, have emerged in recent years. At the same time, the broad adoption of the internet where keyword search is used in many applications, e.g. search engines, has familiarized casual users with using keyword queries to retrieve information on the internet. Unlike this easy-to-use querying, traditional query languages require knowledge of the language itself as well as of the data to be queried. Keyword-based query languages for XML and RDF bridge the gap between the two, aiming at enabling simple querying of semi-structured data, which is relevant e.g. in the context of the emerging Semantic Web. This article presents an overview of the field of keyword querying for XML and RDF
Visual exploration and retrieval of XML document collections with the generic system X2
This article reports on the XML retrieval system X2 which has been developed at the University of Munich over the last five years. In a typical session with X2, the user
first browses a structural summary of the XML database in order to select interesting elements and keywords occurring in documents. Using this intermediate result, queries combining structure and textual references are composed semiautomatically.
After query evaluation, the full set of answers is presented in a visual and structured way. X2 largely exploits the structure found in documents, queries and answers to enable new interactive visualization and exploration techniques that support mixed IR and database-oriented querying, thus bridging the gap between these three views on the data to be retrieved. Another salient characteristic of X2 which distinguishes it from other visual query systems for XML is that it supports various degrees of detailedness in the presentation of answers, as well as techniques for dynamically reordering and grouping retrieved elements once the complete answer set has been computed
Impliance: A Next Generation Information Management Appliance
ably successful in building a large market and adapting to the changes of the
last three decades, its impact on the broader market of information management
is surprisingly limited. If we were to design an information management system
from scratch, based upon today's requirements and hardware capabilities, would
it look anything like today's database systems?" In this paper, we introduce
Impliance, a next-generation information management system consisting of
hardware and software components integrated to form an easy-to-administer
appliance that can store, retrieve, and analyze all types of structured,
semi-structured, and unstructured information. We first summarize the trends
that will shape information management for the foreseeable future. Those trends
imply three major requirements for Impliance: (1) to be able to store, manage,
and uniformly query all data, not just structured records; (2) to be able to
scale out as the volume of this data grows; and (3) to be simple and robust in
operation. We then describe four key ideas that are uniquely combined in
Impliance to address these requirements, namely the ideas of: (a) integrating
software and off-the-shelf hardware into a generic information appliance; (b)
automatically discovering, organizing, and managing all data - unstructured as
well as structured - in a uniform way; (c) achieving scale-out by exploiting
simple, massive parallel processing, and (d) virtualizing compute and storage
resources to unify, simplify, and streamline the management of Impliance.
Impliance is an ambitious, long-term effort to define simpler, more robust, and
more scalable information systems for tomorrow's enterprises.Comment: This article is published under a Creative Commons License Agreement
(http://creativecommons.org/licenses/by/2.5/.) You may copy, distribute,
display, and perform the work, make derivative works and make commercial use
of the work, but, you must attribute the work to the author and CIDR 2007.
3rd Biennial Conference on Innovative Data Systems Research (CIDR) January
710, 2007, Asilomar, California, US
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