1,485 research outputs found
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”
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
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
Answering Regular Path Queries on Workflow Provenance
This paper proposes a novel approach for efficiently evaluating regular path
queries over provenance graphs of workflows that may include recursion. The
approach assumes that an execution g of a workflow G is labeled with
query-agnostic reachability labels using an existing technique. At query time,
given g, G and a regular path query R, the approach decomposes R into a set of
subqueries R1, ..., Rk that are safe for G. For each safe subquery Ri, G is
rewritten so that, using the reachability labels of nodes in g, whether or not
there is a path which matches Ri between two nodes can be decided in constant
time. The results of each safe subquery are then composed, possibly with some
small unsafe remainder, to produce an answer to R. The approach results in an
algorithm that significantly reduces the number of subqueries k over existing
techniques by increasing their size and complexity, and that evaluates each
subquery in time bounded by its input and output size. Experimental results
demonstrate the benefit of this approach
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
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
Development of Use Cases, Part I
For determining requirements and constructs appropriate for a Web query language, or in fact
any language, use cases are of essence. The W3C has published two sets of use cases for XML
and RDF query languages. In this article, solutions for these use cases are presented using
Xcerpt. a novel Web and Semantic Web query language that combines access to standard Web
data such as XML documents with access to Semantic Web metadata
such as RDF resource
descriptions with reasoning abilities and rules familiar from logicprogramming.
To the
best knowledge of the authors, this is the first in depth study of how to solve use cases for
accessing XML and RDF in a single language: Integrated access to data and metadata
has been
recognized by industry and academia as one of the key challenges in data processing for the
next decade. This article is a contribution towards addressing this challenge by demonstrating
along practical and recognized use cases the usefulness of reasoning abilities, rules, and
semistructured
query languages for accessing both data (XML) and metadata
(RDF)
An introduction to Graph Data Management
A graph database is a database where the data structures for the schema
and/or instances are modeled as a (labeled)(directed) graph or generalizations
of it, and where querying is expressed by graph-oriented operations and type
constructors. In this article we present the basic notions of graph databases,
give an historical overview of its main development, and study the main current
systems that implement them
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