8,669 research outputs found
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
Context-Free Path Queries on RDF Graphs
Navigational graph queries are an important class of queries that canextract
implicit binary relations over the nodes of input graphs. Most of the
navigational query languages used in the RDF community, e.g. property paths in
W3C SPARQL 1.1 and nested regular expressions in nSPARQL, are based on the
regular expressions. It is known that regular expressions have limited
expressivity; for instance, some natural queries, like same generation-queries,
are not expressible with regular expressions. To overcome this limitation, in
this paper, we present cfSPARQL, an extension of SPARQL query language equipped
with context-free grammars. The cfSPARQL language is strictly more expressive
than property paths and nested expressions. The additional expressivity can be
used for modelling graph similarities, graph summarization and ontology
alignment. Despite the increasing expressivity, we show that cfSPARQL still
enjoys a low computational complexity and can be evaluated efficiently.Comment: 25 page
A Perfect Match for Reasoning, Explanation, and Reason Maintenance
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
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
Challenges for Efficient Query Evaluation on Structured Probabilistic Data
Query answering over probabilistic data is an important task but is generally
intractable. However, a new approach for this problem has recently been
proposed, based on structural decompositions of input databases, following,
e.g., tree decompositions. This paper presents a vision for a database
management system for probabilistic data built following this structural
approach. We review our existing and ongoing work on this topic and highlight
many theoretical and practical challenges that remain to be addressed.Comment: 9 pages, 1 figure, 23 references. Accepted for publication at SUM
201
Comparative Analysis of Five XML Query Languages
XML is becoming the most relevant new standard for data representation and
exchange on the WWW. Novel languages for extracting and restructuring the XML
content have been proposed, some in the tradition of database query languages
(i.e. SQL, OQL), others more closely inspired by XML. No standard for XML query
language has yet been decided, but the discussion is ongoing within the World
Wide Web Consortium and within many academic institutions and Internet-related
major companies. We present a comparison of five, representative query
languages for XML, highlighting their common features and differences.Comment: TeX v3.1415, 17 pages, 6 figures, to be published in ACM Sigmod
Record, March 200
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”
Relative Expressive Power of Navigational Querying on Graphs
Motivated by both established and new applications, we study navigational
query languages for graphs (binary relations). The simplest language has only
the two operators union and composition, together with the identity relation.
We make more powerful languages by adding any of the following operators:
intersection; set difference; projection; coprojection; converse; and the
diversity relation. All these operators map binary relations to binary
relations. We compare the expressive power of all resulting languages. We do
this not only for general path queries (queries where the result may be any
binary relation) but also for boolean or yes/no queries (expressed by the
nonemptiness of an expression). For both cases, we present the complete Hasse
diagram of relative expressiveness. In particular the Hasse diagram for boolean
queries contains some nontrivial separations and a few surprising collapses.Comment: An extended abstract announcing the results of this paper was
presented at the 14th International Conference on Database Theory, Uppsala,
Sweden, March 201
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