Embedding SPARQL into XQuery/XSLT

2012

Given the sustained growth that we are experiencing in the number of SPARQL endpoints available, the need to be able to send federated SPARQL queries across these has also grown. To address this use case, the W3C SPARQL working group is defining a federation extension for SPARQL 1.1 which allows for combining graph patterns that can be evaluated over several endpoints within a single query. In this paper, we describe the syntax of that extension and formalize its semantics. Additionally, we describe how a query evaluation system can be implemented for that federation extension, describing some static optimization techniques and reusing a query engine used for data-intensive science, so as to deal with large amounts of intermediate and final results. Finally we carry out a series of experiments that show that our optimizations speed up the federated query evaluation process. Recent years have witnessed a large and constant growth in the amount of RDF data available on the Web, exposed by means of Linked Data-enabled dereferenceable URIs in various formats (such as RDF/XML, Turtle, RDFa, etc.) and-of particular interest for the present paper-by SPARQL endpoints. Several nonexhaustive, and sometimes out-of-date or not continuously maintained, lists of SPARQL endpoints or data catalogs are available in different formats like CKAN 1 , The Data Hub 2 , the W3C wiki 3 , etc. Most of these datasets are interlinked, as depicted graphically in the well-known Linked Open Data Cloud diagram 4 , which allows navigating through them and facilitates build

Proceedings of the 30th symposium on Principles of database systems of data - PODS '11, 2011

The Semantic Web is the initiative of the W3C to make information on the Web readable not only by humans but also by machines. RDF is the data model for Semantic Web data, and SPARQL is the standard query language for this data model. In the last ten years, we have witnessed a constant growth in the amount of RDF data available on the Web, which have motivated the theoretical study of some fundamental aspects of SPARQL and the development of efficient mechanisms for implementing this query language. Some of the distinctive features of RDF have made the study and implementation of SPARQL challenging. First, as opposed to usual database applications, the semantics of RDF is open world, making RDF databases inherently incomplete. Thus, one usually obtains partial answers when querying RDF with SPARQL, and the possibility of adding optional information if present is a crucial feature of SPARQL. Second, RDF databases have a graph structure and are interlinked, thus making graph navigational capabilities a necessary component of SPARQL. Last, but not least, SPARQL has to work at Web scale! RDF and SPARQL have attracted interest from the database community. However, we think that this community has much more to say about these technologies, and, in particular, about the fundamental database problems that need to be solved in order to provide solid foundations for the development of these technologies. In this paper, we survey some of the main results about the theory of RDF and SPARQL putting emphasis on some research opportunities for the database community.

2005

Abstract. Metadata processing is recognized as a central challenge for database research in the next decade. Already, novel desktop data management and search applications (cf. Apple's Spotlight and Microsoft's WinFS) are enabled by rich metadata. Efficient and effective access to such data becomes a crucial issue for more and more application scenarios. In this article, we focus on metadata represented in RDF. A number of query languages for RDF have been presented in recent years.

2013

It is well known that end-users have problems to write even simple SQL queries. The new SPARQL query language for RDF databases is a step in the right direction, but is still not suitable for end-users. This lead us to creating a more convenient approach in which end-users could retrieve structured data from the database through a graphical query language named GQL. GQL graphical query language is based on OWL ontology language and SPARQL query language for RDF data. GQL visualization format is based on UML graphical language. To achieve interoperability between all these techniques, a true subset approach did not work -minor modifications were required to achieve a functional solution. The proposed approach is applicable also to querying data from the legacy relational databases through database export to OWL/RDF format.

Advanced Information and Knowledge Processing, 2010

In an era of ever-increasing information needs, the ability to query large databases quickly and efficiently has come to play a major part. For a large share, this growing need is addressed by tools and languages aimed at performing complex queries on distributed data. However, the intuitiveness of designing such complex queries has only been addressed to a limited extent, making such tools available solely for technical users.

Proceedings of the 16th international …, 2007

Many applications in analytical domains often have the need to "connect the dots" i.e., query about the structure of data. In bioinformatics for example, it is typical to want to query about interactions between proteins. The aim of such queries is to "extract" relationships between entities i.e. paths from a data graph. Often, such queries will specify certain constraints that qualifying results must satisfy e.g. paths involving a set of mandatory nodes. Unfortunately, most present day Semantic Web query languages including the current draft of the anticipated recommendation SPARQL, lack the ability to express queries about arbitrary path structures in data. In addition, many systems that support some limited form of path queries rely on main memory graph algorithms limiting their applicability to very large scale graphs.

World Wide Web Journal (WWWJ) (to appear), 2013

The Web of Data is an open environment consisting of a great number of large inter-linked RDF datasets from various do-mains. In this environment, organizations and companies adopt the Linked Data practices utilizing Semantic Web (SW) tech-nologies, in order to publish their data and offer SPARQL endpoints (i.e., SPARQL-based search services). On the other hand, the dominant standard for information exchange in the Web today is XML. Additionally, many international standards (e.g., Dublin Core, MPEG-7, METS, TEI, IEEE LOM) in several domains (e.g., Digital Libraries, GIS, Multimedia, e-Learning) have been expressed in XML Schema. The aforementioned have led to an increasing emphasis on XML data, accessed using the XQuery query language. The SW and XML worlds and their developed infrastructures are based on different data models, semantics and query languages. Thus, it is crucial to develop interoperability mechanisms that allow the Web of Data users to access XML datasets, using SPARQL, from their own working environments. It is unrealistic to expect that all the existing legacy data (e.g., Relational, XML, etc.) will be transformed into SW data. Therefore, publishing legacy data as Linked Data and providing SPARQL endpoints over them has become a major research challenge. In this direction, we introduce the SPARQL2XQuery Framework which creates an interoperable environment, where SPARQL queries are automatically translated to XQuery queries, in order to access XML data across the Web. The SPARQL2XQuery Framework provides a mapping model for the expression of OWL–RDF/S to XML Schema mappings as well as a method for SPARQL to XQuery translation. To this end, our Framework supports both manual and automatic mapping specification between ontologies and XML Schemas. In the automatic mapping specification scenario, the SPARQL2XQuery exploits the XS2OWL component which transforms XML Sche-mas into OWL ontologies. Finally, extensive experiments have been conducted in order to evaluate the schema transfor-mation, mapping generation, query translation and query evaluation efficiency, using both real and synthetic datasets.

International Journal of Advanced Computer Science and Applications

With the advances in native storage means of RDF data and associated querying capabilities using SPARQL, there is a need to let SQL users benefit from such capabilities for interoperability objectives and without any conversion of the RDF data into relational data. In this sense, this work present SQL2SPARQL4RDF an automatic conversion algorithm of SQL queries into SPARQL queries for querying RDF data, which extends the previously established algorithm with relevant SQL elements such as queries with INSERT, DELETE, GROUP BY and HAVING clauses. SQL users are provided with a relational schema of their RDF data against which they can formulate their SQL queries that are then converted into SPARQL equivalent ones with respect to the provided schema. This avoids the birding of translating instances and data replication and thus saving loading times and guaranteeing fast execution especially in the case of massive amounts of data. In addition, the automatic mapping framework developed by the java programming language, and implement many new mapping functionalities. Furthermore, to test and validate the efficiency of the mapping approach and adding a module for automatic execution and evaluation of the various obtained SPARQL queries on Allegrograph.

2008

RDF Schema (RDFS) extends RDF with a schema vocabulary with a predefined semantics. Evaluating queries which involve this vocabulary is challenging, and there is not yet consensus in the Semantic Web community on how to define a query language for RDFS. In this paper, we introduce a language for querying RDFS data. This language is obtained by extending SPARQL with nested regular expressions that allow to navigate through an RDF graph with RDFS vocabulary.

2005

Abstract The integral processing of data and metadata is starting to get recognized as a central challenge for the next decade (eg in Pat Selinger's ICDE 2005 Keynote) not only as part of realizing the Semantic Web vision, but also on a smaller scale as part of the next generation of desktop data management (cf. Apple's Spotlight and Microsoft's WinFS). In this article, we focus on metadata represented in the W3C's RDF formalism.

International Journal on Semantic Web and Information Systems, 2000

2012 23rd International Workshop on Database and Expert Systems Applications, 2012

One of the reasons for the slow adoption of SPARQL is the complexity in query formulation due to data diversity. The principal barrier a user faces when trying to formulate a query is that he generally has no information about the underlying structure and vocabulary of the data.

2018

Querying ontologies is an every-day activity that users need. This interaction will improve when the query is more expressive and easier to develop. For this purpose, a visual query language is an ideal mean for users and ontology engineers for creating queries taking advantage of the easy-to-understand and low time and cost characteristics, specially, for users which does not know textual query languages. On the other side, SPARQL-DL is a powerful and expressive textual query language for OWL-DL based ontologies that can combine TBox/ABox/RBox queries. Considering the advantage of both, we present in this work a visual query language that can be interpreted as SPARQL-DL sentences and thus being used for querying ontologies for its structure and/or instance information. Altogether, we use this idea to create a modified version of crowd, a Web modelling tool with reasoning support, that enables to implement and tests the presented graphical language along with the needed SPARQL-DL su...

Lecture Notes in Computer Science, 2016

A constantly increasing number of data providers publish their data on the Web in the RDF format as Linked Data. SPARQL is the standard query language for retrieving and manipulating RDF data. However, the majority of SPARQL implementations requires the data to be available in advance (in main memory or in a repository), not exploiting thereby the real-time and dynamic nature of Linked Data. In this paper we present SPARQL-LD, an extension of SPARQL 1.1 Federated Query that allows to directly fetch and query RDF data from any Web source. Using SPARQL-LD, one can even query a dataset coming from the partial results of a query (i.e., discovered at query execution time), or RDF data that is dynamically created by Web Services. Such a functionality motivates Web publishers to adopt the Linked Data principles and enrich their digital contents and services with RDF, since their data is made directly accessible and exploitable via SPARQL (without needing to set up and maintain an endpoint). In this paper, we showcase the benefits offered by SPARQL-LD through an example related to the Europeana digital library, we report experimental results that demonstrate the feasibility of SPARQL-LD, and we introduce optimizations that improve its efficiency.

13th International Semantic Web Conference (ISWC '14), 2014

The Web of Data encourages organizations and companies to publish their data according to the Linked Data practices and offer SPARQL endpoints. On the other hand, the dominant standard for information exchange is XML. The SPARQL2XQuery Framework focuses on the automatic translation of SPARQL queries in XQuery expressions in order to access XML data across the Web. In this paper, we outline our ongoing work on supporting update queries in the RDF–XML integration scenario.