Supporting SPARQL Update Queries in RDF-XML Integration

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.Comment: 13th International Semantic Web Conference (ISWC '14

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

Data Mapping for XBRL: A Systematic Literature Review

It is evident the growth of the use of eXtensible Business Reporting Language (XBRL) technology in the context of financial reports on the Internet, either for its advantages and benefits or by government impositions, however, the data to be transported by this language are mostly stored in structures defined as database, some relational other NoSQL. The need to integrate XBRL technology with other data storage technologies has been growing continuously, and research is needed to seek a solution for mapping data between these environments. The possible difficulties in integrating XBRL with other technologies, relational database or NoSQL, CSV files, JSON, need to be mapped and overcome. Generating XBRL documents from the database can be costly, since there is no native alternative that the database manager system exports from the database manager system, the data in XBRL. For this, specific third-party systems are needed to generate XBRL documents. Generally, these systems are proprietary and have a high cost. Integrate these different technologies adds complexity, since these documents do not connect to the database manager system. These difficulties cause performance and storage problems and in cases of large data, such as data delivery to government agencies, complexity increases. Thus, it is essential to study techniques and methods that allow us to infer a solution to perform this integration and/or mapping, preferably in a generic way, that includes the XBRL data structure and the main data models currently used, i.e.  Relational DBMS, NoSQL, JSON or CSV files. It is expected, in this work, through a systematic literature review, to identify the state of the art concerning the mapping of XBRL data

Querying XML Data with SPARQL

Abstract. SPARQL is today the standard access language for Semantic Web data. In the recent years XML databases have also acquired industrial impor-tance due to the widespread applicability of XML in the Web. In this paper we present a framework that bridges the heterogeneity gap and creates an interop-erable environment where SPARQL queries are used to access XML databases. Our approach assumes that fairly generic mappings between ontology con-structs and XML Schema constructs have been automatically derived or manu-ally specified. The mappings are used to automatically translate SPARQL que-ries to semantically equivalent XQuery queries which are used to access the XML databases. We present the algorithms and the implementation of SPARQL2XQuery framework, which is used for answering SPARQL queries over XML databases

Translation of Heterogeneous Databases into RDF, and Application to the Construction of a SKOS Taxonomical Reference

International audienceWhile the data deluge accelerates, most of the data produced remains locked in deep Web databases. For the linked open data to benefit from the potential represented by this huge amount of data, it is crucial to come up with solutions to expose heterogeneous databases as linked data. The xR2RML mapping language is an endeavor towards this goal: it is designed to map various types of databases to RDF, by flexibly adapting to heterogeneous query languages and data models while remaining free from any specific language. It extends R2RML, the W3C recommendation for the mapping of relational databases to RDF, and relies on RML for the handling of various data formats. In this paper we present xR2RML, we analyse data models of several modern databases as well as the format in which query results are returned , and we show how xR2RML translates any result data element into RDF, relying on existing languages such as XPath and JSONPath when necessary. We illustrate some features of xR2RML such as the generation of RDF collections and containers, and the ability to deal with mixed data formats. We also describe a real-world use case in which we applied xR2RML to build a SKOS thesaurus aimed at supporting studies on History of Zoology, Archaeozoology and Conservation Biology

an approach for semantic integration of heterogeneous data sources

Integrating data from multiple heterogeneous data sources entails dealing with data distributed among heterogeneous information sources, which can be structured, semi-structured or unstructured, and providing the user with a unified view of these data. Thus, in general, gathering information is challenging, and one of the main reasons is that data sources are designed to support specific applications. Very often their structure is unknown to the large part of users. Moreover, the stored data is often redundant, mixed with information only needed to support enterprise processes, and incomplete with respect to the business domain. Collecting, integrating, reconciling and efficiently extracting information from heterogeneous and autonomous data sources is regarded as a major challenge. In this paper, we present an approach for the semantic integration of heterogeneous data sources, DIF (Data Integration Framework), and a software prototype to support all aspects of a complex data integration process. The proposed approach is an ontology-based generalization of both Global-as-View and Local-as-View approaches. In particular, to overcome problems due to semantic heterogeneity and to support interoperability with external systems, ontologies are used as a conceptual schema to represent both data sources to be integrated and the global view

Translation of Relational and Non-Relational Databases into RDF with xR2RML

International audienceWith the growing amount of data being continuously produced, it is crucial to come up with solutions to expose data from ever more heterogeneous databases (e.g. NoSQL systems) as linked data.In this paper we present xR2RML, a language designed to describe the mapping of various types of databases to RDF. xR2RML flexibly adapts to heterogeneous query languages and data models while remaining free from any specific language or syntax. It extends R2RML, the W3C recommendation for the mapping of relational databases to RDF, and relies on RML for the handling of various data representation formats.We analyse data models of several modern databases as well as the format in which query results are returned, and we show that xR2RML can translate any data element within such results into RDF, relying on existing languages such as XPath and JSONPath if needed. We illustrate some features of xR2RML such as the generation of RDF collections and containers, and the ability to deal with mixed content