Nikos Bikakis

Ontology mapping and SPARQL rewriting for querying federated RDF data sources

The web of data consists of distributed, diverse (in terms of schema adopted), and large RDF datasets. In this paper we present a SPARQL query rewriting method which can be used to achieve interoperability in semantic information retrieval and/or knowledge discovery processes over interconnected RDF data sources. Formal mappings between different overlapping ontologies are exploited in order to rewrite initial user SPARQL queries, so that they can be evaluated over different RDF data sources on different sites. The proposed environment is utilized by an ontology-based mediator system, which we have developed in order to provide data integration within the Semantic Web environment.

SPARQL-RW: transparent query access over mapped RDF data sources

The Web of Data is an open environment consisting of very large, inter-linked RDF datasets from various domains (e.g., DBpedia, GeoNames, ACM, PubMed, etc.) accessed through SPARQL queries. Establishing interoperability in this environment has become a major research challenge. This paper presents Sparql--Rw (SPARQL--ReWriting), a framework which provides transparent query access over mapped RDF datasets. The Sparql--Rw provides a generic method for SPARQL query rewriting, with respect to a set of predefined mappings between ontology schemas. To this end, it supports a set of rich and flexible mapping types and it is proved to provide semantics preserving queries.

Integrating keywords and semantics on document annotation and search

This paper describes GoNTogle, a framework for document annotation and retrieval, built on top of Semantic Web and IR technologies. GoNTogle supports ontology-based annotation for documents of several formats, in a fully collaborative environment. It provides both manual and automatic annotation mechanisms. Automatic annotation is based on a learning method that exploits user annotation history and textual information to automatically suggest annotations for new documents. GoNTogle also provides search facilities beyond the traditional keyword-based search. A flexible combination of keyword-based and semantic-based search over documents is proposed in conjunction with advanced ontology-based search operations. The proposed methods are implemented in a fully functional tool and their effectiveness is experimentally validated.

GoNTogle: a tool for semantic annotation and search

This paper presents GoNTogle, a tool which provides advanced document annotation and search facilities. GoNTogle allows users to annotate several document formats, using ontology concepts. It also produces automatic annotation suggestions based on textual similarity and previous document annotations. Finally, GoNTogle combines keyword and semantic-based search, offering advanced ontology query facilities.

Querying XML Data with SPARQL

SPARQL is today the standard access language for Semantic Web data. In the recent years XML databases have also acquired industrial importance 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 interoperable environment where SPARQL queries are used to access XML databases. Our approach assumes that fairly generic mappings between ontology constructs and XML Schema constructs have been automatically derived or manually specified. The mappings are used to automatically translate SPARQL queries 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.

Towards a Mediator Based on OWL and SPARQL

We propose a framework that supports a federated environment based on a Mediator Architecture in the Semantic Web. The Mediator supports mappings between the OWL Ontology of the Mediator and the other ontologies in the federated sites. SPARQL queries submitted to the Mediator are decomposed and reformulated to SPARQL queries to the federated sites. The evaluated results return to the Mediator. In this paper we describe the mappings definition and encoding. We also discuss briefly the reformulation approach that is used by the Mediator system that we are currently implementing.

The SPARQL2XQuery interoperability framework

In the context of the emergent Web of Data, a large number of organizations, institutes and companies (e.g., DBpedia, Data.gov, GeoNames, PubMed) adopt the Linked Data practices. Utilizing the Semantic Web (SW) technologies, they 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 Schemas into OWL ontologies. Finally, extensive experiments have been conducted in order to evaluate the schema transformation, mapping generation, query translation and query evaluation efficiency, using both real and synthetic datasets.

The XML and Semantic Web Worlds: Technologies, Interoperability and Integration: A Survey of the State of the Art

In the context of the emergent Web of Data, a large number of organizations, institutes and companies (e.g., DBpedia,ACM, IEEE, IBM, NASA,BBC,etc.) adopt the Linked Data practices and publish their data utilizing Semantic Web (SW) technologies. On the other hand, the dominant standard for information exchange in the Web today is XML. Many international standards (e.g., Dublin Core, MPEG-7,METS, TEI, IEEE LOM,etc.) have been expressed in XML Schema resulting to a large number of XML datasets. The SW and XML worlds and their developed infrastructures are based on different data models, semantics and query languages. Thus, it is crucial to provide interoperability and integration mechanisms to bridge the gap between the SW and XML worlds.

rdf:SynopsViz – A Framework for Hierarchical Linked Data Visual Exploration and Analysis

The purpose of data visualization is to offer intuitive ways for information perception and manipulation, especially for non-expert users. The Web of Data has realized the availability of a huge amount of datasets. However, the volume and heterogeneity of available information make it difficult for humans to manually explore and analyse large datasets. In this paper, we present rdf:SynopsViz, a tool for hierarchical charting and visual exploration of Linked Open Data (LOD). Hierarchical LOD exploration is based on the creation of multiple levels of hierarchically related groups of resources based on the values of one or more properties. The adopted hierarchical model provides effective information abstraction and summarization. Also, it allows efficient -on the fly- statistic computations, using aggregations over the hierarchy levels.

graphVizdb: A scalable platform for interactive large graph visualization

We present a novel platform for the interactive visualization of very large graphs. The platform enables the user to interact with the visualized graph in a way that is very similar to the exploration of maps at multiple levels. Our approach involves an offline preprocessing phase that builds the layout of the graph by assigning coordinates to its nodes with respect to a Euclidean plane. The respective points are indexed with a spatial data structure, i.e., an R-tree, and stored in a database. Multiple abstraction layers of the graph based on various criteria are also created offline, and they are indexed similarly so that the user can explore the dataset at different levels of granularity, depending on her particular needs. Then, our system translates user operations into simple and very efficient spatial operations (i.e., window queries) in the backend. This technique allows for a fine-grained access to very large graphs with extremely low latency and memory requirements and without compromising the functionality of the tool. Our web-based prototype supports three main operations: (1) interactive navigation, (2) multi-level exploration, and (3) keyword search on the graph metadata.