RDF-Based Ontology View for Relational Schema Mediation in Semantic Web

Frame-based ontological view for semantic integration

Semantic integration is crucial for successful collaboration between heterogeneous information systems in an open environment. Traditional ontology-driven approaches rely on the availability of explicit ontologies. However, in many domains, this prerequisite cannot be met. In order to address this issue, this paper investigates the theoretical foundation of ontologies and extends the traditional ontology concept to an ontological view concept. To explicitly and formally specify the ontological views, a Frame-based Ontological view Specification Language (FOSL) is proposed. This language is based on the Frame knowledge representation paradigm and uses XML as the encoding. A prototype environment that supports semantic integration based on ontological views specified with FOSL is introduced.

Despite all the efforts to build up a Semantic Web, where each machine can understand and interpret the data it processes, information is usually still stored in ordinary relational databases. Semantic Web applications needing access to such semantically unexploited data, have to create their own manual relational database to Semantic Web mappings. In this paper we analyze, whether the combination of Relational.OWL as a Semantic Web representation of relational databases and a semantic query language like SPARQL could be an alternative. The benefits of such an approach are clear, since it enables Semantic Web applications to access and query data actually stored in relational databases using their own built-in functionality.

From the beginning it was understood that the success of the Semantic Web hinges on integrating the vast amount of data stored in Relational Databases. This manuscript reflects on the last 10 years of our research results to integrate Relational Databases with the Semantic Web. Since 2007, our research has led us to answer the following question: How and to what extent can Relational Databases be Integrated with the Semantic Web? The answer comes in two parts. We start by presenting how to get from Relational Databases to the Semantic Web via mappings, such as the W3C Direct Mapping and R2RML standards. Subsequently, we present how the Semantic Web can access Relational Databases. We finalize with how Relational Databases and Semantic Web technologies are being used practice for data integration and discuss open challenges.

Ontologies represents main building material for creation of Semantic Web. Without ontologies it could not be possible to enable machine processability of data on the Semantic Web. Data is usually stored inside relational databases that represent the backbone for dynamical web sites. That data represents the invisible Web, ignored by search engines and Web crawlers. This paper presents a way to extract semantics from relational database schema and create OWL ontology automatically. Because relational database schema can capture very limited semantics, ontologies are enriched with additional WordNet semantics.

An article tries to see a group of semantic web representation and communication means like description logics, semantic networks, RDF model and language, OWL language, RDF CFL etc. taking a part at the development of formal ontologies from a slightly higher (meta) level. A focus has been oriented towards properties that semantic web language ought to have to fulfill according to a semantic web idea. Consequently the article tries to draw by the help of the means above the trip towards a proper semantic-web ontology language fulfilling the main demands of expressivity and also easy-to-use conditions. Even if the development of a semantic web language was until now much more complicated with a taking part of a lot of people or companies the authors of the article try to contribute to an analyzing of the actual state by drawing it as a cloud of demands, streams, events or condition’s fulfilling that at the end would have brought into the world an easy-to-usable semantic web ontology language having all the demands fulfilled. The article moreover shows that a language RDF CFL belongs nowadays to the semantic web family as a unique well usable tool of reasoning within semantic web knowledge bases.

In this paper, we develop techniques to produce interoperable queries with object and relational databases. A user poses a local query in a local query language, against a local object or relational schema. We transparently produce appropriate queries with respect to a remote target object or relational schema, corresponding to some remote database which contains data relevant to the user's query. Mapping knowledge to resolve representational heterogeneities in local and remote schemas is expressed in a canonical representation, CRmapping, and is independent of the particular data model. A canonical representation CRquery is also used to resolve heterogeneities of query languages. A set of heterogeneous transformation algorithms define the appropriate transformations from the local queries to the remote queries. The use of canonical representations (CR) allows us to represent queries independent of the particular query language, and to resolve representational conflicts in a uniform manner, independent of models and query languages.

It is the vision of the protagonists of the Semantic Web to achieve “a set of connected applications for data on the Web in such a way as to form a consistent logical Web of data” (Berners-Lee, 1998, p. 1). Therefore, the Semantic Web approach develops languages for expressing information in a machine-processable form (“machine-understandable” in terms of the Semantic Web community). Particularly, the Resource Description Framework, RDF (Lassila & Swick, 1999), and RDF Schema, RDFS (Brickley & Guha, 2000), are considered as the foundations for the implementation of the Semantic Web. RDF provides a data model and a serialization language; RDFS a distinguished vocabulary to model class and property hierarchies and other basic schema primitives that can be referred to from RDF models, thereby allowing for the modeling of object models with cleanly defined semantics. The idea behind this approach is to provide a common minimal framework for the description of Web resources while allowing for application-specific extensions (Berners-Lee, 1998). Such extensions in terms of additional classes and/or properties must be documented in an application-specific schema. Application-specific schemata can be integrated into RDFS by the namespace mechanism (Bray, Hollander & Layman, 1999). Namespaces provide a simple method for qualifying element and attribute names used in RDF documents by associating them with namespaces identified by URI (Uniform Resource Identifier) references (Berners-Lee, Fielding, Irvine & Masinter, 1998).

The emergence of Semantic Web (SW) and the related technologies promise to make the Web a meaningful experience. Conversely, success of SW and its applications depends largely on utilization and interoperability of well-formulated ontology bases in an automated heterogeneous environment. This creates a need to investigate utilization of an (materialized) ontology view as an alternative version of an ontology. However, high level modeling, design and querying techniques still proves to be a challenging task for SW paradigm, as, unlike classical database systems, ontology view definitions and querying have to be done at high-level abstraction. In order to address such an issue, in this chapter, we describe an abstract view formalism forSW (SW-view) with conceptual and logical extensions. SW-views provides the needed conceptual and logical semantics to engineer ontology bases using three levels of abstraction, namely (1) conceptual, (2) logical/schema and (3) instance levels. We first provide the view model and it formal properties including a set of conceptual operators, which enable us to do ontology extraction at the conceptual level. Later, we provide a schemata transformation methodology to materialize SW-views under the Ontology Extraction Methodology (OEM) framework.

PurposeThe purpose of this paper is to explore useful Semantic Web technologies and ontology-based applications for digital libraries. It also investigates the perceptions of university librarians and academicians in Pakistan about Semantic Web technologies and their use in digital libraries.Design/methodology/approachAn exploratory research design based on Delphi research strategy was conducted to answer the research questions. Interviews were conducted with a purposive sample of 50 key informants including university librarians and academicians to explore their perceptions about Semantic Web technologies and their use in digital libraries. Thematic analysis of interview data was conducted to obtain results.FindingsThe results of this paper showed that DuraCloud, Semantic information mashup, OntoEdit and resource description framework (RDF) are the various Semantic Web applications which are useful for digital libraries to develop semantic relationships among digital contents and increase their accessibility in the web environment. Findings revealed that Semantic Web provides precise results and meets user information needs in an effective way. Results also showed that next-generation digital libraries use context-awareness technology, intelligent agent software and detecting sensors to analyze user information needs and provide dynamic information services. This paper recommended that librarians should embrace the use of emerging web technologies in libraries and offer library services through the medium of the web.Practical implicationsThis paper envisaged the future of digital library services and Semantic Web applications that can be used to re-structure metadata of digital library. This paper has practical implications for librarians to consider the useful applications of Semantic Web for digital library and enhance the interoperability of metadata among heterogeneous information systems. Practically, results obtained from this paper are highly useful for library schools and LIS teachers to up-date their curriculum by incorporating new contents related to web languages and Semantic Web applications for digital libraries.Originality/valueThis paper identifies various Semantic Web applications which are useful for developing Semantic Digital Libraries.

Fundamental notions of relative information capacity between database structures are studied in the context of the relational model. Four progressively less restrictive formal definitions of "dominance" between pairs of relational database schemata are given. Each of these is shown to capture intuitively appealing, semantically meaningful properties which are natural for measures of relative information capacity between schemata. Relational schemata, both with and without key dependencies, are studied using these notions. A significant intuitive conclusion concerns the informal notion of relative information capacity often suggested in the conceptual database literature, which is based on accessability of data via queries. Results here indicate that this notion is too general to accurately measure whether an underlying semantic connection exists between database schemata. Another important result of the paper shows that under any natural notion of information capacity equivalence, two relational schemata (with no dependencies) are equivalent if and only if they are identical (up to re-ordering of the attributes and relations). The approach and definitions used here can form part of the foundation for a rigorous investigation of a variety of important database problems involving data relativism, including those of schema integration and schema translation.

although the tendency towards a Semantic Web is increasing, the current Web is keen on more semantic data. There are several web application domains which need to present their data in the form of graphs to get information and knowledge to allow semantic web searching to deal with them. These domains can be for example geographic data, data in the area of bioinformatics, social networks or even corporate search engines. Most of these domains already store their data in relational database management systems which are not capable of being queried directly by semantic web applications. In this paper we will propose a semi-automated method to map the data from relational databases to RDF structures. This is true for both a single source database as well as different source databases. The results show a complexity of order n2 where n is the number of records processed, when it comes to the performance in creating the output from mapping the relational database to RDF files.

One of the main drawbacks of the Semantic Web is the lack of semantically rich data, since most of the information is still stored in relational databases. In this paper, we present an approach to map legacy data stored in relational databases into the Semantic Web using virtually any modern RDF query language, as long as it is closed within RDF. Consequently, a Semantic Web developer does not need to learn and adopt a new mapping language, but he may perform the mapping task using his preferred RDF query language.KeywordsRelational DatabaseResource Description FrameworkQuery LanguageRelational AlgebraSPARQL QueryThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

The quality of data is a critical factor for all kinds of decision-making and transaction processing. While there has been a lot of research on data quality in the past two decades, the topic has not yet received sufficient attention from the Semantic Web community. In this paper, we discuss (1) the data quality issues related to the growing amount of data available on the Semantic Web, (2) how data quality problems can be handled within the Semantic Web technology framework, namely using SPARQL on RDF representations, and (3) how Semantic Web reference data, e.g. from DBPedia, can be used to spot incorrect literal values and functional dependency violations. We show how this approach can be used for data quality management of public Semantic Web data and data stored in relational databases in closed settings alike. As part of our work, we developed generic SPARQL queries to identify (1) missing datatype properties or literal values, (2) illegal values, and (3) functional dependency violations. We argue that using Semantic Web datasets reduces the effort for data quality management substantially. As a use-case, we employ Geonames, a publicly available Semantic Web resource for geographical data, as a trusted reference for managing the quality of other data sources.

The traditional Web stores huge amount of data in the form of Relational Databases (RDB) as it is good at storing objects and relationships between them.Relational Databases are dynamic in nature which allows bringing tables together helping user to search for related material across multiple tables.RDB are scalable to expand as the data grows.The RDB uses a Structured Query Language called SQL to access the databases for several data retrieval purposes.As the world is moving today from the Syntactic form to Semantic form and the Web is also taking its new form of Semantic Web.The Structured Query of the RDB on web can be a Semantic Query on Semantic Web.The SPARQL is the Query Language recommended by W3C for the RDF(Resource Description Framework).RDF is a directed, labeled graph data format for representing information in the Web and is a very important layer of the Semantic Web Architecture.In this paper we consider the Library Management System (LMS) database, taking some tuples of the LMS Relational Schema.We discuss how the RDF code is scripted and validated using RDF Validator and how RDF Triples are generated.Later we give the graphical representation of the RDF triples and see the process of extracting ontology from the RDF Schema and application of the Semantic Query.