Upgrading Relational Legacy Data to eh Semantic Web

In this poster, we describe a framework composed of the R2O mapping language and the ODEMapster processor to upgrade relational legacy data to the Semantic Web. The framework is based on the declarative description of mappings between relational and ontology elements and the exploitation of such mapping descriptions by a generic processor capable of performing both massive and query driven data upgrade

Towards automated knowledge-based mapping between individual conceptualisations to empower personalisation of Geospatial Semantic Web

Geospatial domain is characterised by vagueness, especially in the semantic disambiguation of the concepts in the domain, which makes defining universally accepted geo- ontology an onerous task. This is compounded by the lack of appropriate methods and techniques where the individual semantic conceptualisations can be captured and compared to each other. With multiple user conceptualisations, efforts towards a reliable Geospatial Semantic Web, therefore, require personalisation where user diversity can be incorporated. The work presented in this paper is part of our ongoing research on applying commonsense reasoning to elicit and maintain models that represent users' conceptualisations. Such user models will enable taking into account the users' perspective of the real world and will empower personalisation algorithms for the Semantic Web. Intelligent information processing over the Semantic Web can be achieved if different conceptualisations can be integrated in a semantic environment and mismatches between different conceptualisations can be outlined. In this paper, a formal approach for detecting mismatches between a user's and an expert's conceptual model is outlined. The formalisation is used as the basis to develop algorithms to compare models defined in OWL. The algorithms are illustrated in a geographical domain using concepts from the SPACE ontology developed as part of the SWEET suite of ontologies for the Semantic Web by NASA, and are evaluated by comparing test cases of possible user misconceptions

Fund Finder: A case study of database-to-ontology mapping

The mapping between databases and ontologies is a basic problem when trying to "upgrade" deep web content to the semantic web. Our approach suggests the declarative definition of mappings as a way to achieve domain independency and reusability. A specific language (expressive enough to cover some real world mapping situations like lightly structured databases or not 1st normal form ones) is defined for this purpose. Along with this mapping description language, the ODEMapster processor is in charge of carrying out the effective instance data migration. We illustrate this by testing both the mappings definition and processor on a case study

A Semantic Collaboration Method Based on Uniform Knowledge Graph

The Semantic Internet of Things is the extension of the Internet of Things and the Semantic Web, which aims to build an interoperable collaborative system to solve the heterogeneous problems in the Internet of Things. However, the Semantic Internet of Things has the characteristics of both the Internet of Things and the Semantic Web environment, and the corresponding semantic data presents many new data features. In this study, we analyze the characteristics of semantic data and propose the concept of a uniform knowledge graph, allowing us to be applied to the environment of the Semantic Internet of Things better. Here, we design a semantic collaboration method based on a uniform knowledge graph. It can take the uniform knowledge graph as the form of knowledge organization and representation, and provide a useful data basis for semantic collaboration by constructing semantic links to complete semantic relation between different data sets, to achieve the semantic collaboration in the Semantic Internet of Things. Our experiments show that the proposed method can analyze and understand the semantics of user requirements better and provide more satisfactory outcomes

Automated syntactic mediation for Web service integration

As the Web Services and Grid community adopt Semantic Web technology, we observe a shift towards higher-level workflow composition and service discovery practices. While this provides excellent functionality to non-expert users, more sophisticated middleware is required to hide the details of service invocation and service integration. An investigation of a common Bioinformatics use case reveals that the execution of high-level workflow designs requires additional processing to harmonise syntactically incompatible service interfaces. In this paper, we present an architecture to support the automatic reconciliation of data formats in such Web Service worklflows. The mediation of data is driven by ontologies that encapsulate the information contained in heterogeneous data structures supplying a common, conceptual data representation. Data conversion is carried out by a Configurable Mediator component, consuming mappings between \xml schemas and \owl ontologies. We describe our system and give examples of our mapping language against the background of a Bioinformatics use case