The Semantic Web promises to open innumerable opportunities for automation and information retrieval by standardizing the protocols for metadata exchange. However, just as the success of the World Wide Web can be attributed to the ease of use and ubiquity of Web browsers, we believe that the unfolding of the Semantic Web vision depends on users getting powerful but easy-to-use tools for managing their information. But unlike HTML, which can be easily edited in any text editor, RDF is more complicated to author and does not have an obvious presentation mechanism. Previous work has concentrated on the ideas of generic RDF graph visualization and RDF Schema-based form generation. In this paper, we present a comprehensive platform for constructing end user applications that create, manipulate, and visualize arbitrary RDF-encoded information, adding another layer to the abstraction cake. We discuss a programming environment specifically designed for manipulating RDF and introduce user interface concepts on top that allow the developer to quickly assemble applications that are based on RDF data models. Also, because user interface specifications and program logic are themselves describable in RDF, applications built upon our framework enjoy properties such as network updatability, extensibility, and end user customizability - all desirable characteristics in the spirit of the Semantic Web.

Haystack: A Platform for Authoring End User Semantic Web Applications.

Michael N. Huhns University of South Carolina The Zen of the Web In contrast to the original Web’s content, which was designed for human use and comprehension, the Semantic Web’s1 content is for computer use and understanding. To date, however, most such efforts have focused on the understanding rather than use. This special issue of IC focuses on the use of the Web by computer systems and agents. By supporting the notion of “getting work done,” the Semantic Web will become more useful, valuable, and pragmatic. Many organizations are attempting to make the Web computer-friendly via Web services, but current incarnations of these technologies are subject to several limitations:

Ontologies and the Semantic Web

The amount of digital media that has to be actually managed has already become unaffordable without fine-grained computerised support. This requires an extensive use of multimedia metadata. MPEG-7 is the greatest metadata framework created to date but it is based on XML Schemas. Therefore, its does not have formal semantics, which makes difficult to manage, extend and integrate it. Consequently, there have been a lot attempts to move MPEG-7 to the Semantic Web. Our approach contributes a complete and automatic mapping of the whole MPEG-7 standard to OWL. It is based on a generic XML Schema to OWL mapping. The previous mapping is complemented with an XML metadata instances to RDF mapping that completes a transparent transfer of metadata from the XML to the Semantic Web domain. Once in a semantic space, data integration, which is a crucial factor when several sources of information are available, is facilitated enormously. We have used the generated MPEG-7 OWL ontology as an “upper-ontology” for multimedia metadata, where three different music schemas have been linked. Thus, it has been possible to retrieve related information from instances of all the metadata sources. Furthermore, detecting and merging instances from different sources has allowed us to enhance the description of audio files, both content-based and editorial data.

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Semantic Integration and Retrieval of Multimedia Metadata

The use of different modeling languages in software development makes their integration a must. Most existing integration approaches are meta-model-based with these metamodels representing both an abstract syntax of the corresponding modeling language and also a data structure for storing models. This implementation specific focus, however, does not make explicit certain language concepts, which can complicate integration tasks. Hence, we propose a process which semi-automatically lifts metamodels into ontologies by making implicit concepts in the metamodel explicit in the ontology. Thus, a shift of focus from the implementation of a certain modeling language towards the explicit reification of the concepts covered by this language is made. This allows matching on a solely conceptual level, which helps to achieve better results in terms of mappings that can in turn be a basis for deriving implementation specific transformation code.

Lifting metamodels to ontologies : A step to the semantic integration of modeling languages

Variety and veracity are two distinct characteristics of large-scale and heterogeneous data It has been a great challenge to efficiently represent and process big data with a unified scheme In this paper, a unified tensor model is proposed to represent the unstructured, semistructured, and structured data With tensor extension operator, various types of data are represented as subtensors and then are merged to a unified tensor In order to extract the core tensor which is small but contains valuable information, an incremental high order singular value decomposition (IHOSVD) method is presented By recursively applying the incremental matrix decomposition algorithm, IHOSVD is able to update the orthogonal bases and compute the new core tensor Analyzes in terms of time complexity, memory usage, and approximation accuracy of the proposed method are provided in this paper A case study illustrates that approximate data reconstructed from the core set containing 18% elements can guarantee 93% accuracy in general Theoretical analyzes and experimental results demonstrate that the proposed unified tensor model and IHOSVD method are efficient for big data representation and dimensionality reduction

A Tensor-Based Approach for Big Data Representation and Dimensionality Reduction

In this paper, we discuss the use of ontologies for data integration. We consider two different settings depending on the system architecture: central and peer-to-peer data integration. Within those settings, we discuss five different cases studies that illustrate the use of ontologies in metadata representation, in global conceptualization, in high-level querying, in declarative mediation, and in mapping support. Each case study is described in detail and accompanied by examples.

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The role of ontologies in data integration

XML is becoming the standard for data interchange on the Web. However, XML and its schema languages do not express semantics but rather structure, such as nesting information. Therefore, semantically equivalent documents often present different document structures. We provide an ontology-based framework that aims to make two XML documents intemperate at the semantic level while retaining their nesting structure. In our global-as-view approach, we generate an RDF ontology for each of the participating XML documents, which preserves the nesting structure of the document. An RDF global ontology is the result of merging the individual ontologies. The global ontology unifies the query access and establishes semantic connections among the underlying individual databases. We consider two types of queries: those that are posed on the global ontology and those that are posed on any of the XML documents, in a P2P fashion. The former type is processed using query translation from an RDF query to an XML query. The latter type entails bidirectional query processing: the translation from an XML query to an RDF query followed by the translation from an RDF query to an XML query. To ensure the correctness of the answer to the query in the latter case, we introduce the concept of reversibility of the query translation.

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An ontology-based framework for XML semantic integration

Peer-to-Peer (P2P) data management systems combine traditional schema-based integration techniques with the P2P infrastructure In this paper, we propose a P2P data management framework named PEPSINT that semantically integrates heterogeneous XML and RDF data sources, using a hybrid architecture and a global-as-view approach Our focus is on the query processing techniques over heterogeneous data Queries in PEPSINT are expressed in XQuery and in RDQL We consider two types of queries, depending on whether the query is first posed on the super peer or on one of the peers

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Peer-to-peer semantic integration of XML and RDF data sources

We propose a layered framework for the integration of syntactically, schematically, and semantically heterogeneous networked data sources Their heterogeneity stems from different models (eg, relational, XML, or RDF), different schemas within the same model, and different terms associated with the same meaning We use a semantic based approach that uses a global ontology to mediate among the schemas of the data sources In our framework, a query is expressed in terms of one of the data sources or of the global ontology and is then translated into subqueries on the other data sources using mappings based on a common vocabulary Metadata representation, global conceptualization, declarative mediation, mapping support, and query processing are addressed in detail in our discussion of a case study

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Ontology Driven Data Integration in Heterogeneous Networks

While providing a uniform syntax and a semistructured data model, XML does not express semantics but only structure such as nesting information. In this paper, we consider the problem of data integration and interoperation of heterogeneous XML sources and use an ontology-based framework to address this problem at a semantic level. Ontologies are extensively used for domain knowledge representation, by virtue of their conceptualization of the domain, which carries explicit semantics. In our approach, the global ontology is expressed in RDF Schema (RDFS) and constructed using the global-as-view approach by merging individual local ontologies, which represent XML source schemas. We provide a formal model for the mappings between XML schemas and local RDFS ontologies and those between local ontologies and the global RDFS ontology. We consider two cases of query processing, specifically for data integration and for data interoperation. In the first case, the user poses an RDF query on the global ontology, which is answered using all the mapped XML sources. In the second case, a query is posed on a single source and then is mapped to the XML sources that are connected to that source. For each case, we discuss the problem of query containment and present an equivalent query rewriting algorithm for queries expressed in two languages: conjunctive RDQL and conjunctive XQuery.

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Huiyong Xiao

Papers

The role of ontologies in data integration

An ontology-based framework for XML semantic integration

Peer-to-peer semantic integration of XML and RDF data sources

Ontology Driven Data Integration in Heterogeneous Networks

Integrating and exchanging XML data using ontologies