Mediated Schema Research Articles

Schematic Structure of National Data Harmonization System for Identity Management

Imagine a web-application in which a user can query varieties of information about an individual (like name, age, state of origin, driver’s license number, national identification number, etc.). This information would be stored on different databases, each having its own schema. Often times, these resources are replicated in different locations and on different platforms. Hence, the need for data harmonization or integration. Data harmonization addresses this issue by considering these external resources as materialized views over a virtual mediated schema resulting in “virtual data integration”. When mediated schema is queried, the solution transforms the result into appropriate queries over the various and existing data sources. This paper focuses on data harmonization that cuts across different governmental database and incorporating them all into a centralized view and this is possible as a result of development and implementation of a webbased databank application.

Mapping between BIM and 3D GIS in different levels of detail using schema mediation and instance comparison

Abstract The Building Information Modeling (BIM) domain and the Geographic Information System (GIS) domain share a mutual need for information from each other. Information from GIS can facilitate BIM applications such as site selection and onsite material layout, while BIM models could help generate detailed models in GIS and achieve better utility management. The mapping between the key schemas in the BIM domain and the GIS domain is the most critical step towards interoperability between the two domains. In this study, Industry Foundation Classes (IFC) and City Geography Markup Language (CityGML) were chosen as the key schemas due to their wide applications in the BIM domain and the GIS domain, respectively. We used an instance-based method to generate the mapping rules between IFC and CityGML based on the inspection of entities representing the same component in the same model. It ensures accurate mapping between the two schemas. The transformation of coordinate systems and geometry are two major issues addressed in the instance-based method. Considering the difference in schema structure and information richness between the two schemas, a reference ontology called Semantic City Model was developed and an instance-based method was adopted. The Semantic City Model captures all the relevant information from BIM models and GIS models during the mapping process. Since CityGML is defined in five levels of detail (LoD), the harmonization among LoDs in CityGML was also developed in order to complete the mapping. The test results show that the developed framework can achieve automatic data mapping between IFC and CityGML in different LoDs. Furthermore, the developed Semantic City Model is extensible and can be the basis for other schema mappings between the BIM domain and the GIS domain.

Effectiveness of Indecent Language in Advertising on Young Adult Consumer Attitudes and Purchase Intent

This study applies both the Dual Mediation Hypothesis and Schema Congruity Theory to examine the effectiveness of mild controversial advertising executions on young adult consumer cognitions, affect, and behavior. Findings from this study suggest that advertisements featuring mild indecent language result in more positive advertisement attitudes, brand attitudes, and purchase intentions than when decent language is used. Young adult consumers also report more positive advertisement and brand attitudes, and a greater likelihood of purchase when they perceive the advertisement to be congruent with their existing schema, regardless of whether the execution is mildly controversial or noncontroversial in nature. The findings of this study are important to advertisers in the development of effective creative execution techniques.

FMAMS

To access a unified way to different information sources while hiding the user autonomy, heterogeneity, distribution and evolution of these sources, the authors thought to integrate its different sources of information, one of the existing integration approaches is mediation or virtual approach. The integration in mediation approach is done with a schema, called schema mediation, and a set of mapping (links) associating schemas of sources to integrate with the global schema. The problem arises in creating the set of correspondences between the elements of the schema global and all the elements of local schemas, in this paper the authors present their approach FMAMS: Fuzzy Mapping Approach for Mediation Systems, a new approach based on fundamental principles of the theory of fuzzy sets. The authors’ approach is to define and associate to each link between two elements a weight that reflects the degree of its existence, it is present in an analysis using two components: syntactic and semantic.

Defining a semantic mapping of VRA Core 4.0 to the CIDOC conceptual reference model

In the recent decades, we have witnessed a tremendous proliferation of metadata schemas, particularly in the cultural heritage domain. As a consequence, cultural heritage communities face a growing need to integrate these schemas as they encounter a number of problems, mainly concerning interoperability issues and loss of implicit knowledge. In this paper, we present a semantic mapping of VRA Core 4.0, a cultural heritage metadata schema describing visual resources, to CIDOC CRM. The mapping rules are expressed formally using a path-based mapping language called Mapping Description Language MDL. More specifically, each element of the schema along with its subelements and attributes is mapped to the equivalent CRM path represented as a sequence of classes and properties. In case an attribute is assigned to an element/subelement, this is also mapped to equivalent CRM paths, expanding the semantic correspondences between the two schemas. This work is part of a semantic integration scenario, where CIDOC CRM acts as a mediation schema.

SCHEMA MEDIATION IN PEER DATA MANAGEMENT SYSTEMS

Peer Data Management Systems (PDMSs) allow the efficient sharing of data between peers with overlapping sources of information. These sources share data through mappings between peers. In current systems, queries are asked over each peer's local schema and then translated using the mappings between peers. While this allows the data to be accessed uniformly, users lack access to information that is not in their own schemas. In this paper, we propose a light-weight, automatic method to create a mediated schema in a PDMS. Our work benefits PDMSs by allowing access to more data and without unduly stressing the peer's resources or requiring additional resources such as ontologies. We present our system — MePSys, which creates a mediated schema in PDMSs automatically using the existing mappings provided to translate queries. We further discuss how to update the mediated schema in a stable state, i.e. after the system setup period.

Intelligent query processing for semantic mediation of information systems

We propose an intelligent and an efficient query processing approach for semantic mediation of information systems. We propose also a generic multi agent architecture that supports our approach. Our approach focuses on the exploitation of intelligent agents for query reformulation and the use of a new technology for the semantic representation. The algorithm is self-adapted to the changes of the environment, offers a wide aptitude and solves the various data conflicts in a dynamic way; it also reformulates the query using the schema mediation method for the discovered systems and the context mediation for the other systems.

Lightweight XML semantic integration: a global schema independent approach

In recent years XML has established its position as one of the most prevalent technologies for data exchange. However, its widespread but uncontrolled use has generated vast amounts of semantically alike but structurally different XML data sources. This hinders the ability to meaningfully synthesise related information which partially defeats the purpose of XML. Many solutions have been proposed for the integration of XML semantics, most of which rely on the creation of a global mediated schema. In this paper, we present a novel approach for decentralised integration of heterogeneous XML data sources; thus eliminating the need to create and maintain a global schema. Moreover, our solution is portable which enables the XML data sources to be semantically integrated into different systems without additional efforts. We achieved these objectives by introducing two new components namely, XML semantic schema (XMLSS) and XML semantic query language (XMLSQL), and by providing a query translation algorithm to translate XMLSQL to standard XQuery.

Double-layered schema integration of heterogeneous XML sources

Schema integration aims to create a mediated schema as a unified representation of existing heterogeneous sources sharing a common application domain. These sources have been increasingly written in XML due to its versatility and expressive power. Unfortunately, these sources often use different elements and structures to express the same concepts and relations, thus causing substantial semantic and structural conflicts. Such a challenge impedes the creation of high-quality mediated schemas and has not been adequately addressed by existing integration methods. In this paper, we propose a novel method, named XINTOR, for automating the integration of heterogeneous schemas. Given a set of XML sources and a set of correspondences between the source schemas, our method aims to create a complete and minimal mediated schema: it completely captures all of the concepts and relations in the sources without duplication, provided that the concepts do not overlap. Our contributions are fourfold. First, we resolve structural conflicts inherent in the source schemas. Second, we introduce a new statistics-based measure, called path cohesion, for selecting concepts and relations to be a part of the mediated schema. The path cohesion is statistically computed based on multiple path quality dimensions such as average path length and path frequency. Third, we resolve semantic conflicts by augmenting the semantics of similar concepts with context-dependent information. Finally, we propose a novel double-layered mediated schema to retain a wider range of concepts and relations than existing mediated schemas, which are at best either complete or minimal, but not both. Performed on both real and synthetic datasets, our experimental results show that XINTOR outperforms existing methods with respect to (i) the mediated-schema quality using precision, recall, F-measure, and schema minimality; and (ii) the execution performance based on execution time and scale-up performance.

A Scalable and Efficient Query Answering for a Context and Schema Mediation

A Scalable and Efficient Query Answering for a Context and Schema Mediation

Describing the Semantic Relation of the Deep Web Query Interfaces Using Ontology Extended LAV

The key element in a Deep Web information fusion system is the data source modeling problem, which is the determinant technical factor of the whole system. The query interfaces provided by the Deep Web are the clues to disclose the hidden schemas. But the complicated semantic relationships in the query interfaces lead to the lower generality and ability of local as view (LAV) method in the traditional information fusion system. An approach of extracting attributes and semantic relationships from the interfaces utilizing Ontology is present in this paper, and WordNet is introduced as an Ontology instrument. The semantic relationships between semantic related attributes are evaluated by the WordNet. The meaningless attributes are instantiated by instance information embedded in the interfaces. A semantic matrix is generated and used to evaluate the semantic related groups in the specific domains. The expression ability of LAV is extended by the mapping and matching mechanism based on the semantic related groups. The experiment is carried out on the famous dataset, and the results show the efficiency of Ontology extended LAV of building mappings between local schemas and mediator schema..

PORSCHE: Performance ORiented SCHEma mediation

Semantic matching of schemas in heterogeneous data sharing systems is time consuming and error prone. Existing mapping tools employ semi-automatic techniques for mapping two schemas at a time. In a large-scale scenario, where data sharing involves a large number of data sources, such techniques are not suitable. We present a new robust automatic method which discovers semantic schema matches in a large set of XML schemas, incrementally creates an integrated schema encompassing all schema trees, and defines mappings from the contributing schemas to the integrated schema. Our method, PORSCHE (Performance ORiented SCHEma mediation), utilises a holistic approach which first clusters the nodes based on linguistic label similarity. Then it applies a tree mining technique using node ranks calculated during depth-first traversal. This minimises the target node search space and improves performance, which makes the technique suitable for large-scale data sharing. The PORSCHE framework is hybrid in nature and flexible enough to incorporate more matching techniques or algorithms. We report on experiments with up to 80 schemas containing 83,770 nodes, with our prototype implementation taking 587 s on average to match and merge them, resulting in an integrated schema and returning mappings from all input schemas to the integrated schema. The quality of matching in PORSCHE is shown using precision, recall and F-measure on randomly selected pairs of schemas from the same domain. We also discuss the integrity of the mediated schema in the light of completeness and minimality measures.

DartGrid: a semantic infrastructure for building database Grid applications

AbstractIn the presence of a Database Grid where a huge number of highly diverse, widely distributed, autonomously managed databases can be involved in a sharing cycle, database tools and middleware should be well suited for schema mediation and query processing in a semantically meaningful way. In this paper, an implemented system called DartGrid is presented. DartGrid is intended to provide a semantic infrastructure for building database grid applications. We explore the essential and fundamental roles played by Resource Description Framework (RDF) semantics for database grids and implement a set of semantically enabled tools and grid services such as semantic browser, semantic mapping tools, ontology service, semantic query service and semantic registration service. We propose an RDF‐View‐based approach for relational schema mediation and describe the view‐based semantic query rewriting algorithm implemented in DartGrid. DartGrid has been used to build a real database grid application for Traditional Chinese Medicine in China. Copyright © 2006 John Wiley & Sons, Ltd.

Schema mediation for large-scale semantic data sharing

Intuitively, data management and data integration tools should be well suited for exchanging information in a semantically meaningful way. Unfortunately, they suffer from two significant problems: they typically require a common and comprehensive schema design before they can be used to store or share information, and they are difficult to extend because schema evolution is heavyweight and may break backward compatibility. As a result, many large-scale data sharing tasks are more easily facilitated by non-database-oriented tools that have little support for semantics.The goal of the peer data management system (PDMS) is to address this need: we propose the use of a decentralized, easily extensible data management architecture in which any user can contribute new data, schema information, or even mappings between other peers’ schemas. PDMSs represent a natural step beyond data integration systems, replacing their single logical schema with an interlinked collection of semantic mappings between peers’ individual schemas.This paper considers the problem of schema mediation in a PDMS. Our first contribution is a flexible language for mediating between peer schemas that extends known data integration formalisms to our more complex architecture. We precisely characterize the complexity of query answering for our language. Next, we describe a reformulation algorithm for our language that generalizes both global-as-view and local-as-view query answering algorithms. Then we describe several methods for optimizing the reformulation algorithm and an initial set of experiments studying its performance. Finally, we define and consider several global problems in managing semantic mappings in a PDMS.

The Piazza Peer Data Management System

Intuitively, data management and data integration tools are well-suited for exchanging information in a semantically meaningful way. Unfortunately, they suffer from two significant problems: They typically require a comprehensive schema design before they can be used to store or share information and they are difficult to extend because schema evolution is heavyweight and may break backward compatibility. As a result, many small-scale data sharing tasks are more easily facilitated by nondatabase-oriented tools that have little support for semantics. The goal of the peer data management system (PDMS) is to address this need: We propose the use of a decentralized, easily extensible data management architecture in which any user can contribute new data, schema information, or even mappings between other peers' schemes. PDMSs represent a natural step beyond data integration systems, replacing their single logical schema with an interlinked collection of semantic mappings between peers' individual schemas. This paper describes-several aspects of the Piazza PDMS, including the schema mediation formalism, query answering and optimization algorithms, and the relevance of PDMSs to the semantic Web.

Schema mediation in categorization learning

Subjects categorized unfamiliar stimuli representative of previously learned schema-defined categories significantly better than chance. Categorization performance was not dependent upon knowledge of results. These findings are related to traditional views of concept learning and concept mediation.