Debugging Ontology Mappings: A Static Approach

Ontology mapping is the bottleneck in solving interoperation between Semantic Web applications using heterogeneous ontologies. Many mapping methods have been proposed in recent years, but in practice, it is still difficult to obtain satisfactory mapping results having high precision and recall. Different from existing methods, which focus on finding efficient and effective solutions for the ontology mapping problem, we place emphasis on analyzing the mapping result to detect/diagnose the mapping defects. In this paper, a novel technique called debugging ontology mappings is presented. During debugging, some types of mapping errors, such as redundant and inconsistent mappings, can be detected. Some warnings, including imprecise mappings or abnormal mappings, are also locked by analyzing the features of mapping result. More importantly, some errors and warnings can be repaired automatically or can be presented to users with revising suggestions. The experimental results reveal that the ontology debugging technique is promising, and it can improve the quality of mapping result

A Survey of the State of Dataspaces

Published in International Journal of Computer and Information Technology.This paper presents a survey of the state of dataspaces. With dataspaces becoming the modern technique of systems integration, the achievement of complete dataspace development is a critical issue. This has led to the design and implementation of dataspace systems using various approaches. Dataspaces are data integration approaches that target for data coexistence in the spatial domain. Unlike traditional data integration techniques, they do not require up front semantic integration of data. In this paper, we outline and compare the properties and implementations of dataspaces including the approaches of optimizing dataspace development. We finally present actual dataspace development recommendations to provide a global overview of this significant research topic.This paper presents a survey of the state of dataspaces . With dataspaces becoming the modern technique of systems integration, the ach ievement of complete dataspace development is a critical issue. This has led to the design and implementation of dataspace systems using various approaches. Dataspaces are data integration approaches that target for data coexistence in the spatial domain. Unlike traditional data integration techniques, they do not require up front semantic integration of data. In this paper, we outline and compare the properties and implementations of dataspaces including the approaches of optimizing dataspace development. We finally present actual dataspace development recommendations to provide a global overview of this significant research topic

A schema-only approach to validate XML schema mappings

Since the emergence of the Web, the ability to map XML data between different data sources has become crucial. Defining a mapping is however not a fully automatic process. The designer needs to figure out whether the mapping is what was intended. Our approach to this validation consists of defining and checking certain desirable properties of mappings. We translate the XML schemas and the mapping into first-order logic formalism and apply a reasoning mechanism to check the desirable properties automatically, without assuming any particular instantiation of the schemas.Preprin

Validation of schema mappings with nested queries

With the emergence of the Web and the wide use of XML for representing data, the ability to map not only flat relational but also nested data has become crucial. The design of schema mappings is a semi-automatic process. A human designer is needed to guide the process, choose among mapping candidates, and successively refine the mapping. The designer needs a way to figure out whether the mapping is what was intended. Our approach to mapping validation allows the designer to check whether the mapping satisfies certain desirable properties. In this paper, we focus on the validation of mappings between nested relational schemas, in which the mapping assertions are either inclusions or equalities of nested queries. We focus on the nested relational setting since most XML’s Document Type Definitions (DTDs) can be represented in this model. We perform the validation by reasoning on the schemas and mapping definition. We take into account the integrity constraints defined on both the source and target schema.Preprin

Validation of mappings between schemas

Mappings between schemas are key elements in several contexts such as data exchange, data integration, peer data management systems, etc. In all these contexts, the process of designing a mapping requires the participation of a mapping designer that needs a way to validate the mapping being defined, i.e., to check whether the mapping is in fact what the designer intended. However, to date very little work has directly focused on the effective validation of schema mappings. In this paper, we present a new approach for validating schema mappings that allows the mapping designer to ask questions about the accomplishment of certain desirable properties of these mappings. We consider four properties of mappings: mapping satisfiability, mapping inference, query answerability and mapping losslessness. We reformulate these properties in terms of the problem of checking the liveliness of a derived predicate. We emphasize that this approach is independent of any particular method for liveliness checking and, to show the feasibility of our approach, we use an implementation of the CQC Method and provide some experimental results.Postprint (published version

A User-driven Annotation Framework for Scientific Data

Annotations play an increasingly crucial role in scientific exploration and discovery, as the amount of data and the level of collaboration among scientists increases. There are many systems today focusing on annotation management, querying, and propagation. Although all such systems are implemented to take user input (i.e., the annotations themselves), very few systems are user-driven, taking into account user preferences on how annotations should be propagated and applied over data. In this thesis, we propose to treat annotations as first-class citizens for scientific data by introducing a user-driven, view-based annotation framework. Under this framework, we try to resolve two critical questions: Firstly, how do we support annotations that are scalable both from a system point of view and also from a user point of view? Secondly, how do we support annotation queries both from an annotator point of view and a user point of view, in an efficient and accurate way? To address these challenges, we propose the VIew-base annotation Propagation (ViP) framework to empower users to express their preferences over the time semantics of annotations and over the network semantics of annotations, and define three query types for annotations. To efficiently support such novel functionality, ViP utilizes database views and introduces new annotation caching techniques. The use of views also brings a more compact representation of annotations, making our system easier to scale. Through an extensive experimental study on a real system (with both synthetic and real data), we show that the ViP framework can seamlessly introduce user-driven annotation propagation semantics while at the same time significantly improving the performance (in terms of query execution time) over the current state of the art