Vol. 27 · No. 1

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.

Knowledge integration and exchange of data within and among organizations is a universally recognized need in bioinformatics and genomics research through the e-science field. The main problem looming over the lack of integration is the fact that the current Web is an environment primarily developed for human users and micro-array data resources lack widely accepted standards; this leads to a tremendous data heterogeneity. Using semantic technologies as a key technology for interoperation of various datasets enables knowledge integration of the vast amount of biological and biomedical data. In this paper, we aim at providing a semantically-enhanced bioinformatics platform (SEBIO), which handles these issues effectively. We will describe the problems arisen and the solutions applied so far. For that, the SEBIO approach is unfolded and its main components explained, to see in more detail how perfectly it copes with the aforementioned difficulties.

There are a lot of life science databases and services on the Internet nowadays, especially in life science e-science. In this paper, we will present an E-Learning Semantic Grid that integrates these resources provided by both teachers and scientists for life science education. It uses domain ontologies to break integrate these heterogeneous life science database and service resources, and supports ontology-based e-learning data-sharing and service-coordination for life science teachers and students in an e-learning virtual organization. Our system provides life science students with semantically superior experience in learning activities, and also extends the function of life science e-science. It has a promising future in the domain of life science education.

Interoperable access of geospatial information across disparate geospatial applications has become essential. Geospatial data are highly heterogeneous – the heterogeneity arises both at the syntactic and semantic levels. Finding and accessing appropriate data in such a distributed environment is an important research issue. The paper proposes a methodology for interoperable access of geospatial information based on Open Geospatial Consortium (OGC) specified standards. An architecture for integrating diverse geospatial data repositories has been proposed using service-based methodology. The semantic issues for discovery and retrieval of geospatial data over distributed geospatial services have also been proposed in the paper. The proposed architecture utilizes the ontological concepts for service description and subsequent discovery of services. An approach for semantic similarity assessment of geospatial services has been discussed.

In this paper we analyze several semantic-aware Grid middleware services used in e-Science applications. We describe them according to a common analysis framework, so as to find their commonalities and their distinguishing features. As a result of this analysis we categorize these services into three groups: information services, data access services and decision support services. We make comparisons and provide additional conclusions that are useful to understand better how these services have been developed and deployed, and how similar services would be developed in the future, mainly in the context of e-Science applications.

This paper reports ongoing work on using an ontology as a mechanism to bridge various types of country-based information systems at the Food and Agriculture Organization (FAO) of the United Nations.

In today's IT-centric environment, businesses rely more heavily on IT technologies. Organizations are often obliged to satisfy different requirements demanded and imposed by customers, business partners and legal entities. With increasing regulatory requirements, various best practices and standards are phenomenally employed to benchmark organizational adherence to different regulations. In a heterogeneous, multi-regulated, multi-disciplined and global environment, corporations are often required to consult with multiple standards. Interoperability between the standards for heterogeneous compliance management in the forms of semantic data translation and data integration is subsequently required. Semantic translation between standards allows compliance efforts established on a standard to be based on another standard. On the other hand, semantic data integration enables an integrated view of multiple standards. We present in this paper an ontology-based approach to the semantic interoperability problem in the domain of IT governance.