Abstract
The widespread adoption of the semantic web and information technologies has led to the development of ontologies to represent domain concepts in a very specific, independent and formal way. However, the proliferation of these ontologies now pose a different kind of problem in terms of managing and reusing ontologies effectively. The heterogeneity in the structure, content, representation, and purpose of the ontologies make it difficult to find appropriate ontologies for specific tasks. Similar ontologies with overlapping content and coverage can be integrated to begin to address this issue. Thus, it is worthwhile to merge some of the ontologies in a particular domain into a more general ontology with a common representation and clearly articulated semantic information. In order to make progress in developing a scalable approach for integrating ontologies, one needs to analyze and understand the existing approaches so that the gaps and the limitations can be clearly explicated and then develop approaches to mitigate these problems. A clear understanding of the status-quo will go a long way in developing a robust approach for mapping ontologies and integrating the semantic information. Thus, the aim of this research is to survey the existing literature and develop an understanding of the approaches used for extracting information from ontologies, identifying similar content, and integrating the semantic information. The existing mapping techniques are briefly summarized below. A) Structure based technique – the structure of entities found in ontologies can be compared, in addition to comparing their names or identifiers. This comparison can be on the internal structure of an entity, i.e., besides its name and annotations, its properties or, in the case of OWL ontologies, the properties which take their values in a datatype, or the comparison of the entity with other entities to which it is related. B) Instance based technique – this method determines the similarity between concepts of different ontologies by examining the extensional information of concepts that is the instance data. C) Semantic based technique – semantic based techniques find the semantic relations between ontologies and making corresponding mapping rules first, and then integrating all independent ontologies into a whole to be operated. Semantic based methodology uses semantics or the science of meaning in language, to produce highly relevant search results. D) Terminological based technique – some terminological methods compare strings. They can be applied to the name, the label or the comments of entities in order to find those which are similar. This can be used for comparing class names and/or URIs. Ontology mapping is needed to promote knowledge sharing and integrating semantics in an environment with different underlying ontologies. For given two ontologies, A and B, mapping one ontology with another means that for each concept in ontology A, finding the same or similar semantics in ontology B, and vice versa. The various ontology mapping methods and ontology integration techniques applied in different domain ontologies need to be compared based on various parameters such as input, output, sources of knowledge, algorithms and methods used, evaluation result etc. In this research, we focus on understanding the different levels of ontology mapping, ontology merging, aligning and integrating into a single ontology for the same domain. Different techniques have been used to map the different ontologies of same domain and we focus on how the semantic information is integrated using mapping techniques. Our future work includes additional literature survey and building a tool for mapping ontologies and developing an architecture for integrating into a target ontology using temporal information.
Recommended Citation
Pushpavathi, K.; Somasundaram, K.; and Sugumaran, Vijayan, "Ontology Mapping Techniques for Semantic Information Integration - A Literature Survey" (2019). AMCIS 2019 Proceedings. 31.
https://aisel.aisnet.org/amcis2019/treo/treos/31
Ontology Mapping Techniques for Semantic Information Integration - A Literature Survey
The widespread adoption of the semantic web and information technologies has led to the development of ontologies to represent domain concepts in a very specific, independent and formal way. However, the proliferation of these ontologies now pose a different kind of problem in terms of managing and reusing ontologies effectively. The heterogeneity in the structure, content, representation, and purpose of the ontologies make it difficult to find appropriate ontologies for specific tasks. Similar ontologies with overlapping content and coverage can be integrated to begin to address this issue. Thus, it is worthwhile to merge some of the ontologies in a particular domain into a more general ontology with a common representation and clearly articulated semantic information. In order to make progress in developing a scalable approach for integrating ontologies, one needs to analyze and understand the existing approaches so that the gaps and the limitations can be clearly explicated and then develop approaches to mitigate these problems. A clear understanding of the status-quo will go a long way in developing a robust approach for mapping ontologies and integrating the semantic information. Thus, the aim of this research is to survey the existing literature and develop an understanding of the approaches used for extracting information from ontologies, identifying similar content, and integrating the semantic information. The existing mapping techniques are briefly summarized below. A) Structure based technique – the structure of entities found in ontologies can be compared, in addition to comparing their names or identifiers. This comparison can be on the internal structure of an entity, i.e., besides its name and annotations, its properties or, in the case of OWL ontologies, the properties which take their values in a datatype, or the comparison of the entity with other entities to which it is related. B) Instance based technique – this method determines the similarity between concepts of different ontologies by examining the extensional information of concepts that is the instance data. C) Semantic based technique – semantic based techniques find the semantic relations between ontologies and making corresponding mapping rules first, and then integrating all independent ontologies into a whole to be operated. Semantic based methodology uses semantics or the science of meaning in language, to produce highly relevant search results. D) Terminological based technique – some terminological methods compare strings. They can be applied to the name, the label or the comments of entities in order to find those which are similar. This can be used for comparing class names and/or URIs. Ontology mapping is needed to promote knowledge sharing and integrating semantics in an environment with different underlying ontologies. For given two ontologies, A and B, mapping one ontology with another means that for each concept in ontology A, finding the same or similar semantics in ontology B, and vice versa. The various ontology mapping methods and ontology integration techniques applied in different domain ontologies need to be compared based on various parameters such as input, output, sources of knowledge, algorithms and methods used, evaluation result etc. In this research, we focus on understanding the different levels of ontology mapping, ontology merging, aligning and integrating into a single ontology for the same domain. Different techniques have been used to map the different ontologies of same domain and we focus on how the semantic information is integrated using mapping techniques. Our future work includes additional literature survey and building a tool for mapping ontologies and developing an architecture for integrating into a target ontology using temporal information.