One of the main hurdles towards a wide endorsement of ontologies is the high cost of constructing them. Reuse of existing ontologies offers a much cheaper alternative than building new ones from scratch, yet tools to support such reuse are still in their infancy. However, more ontologies are becoming available on the web, and online libraries for storing and indexing ontologies are increasing in number and demand. Search engines have also started to appear, to facilitate search and retrieval of online ontologies. This paper presents a fresh view on constructing ontologies automatically, by identifying, ranking, and merging fragments of online ontologies.

Abstract. One of the main open issues in the ontology matching field is the selection of a current relevant and suitable matcher. The suitability of the given approaches is determined w.r.t the requirements of the application and with careful consideration of a number of factors. This work proposes a multilevel characteristic for matching approaches, which provides a basis for the comparison of different matchers and is used in the decision making process for selection the most appropriate algorithm. 1

Abstract. As more and more applications use ontology to represent semantic information, how to support ontology reuse is becoming more and more important. In the OWL Web Ontology Language, the main primitive for ontology reuse is owl:imports. However, this “copy-andpaste” approach suffers a number of problems. In this paper, we propose a new import primitive, called semantic import, to facilitate partial ontology reuse. The main contributions of this paper include the semantics of semantic import and reasoning support for TBox reasoning in simple ontology spaces, where an ontology semantically imports vocabulary from another ontology. The semantic import approach provides a brand new way for partial ontology reuse. 1

Abstract: The digital media and games industry is one of the biggest IT based industries worldwide. Recent observations therein showed that current production workflows may be potentially improved as multimedia objects are mostly created from scratch due to insufficient reusability capacities of existing tools. In this paper we provide reasons for that, provide a potential solution based on semantic technologies, show the potential of ontologies, and provide scenarios for the application of semantic technologies in the digital media and games industry.

Realizing the Semantic Web involves creating ontologies, a tedious and costly challenge. Reuse can reduce the cost of ontology engineering. Semantic Web ontologies can provide useful input for ontology reuse. However, the automated reuse of such ontologies remains underexplored. This paper presents a generic architecture for automated ontology reuse. With our implementation of this architecture, we show the practicality of automating ontology generation through ontology reuse. We experimented with a large generic ontology as a basis for automatically generating domain ontologies that fit the scope of sample natural-language web pages. The results were encouraging, resulting in five lessons pertinent to future automated ontology reuse study.

Abstract. Software systems and information about them diverge quickly in time, resulting in difficulties understanding and maintaining them. Information about software systems, or system metadata, may include functional and nonfunctional requirements documentation, metrics, the success or failure of tests and the means by which various components interact or were intended to interact. Various proposals have been made to link software components and their metadata. We propose another such system using Semantic Web techniques to encode system metadata and demonstrate the particular advantages that these techniques offer. Specifically, we show how the use of an OWL-DL ontology of software engineering concepts, RDF encoding of system metadata and SPARQL queries over the resulting RDF graph can be used to enable languageneutral relational navigation of software systems thus facilitating software understanding and maintenance. 1

Current algorithms can not to be used optimally in automatic and semi-automatic ontology matching tasks as those envisioned by the Semantic Web community, mainly because of the inherent dependency between particular algorithms and ontology properties such as size, representation language or underlying graph structure, and because of performance and scalability limitations. In order to cope with the first problem we designed a generic matching framework which exploits the valuable ideas embedded in current matching approaches, but in the same time accounts for their limitations—for specific input ontologies it optimizes the matching results by automatically eliminating unsuitable candidate matching methods.

Abstract. Due to the inherent difficulties associated with manual ontology building, knowledge acquisition and reuse are often seen as methods that can make this tedious process easier. In this paper we present an NLP-based method to aid ontology design in a specific setting, namely that of semantic annotation of text. The method uses the World Wide Web in its analysis of the domain-specific documents, eliminating the need for linguistic knowledge and resources, and suggests ways to specify domain ontologies in a “linguistics-friendly ” format in order to improve further ontology-based natural language processing tasks such as semantic annotation. We evaluate the method on a corpora in a real-world setting in the medical domain and compare the costs and the benefits of the NLP-based ontology engineering approach against a similar reuseoriented experiment. 1

Abstract. Realizing the Semantic Web involves creating ontologies, a tedious and costly challenge. Reuse can reduce the cost of ontology engineering. Semantic Web ontologies can provide useful input for ontology reuse. However, the automated reuse of such ontologies remains underexplored. This paper presents a generic architecture for automated ontology reuse. With our implementation of this architecture, we show the practicality of automating ontology generation through ontology reuse. We experimented with a large generic ontology as a basis for automatically generating domain ontologies that fit the scope of sample natural-language web pages. The results were encouraging, resulting in five lessons pertinent to future automated ontology reuse study. 1

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