74 research outputs found
Semantic Web Techniques to Support Interoperability in Distributed Networked Environments
We explore two Semantic Web techniques arising from ITA research into semantic alignment and interoperability in distributed networks. The first is POAF (Portable Ontology Aligned Fragments) which addresses issues relating to the portability and usage of ontology alignments. POAF uses an ontology fragmentation strategy to achieve portability, and enables subsequent usage through a form of automated ontology modularization. The second technique, SWEDER (Semantic Wrapping of Existing Data sources with Embedded Rules), is grounded in the creation of lightweight ontologies to semantically wrap existing data sources, to facilitate rapid semantic integration through representational homogeneity. The semantic integration is achieved through the creation of context ontologies which define the integrations and provide a portable definition of the integration rules in the form of embedded SPARQL construct clauses. These two Semantic Web techniques address important practical issues relevant to the potential future adoption of ontologies in distributed network environments
OntoMaven: Maven-based Ontology Development and Management of Distributed Ontology Repositories
In collaborative agile ontology development projects support for modular
reuse of ontologies from large existing remote repositories, ontology project
life cycle management, and transitive dependency management are important
needs. The Apache Maven approach has proven its success in distributed
collaborative Software Engineering by its widespread adoption. The contribution
of this paper is a new design artifact called OntoMaven. OntoMaven adopts the
Maven-based development methodology and adapts its concepts to knowledge
engineering for Maven-based ontology development and management of ontology
artifacts in distributed ontology repositories.Comment: Pre-print submission to 9th International Workshop on Semantic Web
Enabled Software Engineering (SWESE2013). Berlin, Germany, December 2-5, 201
An empirically-based framework for ontology modularization
Modularity is being increasingly used as an approach to solve for the information overload problem in ontologies. It eases cognitive complexity for humans, and computational complexity for machines. The current literature for modularity focuses mainly on techniques, tools, and on evaluation metrics. However, ontology developers still face difficulty in selecting the correct technique for specific applications and the current tools for modularity are not sufficient.
These issues stem from a lack of theory about the modularisation process. To solve this problem, several researchers propose a framework for modularity, but alas, this has not been realised, up until now. In this article, we survey the existing literature to identify and populate dimensions of modules, experimentally evaluate and characterise 189 existing modules, and create a framework for modularity based on these results. The framework guides the ontology developer throughout the modularisation process. We evaluate the framework with a use-case for the Symptom ontology
Ontology Repositories
The growing use and application of ontologies in the last years has led to an increased interest of researchers and practitioners in the development of ontologies, either from scratch o by reusing existing ones. ..
Toward a framework for ontology modularity
Dividing up data or information into smaller components---modules---is a well-know approach to a range of problems, such as scalability and model comprehension. The use of modules in ontologies at the knowledge layer is receiving increased attention, and a plethora of approaches, algorithms, and tools exist, which, however, yield only very limited success. This is mainly because wrong combinations of techniques are being used. To solve this issue, we examine the modules' use-cases, types, techniques, and properties from the literature. This is used to create a framework for ontology modularity, such that a user with a certain use case will know the type of modules needed, and therewith then also the appropriate technique to realise it and what properties the resultant modules will have. This framework is then evaluated with three case studies, begin the QUDT, FMA, and OpenGalen ontologies
Requirements and Use Cases ; Report I on the sub-project Smart Content Enrichment
In this technical report, we present the results of the first milestone phase
of the Corporate Smart Content sub-project "Smart Content Enrichment". We
present analyses of the state of the art in the fields concerning the three
working packages defined in the sub-project, which are aspect-oriented
ontology development, complex entity recognition, and semantic event pattern
mining. We compare the research approaches related to our three research
subjects and outline briefly our future work plan
A method to generate a modular ifcOWL ontology
Building Information Modeling (BIM) and Semantic Web technologies are becoming more and more popular in the Architecture Engineering Construction (AEC) and Facilities Management (FM) industry to support information management, information exchange and data interoperability. One of the key integration gateways between BIM and Semantic Web is represented by the ifcOWL ontology, i.e. the Web Ontology Language (OWL) version of the IFC standard, being one of reference technical standard for AEC/FM. Previous studies have shown how a recommended ifcOWL ontology can be automatically generated by converting the IFC standard from the official EXPRESS schema. However, the resulting ifcOWL is a large monolithic ontology that presents serious limitations for real industrial applications in terms of usability and performance (i.e. querying and reasoning). Possible enhancements to reduce the complexity and the data size consist in (1) modularization of ifcOWL making it easier to use subsets of the entire ontology, and (2) rethinking the contents and structure of an ontology for AEC/FM to better fit in the semantic web scope and make its usage more efficient. The second approach can be enabled by the first one, since it would make it easier to replace some of the ifcOWL modules with new optimized ontologies for the AEC-FM industry. This paper focuses on the first approach presenting a method to automatically generate a modular ifcOWL ontology. The method aims at minimizing the dependencies between modules to better exploit the modularization. The results are compared with simpler and more straight-forward solutions
Git4Voc: Git-based Versioning for Collaborative Vocabulary Development
Collaborative vocabulary development in the context of data integration is
the process of finding consensus between the experts of the different systems
and domains. The complexity of this process is increased with the number of
involved people, the variety of the systems to be integrated and the dynamics
of their domain. In this paper we advocate that the realization of a powerful
version control system is the heart of the problem. Driven by this idea and the
success of Git in the context of software development, we investigate the
applicability of Git for collaborative vocabulary development. Even though
vocabulary development and software development have much more similarities
than differences there are still important differences. These need to be
considered within the development of a successful versioning and collaboration
system for vocabulary development. Therefore, this paper starts by presenting
the challenges we were faced with during the creation of vocabularies
collaboratively and discusses its distinction to software development. Based on
these insights we propose Git4Voc which comprises guidelines how Git can be
adopted to vocabulary development. Finally, we demonstrate how Git hooks can be
implemented to go beyond the plain functionality of Git by realizing
vocabulary-specific features like syntactic validation and semantic diffs
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