Matching ontologies for context

euzenat2007dNo abstract available

Facilitating file retrieval on resource limited devices

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The rapid development of mobile technologies has facilitated users to generate and store files on mobile devices. However, it has become a challenging issue for users to search efficiently and effectively for files of interest in a mobile environment that involves a large number of mobile nodes. In this thesis, file management and retrieval alternatives have been investigated to propose a feasible framework that can be employed on resource-limited devices without altering their operating systems. The file annotation and retrieval framework (FARM) proposed in the thesis automatically annotates the files with their basic file attributes by extracting them from the underlying operating system of the device. The framework is implemented in the JME platform as a case study. This framework provides a variety of features for managing the metadata and file search features on the device itself and on other devices in a networked environment. FARM not only automates the file-search process but also provides accurate results as demonstrated by the experimental analysis. In order to facilitate a file search and take advantage of the Semantic Web Technologies, the SemFARM framework is proposed which utilizes the knowledge of a generic ontology. The generic ontology defines the most common keywords that can be used as the metadata of stored files. This provides semantic-based file search capabilities on low-end devices where the search keywords are enriched with additional knowledge extracted from the defined ontology. The existing frameworks annotate image files only, while SemFARM can be used to annotate all types of files. Semantic heterogeneity is a challenging issue and necessitates extensive research to accomplish the aim of a semantic web. For this reason, significant research efforts have been made in recent years by proposing an enormous number of ontology alignment systems to deal with ontology heterogeneities. In the process of aligning different ontologies, it is essential to encompass their semantic, structural or any system-specific measures in mapping decisions to produce more accurate alignments. The proposed solution, in this thesis, for ontology alignment presents a structural matcher, which computes the similarity between the super-classes, sub-classes and properties of two entities from different ontologies that require aligning. The proposed alignment system (OARS) uses Rough Sets to aggregate the results obtained from various matchers in order to deal with uncertainties during the mapping process of entities. The OARS uses a combinational approach by using a string-based and linguistic-based matcher, in addition to structural-matcher for computing the overall similarity between two entities. The performance of the OARS is evaluated in comparison with existing state of the art alignment systems in terms of precision and recall. The performance tests are performed by using benchmark ontologies and the results show significant improvements, specifically in terms of recall on all groups of test ontologies. There is no such existing framework, which can use alignments for file search on mobile devices. The ontology alignment paradigm is integrated in the SemFARM to further enhance the file search features of the framework as it utilises the knowledge of more than one ontology in order to perform a search query. The experimental evaluations show that it performs better in terms of precision and recall where more than one ontology is available when searching for a required file.Education Commission of Pakistan and the University of Engineering & Technology, Peshawa

A context information manager for pervasive environments

euzenat2006bInternational audienceIn a pervasive computing environment, heterogeneous devices need to communicate in order to provide services adapted to the situation of users. So, they need to assess this situation as their context. We have developed an extensible context model using semantic web technologies and a context information management component that enable the interaction between context information producer devices and context information consumer devices and as well as their insertion in an open environment

Integration of OntoLight with the Alignment server

euzenat2008fThis deliverable describes the integration of the OntoLight matcher within the Alignment server and the NeOn toolkit. This integration uses a web service connection from the Alignment server to an OntoLight web service interface

Data in Crisis: anticipating risk, vulnerability, and resilience through communication infrastructures

This paper explores the implications of having interactions around crises progressively based in information and communication technology (ICT), data, and their infrastructures. Drawing on applied research from multidisciplinary projects to design crisis ICT, we describe the how these tools become fundamental to how crisis communication and governance can and does work. Crisis ICT facilitate collaboration and interoperability in ways that make it possible for crisis managers to share each other’s strategies, processes, goals, and perspectives. They also bring together different histories of risk assessment practices and socio-political situations. Combining them meaningfully requires anyone working with the ICT to actively negotiate and deliberate what that combined view includes. We examine a series of tensions raised by infrastructuringdiverse crisis data and discuss what they mean for conceptions of crisis risk, vulnerability, and resilience. First, are tensions that emerge when trying to provide an underpinning logic that makes data shareable and comparable. Second, are the dynamics that come from misunderstandings as crisis practitioners from different disciplines and cultures engage with each other through these infrastructures. Third are the tensions raised through the anticipatory conflicts between concrete data needs of a technology and the uncertainties of how crises unfold. Finally, we consider how these infrastructures stabilise crises to make them visible, actionable, and contestable. We argue that crisis communication requires reflexive perspectives, building into all communication practices mechanisms by which actors can be mutually responsive to each other. Our aim is to provoke those engaging with such tools to consider how risk, vulnerability, resilience, and the lived experience of crises are intertwined with the infrastructures that make communication possible

Network alliances: precarious governance through data, standards and code

First paragraph: We share the general concerns of this book about the ways in which education, alongside most other social services from health care to air travel and banking, is being managed through comparative technologies. These effectively translate complex knowledge processes and human relationships into data. Such translations render processes calculable, and enrol them into massive digital networks that track, sequence, assess, procure and direct most social activity in advanced societies. To better understand how these processes mobilize particular educational practices, we argue for the utility of network analysis following Bruno Latour (2005). While controversial, versions of actor-network theory are increasingly brought to bear in educational studies of governmentality and knowledge. These approaches tend to avoid the limitations inherent in explanations that rely upon dominant ‘paradigms' and political ideologies. They also deliberately decentre human actors, their meanings and politics. Instead, we argue for analysis that traces myriad negotiations among material devices, embodiments, and technologies with social desires and discourses. Through these sociomaterial vitalities, particular forms of knowledge become performed and stabilized

Revision in networks of ontologies

euzenat2015aInternational audienceNetworks of ontologies are made of a collection of logic theories, called ontologies, related by alignments. They arise naturally in distributed contexts in which theories are developed and maintained independently, such as the semantic web. In networks of ontologies, inconsistency can come from two different sources: local inconsistency in a particular ontology or alignment, and global inconsistency between them. Belief revision is well-defined for dealing with ontologies; we investigate how it can apply to networks of ontologies. We formulate revision postulates for alignments and networks of ontologies based on an abstraction of existing semantics of networks of ontologies. We show that revision operators cannot be simply based on local revision operators on both ontologies and alignments. We adapt the partial meet revision framework to networks of ontologies and show that it indeed satisfies the revision postulates. Finally, we consider strategies based on network characteristics for designing concrete revision operators

Facilitating file retrieval on resource limited devices

The rapid development of mobile technologies has facilitated users to generate and store files on mobile devices. However, it has become a challenging issue for users to search efficiently and effectively for files of interest in a mobile environment that involves a large number of mobile nodes. In this thesis, file management and retrieval alternatives have been investigated to propose a feasible framework that can be employed on resource-limited devices without altering their operating systems. The file annotation and retrieval framework (FARM) proposed in the thesis automatically annotates the files with their basic file attributes by extracting them from the underlying operating system of the device. The framework is implemented in the JME platform as a case study. This framework provides a variety of features for managing the metadata and file search features on the device itself and on other devices in a networked environment. FARM not only automates the file-search process but also provides accurate results as demonstrated by the experimental analysis. In order to facilitate a file search and take advantage of the Semantic Web Technologies, the SemFARM framework is proposed which utilizes the knowledge of a generic ontology. The generic ontology defines the most common keywords that can be used as the metadata of stored files. This provides semantic-based file search capabilities on low-end devices where the search keywords are enriched with additional knowledge extracted from the defined ontology. The existing frameworks annotate image files only, while SemFARM can be used to annotate all types of files. Semantic heterogeneity is a challenging issue and necessitates extensive research to accomplish the aim of a semantic web. For this reason, significant research efforts have been made in recent years by proposing an enormous number of ontology alignment systems to deal with ontology heterogeneities. In the process of aligning different ontologies, it is essential to encompass their semantic, structural or any system-specific measures in mapping decisions to produce more accurate alignments. The proposed solution, in this thesis, for ontology alignment presents a structural matcher, which computes the similarity between the super-classes, sub-classes and properties of two entities from different ontologies that require aligning. The proposed alignment system (OARS) uses Rough Sets to aggregate the results obtained from various matchers in order to deal with uncertainties during the mapping process of entities. The OARS uses a combinational approach by using a string-based and linguistic-based matcher, in addition to structural-matcher for computing the overall similarity between two entities. The performance of the OARS is evaluated in comparison with existing state of the art alignment systems in terms of precision and recall. The performance tests are performed by using benchmark ontologies and the results show significant improvements, specifically in terms of recall on all groups of test ontologies. There is no such existing framework, which can use alignments for file search on mobile devices. The ontology alignment paradigm is integrated in the SemFARM to further enhance the file search features of the framework as it utilises the knowledge of more than one ontology in order to perform a search query. The experimental evaluations show that it performs better in terms of precision and recall where more than one ontology is available when searching for a required file.EThOS - Electronic Theses Online ServiceEducation Commission of PakistanTechnology, PeshawarGBUnited Kingdo