IoT and semantic web technologies for event detection in natural disasters

This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.Natural disasters cannot be predicted well in advance, but it is still possible to decrease the loss of life and mitigate the damages, exploiting some peculiarities that distinguish them. Smart collection, integration, and analysis of data produced by distributed sensors and services are key elements for understanding the context and supporting decision making process for disaster prevention and management. In this paper, we demonstrate how Internet of Things and Semantic Web technologies can be effectively used for abnormal event detection in the contest of an earthquake. In our proposal, a prototype system, which retrieves the data streams from IoT sensors and web services, is presented. In order to contextualize and give a meaning to the data, semantic web technologies are applied for data annotation. We evaluate our system performances by measuring the response time and other parameters that are important in a disaster detection scenario.Peer ReviewedPostprint (author's final draft

Cognition-based approaches for high-precision text mining

This research improves the precision of information extraction from free-form text via the use of cognitive-based approaches to natural language processing (NLP). Cognitive-based approaches are an important, and relatively new, area of research in NLP and search, as well as linguistics. Cognitive approaches enable significant improvements in both the breadth and depth of knowledge extracted from text. This research has made contributions in the areas of a cognitive approach to automated concept recognition in. Cognitive approaches to search, also called concept-based search, have been shown to improve search precision. Given the tremendous amount of electronic text generated in our digital and connected world, cognitive approaches enable substantial opportunities in knowledge discovery. The generation and storage of electronic text is ubiquitous, hence opportunities for improved knowledge discovery span virtually all knowledge domains. While cognition-based search offers superior approaches, challenges exist due to the need to mimic, even in the most rudimentary way, the extraordinary powers of human cognition. This research addresses these challenges in the key area of a cognition-based approach to automated concept recognition. In addition it resulted in a semantic processing system framework for use in applications in any knowledge domain. Confabulation theory was applied to the problem of automated concept recognition. This is a relatively new theory of cognition using a non-Bayesian measure, called cogency, for predicting the results of human cognition. An innovative distance measure derived from cogent confabulation and called inverse cogency, to rank order candidate concepts during the recognition process. When used with a multilayer perceptron, it improved the precision of concept recognition by 5% over published benchmarks. Additional precision improvements are anticipated. These research steps build a foundation for cognition-based, high-precision text mining. Long-term it is anticipated that this foundation enables a cognitive-based approach to automated ontology learning. Such automated ontology learning will mimic human language cognition, and will, in turn, enable the practical use of cognitive-based approaches in virtually any knowledge domain --Abstract, page iii

A Nine Month Progress Report on an Investigation into Mechanisms for Improving Triple Store Performance

This report considers the requirement for fast, efficient, and scalable triple stores as part of the effort to produce the Semantic Web. It summarises relevant information in the major background field of Database Management Systems (DBMS), and provides an overview of the techniques currently in use amongst the triple store community. The report concludes that for individuals and organisations to be willing to provide large amounts of information as openly-accessible nodes on the Semantic Web, storage and querying of the data must be cheaper and faster than it is currently. Experiences from the DBMS field can be used to maximise triple store performance, and suggestions are provided for lines of investigation in areas of storage, indexing, and query optimisation. Finally, work packages are provided describing expected timetables for further study of these topics

EXPRESS: Resource-oriented and RESTful Semantic Web services

This thesis investigates an approach that simplifies the development of Semantic Web services (SWS) by removing the need for additional semantic descriptions.The most actively researched approaches to Semantic Web services introduce explicit semantic descriptions of services that are in addition to the existing semantic descriptions of the service domains. This increases their complexity and design overhead. The need for semantically describing the services in such approaches stems from their foundations in service-oriented computing, i.e. the extension of already existing service descriptions. This thesis demonstrates that adopting a resource-oriented approach based on REST will, in contrast to service-oriented approaches, eliminate the need for explicit semantic service descriptions and service vocabularies. This reduces the development efforts while retaining the significant functional capabilities.The approach proposed in this thesis, called EXPRESS (Expressing RESTful Semantic Services), utilises the similarities between REST and the Semantic Web, such as resource realisation, self-describing representations, and uniform interfaces. The semantics of a service is elicited from a resource’s semantic description in the domain ontology and the semantics of the uniform interface, hence eliminating the need for additional semantic descriptions. Moreover, stub-generation is a by-product of the mapping between entities in the domain ontology and resources.EXPRESS was developed to test the feasibility of eliminating explicit service descriptions and service vocabularies or ontologies, to explore the restrictions placed on domain ontologies as a result, to investigate the impact on the semantic quality of the description, and explore the benefits and costs to developers. To achieve this, an online demonstrator that allows users to generate stubs has been developed. In addition, a matchmaking experiment was conducted to show that the descriptions of the services are comparable to OWL-S in terms of their ability to be discovered, while improving the efficiency of discovery. Finally, an expert review was undertaken which provided evidence of EXPRESS’s simplicity and practicality when developing SWS from scratch

Beyond South Seas: Making History in Networked Digital Technologies

In this paper, I discuss some of the more salient intellectual and technological dimensions of work over the past year, focused on developing an open source knowledge creation, management and publication system. In key respects, our work seeks to anticipate developments in national collaborative e-research infrastructure over the next five or so years. Especially in view of recent statements on innovation policy by the Australian government, we can expect the next five or so years will see significant advances in the development of online knowledge repositories for not only more complex kinds of quantitative research data, but also for qualitative data in rich and diverse media forms that will offer new possibilities for humanities research. We will also see improved or new middleware, allowing Australian research communities in the humanities collaboratively to create, share and interrogate new knowledge of cultural and social phenomena. However, if humanities researchers are to exploit these and other possible advances in digital research infrastructure, then what they will also need are ‘tools’ enabling the creation, reception and use of knowledge that these infrastructural advances can put into intellectual circulation. They will need the means of using networked digital technologies as primary media for research, and to publish their findings as complex multimedia artifacts

Context Aware Computing for The Internet of Things: A Survey

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201