A Semantic Rule-Based Approach for Software Privacy by Design

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the URI link. Open access journalInformation system business is currently witnessing an increasing demand for system conformance with the international regime of GRC Governance, Risk and Compliance. Among different compliance approaches, data protection and privacy laws plays a key role. In this paper, we propose a compliance requirement analysis method from early stages of system modelling based on a semantically-rich model, where a mapping can be established from data protection and privacy requirements defined by laws and regulations to system business goals and contexts. The early consideration of requirements satisfies Privacy by Design, a key concept in General Data Protection Regulation 2012. The proposed semantic model consists of a number of ontologies each corresponding to a knowledge component within the developed framework of our approach. Each ontology is a thesaurus of concepts in the compliance related to system along with relationships and rules between these concepts that encompass the domain knowledge. The main contribution of the work presented in this paper is the ontology-based compliance framework that demonstrates how description-logic reasoning techniques can be used to simulate legal reasoning requirements employed by legal professions against the description of each ontology

An intelligent framework for dynamic web services composition in the semantic web

As Web services are being increasingly adopted as the distributed computing technology of choice to securely publish application services beyond the firewall, the importance of composing them to create new, value-added service, is increasing. Thus far, the most successful practical approach to Web services composition, largely endorsed by the industry falls under the static composition category where the service selection and flow management are done a priori and manually. The second approach to web-services composition aspires to achieve more dynamic composition by semantically describing the process model of Web services and thus making it comprehensible to reasoning engines or software agents. The practical implementation of the dynamic composition approach is still in its infancy and many complex problems need to be resolved before it can be adopted outside the research communities. The investigation of automatic discovery and composition of Web services in this thesis resulted in the development of the eXtended Semantic Case Based Reasoner (XSCBR), which utilizes semantic web and AI methodology of Case Based Reasoning (CBR). Our framework uses OWL semantic descriptions extensively for implementing both the matchmaking profiles of the Web services and the components of the CBR engine. In this research, we have introduced the concept of runtime behaviour of services and consideration of that in Web services selection. The runtime behaviour of a service is a result of service execution and how the service will behave under different circumstances, which is difficult to presume prior to service execution. Moreover, we demonstrate that the accuracy of automatic matchmaking of Web services can be further improved by taking into account the adequacy of past matchmaking experiences for the requested task. Our XSCBR framework allows annotating such runtime experiences in terms of storing execution values of non-functional Web services parameters such as availability and response time into a case library. The XSCBR algorithm for matchmaking and discovery considers such stored Web services execution experiences to determine the adequacy of services for a particular task. We further extended our fundamental discovery and matchmaking algorithm to cater for web services composition. An intensive knowledge-based substitution approach was proposed to adapt the candidate service experiences to the requested solution before suggesting more complex and computationally taxing AI-based planning-based transformations. The inconsistency problem that occurs while adapting existing service composition solutions is addressed with a novel methodology based on Constraint Satisfaction Problem (CSP). From the outset, we adopted a pragmatic approach that focused on delivering an automated Web services discovery and composition solution with the minimum possible involvement of all composition participants: the service provider, the requestor and the service composer. The qualitative evaluation of the framework and the composition tools, together with the performance study of the XSCBR framework has verified that we were successful in achieving our goal

Scalable software framework for real-time data processing in the railway environment

B

A FRAMEWORK FOR ONTOLOGY- BASED DIABETES DIAGNOSIS USING BAYELSIAN OPTIMIZATION TECHNIQUE

Diabetes Management System (DMS) is a computer-based system which aid physicians in properly diagnosing diabetes mellitus disease in patients. The DMS is essential in making individuals who have diabetes aware of their state and type. Existing approaches employed have not been efficient in considering all the diabetes type as well as making full prescription to diabetes patients. In this paper, a framework for an improved Ontology-based Diabetes Management System with a Bayesian optimization technique is presented. This helped in managing the diagnosis of diabetes and the prescription of treatment and drug to patients using the ontology knowledge management. The framework was implemented using Java programming language on Netbeans IDE, Protégé 4.2 and mysql. An extract of the ontology graph and acyclic probability graph was shown. The result showed that the nature of Bayesian network which has to do with statistical calculations based on equations, functions and sample frequencies led to more precise and reliable outcome.   &nbsp

Ontology-based context management for mobile devices

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Scalable software framework for real-time data processing in the railway environment

Background: Ticks are obligate haematophagous ectoparasites of vertebrates and frequently parasitize avian species that can carry them across continents during their long-distance migrations. Ticks may have detrimental effects on the health state of their avian hosts, which can be either directly caused by blood-draining or mediated by microbial pathogens transmitted during the blood meal. Indeed, ticks host complex microbial communities, including bacterial pathogens and symbionts. Midichloria bacteria (Rickettsiales) are widespread tick endosymbionts that can be transmitted to vertebrate hosts during the tick bite, inducing an antibody response. Their actual role as infectious/pathogenic agents is, however, unclear. Methods: We screened for Midichloria DNA African ticks and blood samples collected from trans-Saharan migratory songbirds at their arrival in Europe during spring migration. Results: Tick infestation rate was 5.7%, with most ticks belonging to the Hyalomma marginatum species complex. Over 90% of Hyalomma ticks harboured DNA of Midichloria bacteria belonging to the monophylum associated with ticks. Midichloria DNA was detected in 43% of blood samples of avian hosts. Tick-infested adult birds were significantly more likely to test positive to the presence of Midichloria DNA than non-infested adults and second-year individuals, suggesting a long-term persistence of these bacteria within avian hosts. Tick parasitism was associated with a significantly delayed timing of spring migration of avian hosts but had no significant effects on body condition, whereas blood Midichloria DNA presence negatively affected fat deposits of tick-infested avian hosts. Conclusions: Our results show that ticks effectively transfer Midichloria bacteria to avian hosts, supporting the hypothesis that they are infectious to vertebrates. Bird infection likely enhances the horizontal spread of these bacteria across haematophagous ectoparasite populations. Moreover, we showed that Midichloria and tick parasitism have detrimental non-independent effects on avian host health during migration, highlighting the complexity of interactions involving ticks, their vertebrate hosts, and tick-borne bacteria

A process model in platform independent and neutral formal representation for design engineering automation

An engineering design process as part of product development (PD) needs to satisfy ever-changing customer demands by striking a balance between time, cost and quality. In order to achieve a faster lead-time, improved quality and reduced PD costs for increased profits, automation methods have been developed with the help of virtual engineering. There are various methods of achieving Design Engineering Automation (DEA) with Computer-Aided (CAx) tools such as CAD/CAE/CAM, Product Lifecycle Management (PLM) and Knowledge Based Engineering (KBE). For example, Computer Aided Design (CAD) tools enable Geometry Automation (GA), PLM systems allow for sharing and exchange of product knowledge throughout the PD lifecycle. Traditional automation methods are specific to individual products and are hard-coded and bound by the proprietary tool format. Also, existing CAx tools and PLM systems offer bespoke islands of automation as compared to KBE. KBE as a design method incorporates complete design intent by including re-usable geometric, non-geometric product knowledge as well as engineering process knowledge for DEA including various processes such as mechanical design, analysis and manufacturing. It has been recognised, through an extensive literature review, that a research gap exists in the form of a generic and structured method of knowledge modelling, both informal and formal modelling, of mechanical design process with manufacturing knowledge (DFM/DFA) as part of model based systems engineering (MBSE) for DEA with a KBE approach. There is a lack of a structured technique for knowledge modelling, which can provide a standardised method to use platform independent and neutral formal standards for DEA with generative modelling for mechanical product design process and DFM with preserved semantics. The neutral formal representation through computer or machine understandable format provides open standard usage. This thesis provides a contribution to knowledge by addressing this gap in two-steps: • In the first step, a coherent process model, GPM-DEA is developed as part of MBSE which can be used for modelling of mechanical design with manufacturing knowledge utilising hybrid approach, based on strengths of existing modelling standards such as IDEF0, UML, SysML and addition of constructs as per author’s Metamodel. The structured process model is highly granular with complex interdependencies such as activities, object, function, rule association and includes the effect of the process model on the product at both component and geometric attributes. • In the second step, a method is provided to map the schema of the process model to equivalent platform independent and neutral formal standards using OWL/SWRL ontology for system development using Protégé tool, enabling machine interpretability with semantic clarity for DEA with generative modelling by building queries and reasoning on set of generic SWRL functions developed by the author. Model development has been performed with the aid of literature analysis and pilot use-cases. Experimental verification with test use-cases has confirmed the reasoning and querying capability on formal axioms in generating accurate results. Some of the other key strengths are that knowledgebase is generic, scalable and extensible, hence provides re-usability and wider design space exploration. The generative modelling capability allows the model to generate activities and objects based on functional requirements of the mechanical design process with DFM/DFA and rules based on logic. With the help of application programming interface, a platform specific DEA system such as a KBE tool or a CAD tool enabling GA and a web page incorporating engineering knowledge for decision support can consume relevant part of the knowledgebase

Knowledge modelling of emerging technologies for sustainable building development

In the quest for improved performance of buildings and mitigation of climate change, governments are encouraging the use of innovative sustainable building technologies. Consequently, there is now a large amount of information and knowledge on sustainable building technologies over the web. However, internet searches often overwhelm practitioners with millions of pages that they browse to identify suitable innovations to use on their projects. It has been widely acknowledged that the solution to this problem is the use of a machine-understandable language with rich semantics - the semantic web technology. This research investigates the extent to which semantic web technologies can be exploited to represent knowledge about sustainable building technologies, and to facilitate system decision-making in recommending appropriate choices for use in different situations. To achieve this aim, an exploratory study on sustainable building and semantic web technologies was conducted. This led to the use of two most popular knowledge engineering methodologies - the CommonKADS and "Ontology Development 101" in modelling knowledge about sustainable building technology and PV -system domains. A prototype system - Photo Voltaic Technology ONtology System (PV -TONS) - that employed sustainable building technology and PV -system domain knowledge models was developed and validated with a case study. While the sustainable building technology ontology and PV -TONS can both be used as generic knowledge models, PV -TONS is extended to include applications for the design and selection of PV -systems and components. Although its focus was on PV -systems, the application of semantic web technologies can be extended to cover other areas of sustainable building technologies. The major challenges encountered in this study are two-fold. First, many semantic web technologies are still under development and very unstable, thus hindering their full exploitation. Second, the lack of learning resources in this field steepen the learning curve and is a potential set-back in using semantic web technologies

Automatic Geospatial Data Conflation Using Semantic Web Technologies

Duplicate geospatial data collections and maintenance are an extensive problem across Australia government organisations. This research examines how Semantic Web technologies can be used to automate the geospatial data conflation process. The research presents a new approach where generation of OWL ontologies based on output data models and presenting geospatial data as RDF triples serve as the basis for the solution and SWRL rules serve as the core to automate the geospatial data conflation processes