Ontology Winnowing: A Case Study on the AKT Reference Ontology

Many ontologies are built for the main purpose of representing a domain, rather than to meet the requirements of a specific application. When applications and services are deployed over an ontology, it is sometimes the case that only few parts of the ontology are queried and used. Identifying which parts of an ontology are being used could useful for realising the necessary fragments of the ontology to run the applications. Such information could be used to winnow an ontology, i.e., simplifying or shrinking the ontology to smaller, more fit for purpose sizes. This paper presents a study on the use of the AKT Reference Ontology by a number of applications and services, and investigate the possibility of using this information to winnow that ontology

Analysis of the usability of a preliminary design for an EDM metadata mapping tool

Europeana aims to bring together metadata for cultural heritage objects from institutions throughout Europe, to increase their visibility and accessibility. This project requires that metadata created and stored in a multitude of different formats and variations to be normalized into a single, standard format, which is soon to be EDM. This constitutes a massive effort on the part of institutions and aggregators, and any system that can ease the process of converting millions of metadata records could be very beneficial to these cultural institutions. This research explores the usability of a potential design for a metadata mapping tool intended to assist in the creation of a mapping specification from a local schema to Europeana’s EDM format. The design incorporates five components necessary to consider when creating a quality mapping of elements. In order to ascertain usability, a prototype system was created, and a cognitive walkthrough was conducted to identify usability issues. While the design could be a viable option, usability issues must first be addressed, including how metadata information is presented and how the tool handles complex mapping situations.Joint Master Degree in Digital Library Learning (DILL

Modeling ontology views: An abstract view model for semantic web

The emergence of Semantic Web (SW) and the related technologies promise to make the web a meaningful experience. However, high level modelling, design and querying techniques proves to be a challenging task for organizations that are hoping to utilize the SW paradigm for their industrial applications. To address one such issue, in this paper, we propose an abstract view model with conceptual extensions for the SW. First we outline the view model, its properties and some modelling issues with the help of an industrial case study example. Then, we provide some discussions on constructing such views (at the conceptual level) using a set of operators. Later we provide a brief discussion on how such this view model can utilized in the MOVE [1] system, to design and construct materialized Ontology views to support Ontology extraction

Semantic Modelling of e-Solutions Using a View Formalism with Conceptual and Logical Extensions

In industrial informatics, there exists a requirement to model and design views at a higher level of abstraction. Since the classical view definitions are only available at the query or instance level, modelling and maintaining such views for complex enterprise information systems (EIS) is a challenging task. Further, the introduction of semi-structured data (namely XML) and its rapid adaptation by the commercial and industrial systems increased the complexity for view design and specification. To address such and issue, in this paper we present; (a) a layered view model for XML, (b) a design methodology for such views and (c) some real-world industrial applications of the view model. The XML view formalism is defined at the conceptual level and the design methodology is based on the XML semantic (XSemantic) nets, a high-level object-oriented (OO) modelling language for XML domains

Structuring visual exploratory analysis of skill demand

The analysis of increasingly large and diverse data for meaningful interpretation and question answering is handicapped by human cognitive limitations. Consequently, semi-automatic abstraction of complex data within structured information spaces becomes increasingly important, if its knowledge content is to support intuitive, exploratory discovery. Exploration of skill demand is an area where regularly updated, multi-dimensional data may be exploited to assess capability within the workforce to manage the demands of the modern, technology- and data-driven economy. The knowledge derived may be employed by skilled practitioners in defining career pathways, to identify where, when and how to update their skillsets in line with advancing technology and changing work demands. This same knowledge may also be used to identify the combination of skills essential in recruiting for new roles. To address the challenges inherent in exploring the complex, heterogeneous, dynamic data that feeds into such applications, we investigate the use of an ontology to guide structuring of the information space, to allow individuals and institutions to interactively explore and interpret the dynamic skill demand landscape for their specific needs. As a test case we consider the relatively new and highly dynamic field of Data Science, where insightful, exploratory data analysis and knowledge discovery are critical. We employ context-driven and task-centred scenarios to explore our research questions and guide iterative design, development and formative evaluation of our ontology-driven, visual exploratory discovery and analysis approach, to measure where it adds value to users’ analytical activity. Our findings reinforce the potential in our approach, and point us to future paths to build on

A requirement-driven approach for modelling software architectures

Throughout the software development lifecycle (SDLC) there are many pitfalls which software engineers have to face. Regardless of the methodology adopted, classic methodologies such as waterfall or more modern ones such as agile or scrum, defects can be injected in any phase of the SDLC. The main avenue to detect and remove defects is through Quality Assurance (QA) activities. The planned activities to detect, fix and remove defects occur later on and there is less effort spent in the initial phases of the SDLC to either detect, remove or prevent the injection of defects. In fact, the cost of detecting and fixing a defect in the later phases of the SDLC such as development, deployment, maintenance and support is much higher than detecting and fixing defects in the initial phases of the SDLC. The software architecture of the application also has an incidence on defect injection whereby the software architecture can be regarded asthe fundamental structures of a software system. The impact of detecting and fixing defects later on is exacerbated for software architecture which are distributed, such as service-oriented architectures or microservices. Thus, the aim of this research is to develop a semi-automated framework to translate requirements into design with the aim of reducing the introduction of defects from the early phases of the SDLC. Part of the objectives of this work is to conceptualize a design for architectural paradigms such as object-oriented and service-oriented programming. The proposed framework uses a series of techniques from Natural Language Processing (NLP) and a blend of techniques from intelligent learning systems such as ontologies and neural networks to partially automate the translation of requirements into a design. The novelty focuses on moulding the design into an architecture which is better adapted for distributed systems. The framework is evaluated with a case study where the design and architecture from the framework is compared to a design and architecture which was drawn by a software architect. In addition, the evaluation using a case study aims to demonstrate the use of the framework and how each individual design and architecture artefacts fair

Automated Test Case Generation from Domain-Specific High-Level Requirement Models

One of the most researched aspects of the software engineering process is the verification and validation of software systems using various techniques. The need to ensure that the developed software system addresses its intended specifications has led to several approaches that link the requirements gathering and software testing phases of development. This thesis presents a framework that bridges the gap between requirement specification and testing of software using domain-specific modelling concepts. The proposed modelling notation, High-Level Requirement Modelling Language (HRML), addresses the drawbacks of Natural Language (NL) for high-level requirement specifications including ambiguity and incompleteness. Real-time checks are implemented to ensure valid HRML specification models are utilised for the automated test cases generation. The type of HRML requirement specified in the model determines the approach to be employed to generate corresponding test cases. Boundary Value Analysis and Equivalence Partitioning is applied to specifications with predefined range values to generate valid and invalid inputs for robustness test cases. Structural coverage test cases are also generated to satisfy the Modified Condition/Decision Coverage (MC/DC) criteria for HRML specifications with logic expressions. In scenarios where the conditional statements are combined with logic expressions, the MC/DC approach is extended to generate the corresponding tests cases. Evaluation of the proposed framework by industry experts in a case study, its scalability, comparative study and the assessment of its learnability by non-experts are reported. The results indicate a reduction in the test case generation process in the case study, however non-experts spent more time in modelling the requirement in HRML while the time taken for test case generation is also reduced

A Process Modelling Framework Based on Point Interval Temporal Logic with an Application to Modelling Patient Flows

This thesis considers an application of a temporal theory to describe and model the patient journey in the hospital accident and emergency (A&E) department. The aim is to introduce a generic but dynamic method applied to any setting, including healthcare. Constructing a consistent process model can be instrumental in streamlining healthcare issues. Current process modelling techniques used in healthcare such as flowcharts, unified modelling language activity diagram (UML AD), and business process modelling notation (BPMN) are intuitive and imprecise. They cannot fully capture the complexities of the types of activities and the full extent of temporal constraints to an extent where one could reason about the flows. Formal approaches such as Petri have also been reviewed to investigate their applicability to the healthcare domain to model processes. Additionally, to schedule patient flows, current modelling standards do not offer any formal mechanism, so healthcare relies on critical path method (CPM) and program evaluation review technique (PERT), that also have limitations, i.e. finish-start barrier. It is imperative to specify the temporal constraints between the start and/or end of a process, e.g., the beginning of a process A precedes the start (or end) of a process B. However, these approaches failed to provide us with a mechanism for handling these temporal situations. If provided, a formal representation can assist in effective knowledge representation and quality enhancement concerning a process. Also, it would help in uncovering complexities of a system and assist in modelling it in a consistent way which is not possible with the existing modelling techniques. The above issues are addressed in this thesis by proposing a framework that would provide a knowledge base to model patient flows for accurate representation based on point interval temporal logic (PITL) that treats point and interval as primitives. These objects would constitute the knowledge base for the formal description of a system. With the aid of the inference mechanism of the temporal theory presented here, exhaustive temporal constraints derived from the proposed axiomatic system’ components serves as a knowledge base. The proposed methodological framework would adopt a model-theoretic approach in which a theory is developed and considered as a model while the corresponding instance is considered as its application. Using this approach would assist in identifying core components of the system and their precise operation representing a real-life domain deemed suitable to the process modelling issues specified in this thesis. Thus, I have evaluated the modelling standards for their most-used terminologies and constructs to identify their key components. It will also assist in the generalisation of the critical terms (of process modelling standards) based on their ontology. A set of generalised terms proposed would serve as an enumeration of the theory and subsume the core modelling elements of the process modelling standards. The catalogue presents a knowledge base for the business and healthcare domains, and its components are formally defined (semantics). Furthermore, a resolution theorem-proof is used to show the structural features of the theory (model) to establish it is sound and complete. After establishing that the theory is sound and complete, the next step is to provide the instantiation of the theory. This is achieved by mapping the core components of the theory to their corresponding instances. Additionally, a formal graphical tool termed as point graph (PG) is used to visualise the cases of the proposed axiomatic system. PG facilitates in modelling, and scheduling patient flows and enables analysing existing models for possible inaccuracies and inconsistencies supported by a reasoning mechanism based on PITL. Following that, a transformation is developed to map the core modelling components of the standards into the extended PG (PG*) based on the semantics presented by the axiomatic system. A real-life case (from the King’s College hospital accident and emergency (A&E) department’s trauma patient pathway) is considered to validate the framework. It is divided into three patient flows to depict the journey of a patient with significant trauma, arriving at A&E, undergoing a procedure and subsequently discharged. Their staff relied upon the UML-AD and BPMN to model the patient flows. An evaluation of their representation is presented to show the shortfalls of the modelling standards to model patient flows. The last step is to model these patient flows using the developed approach, which is supported by enhanced reasoning and scheduling