Towards Accessible, Usable Knowledge Frameworks in Engineering

A substantial amount of research has been done in the field of engineering knowledge management, where countless ontologies have been developed for various applications within the engineering community. However, despite the success shown in these research efforts, the techniques have not been adopted by industry. This research aims to uncover the reasons for the slow adoption of engineering knowledge frameworks, namely ontologies, in industry. There are two projects covered in this thesis. The first project is the development of a cross-domain ontology for the Biomesh Project, which spans the fields of mechanical engineering, biology, and anthropology. The biology community is known for its embrace of ontologies and has made their use quite popular with the creation of the Gene Ontology. This ontology spawned the establishment of the Open Biological and Biomedical Ontologies (OBO) Foundry, a consortium which approves and curates ontologies in the biology field. No such consortium exists in the field of engineering. This project demonstrates the usefulness of curated reference ontologies. Ontological knowledge bases in four different domains were imported and integrated together to connect previously disparate information. A case study with data from the Biomesh Project demonstrates cross-domain queries and inferences that were not possible before the creation of this ontology. In the second part of this thesis we investigate the usability of current ontology tools. Protégé, the most popular ontology editing tool, is compared to OntoWiki, a semantic wiki. This comparison is done using proven techniques from the field of Human-computer interaction to uncover usability problems and point out areas where each system excels. A field of 16 subjects completed a set of tasks in each system and gave feedback based on their experience. It is shown that while OntoWiki offers users a satisfying interface, it lacks in some areas that can be easily improved. Protégé provides users with adequate functionality, but it is not intended for a novice user

A semantic memory bank assisted by an embodied conversational agents for mobile devices

Alzheimer’s disease is a type of dementia that causes memory loss and interferes with intellectual abilities seriously. It has no current cure and therapeutic efficiency of current medication is limited. However, there is evidence that non-pharmacological treatments could be useful to stimulate cognitive abilities. In the last few year, several studies have focused on describing and under- standing how Virtual Coaches (VC) could be key drivers for health promotion in home care settings. The use of VC gains an augmented attention in the considerations of medical innovations. In this paper, we propose an approach that exploits semantic technologies and Embodied Conversational Agents to help patients training cognitive abilities using mobile devices. In this work, semantic technologies are used to provide knowledge about the memory of a specific person, who exploits the structured data stored in a linked data repository and take advantage of the flexibility provided by ontologies to define search domains and expand the agent’s capabilities. Our Memory Bank Embodied Conversational Agent (MBECA) is used to interact with the patient and ease the interaction with new devices. The framework is oriented to Alzheimer’s patients, caregivers, and therapists

Agents for educational games and simulations

This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications

Design and Architecture of an Ontology-driven Dialogue System for HPV Vaccine Counseling

Speech and conversational technologies are increasingly being used by consumers, with the inevitability that one day they will be integrated in health care. Where this technology could be of service is in patient-provider communication, specifically for communicating the risks and benefits of vaccines. Human papillomavirus (HPV) vaccine, in particular, is a vaccine that inoculates individuals from certain HPV viruses responsible for adulthood cancers - cervical, head and neck cancers, etc. My research focuses on the architecture and development of speech-enabled conversational agent that relies on series of consumer-centric health ontologies and the technology that utilizes these ontologies. Ontologies are computable artifacts that encode and structure domain knowledge that can be utilized by machines to provide high level capabilities, such as reasoning and sharing information. I will focus the agent’s impact on the HPV vaccine domain to observe if users would respond favorably towards conversational agents and the possible impact of the agent on their beliefs of the HPV vaccine. The approach of this study involves a multi-tier structure. The first tier is the domain knowledge base, the second is the application interaction design tier, and the third is the feasibility assessment of the participants. The research in this study proposes the following questions: Can ontologies support the system architecture for a spoken conversational agent for HPV vaccine counseling? How would prospective users’ perception towards an agent and towards the HPV vaccine be impacted after using conversational agent for HPV vaccine education? The outcome of this study is a comprehensive assessment of a system architecture of a conversational agent for patient-centric HPV vaccine counseling. Each layer of the agent architecture is regulated through domain and application ontologies, and supported by the various ontology-driven software components that I developed to compose the agent architecture. Also discussed in this work, I present preliminary evidence of high usability of the agent and improvement of the users’ health beliefs toward the HPV vaccine. All in all, I introduce a comprehensive and feasible model for the design and development of an open-sourced, ontology-driven conversational agent for any health consumer domain, and corroborate the viability of a conversational agent as a health intervention tool

Ontology-based personalisation of e-learning resources for disabled students

Students with disabilities are often expected to use e-learning systems to access learning materials but most systems do not provide appropriate adaptation or personalisation to meet their needs.The difficulties related to inadaptability of current learning environments can now be resolved using semantic web technologies such as web ontologies which have been successfully used to drive e-learning personalisation. Nevertheless, e-learning personalisation for students with disabilities has mainly targeted those with single disabilities such as dyslexia or visual impairment, often neglecting those with multiple disabilities due to the difficulty of designing for a combination of disabilities.This thesis argues that it is possible to personalise learning materials for learners with disabilities, including those with multiple disabilities. This is achieved by developing a model that allows the learning environment to present the student with learning materials in suitable formats while considering their disability and learning needs through an ontology-driven and disability-aware personalised e-learning system model (ONTODAPS). A disability ontology known as the Abilities and Disabilities Ontology for Online LEarning and Services (ADOOLES) is developed and used to drive this model. To test the above hypothesis, some case studies are employed to show how the model functions for various individuals with and without disabilities and then the implemented visual interface is experimentally evaluated by eighteen students with disabilities and heuristically by ten lecturers. The results are collected and statistically analysed.The results obtained confirm the above hypothesis and suggest that ONTODAPS can be effectively employed to personalise learning and to manage learning resources. The student participants found that ONTODAPS could aid their learning experience and all agreed that they would like to use this functionality in an existing learning environment. The results also suggest that ONTODAPS provides a platform where students with disabilities can have equivalent learning experience with their peers without disabilities. For the results to be generalised, this study could be extended through further experiments with more diverse groups of students with disabilities and across multiple educational institutions

A framework for developing a conversational agent to improve normal age- associated memory loss and increase subjective wellbeing

Research has developed a baseline conversational agent (CA) framework that experiments suggest may improve normal ageing memory problems and increase Subjective Wellbeing (SWB) in participants aged 60+ with normal age-associated memory loss. In 2008, 1.3 million people in the United Kingdom were aged 85+, this figure is projected to reach 3.3 million by 2033 (Morse, 2010). Thus, as the population profile changes, ageing memory impairment problems will become acuter (Morse, 2010). The number of people worldwide with diagnosed clinical memory problems is expected to double every 20 years to 66 million by 2030 and 115 million by 2050 (Casey et al., 2016, Prince et al., 2013). Improving memory impairment reduces distress for individuals and enhances wellbeing and independence (Dorin, 2007); (Wagner et al., 2010). The quality of life in old age can be improved by increasing SWB (George, 2010) that is concerned with how people experience the quality of their lives and includes both emotional reactions and cognitive judgments (George, 2010). Experiments performed as part of the pilot study suggested evidence of increased SWB and improved memory after use of the CA. To support these early findings, modification to the agent and further experimentation was undertaken. Further work enhanced the preliminary work that was carried out and provided the opportunity to run further, more in-depth evaluations of the CA as both a reminiscence aid and as an improver of SWB. This PhD study applied for and gained ethical approval (SE111219) from the Faculty of Science & Engineering Ethics Committee, Manchester Metropolitan University on 25 October 2012

An ontology for formal representation of medication adherence-related knowledge : case study in breast cancer

Indiana University-Purdue University Indianapolis (IUPUI)Medication non-adherence is a major healthcare problem that negatively impacts the health and productivity of individuals and society as a whole. Reasons for medication non-adherence are multi-faced, with no clear-cut solution. Adherence to medication remains a difficult area to study, due to inconsistencies in representing medicationadherence behavior data that poses a challenge to humans and today’s computer technology related to interpreting and synthesizing such complex information. Developing a consistent conceptual framework to medication adherence is needed to facilitate domain understanding, sharing, and communicating, as well as enabling researchers to formally compare the findings of studies in systematic reviews. The goal of this research is to create a common language that bridges human and computer technology by developing a controlled structured vocabulary of medication adherence behavior—“Medication Adherence Behavior Ontology” (MAB-Ontology) using breast cancer as a case study to inform and evaluate the proposed ontology and demonstrating its application to real-world situation. The intention is for MAB-Ontology to be developed against the background of a philosophical analysis of terms, such as belief, and desire to be human, computer-understandable, and interoperable with other systems that support scientific research. The design process for MAB-Ontology carried out using the METHONTOLOGY method incorporated with the Basic Formal Ontology (BFO) principles of best practice. This approach introduces a novel knowledge acquisition step that guides capturing medication-adherence-related data from different knowledge sources, including adherence assessment, adherence determinants, adherence theories, adherence taxonomies, and tacit knowledge source types. These sources were analyzed using a systematic approach that involved some questions applied to all source types to guide data extraction and inform domain conceptualization. A set of intermediate representations involving tables and graphs was used to allow for domain evaluation before implementation. The resulting ontology included 629 classes, 529 individuals, 51 object property, and 2 data property. The intermediate representation was formalized into OWL using Protégé. The MAB-Ontology was evaluated through competency questions, use-case scenario, face validity and was found to satisfy the requirement specification. This study provides a unified method for developing a computerized-based adherence model that can be applied among various disease groups and different drug categories