A collective artefact design of decision support systems: design science research perspective

Purpose - The knowledge of artefact design in design science research can have an important application in the improvement of decision support systems (DSS) development research. Recent DSS literature has identified a significant need to develop user-centric DSS method for greater relevance with respect to context of use. To address this, this study develops a collective DSS design artefact as method in a practical industry context. Design/methodology/approach - Under the influence of goal-directed interaction design principles the study outlines the innovative DSS artefact based on design science methodology to deliver a cutting-edge decision support solution, which provides user-centric provisions through the use of design environment and ontology techniques. Findings - The DSS artefact as collective IT applications through the application of design science knowledge can effectively be designed to meet decision makers’ contextual needs in an agricultural industry context. Research limitations/implications - The study has limitations in that it was developed in a case study context and remains to be fully tested in a real business context. It is also assumed that the domain decisions can be parameterised and represented using a constraint programming language. Practical implications - We conclude that the DSS artefact design and this development successfully overcomes some of the limitations of traditional DSS such as low user uptake, system obsolescence, low returns on investment and a requirement for continual re-engineering effort. Originality/value - The design science paradigm provides structural guidance throughout the defined process, helping ensure fidelity both to best industry knowledge and to changing user contexts

Human-Intelligence and Machine-Intelligence Decision Governance Formal Ontology

Since the beginning of the human race, decision making and rational thinking played a pivotal role for mankind to either exist and succeed or fail and become extinct. Self-awareness, cognitive thinking, creativity, and emotional magnitude allowed us to advance civilization and to take further steps toward achieving previously unreachable goals. From the invention of wheels to rockets and telegraph to satellite, all technological ventures went through many upgrades and updates. Recently, increasing computer CPU power and memory capacity contributed to smarter and faster computing appliances that, in turn, have accelerated the integration into and use of artificial intelligence (AI) in organizational processes and everyday life. Artificial intelligence can now be found in a wide range of organizational systems including healthcare and medical diagnosis, automated stock trading, robotic production, telecommunications, space explorations, and homeland security. Self-driving cars and drones are just the latest extensions of AI. This thrust of AI into organizations and daily life rests on the AI community’s unstated assumption of its ability to completely replicate human learning and intelligence in AI. Unfortunately, even today the AI community is not close to completely coding and emulating human intelligence into machines. Despite the revolution of digital and technology in the applications level, there has been little to no research in addressing the question of decision making governance in human-intelligent and machine-intelligent (HI-MI) systems. There also exists no foundational, core reference, or domain ontologies for HI-MI decision governance systems. Further, in absence of an expert reference base or body of knowledge (BoK) integrated with an ontological framework, decision makers must rely on best practices or standards that differ from organization to organization and government to government, contributing to systems failure in complex mission critical situations. It is still debatable whether and when human or machine decision capacity should govern or when a joint human-intelligence and machine-intelligence (HI-MI) decision capacity is required in any given decision situation. To address this deficiency, this research establishes a formal, top level foundational ontology of HI-MI decision governance in parallel with a grounded theory based body of knowledge which forms the theoretical foundation of a systemic HI-MI decision governance framework

Adaptive intelligent personalised learning (AIPL) environment

As individuals the ideal learning scenario would be a learning environment tailored just for how we like to learn, personalised to our requirements. This has previously been almost inconceivable given the complexities of learning, the constraints within the environments in which we teach, and the need for global repositories of knowledge to facilitate this process. Whilst it is still not necessarily achievable in its full sense this research project represents a path towards this ideal.In this thesis, findings from research into the development of a model (the Adaptive Intelligent Personalised Learning (AIPL)), the creation of a prototype implementation of a system designed around this model (the AIPL environment) and the construction of a suite of intelligent algorithms (Personalised Adaptive Filtering System (PAFS)) for personalised learning are presented and evaluated. A mixed methods approach is used in the evaluation of the AIPL environment. The AIPL model is built on the premise of an ideal system being one which does not just consider the individual but also considers groupings of likeminded individuals and their power to influence learner choice. The results show that: (1) There is a positive correlation for using group-learning-paradigms. (2) Using personalisation as a learning aid can help to facilitate individual learning and encourage learning on-line. (3) Using learning styles as a way of identifying and categorising the individuals can improve their on-line learning experience. (4) Using Adaptive Information Retrieval techniques linked to group-learning-paradigms can reduce and improve the problem of mis-matching. A number of approaches for further work to extend and expand upon the work presented are highlighted at the end of the Thesis

Strategic Assessment of Organizational Commitment

The concept of organizational commitment has been widely studied over recent decades, yet it remains one of the most challenging concepts in organizational research. While commitment is understood to be highly valuable in today’s dynamic business environment, its multifaceted nature is not necessarily understood adequately. The purpose of this study was to examine the concept of organizational commitment and its measurement issues within organizations, and to develop a practical evaluation tool for management, which is based on previous scientific research. First, a theoretical framework discussing organizational commitment and engagement was established. Based on the literature research, three ontologies were developed addressing organizational commitment and engagement, as well as academic engagement. The ontologies were constructed as a synthesis of existing theories. With the help of the ontologies and the created evaluation system, it is possible to better understand these concepts, gain a collective view of the organization’s current state and vision for the future, and to open a dialogue between members of the organization regarding their development. The results of the empirical case studies are presented at the end of this thesis, as well as in the attached research papers. The empirical results indicate that, by using these applications, it is possible to gain insights about the respondents’ feelings and aspirations, which can be used to support effective decision-making and as the basis for creating development actions within the organization.Organisaatiositoutumisen käsitettä on tutkittu laajasti kuluneiden vuosikymmenten aikana, kuitenkin se on edelleen yksi organisaatiotutkimuksen haastavimmista käsitteistä. Sitoutuminen on laajalti ymmärretty erittäin tärkeäksi tämän päivän liiketoimintaympäristössä mutta sen moniulotteista luonnetta ei yrityksissä ole välttämättä ymmärretty riittävästi. Tämän tutkimuksen tavoitteena oli tarkastella organisatorisen sitoutumisen käsitettä ja sen mittaamisen ongelmallisuutta sekä kehittää aikaisempaan tieteelliseen tutkimukseen perustuva käytännön sovellus sitoutumisen tason määrittämiseksi. Tutkimuksen ensimmäisessä osassa laadittiin organisaatioon sitoutumista käsittelevä teoreettinen viitekehys, jonka perusteella kehitettiin kolme ontologiaa. Ontologiat käsittelevät organisaation sitoutumista eri näkökulmista sekä opiskelijoiden akateemista sitoutumista. Ontologioiden sekä laaditun arviointijärjestelmän avulla on mahdollista ymmärtää sitoutumiseen liittyviä käsitteitä, saada yhteinen näkemys organisaation nykytilasta ja tulevaisuuden näkemyksestä sekä löytää mahdollisia kehityskohteita. Empiiristen case-tutkimusten tuloksia on esitetty tämän työn loppuosassa sekä liitteenä olevissa tutkimusartikkeleissa. Tulokset osoittavat, että laadittujen sovellusten avulla on mahdollista saada tietoa vastaajien tuntemuksista ja pyrkimyksistä. Tätä tietoa voidaan hyödyntää päätöksenteon tukena sekä perustana kehitystoimien luomiselle.fi=vertaisarvioitu|en=peerReviewed

Models for Learning (Mod4L) Final Report: Representing Learning Designs

The Mod4L Models of Practice project is part of the JISC-funded Design for Learning Programme. It ran from 1 May – 31 December 2006. The philosophy underlying the project was that a general split is evident in the e-learning community between development of e-learning tools, services and standards, and research into how teachers can use these most effectively, and is impeding uptake of new tools and methods by teachers. To help overcome this barrier and bridge the gap, a need is felt for practitioner-focused resources which describe a range of learning designs and offer guidance on how these may be chosen and applied, how they can support effective practice in design for learning, and how they can support the development of effective tools, standards and systems with a learning design capability (see, for example, Griffiths and Blat 2005, JISC 2006). Practice models, it was suggested, were such a resource. The aim of the project was to: develop a range of practice models that could be used by practitioners in real life contexts and have a high impact on improving teaching and learning practice. We worked with two definitions of practice models. Practice models are: 1. generic approaches to the structuring and orchestration of learning activities. They express elements of pedagogic principle and allow practitioners to make informed choices (JISC 2006) However, however effective a learning design may be, it can only be shared with others through a representation. The issue of representation of learning designs is, then, central to the concept of sharing and reuse at the heart of JISC’s Design for Learning programme. Thus practice models should be both representations of effective practice, and effective representations of practice. Hence we arrived at the project working definition of practice models as: 2. Common, but decontextualised, learning designs that are represented in a way that is usable by practitioners (teachers, managers, etc).(Mod4L working definition, Falconer & Littlejohn 2006). A learning design is defined as the outcome of the process of designing, planning and orchestrating learning activities as part of a learning session or programme (JISC 2006). Practice models have many potential uses: they describe a range of learning designs that are found to be effective, and offer guidance on their use; they support sharing, reuse and adaptation of learning designs by teachers, and also the development of tools, standards and systems for planning, editing and running the designs. The project took a practitioner-centred approach, working in close collaboration with a focus group of 12 teachers recruited across a range of disciplines and from both FE and HE. Focus group members are listed in Appendix 1. Information was gathered from the focus group through two face to face workshops, and through their contributions to discussions on the project wiki. This was supplemented by an activity at a JISC pedagogy experts meeting in October 2006, and a part workshop at ALT-C in September 2006. The project interim report of August 2006 contained the outcomes of the first workshop (Falconer and Littlejohn, 2006). The current report refines the discussion of issues of representing learning designs for sharing and reuse evidenced in the interim report and highlights problems with the concept of practice models (section 2), characterises the requirements teachers have of effective representations (section 3), evaluates a number of types of representation against these requirements (section 4), explores the more technically focused role of sequencing representations and controlled vocabularies (sections 5 & 6), documents some generic learning designs (section 8.2) and suggests ways forward for bridging the gap between teachers and developers (section 2.6). All quotations are taken from the Mod4L wiki unless otherwise stated

Advanced Knowledge Technologies at the Midterm: Tools and Methods for the Semantic Web

The University of Edinburgh and research sponsors are authorised to reproduce and distribute reprints and on-line copies for their purposes notwithstanding any copyright annotation hereon. The views and conclusions contained herein are the author’s and shouldn’t be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of other parties.In a celebrated essay on the new electronic media, Marshall McLuhan wrote in 1962:Our private senses are not closed systems but are endlessly translated into each other in that experience which we call consciousness. Our extended senses, tools, technologies, through the ages, have been closed systems incapable of interplay or collective awareness. Now, in the electric age, the very instantaneous nature of co-existence among our technological instruments has created a crisis quite new in human history. Our extended faculties and senses now constitute a single field of experience which demands that they become collectively conscious. Our technologies, like our private senses, now demand an interplay and ratio that makes rational co-existence possible. As long as our technologies were as slow as the wheel or the alphabet or money, the fact that they were separate, closed systems was socially and psychically supportable. This is not true now when sight and sound and movement are simultaneous and global in extent. (McLuhan 1962, p.5, emphasis in original)Over forty years later, the seamless interplay that McLuhan demanded between our technologies is still barely visible. McLuhan’s predictions of the spread, and increased importance, of electronic media have of course been borne out, and the worlds of business, science and knowledge storage and transfer have been revolutionised. Yet the integration of electronic systems as open systems remains in its infancy.Advanced Knowledge Technologies (AKT) aims to address this problem, to create a view of knowledge and its management across its lifecycle, to research and create the services and technologies that such unification will require. Half way through its sixyear span, the results are beginning to come through, and this paper will explore some of the services, technologies and methodologies that have been developed. We hope to give a sense in this paper of the potential for the next three years, to discuss the insights and lessons learnt in the first phase of the project, to articulate the challenges and issues that remain.The WWW provided the original context that made the AKT approach to knowledge management (KM) possible. AKT was initially proposed in 1999, it brought together an interdisciplinary consortium with the technological breadth and complementarity to create the conditions for a unified approach to knowledge across its lifecycle. The combination of this expertise, and the time and space afforded the consortium by the IRC structure, suggested the opportunity for a concerted effort to develop an approach to advanced knowledge technologies, based on the WWW as a basic infrastructure.The technological context of AKT altered for the better in the short period between the development of the proposal and the beginning of the project itself with the development of the semantic web (SW), which foresaw much more intelligent manipulation and querying of knowledge. The opportunities that the SW provided for e.g., more intelligent retrieval, put AKT in the centre of information technology innovation and knowledge management services; the AKT skill set would clearly be central for the exploitation of those opportunities.The SW, as an extension of the WWW, provides an interesting set of constraints to the knowledge management services AKT tries to provide. As a medium for the semantically-informed coordination of information, it has suggested a number of ways in which the objectives of AKT can be achieved, most obviously through the provision of knowledge management services delivered over the web as opposed to the creation and provision of technologies to manage knowledge.AKT is working on the assumption that many web services will be developed and provided for users. The KM problem in the near future will be one of deciding which services are needed and of coordinating them. Many of these services will be largely or entirely legacies of the WWW, and so the capabilities of the services will vary. As well as providing useful KM services in their own right, AKT will be aiming to exploit this opportunity, by reasoning over services, brokering between them, and providing essential meta-services for SW knowledge service management.Ontologies will be a crucial tool for the SW. The AKT consortium brings a lot of expertise on ontologies together, and ontologies were always going to be a key part of the strategy. All kinds of knowledge sharing and transfer activities will be mediated by ontologies, and ontology management will be an important enabling task. Different applications will need to cope with inconsistent ontologies, or with the problems that will follow the automatic creation of ontologies (e.g. merging of pre-existing ontologies to create a third). Ontology mapping, and the elimination of conflicts of reference, will be important tasks. All of these issues are discussed along with our proposed technologies.Similarly, specifications of tasks will be used for the deployment of knowledge services over the SW, but in general it cannot be expected that in the medium term there will be standards for task (or service) specifications. The brokering metaservices that are envisaged will have to deal with this heterogeneity.The emerging picture of the SW is one of great opportunity but it will not be a wellordered, certain or consistent environment. It will comprise many repositories of legacy data, outdated and inconsistent stores, and requirements for common understandings across divergent formalisms. There is clearly a role for standards to play to bring much of this context together; AKT is playing a significant role in these efforts. But standards take time to emerge, they take political power to enforce, and they have been known to stifle innovation (in the short term). AKT is keen to understand the balance between principled inference and statistical processing of web content. Logical inference on the Web is tough. Complex queries using traditional AI inference methods bring most distributed computer systems to their knees. Do we set up semantically well-behaved areas of the Web? Is any part of the Web in which semantic hygiene prevails interesting enough to reason in? These and many other questions need to be addressed if we are to provide effective knowledge technologies for our content on the web

Ontology for Psychophysiological Dysregulation of Anger/Aggression

The advancement of Information Technology in the last four decades led to the use of computers in medicine. A new area called Medical Informatics has emerged. This area comprises the application of IT to healthcare with the aim of creating tools that help healthcare personnel diagnose and treat patients more accurately and efficiently. IT not only provides tools for storing, integrating, and updating patient information base but also for processing information efficiently. One of such tools is a Clinical Decision Support System. Ontologies are an integral part of clinical decision support systems because they help formalize and integrate domain knowledge. In this project, we developed a software program that assists clinicians in making diagnostic decisions about a particular problem type called ‘psychophysiological dysregulation of anger/aggression’. We created a new ontology for the problem domain. The computer program asks a set of pertinent questions and the patient or clinician on behalf of the patient is required to answer it. All these answers along with the results from various lab assessment tests are fed into the software program which then outputs a diagnosis by interacting with the ontology and also proposes the preferred treatment plan. While undergoing the treatment the patient is monitored at regular intervals by the clinician and this data is recorded as the treatment episode data. The tools and technologies used for this project are Web Ontology Language (OWL) version 2, Protégé 4.1.0 Beta, Java, Eclipse Helios IDE and IBM DB2. Adviser: Jitender S. Deogu

Ontology for Psychophysiological Dysregulation of Anger/Aggression

The advancement of Information Technology in the last four decades led to the use of computers in medicine. A new area called Medical Informatics has emerged. This area comprises the application of IT to healthcare with the aim of creating tools that help healthcare personnel diagnose and treat patients more accurately and efficiently. IT not only provides tools for storing, integrating, and updating patient information base but also for processing information efficiently. One of such tools is a Clinical Decision Support System. Ontologies are an integral part of clinical decision support systems because they help formalize and integrate domain knowledge. In this project, we developed a software program that assists clinicians in making diagnostic decisions about a particular problem type called ‘psychophysiological dysregulation of anger/aggression’. We created a new ontology for the problem domain. The computer program asks a set of pertinent questions and the patient or clinician on behalf of the patient is required to answer it. All these answers along with the results from various lab assessment tests are fed into the software program which then outputs a diagnosis by interacting with the ontology and also proposes the preferred treatment plan. While undergoing the treatment the patient is monitored at regular intervals by the clinician and this data is recorded as the treatment episode data. The tools and technologies used for this project are Web Ontology Language (OWL) version 2, Protégé 4.1.0 Beta, Java, Eclipse Helios IDE and IBM DB2. Adviser: Jitender S. Deogu

Improving Knowledge Acquisition in Collaborative Knowledge Construction Tool with Virtual Catalyst

Noctua is a web tool to assist in Knowledge Acquisition and Collaborative Knowledge Construction processes. Noctua has an innovation: a Virtual Catalyst designed to facilitate the task of eliciting and validating knowledge. The Virtual Catalyst queries participants, proposing new knowledge, seeking confirmation to the knowledge already elicited, and showing conflicting opinions. The Virtual Catalyst takes into account participants' profiles in order to automatically ask them questions related to each one's field of knowledge or interest. This paper presents Noctua and its Virtual Catalyst. The tool was submitted to experimentation and the analysis of the results showed that the primary goal of increasing the rate of knowledge construction was achieved (up to 144 % in the rate of knowledge creation), and also showed some unexpected beneficial outcomes