Multi-perspective modelling for knowledge management and knowledge engineering

ii It seems almost self-evident that “knowledge management ” and “knowledge engineering” should be related disciplines that may share techniques and methods between them. However, attempts by knowledge engineers to apply their techniques to knowledge management have been praised by some and derided by others, who claim that knowledge engineers have a fundamentally wrong concept of what “knowledge management” is. The critics also point to specific weaknesses of knowledge engineering, notably the lack of a broad context for the knowledge. Knowledge engineering has suffered some criticism from within its own ranks, too, particularly of the “rapid prototyping ” approach, in which acquired knowledge was encoded directly into an iteratively developed computer system. This approach was indeed rapid, but when used to deliver a final system, it became nearly impossible to verify and validate the system or to maintain it. A solution to this has come in the form of knowledge engineering methodology, and particularly in the CommonKAD

An integration framework for managing rich organisational process knowledge

The problem we have addressed in this dissertation is that of designing a pragmatic framework for integrating the synthesis and management of organisational process knowledge which is based on domain-independent AI planning and plan representations. Our solution has focused on a set of framework components which provide methods, tools and representations to accomplish this task.In the framework we address a lifecycle of this knowledge which begins with a methodological approach to acquiring information about the process domain. We show that this initial domain specification can be translated into a common constraint-based model of activity (based on the work of Tate, 1996c and 1996d) which can then be operationalised for use in an AI planner. This model of activity is ontologically underpinned and may be expressed with a flexible and extensible language based on a sorted first-order logic. The model combines perspectives covering both the space of behaviour as well as the space of decisions. Synthesised or modified processes/plans can be translated to and from the common representation in order to support knowledge sharing, visualisation and mixed-initiative interaction.This work united past and present Edinburgh research on planning and infused it with perspectives from design rationale, requirements engineering, and process knowledge sharing. The implementation has been applied to a portfolio of scenarios which include process examples from business, manufacturing, construction and military operations. An archive of this work is available at: http://www.aiai.ed.ac.uk/~oplan/cpf

AN EXPLORATORY CONSTRUCTIVIST GROUNDED THEORY STUDY: HOW SECONDARY SCHOOL SCIENCE TEACHERS INTERPRET STUDENTS’ SCIENTIFIC MODELS THAT ARE COMPRISED OF DRAWING ACTIVITIES

Extant literature lacks an explanation of the thought processes used by secondary school science teachers to interpret students’ scientific models that are comprised of drawing activities. In this exploratory study, a constructivist grounded theory (CGT) was developed to generate an interpretive understanding. The CGT was generated from observations, interviews, and document analyses of five research participants consisting of secondary school science teachers from lower New York State. To generate a CGT, concepts, terms, assumptions, and definitions from selected theories—decolonizing methodologies theory (DMT), visual semiotic theory (VST), and cultural studies theory (CST)—collectively provided a fresh onto-epistemological lens for initially examining and bringing transparency to the invisible influences on the intangible thought processes of science teachers when they interpret students’ scientific models. At the end of the study, a CGT was developed which is expressed as nine assertions, a diagrammatic display/axial coding paradigm, and an explanation consisting of found poetry developed from the research findings. Using reflective and reflexive analytical memos, this study revealed that the thoughts of secondary school science teachers consist of five themes: (1) direction or rules, (2) forms of communication, (3) creations (4) interpretation or understanding, and (5) problem-solving heuristics during students’ struggle. In addition, the theory illustrated that in the context of lower New York State, science disciplinary culture works by crossing borders (Aikenhead & Elliott, 2010; Carter, 2011; New York State Education Department, 2019a; Rasheed, 2001, 2006; Snively & Corsiglia, 2001) between Western cultural thoughts and non-Western/Indigenous cultural thoughts. This study will benefit both stakeholders and scholars. For stakeholders, this study offers a substantive theory for understanding the assessment practices of science teachers. For scholars, this study provides a CGT that integrates theories/subdisciplines that are epistemologically distant/close and generates ongoing research. In particular, the theory provides scholars with findings that can be used to subsequently conduct a quantitative study, whereby a culturally sensitive survey instrument can be generated and validated

Methodological guidelines for reusing general ontologies

Currently, there is a great deal of well-founded explicit knowledge formalizing general notions, such as time concepts and the part_of relation. Yet, it is often the case that instead of reusing ontologies that implement such notions (the so-called general ontologies), engineers create procedural programs that implicitly implement this knowledge. They do not save time and code by reusing explicit knowledge, and devote effort to solve problems that other people have already adequately solved. Consequently, we have developed a methodology that helps engineers to: (a) identify the type of general ontology to be reused; (b) find out which axioms and definitions should be reused; (c) make a decision, using formal concept analysis, on what general ontology is going to be reused; and (d) adapt and integrate the selected general ontology in the domain ontology to be developed. To illustrate our approach we have employed use-cases. For each use case, we provide a set of heuristics with examples. Each of these heuristics has been tested in either OWL or Prolog. Our methodology has been applied to develop a pharmaceutical product ontology. Additionally, we have carried out a controlled experiment with graduated students doing a MCs in Artificial Intelligence. This experiment has yielded some interesting findings concerning what kind of features the future extensions of the methodology should have

Semantic Similarity of Spatial Scenes

The formalization of similarity in spatial information systems can unleash their functionality and contribute technology not only useful, but also desirable by broad groups of users. As a paradigm for information retrieval, similarity supersedes tedious querying techniques and unveils novel ways for user-system interaction by naturally supporting modalities such as speech and sketching. As a tool within the scope of a broader objective, it can facilitate such diverse tasks as data integration, landmark determination, and prediction making. This potential motivated the development of several similarity models within the geospatial and computer science communities. Despite the merit of these studies, their cognitive plausibility can be limited due to neglect of well-established psychological principles about properties and behaviors of similarity. Moreover, such approaches are typically guided by experience, intuition, and observation, thereby often relying on more narrow perspectives or restrictive assumptions that produce inflexible and incompatible measures. This thesis consolidates such fragmentary efforts and integrates them along with novel formalisms into a scalable, comprehensive, and cognitively-sensitive framework for similarity queries in spatial information systems. Three conceptually different similarity queries at the levels of attributes, objects, and scenes are distinguished. An analysis of the relationship between similarity and change provides a unifying basis for the approach and a theoretical foundation for measures satisfying important similarity properties such as asymmetry and context dependence. The classification of attributes into categories with common structural and cognitive characteristics drives the implementation of a small core of generic functions, able to perform any type of attribute value assessment. Appropriate techniques combine such atomic assessments to compute similarities at the object level and to handle more complex inquiries with multiple constraints. These techniques, along with a solid graph-theoretical methodology adapted to the particularities of the geospatial domain, provide the foundation for reasoning about scene similarity queries. Provisions are made so that all methods comply with major psychological findings about people’s perceptions of similarity. An experimental evaluation supplies the main result of this thesis, which separates psychological findings with a major impact on the results from those that can be safely incorporated into the framework through computationally simpler alternatives

Reinterpreting the Kuhnian paradigm in information systems

The goal of this paper is to raise the level of discourse surrounding paradigms by drawing out a number of observations on how paradigms are interpreted in the IS field, and to reclaim the transformative potential of the Kuhnian paradigm concept in encouraging novel, interesting and relevant research and theorizing. After positioning the contribution of the Kuhnian paradigm and its significance in the philosophy of science, we describe the negative impacts of a research community’s preoccupation with the epistemological sense of paradigm, which ignited within the organizational sciences decades of unnecessary “paradigm wars” and a misplaced focus on methodology. We show how this epistemological rendering of paradigm, which is adopted by the IS field, differs from the opinions of well-known critics of Kuhn and how this view obscures the Kuhnian paradigm’s potential for innovative research. To provide valuable insights into these issues, we introduce Masterman’s interpretation of Kuhn’s model, which Kuhn himself endorses, and unpack the paradigm concept into its metaphysical, sociological and artefactual components. Using Masterman’s interpretation to highlight the primary meaning of Kuhn's paradigm concept as model problem-solution and exemplar, we describe how this multifaceted transformative view of paradigm benefits the IS field

ACLRO: An Ontology for the Best Practice in ACLR Rehabilitation

Indiana University-Purdue University Indianapolis (IUPUI)With the rise of big data and the demands for leveraging artificial intelligence (AI), healthcare requires more knowledge sharing that offers machine-readable semantic formalization. Even though some applications allow shared data interoperability, they still lack formal machine-readable semantics in ICD9/10 and LOINC. With ontology, the further ability to represent the shared conceptualizations is possible, similar to SNOMED-CT. Nevertheless, SNOMED-CT mainly focuses on electronic health record (EHR) documenting and evidence-based practice. Moreover, due to its independence on data quality, the ontology enhances advanced AI technologies, such as machine learning (ML), by providing a reusable knowledge framework. Developing a machine-readable and sharable semantic knowledge model incorporating external evidence and individual practice’s values will create a new revolution for best practice medicine. The purpose of this research is to implement a sharable ontology for the best practice in healthcare, with anterior cruciate ligament reconstruction (ACLR) as a case study. The ontology represents knowledge derived from both evidence-based practice (EBP) and practice-based evidence (PBE). First, the study presents how the domain-specific knowledge model is built using a combination of Toronto Virtual Enterprise (TOVE) and a bottom-up approach. Then, I propose a top-down approach using Open Biological and Biomedical Ontology (OBO) Foundry ontologies that adheres to the Basic Formal Ontology (BFO)’s framework. In this step, the EBP, PBE, and statistic ontologies are developed independently. Next, the study integrates these individual ontologies into the final ACLR Ontology (ACLRO) as a more meaningful model that endorses the reusability and the ease of the model-expansion process since the classes can grow independently from one another. Finally, the study employs a use case and DL queries for model validation. The study's innovation is to present the ontology implementation for best-practice medicine and demonstrate how it can be applied to a real-world setup with semantic information. The ACLRO simultaneously emphasizes knowledge representation in health-intervention, statistics, research design, and external research evidence, while constructing the classes of data-driven and patient-focus processes that allow knowledge sharing explicit of technology. Additionally, the model synthesizes multiple related ontologies, which leads to the successful application of best-practice medicine