ATOS-1: Designing the infrastructure for an advanced spacecraft operations system

The space industry has identified the need to use artificial intelligence and knowledge based system techniques as integrated, central, symbolic processing components of future mission design, support and operations systems. Various practical and commercial constraints require that off-the-shelf applications, and their knowledge bases, are reused where appropriate and that different mission contractors, potentially using different KBS technologies, can provide application and knowledge sub-modules of an overall integrated system. In order to achieve this integration, which we call knowledge sharing and distributed reasoning, there needs to be agreement on knowledge representations, knowledge interchange-formats, knowledge level communications protocols, and ontology. Research indicates that the latter is most important, providing the applications with a common conceptualization of the domain, in our case spacecraft operations, mission design, and planning. Agreement on ontology permits applications that employ different knowledge representations to interwork through mediators which we refer to as knowledge agents. This creates the illusion of a shared model without the constraints, both technical and commercial, that occur in centralized or uniform architectures. This paper explains how these matters are being addressed within the ATOS program at ESOC, using techniques which draw upon ideas and standards emerging from the DARPA Knowledge Sharing Effort. In particular, we explain how the project is developing an electronic Ontology of Spacecraft Operations and how this can be used as an enabling component within space support systems that employ advanced software engineering. We indicate our hope and expectation that the core ontology developed in ATOS, will permit the full development of standards for such systems throughout the space industry

A Boxology of Design Patterns for Hybrid Learning and Reasoning Systems

We propose a set of compositional design patterns to describe a large variety of systems that combine statistical techniques from machine learning with symbolic techniques from knowledge representation. As in other areas of computer science (knowledge engineering, software engineering, ontology engineering, process mining and others), such design patterns help to systematize the literature, clarify which combinations of techniques serve which purposes, and encourage re-use of software components. We have validated our set of compositional design patterns against a large body of recent literature.Comment: 12 pages,55 reference

The Semantic Grid: A future e-Science infrastructure

e-Science offers a promising vision of how computer and communication technology can support and enhance the scientific process. It does this by enabling scientists to generate, analyse, share and discuss their insights, experiments and results in an effective manner. The underlying computer infrastructure that provides these facilities is commonly referred to as the Grid. At this time, there are a number of grid applications being developed and there is a whole raft of computer technologies that provide fragments of the necessary functionality. However there is currently a major gap between these endeavours and the vision of e-Science in which there is a high degree of easy-to-use and seamless automation and in which there are flexible collaborations and computations on a global scale. To bridge this practice–aspiration divide, this paper presents a research agenda whose aim is to move from the current state of the art in e-Science infrastructure, to the future infrastructure that is needed to support the full richness of the e-Science vision. Here the future e-Science research infrastructure is termed the Semantic Grid (Semantic Grid to Grid is meant to connote a similar relationship to the one that exists between the Semantic Web and the Web). In particular, we present a conceptual architecture for the Semantic Grid. This architecture adopts a service-oriented perspective in which distinct stakeholders in the scientific process, represented as software agents, provide services to one another, under various service level agreements, in various forms of marketplace. We then focus predominantly on the issues concerned with the way that knowledge is acquired and used in such environments since we believe this is the key differentiator between current grid endeavours and those envisioned for the Semantic Grid

Deploying ontologies in software design

In this thesis we will be concerned with the relation between ontologies and software design. Ontologies are studied in the artificial intelligence community as a means to explicitly represent standardised domain knowledge in order to enable knowledge shar¬ ing and reuse. We deploy ontologies in software design with emphasis on a traditional software engineering theme: error detection. In particular, we identify a type of error that is often difficult to detect: conceptual errors. These are related to the description of the domain whom which the system will operate. They require subjective knowledge about correct forms of domain description to detect them. Ontologies provide these forms of domain description and we are interested in applying them and verify their correctness(chapter 1). After presenting an in depth analysis of the field of ontologies and software testing as conceived and implemented by the software engineering and artificial intelligence communities(chapter 2), we discuss an approach which enabled us to deploy ontologies in the early phases of software development (i.e., specifications) in order to detect conceptual errors (chapter 3). This is based on the provision of ontological axioms which are used to verify conformance of specification constructs to the underpinning ontology. To facilitate the integration of ontology with applications that adopt it we developed an architecture and built tools to implement this form of conceptual error check(chapter 4). We apply and evaluate the architecture in a variety of contexts to identify potential uses (chapter 5). An implication of this method for de¬ ploying ontologies to reason about the correctness of applications is to raise our trust in the given ontologies. However, when the ontologies themselves are erroneous we might fail to reveal pernicious discrepancies. To cope with this problem we extended the architecture to a multi-layer form(chapter 4) which gives us the ability to check the ontologies themselves for correctness. We apply this multi-layer architecture to cap¬ ture errors found in a complex ontologies lattice(chapter 6). We further elaborate on the weaknesses in ontology evaluation methods and employ a technique stemming from software engineering, that of experience management, to facilitate ontology testing and deployment(chapter 7). The work presented in this thesis aims to improve practice in ontology use and identify areas to which ontologies could be of benefits other than the advocated ones of knowledge sharing and reuse(chapter 8)

Ontology-Based Modeling for Newborn Behavior Simulation during Cardiopulmonary Resuscitation

This chapter concerns the formulation of a methodology and its implementation to elaborate a training simulator for medical staff who may be confronted with the critical situations of newborn resuscitation. The simulator reproduces the different cardiopulmonary pathological behaviors of newborns, the working environment of resuscitation rooms, and the monitoring and control environment of the learners by a teacher. Conceptual models of newborn behaviors combined with the cardiopulmonary resuscitation gestures have been developed. The methodological process is jointly using cognitive approaches with formal modeling and simulation. Cognitive approaches are mobilized to elaborate application ontologies to be the bases for the development of the conceptual models and the specification of the simulator. Ontologies have been developed on the bases of a corpus of academic documents, return on experience documents, and practitioner interviews, by means of the knowledge-oriented design (KOD) method. A discrete event formalism has been used to formalize the conceptual models of the newborn behaviors. As a result, a simulator has been built to train medical practitioners to face situations, which are reported to potentially cause errors, and thus improve the safety of the resuscitation gestures

Modélisation basée sur une ontologie pour la simulation de comportements de nouveaux-nés lors de la réanimation cardio-pulmonaire

International audienceThis chapter concerns the formulation of a methodology and its implementation to elaborate a training simulator for medical staff who may be confronted with the critical situations of new-borns resuscitation. The simulator reproduces the different cardio-pulmonary pathological behaviours of new-borns, the working environment of resuscitation rooms, and the monitoring and control environment of the learners by a teacher. Conceptual models of new-borns behaviours combined with the cardio-pulmonary resuscitation gestures have been developed. The methodological process is jointly using cognitive approaches with formal modelling and simulation. Cognitive approaches are mobilized to elaborate application ontologies to be the bases for the development of the conceptual models and the specification of the simulator. Ontologies have been developed on the bases of a corpus of academic documents, return on experience documents, and practitioner interviews, by means of the Knowledge Oriented Design (KOD) method. A discrete event formalism has been used to formalize the conceptual models of the new-borns behaviours. As a result, a simulator has been built to train medical practitioners to face situations, which are reported to potentially cause errors and thus improve the safety of the resuscitation gestures

The strategic value of targeted knowledge management - case study of an Australian refrigeration company

 This thesis is a study of design and implementation of an engineering knowledge management system to facilitate knowledge capture, sharing and reuse to both ensure business continuity and resolve a make-span problem in an Australian refrigeration company. The company had encountered problems with a number of engineering staff in the small product development team leaving the company and taking their expertise with them. This situation has impacted the business continuity of the company, because the knowledge and expertise used in the refrigerated display cabinet development process is a combination of explicit and tacit knowledge as the engineers conduct the product development process intuitively. Records of previous design and testing processes were either non-existent or stored in ways that were not accessible. The other business problem in the company resulted from product development taking too long, in effect from 6 weeks up to the worst case of one year. The company needed research solutions to both of these problems to strategically maintain the competitiveness of the company business. This research applied a single case study research method with a problem-solving paradigm, Design Science methodology, to develop and then test solutions. Design Science as a research methodology has two components, first design development and second, design evaluation. The researcher developed an engineering knowledge based system as an artefact to solve the problem of enabling company business continuity. Using ontology as a structural base, the KBS contains both knowledge elements captured from the engineers during the data collection process and existing knowledge artefacts in the company. The research used a set of multilayered research techniques, including semi-formal and formal interviews, serendipitous interviews, group meetings, observation and shadowing, to capture and then structure both the tacit and explicit knowledge. The resultant ontology was used to build the KBS to store both tacit and explicit knowledge and answer the engineers’ questions about their existing and previous product development processes. The KBS developed in this research is a knowledge repository to maintain records of the products design and testing processes in a searchable form. Use and then an evaluation of the system by the engineers and the executive staff of the company confirmed that the intention of the system to address the business continuity problem by knowledge capture, classification and storage was achieved and met the company’s business needs. This research also applied Heuristic Process Mining to the knowledge stored in the KBS to address the second problem identified initially by the company, that of lengthy make span in new product design and development. HPM is a technique using mathematical models to find relationships between tasks in the process. HMP measures dependency and frequency values between tasks and tasks with low D/F value can be eliminated from the process. This then can lead to the shorter product testing process. The research showed that the application of HPM to the stored process knowledge in the KMS was able to significantly reduce the product design and testing process in the company

Reusability in manufacturing, supported by value net and patterns approaches

The concept of manufacturing and the need or desire to create artefacts or products is very, very old, yet it is still an essential component of all modem economies. Indeed, manufacturing is one of the few ways that wealth is created. The creation or identification of good quality, sustainable product designs is fundamental to the success of any manufacturing enterprise. Increasingly, there is also a requirement for the manufacturing system which will be used to manufacture the product, to be designed (or redesigned) in parallel with the product design. Many different types of manufacturing knowledge and information will contribute to these designs. A key question therefore for manufacturing companies to address is how to make the very best use of their existing, valuable, knowledge resources. […] The research reported in this thesis examines ways of reusing existing manufacturing knowledge of many types, particularly in the area of manufacturing systems design. The successes and failures of reported reuse programmes are examined, and lessons learnt from their experiences. This research is therefore focused on identifying solutions that address both technical and non-technical requirements simultaneously, to determine ways to facilitate and increase the reuse of manufacturing knowledge in manufacturing system design. [Continues.

Living ontologies: collaborative knowledge structuring on the Internet

This thesis discusses the issues involving the support of Living Ontologies: collaborating in the construction and maintenance of ontologies using the Internet. Ontologies define the concepts used in describing a domain: they are used by knowledge engineers as reusable components of knowledge-based systems. Knowledge engineers create ontologies by eliciting information from domain experts. However, experts often have different conceptualisations of a domain and knowledge engineers often have different ways of formalising their conceptualisations. Taking a constructivist perspective, constructing ontologies from multiple conflicting conceptualisations can be seen as a design activity, in which knowledge engineers make choices according to the context in which the representation will be used. Based on this theory, a methodology for collaboratively constructing ontologies might involve comparing differing conceptualisations and using these comparisons to initiate discussion, changes to the conceptualisations and the development of criteria against which they can be evaluated. APECKS (Adaptive Presentation Environment for Collaborative Knowledge Structuring) is designed to support this methodology. APECKS aims not only to support the collaborative construction of ontologies but also to use ontologies to present information to its users adaptively within a virtual environment. It demonstrates a number of innovations over conventional ontology servers, such as prompted knowledge elicitation from domain experts, automated comparisons between ontologies, the creation of design rationales and change tracking. A small evaluation of APECKS has shown that it is usable by domain experts and that automated comparisons between ontologies can be used to initiate alterations, investigations of others' conceptualisations and as a basis for discussion. Possible future development of APECKS includes tighter integration with a virtual environment and with other networked knowledge-based tools. Further research is also needed to develop the methodology on which APECKS is based, by investigating ways of comparing, combining and discussing ontologies