The Experts below are selected from a list of 7713 Experts worldwide ranked by ideXlab platform
Christer Carlsson - One of the best experts on this subject based on the ideXlab platform.
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Decision analytics—Key to digitalisation
Information Sciences, 2018Co-Authors: Christer CarlssonAbstract:Abstract The context we address is digitalisation and we want to make the case for decision analytics as one of the key drivers to both meet the challenges from big data/fast data and to work out the new possibilities we are getting to mobilise Knowledge, i.e. to make tacit Knowledge explicit and to make it accessible and usable for automated, intelligent systems. The use of powerful, intelligent systems is one of the relevant solutions in the digitalisation that is now spreading in industry and business. Digitalisation brings increasing competition, slimmer margins for productivity and profitability and more pronounced requirements for effective planning, problem solving and decision making. This requires a transfer of Knowledge from experts and experienced people to novice system operators—and to automated, intelligent systems—a transfer we call Knowledge Mobilisation. We will work out reasons for why digital coaching will be a key part of Knowledge Mobilisation and a key step in the development of instruments we need for the progress of digitalisation.
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Fuzzy Ontology Support for Knowledge Mobilisation
Frontiers in Computational Intelligence, 2017Co-Authors: Christer CarlssonAbstract:Classical management science is making the transition to analytics, which has the same agenda to support managerial planning, problem solving and decision making in industrial and business contexts but is combining the classical models and algorithms with modern, advanced technology for handling data, information and Knowledge. We run a Knowledge Mobilisation project as a joint effort by Institute for Advanced Management Systems Research, and VTT Technical Research Centre of Finland. The goal was to mobilise Knowledge stored in heterogeneous databases for users with various backgrounds, geographical locations and situations. The working hypothesis of the project was that fuzzy mathematics combined with domain-specific data models, in other words, fuzzy ontologies, would help manage the uncertainty in finding information that matches the users’ needs. In this paper, we describe an industrial application of fuzzy ontologies in information retrieval for a paper machine where problem-solving reports are annotated with keywords and then stored in a database for later use. One of the key insights turned out to be that using the Bellmann-Zadeh principles for fuzzy decision-making are useful for identifying keyword dependencies in a keyword taxonomic tree.
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Fuzzy Ontology Used for Knowledge Mobilization
International Journal of Intelligent Systems, 2012Co-Authors: Christer Carlsson, Jozsef Mezei, Matteo BrunelliAbstract:Knowledge mobilization is a transition from the prevailing Knowledge management to a new methodology through some innovative methods for Knowledge representation, formation, and development and for Knowledge retrieval and distribution. The context is industrial processes and finding solutions to complex problems that arise and for which at least partial solutions have been documented. The fact that a problem has been solved before normally makes it easier to solve it again and the existence of documents that describe how it was solved supports the problem-solving process. But documents that describe the problem solving have to be retrieved from a large database of documents and the information that describes the content of a document is not precise. We show that fuzzy ontology will be useful for finding a sufficiently small set of documents that are relevant for the problem solving even if they are imprecisely classified with keywords. © 2013 Wiley Periodicals, Inc. (This paper is an extended version of “Carlsson C., Brunelli M. and Mezei J. (2010): Fuzzy Ontology and Information Granulation: An Approach to Knowledge Mobilisation. IPMU 2010, Part II (pp. 420–429), Springer”. An earlier paper “Knowledge Mobilisation through Fuzzy Ontology and Information Granulation” was presented at the World Conference on Soft Computing in San Francisco, 2011.)
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Decision making with a fuzzy ontology
Soft Computing, 2011Co-Authors: Christer Carlsson, Matteo Brunelli, Jozsef MezeiAbstract:Knowledge Mobilisation is a transition from the prevailing Knowledge management technology that has been widely used in industry for the last 20 years to a new methodology and some innovative methods for Knowledge representation, formation and development and for Knowledge retrieval and distribution. Knowledge Mobilisation aims at coming to terms with some of the problems of Knowledge management and at the same time to introduce new theory, new methods and new technology. More precisely, this paper presents an outline of a fuzzy ontology as an enhanced version of classical ontology and demonstrates some advantages for practical decision making. We show that a number of soft computing techniques, e.g. aggregation functions and interval valued fuzzy numbers, will support effective and practical decision making on the basis of the fuzzy ontology. We demonstrate the Knowledge Mobilisation methods with the construction of a support system for finding the best available wine for a number of wine drinking occasions using a fuzzy wine ontology and fuzzy reasoning methods; the support system has been implemented for a Nokia N900 smart phone.
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Bled eConference - Knowledge Mobilisation for Knowledge Whenever and Wherever Needed
2010Co-Authors: Christer Carlsson, Matteo Brunelli, Jozsef MezeiAbstract:Knowledge Mobilisation is a transition from the prevailing Knowledge management technology to some innovative methods for Knowledge representation, formation and development and for Knowledge retrieval and distribution. Knowledge Mobilisation also carries the connotation on “Knowledge on mobile phones” and this is actually one of the platforms that will be used. Fuzzy ontology replaces classical ontology for Knowledge representation. We will show that fuzzy ontology is useful to represent real world Knowledge and to give us answers which are sufficiently good for real world situations for which we need sufficiently good Knowledge. We demonstrate the Knowledge Mobilisation approach by showing how amateurs can become wine connoisseurs with support from the technology.
Jozsef Mezei - One of the best experts on this subject based on the ideXlab platform.
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Fuzzy Ontology Used for Knowledge Mobilization
International Journal of Intelligent Systems, 2012Co-Authors: Christer Carlsson, Jozsef Mezei, Matteo BrunelliAbstract:Knowledge mobilization is a transition from the prevailing Knowledge management to a new methodology through some innovative methods for Knowledge representation, formation, and development and for Knowledge retrieval and distribution. The context is industrial processes and finding solutions to complex problems that arise and for which at least partial solutions have been documented. The fact that a problem has been solved before normally makes it easier to solve it again and the existence of documents that describe how it was solved supports the problem-solving process. But documents that describe the problem solving have to be retrieved from a large database of documents and the information that describes the content of a document is not precise. We show that fuzzy ontology will be useful for finding a sufficiently small set of documents that are relevant for the problem solving even if they are imprecisely classified with keywords. © 2013 Wiley Periodicals, Inc. (This paper is an extended version of “Carlsson C., Brunelli M. and Mezei J. (2010): Fuzzy Ontology and Information Granulation: An Approach to Knowledge Mobilisation. IPMU 2010, Part II (pp. 420–429), Springer”. An earlier paper “Knowledge Mobilisation through Fuzzy Ontology and Information Granulation” was presented at the World Conference on Soft Computing in San Francisco, 2011.)
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Decision making with a fuzzy ontology
Soft Computing, 2011Co-Authors: Christer Carlsson, Matteo Brunelli, Jozsef MezeiAbstract:Knowledge Mobilisation is a transition from the prevailing Knowledge management technology that has been widely used in industry for the last 20 years to a new methodology and some innovative methods for Knowledge representation, formation and development and for Knowledge retrieval and distribution. Knowledge Mobilisation aims at coming to terms with some of the problems of Knowledge management and at the same time to introduce new theory, new methods and new technology. More precisely, this paper presents an outline of a fuzzy ontology as an enhanced version of classical ontology and demonstrates some advantages for practical decision making. We show that a number of soft computing techniques, e.g. aggregation functions and interval valued fuzzy numbers, will support effective and practical decision making on the basis of the fuzzy ontology. We demonstrate the Knowledge Mobilisation methods with the construction of a support system for finding the best available wine for a number of wine drinking occasions using a fuzzy wine ontology and fuzzy reasoning methods; the support system has been implemented for a Nokia N900 smart phone.
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Bled eConference - Knowledge Mobilisation for Knowledge Whenever and Wherever Needed
2010Co-Authors: Christer Carlsson, Matteo Brunelli, Jozsef MezeiAbstract:Knowledge Mobilisation is a transition from the prevailing Knowledge management technology to some innovative methods for Knowledge representation, formation and development and for Knowledge retrieval and distribution. Knowledge Mobilisation also carries the connotation on “Knowledge on mobile phones” and this is actually one of the platforms that will be used. Fuzzy ontology replaces classical ontology for Knowledge representation. We will show that fuzzy ontology is useful to represent real world Knowledge and to give us answers which are sufficiently good for real world situations for which we need sufficiently good Knowledge. We demonstrate the Knowledge Mobilisation approach by showing how amateurs can become wine connoisseurs with support from the technology.
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fuzzy ontologies and Knowledge Mobilisation turning amateurs into wine connoisseurs
IEEE International Conference on Fuzzy Systems, 2010Co-Authors: Christer Carlsson, Matteo Brunelli, Jozsef MezeiAbstract:Knowledge Mobilisation is a transition from the prevailing Knowledge management technology to a new methodology and some innovative methods for Knowledge representation, formation and development and for Knowledge retrieval and distribution. We show that fuzzy ontology will be useful to represent real world Knowledge and that approximate reasoning schemes can give us answers which are sufficiently good for real world situations in which we need sufficiently good Knowledge. We demonstrate the Knowledge Mobilisation approach by showing how amateurs can become wine connoisseurs with support from the technology.
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fuzzy ontology and information granulation an approach to Knowledge Mobilisation
International Conference Information Processing, 2010Co-Authors: Christer Carlsson, Matteo Brunelli, Jozsef MezeiAbstract:In order to find a common conceptual framework to address the problems of representation and management of imprecise and vague Knowledge in a semantic web we have analysed the role played by information granulation in human cognition. Fuzzy granulation underlies the basic concepts of linguistic variable and fuzzy if-then rules, which play a major role in the applications of fuzzy logic to the representation and treatment of imprecision and vagueness. Fuzzy information granulation is central to fuzzy logic because it is central to concept formation in human reasoning and to the design of intelligent systems, and therefore is central to the modelling of fuzzy ontologies.
Louise Freebairn - One of the best experts on this subject based on the ideXlab platform.
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Applying systems thinking to Knowledge Mobilisation in public health.
Health research policy and systems, 2020Co-Authors: Abby Haynes, Louise Freebairn, Lucie Rychetnik, Diane T. Finegood, Michelle Irving, Penelope HaweAbstract:Context Knowledge Mobilisation (KM) is a vital strategy in efforts to improve public health policy and practice. Linear models describing Knowledge transfer and translation have moved towards multi-directional and complexity-attuned approaches where Knowledge is produced and becomes meaningful through social processes. There are calls for systems approaches to KM but little guidance on how this can be operationalised. This paper describes the contribution that systems thinking can make to KM and provides guidance about how to put it into action. Methods We apply a model of systems thinking (which focuses on leveraging change in complex systems) to eight KM practices empirically identified by others. We describe how these models interact and draw out some key learnings for applying systems thinking practically to KM in public health policy and practice. Examples of empirical studies, tools and targeted strategies are provided. Findings Systems thinking can enhance and fundamentally transform KM. It upholds a pluralistic view of Knowledge as informed by multiple parts of the system and reconstituted through use. Mobilisation is conceived as a situated, non-prescriptive and potentially destabilising practice, no longer conceptualised as a discrete piece of work within wider efforts to strengthen public health but as integral to and in continual dialogue with those efforts. A systems approach to KM relies on contextual understanding, collaborative practices, addressing power imbalances and adaptive learning that responds to changing interactions between Mobilisation activities and context. Conclusion Systems thinking offers valuable perspectives, tools and strategies to better understand complex problems in their settings and for strengthening KM practice. We make four suggestions for further developing empirical evidence and debate about how systems thinking can enhance our capacity to mobilise Knowledge for solving complex problems - (1) be specific about what is meant by 'systems thinking', (2) describe counterfactual KM scenarios so the added value of systems thinking is clearer, (3) widen conceptualisations of impact when evaluating KM, and (4) use methods that can track how and where Knowledge is mobilised in complex systems.
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Knowledge Mobilisation for policy development: implementing systems approaches through participatory dynamic simulation modelling.
Health research policy and systems, 2017Co-Authors: Louise Freebairn, Lucie Rychetnik, Jo-an Atkinson, Paul M. Kelly, Geoff Mcdonnell, Nick Roberts, Christine Whittall, Sally RedmanAbstract:Evidence-based decision-making is an important foundation for health policy and service planning decisions, yet there remain challenges in ensuring that the many forms of available evidence are considered when decisions are being made. Mobilising Knowledge for policy and practice is an emergent process, and one that is highly relational, often messy and profoundly context dependent. Systems approaches, such as dynamic simulation modelling can be used to examine both complex health issues and the context in which they are embedded, and to develop decision support tools. This paper reports on the novel use of participatory simulation modelling as a Knowledge Mobilisation tool in Australian real-world policy settings. We describe how this approach combined systems science methodology and some of the core elements of Knowledge Mobilisation best practice. We describe the strategies adopted in three case studies to address both technical and socio-political issues, and compile the experiential lessons derived. Finally, we consider the implications of these Knowledge Mobilisation case studies and provide evidence for the feasibility of this approach in policy development settings. Participatory dynamic simulation modelling builds on contemporary Knowledge Mobilisation approaches for health stakeholders to collaborate and explore policy and health service scenarios for priority public health topics. The participatory methods place the decision-maker at the centre of the process and embed deliberative methods and co-production of Knowledge. The simulation models function as health policy and programme dynamic decision support tools that integrate diverse forms of evidence, including research evidence, expert Knowledge and localised contextual information. Further research is underway to determine the impact of these methods on health service decision-making.
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Simulation modelling as a tool for Knowledge Mobilisation in health policy settings: a case study protocol.
Health research policy and systems, 2016Co-Authors: Louise Freebairn, Jo-an Atkinson, Paul M. Kelly, Geoff Mcdonnell, Lucie RychetnikAbstract:Background Evidence-informed decision-making is essential to ensure that health programs and services are effective and offer value for money; however, barriers to the use of evidence persist. Emerging systems science approaches and advances in technology are providing new methods and tools to facilitate evidence-based decision-making. Simulation modelling offers a unique tool for synthesising and leveraging existing evidence, data and expert local Knowledge to examine, in a robust, low risk and low cost way, the likely impact of alternative policy and service provision scenarios. This case study will evaluate participatory simulation modelling to inform the prevention and management of gestational diabetes mellitus (GDM). The risks associated with GDM are well recognised; however, debate remains regarding diagnostic thresholds and whether screening and treatment to reduce maternal glucose levels reduce the associated risks. A diagnosis of GDM may provide a leverage point for multidisciplinary lifestyle modification interventions. This research will apply and evaluate a simulation modelling approach to understand the complex interrelation of factors that drive GDM rates, test options for screening and interventions, and optimise the use of evidence to inform policy and program decision-making.
Lucie Rychetnik - One of the best experts on this subject based on the ideXlab platform.
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Applying systems thinking to Knowledge Mobilisation in public health.
Health research policy and systems, 2020Co-Authors: Abby Haynes, Louise Freebairn, Lucie Rychetnik, Diane T. Finegood, Michelle Irving, Penelope HaweAbstract:Context Knowledge Mobilisation (KM) is a vital strategy in efforts to improve public health policy and practice. Linear models describing Knowledge transfer and translation have moved towards multi-directional and complexity-attuned approaches where Knowledge is produced and becomes meaningful through social processes. There are calls for systems approaches to KM but little guidance on how this can be operationalised. This paper describes the contribution that systems thinking can make to KM and provides guidance about how to put it into action. Methods We apply a model of systems thinking (which focuses on leveraging change in complex systems) to eight KM practices empirically identified by others. We describe how these models interact and draw out some key learnings for applying systems thinking practically to KM in public health policy and practice. Examples of empirical studies, tools and targeted strategies are provided. Findings Systems thinking can enhance and fundamentally transform KM. It upholds a pluralistic view of Knowledge as informed by multiple parts of the system and reconstituted through use. Mobilisation is conceived as a situated, non-prescriptive and potentially destabilising practice, no longer conceptualised as a discrete piece of work within wider efforts to strengthen public health but as integral to and in continual dialogue with those efforts. A systems approach to KM relies on contextual understanding, collaborative practices, addressing power imbalances and adaptive learning that responds to changing interactions between Mobilisation activities and context. Conclusion Systems thinking offers valuable perspectives, tools and strategies to better understand complex problems in their settings and for strengthening KM practice. We make four suggestions for further developing empirical evidence and debate about how systems thinking can enhance our capacity to mobilise Knowledge for solving complex problems - (1) be specific about what is meant by 'systems thinking', (2) describe counterfactual KM scenarios so the added value of systems thinking is clearer, (3) widen conceptualisations of impact when evaluating KM, and (4) use methods that can track how and where Knowledge is mobilised in complex systems.
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Knowledge Mobilisation for policy development: implementing systems approaches through participatory dynamic simulation modelling.
Health research policy and systems, 2017Co-Authors: Louise Freebairn, Lucie Rychetnik, Jo-an Atkinson, Paul M. Kelly, Geoff Mcdonnell, Nick Roberts, Christine Whittall, Sally RedmanAbstract:Evidence-based decision-making is an important foundation for health policy and service planning decisions, yet there remain challenges in ensuring that the many forms of available evidence are considered when decisions are being made. Mobilising Knowledge for policy and practice is an emergent process, and one that is highly relational, often messy and profoundly context dependent. Systems approaches, such as dynamic simulation modelling can be used to examine both complex health issues and the context in which they are embedded, and to develop decision support tools. This paper reports on the novel use of participatory simulation modelling as a Knowledge Mobilisation tool in Australian real-world policy settings. We describe how this approach combined systems science methodology and some of the core elements of Knowledge Mobilisation best practice. We describe the strategies adopted in three case studies to address both technical and socio-political issues, and compile the experiential lessons derived. Finally, we consider the implications of these Knowledge Mobilisation case studies and provide evidence for the feasibility of this approach in policy development settings. Participatory dynamic simulation modelling builds on contemporary Knowledge Mobilisation approaches for health stakeholders to collaborate and explore policy and health service scenarios for priority public health topics. The participatory methods place the decision-maker at the centre of the process and embed deliberative methods and co-production of Knowledge. The simulation models function as health policy and programme dynamic decision support tools that integrate diverse forms of evidence, including research evidence, expert Knowledge and localised contextual information. Further research is underway to determine the impact of these methods on health service decision-making.
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Simulation modelling as a tool for Knowledge Mobilisation in health policy settings: a case study protocol.
Health research policy and systems, 2016Co-Authors: Louise Freebairn, Jo-an Atkinson, Paul M. Kelly, Geoff Mcdonnell, Lucie RychetnikAbstract:Background Evidence-informed decision-making is essential to ensure that health programs and services are effective and offer value for money; however, barriers to the use of evidence persist. Emerging systems science approaches and advances in technology are providing new methods and tools to facilitate evidence-based decision-making. Simulation modelling offers a unique tool for synthesising and leveraging existing evidence, data and expert local Knowledge to examine, in a robust, low risk and low cost way, the likely impact of alternative policy and service provision scenarios. This case study will evaluate participatory simulation modelling to inform the prevention and management of gestational diabetes mellitus (GDM). The risks associated with GDM are well recognised; however, debate remains regarding diagnostic thresholds and whether screening and treatment to reduce maternal glucose levels reduce the associated risks. A diagnosis of GDM may provide a leverage point for multidisciplinary lifestyle modification interventions. This research will apply and evaluate a simulation modelling approach to understand the complex interrelation of factors that drive GDM rates, test options for screening and interventions, and optimise the use of evidence to inform policy and program decision-making.
Matteo Brunelli - One of the best experts on this subject based on the ideXlab platform.
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Fuzzy Ontology Used for Knowledge Mobilization
International Journal of Intelligent Systems, 2012Co-Authors: Christer Carlsson, Jozsef Mezei, Matteo BrunelliAbstract:Knowledge mobilization is a transition from the prevailing Knowledge management to a new methodology through some innovative methods for Knowledge representation, formation, and development and for Knowledge retrieval and distribution. The context is industrial processes and finding solutions to complex problems that arise and for which at least partial solutions have been documented. The fact that a problem has been solved before normally makes it easier to solve it again and the existence of documents that describe how it was solved supports the problem-solving process. But documents that describe the problem solving have to be retrieved from a large database of documents and the information that describes the content of a document is not precise. We show that fuzzy ontology will be useful for finding a sufficiently small set of documents that are relevant for the problem solving even if they are imprecisely classified with keywords. © 2013 Wiley Periodicals, Inc. (This paper is an extended version of “Carlsson C., Brunelli M. and Mezei J. (2010): Fuzzy Ontology and Information Granulation: An Approach to Knowledge Mobilisation. IPMU 2010, Part II (pp. 420–429), Springer”. An earlier paper “Knowledge Mobilisation through Fuzzy Ontology and Information Granulation” was presented at the World Conference on Soft Computing in San Francisco, 2011.)
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Decision making with a fuzzy ontology
Soft Computing, 2011Co-Authors: Christer Carlsson, Matteo Brunelli, Jozsef MezeiAbstract:Knowledge Mobilisation is a transition from the prevailing Knowledge management technology that has been widely used in industry for the last 20 years to a new methodology and some innovative methods for Knowledge representation, formation and development and for Knowledge retrieval and distribution. Knowledge Mobilisation aims at coming to terms with some of the problems of Knowledge management and at the same time to introduce new theory, new methods and new technology. More precisely, this paper presents an outline of a fuzzy ontology as an enhanced version of classical ontology and demonstrates some advantages for practical decision making. We show that a number of soft computing techniques, e.g. aggregation functions and interval valued fuzzy numbers, will support effective and practical decision making on the basis of the fuzzy ontology. We demonstrate the Knowledge Mobilisation methods with the construction of a support system for finding the best available wine for a number of wine drinking occasions using a fuzzy wine ontology and fuzzy reasoning methods; the support system has been implemented for a Nokia N900 smart phone.
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Bled eConference - Knowledge Mobilisation for Knowledge Whenever and Wherever Needed
2010Co-Authors: Christer Carlsson, Matteo Brunelli, Jozsef MezeiAbstract:Knowledge Mobilisation is a transition from the prevailing Knowledge management technology to some innovative methods for Knowledge representation, formation and development and for Knowledge retrieval and distribution. Knowledge Mobilisation also carries the connotation on “Knowledge on mobile phones” and this is actually one of the platforms that will be used. Fuzzy ontology replaces classical ontology for Knowledge representation. We will show that fuzzy ontology is useful to represent real world Knowledge and to give us answers which are sufficiently good for real world situations for which we need sufficiently good Knowledge. We demonstrate the Knowledge Mobilisation approach by showing how amateurs can become wine connoisseurs with support from the technology.
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fuzzy ontologies and Knowledge Mobilisation turning amateurs into wine connoisseurs
IEEE International Conference on Fuzzy Systems, 2010Co-Authors: Christer Carlsson, Matteo Brunelli, Jozsef MezeiAbstract:Knowledge Mobilisation is a transition from the prevailing Knowledge management technology to a new methodology and some innovative methods for Knowledge representation, formation and development and for Knowledge retrieval and distribution. We show that fuzzy ontology will be useful to represent real world Knowledge and that approximate reasoning schemes can give us answers which are sufficiently good for real world situations in which we need sufficiently good Knowledge. We demonstrate the Knowledge Mobilisation approach by showing how amateurs can become wine connoisseurs with support from the technology.
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fuzzy ontology and information granulation an approach to Knowledge Mobilisation
International Conference Information Processing, 2010Co-Authors: Christer Carlsson, Matteo Brunelli, Jozsef MezeiAbstract:In order to find a common conceptual framework to address the problems of representation and management of imprecise and vague Knowledge in a semantic web we have analysed the role played by information granulation in human cognition. Fuzzy granulation underlies the basic concepts of linguistic variable and fuzzy if-then rules, which play a major role in the applications of fuzzy logic to the representation and treatment of imprecision and vagueness. Fuzzy information granulation is central to fuzzy logic because it is central to concept formation in human reasoning and to the design of intelligent systems, and therefore is central to the modelling of fuzzy ontologies.
