Information and knowledge management in complex systems

16th IFIP WG8.1 International Conference on Informatics and Semiotics in Organisations, ICISO 2015

Mapping Educational Specialist knowHow (MESH): the building of a knowledge management system for research informed practice

In this invited article the authors present an evaluative report on the development of the MESHGuides project (http://www.meshguides.org/). MESHGuides’ objective is to provide education with an international knowledge management system. MESHGuides were conceived as research summaries for supporting teachers’ in developing evidence-based practice. Their aim is to enhance teachers’ capacity to engage actively with research in their own classrooms. The original thinking for MESH arose from the work of UK-based academics Professor Marilyn Leask and Dr Sarah Younie in response to a desire, which has recently gathered momentum in the UK, for the development of a more research-informed teaching profession and for the establishment of an on-line platform to support evidence-based practice (DfE, 2015; Leask and Younie 2001; OECD 2009). The focus of this article is on how the MESHGuides project was conceived and structured, the technical systems supporting it and the practical reality for academics and teachers of composing and using MESHGuides. The project and the guides are in the early stages of development, and discussion indicates future possibilities for more global engagement with this knowledge management system.

English language teaching and educational reform in Western China: a knowledge management perspective

This study examines the impact of a large-scale UK-based teacher development programme on innovation and change in English language education in Western China within a knowledge management (KM) framework. Questionnaire data were collected from 229 returnee teachers in 15 cohorts. Follow-up interviews and focus groups were conducted with former participants, middle and senior managers, and teachers who had not participated in the UK programme. The results showed evidence of knowledge creation and amplification at individual, group and inter-organizational levels. However, the present study also identified knowledge creation potential through the more effective organization of follow-up at the national level, particularly for the returnee teachers. It is argued that the KM framework might offer a promising alternative to existing models and metaphors of Continuing Professional Development (CPD).

Knowledge communication and translation- A knowledge transfer model

Purpose – The purpose of this paper is to propose a process model for knowledge transfer in using theories relating knowledge communication and knowledge translation. Design/methodology/approach – Most of what is put forward in this paper is based on a research project titled “Procurement for innovation and knowledge transfer (ProFIK)”. The project is funded by a UK government research council – The Engineering and Physical Sciences Research Council (EPSRC). The discussions are mainly grounded on a thorough review of literature accomplished as part of the research project. Findings – The process model developed in this paper has built upon the theory of knowledge transfer and the theory of communication. Knowledge transfer, per se, is not a mere transfer of knowledge. It involves different stages of knowledge transformation. Depending on the context of knowledge transfer, it can also be influenced by many factors; some positive and some negative. The developed model of knowledge transfer attempts to encapsulate all these issues in order to create a holistic framework. Originality/value of paper – An attempt has been made in the paper to combine some of the significant theories or findings relating to knowledge transfer together, making the paper an original and valuable one.

Sensitivity analysis of a catchment-scale nitrogen model

There are now considerable expectations that semi-distributed models are useful tools for supporting catchment water quality management. However, insufficient attention has been given to evaluating the uncertainties inherent to this type of model, especially those associated with the spatial disaggregation of the catchment. The Integrated Nitrogen in Catchments model (INCA) is subjected to an extensive regionalised sensitivity analysis in application to the River Kennet, part of the groundwater-dominated upper Thames catchment, UK The main results are: (1) model output was generally insensitive to land-phase parameters, very sensitive to groundwater parameters, including initial conditions, and significantly sensitive to in-river parameters; (2) INCA was able to produce good fits simultaneously to the available flow, nitrate and ammonium in-river data sets; (3) representing parameters as heterogeneous over the catchment (206 calibrated parameters) rather than homogeneous (24 calibrated parameters) produced a significant improvement in fit to nitrate but no significant improvement to flow and caused a deterioration in ammonium performance; (4) the analysis indicated that calibrating the flow-related parameters first, then calibrating the remaining parameters (as opposed to calibrating all parameters together) was not a sensible strategy in this case; (5) even the parameters to which the model output was most sensitive suffered from high uncertainty due to spatial inconsistencies in the estimated optimum values, parameter equifinality and the sampling error associated with the calibration method; (6) soil and groundwater nutrient and flow data are needed to reduce. uncertainty in initial conditions, residence times and nitrogen transformation parameters, and long-term historic data are needed so that key responses to changes in land-use management can be assimilated. The results indicate the general, difficulty of reconciling the questions which catchment nutrient models are expected to answer with typically limited data sets and limited knowledge about suitable model structures. The results demonstrate the importance of analysing semi-distributed model uncertainties prior to model application, and illustrate the value and limitations of using Monte Carlo-based methods for doing so. (c) 2005 Elsevier B.V. All rights reserved.

An analytic knowledge network process for construction entrepreneurship education

Purpose - The purpose of this paper is to provide a quantitative multicriteria decision-making approach to knowledge management in construction entrepreneurship education by means of an analytic knowledge network process (KANP) Design/methodology/approach- The KANP approach in the study integrates a standard industrial classification with the analytic network process (ANP). For the construction entrepreneurship education, a decision-making model named KANP.CEEM is built to apply the KANP method in the evaluation of teaching cases to facilitate the case method, which is widely adopted in entrepreneurship education at business schools. Findings- The study finds that there are eight clusters and 178 nodes in the KANP.CEEM model, and experimental research on the evaluation of teaching cases discloses that the KANP method is effective in conducting knowledge management to the entrepreneurship education. Research limitations/implications- As an experimental research, this paper ignores the concordance between a selected standard classification and others, which perhaps limits the usefulness of KANP.CEEM model elsewhere. Practical implications- As the KANP.CEEM model is built based on the standard classification codes and the embedded ANP, it is thus expected that the model has a wide potential in evaluating knowledge-based teaching materials for any education purpose with a background from the construction industry, and can be used by both faculty and students. Originality/value- This paper fulfils a knowledge management need and offers a practical tool for an academic starting out on the development of knowledge-based teaching cases and other teaching materials or for a student going through the case studies and other learning materials.

A neurofuzzy network knowledge extraction and extended gram-Schmidt algorithm for model subspace decomposition

This paper introduces a new neurofuzzy model construction and parameter estimation algorithm from observed finite data sets, based on a Takagi and Sugeno (T-S) inference mechanism and a new extended Gram-Schmidt orthogonal decomposition algorithm, for the modeling of a priori unknown dynamical systems in the form of a set of fuzzy rules. The first contribution of the paper is the introduction of a one to one mapping between a fuzzy rule-base and a model matrix feature subspace using the T-S inference mechanism. This link enables the numerical properties associated with a rule-based matrix subspace, the relationships amongst these matrix subspaces, and the correlation between the output vector and a rule-base matrix subspace, to be investigated and extracted as rule-based knowledge to enhance model transparency. The matrix subspace spanned by a fuzzy rule is initially derived as the input regression matrix multiplied by a weighting matrix that consists of the corresponding fuzzy membership functions over the training data set. Model transparency is explored by the derivation of an equivalence between an A-optimality experimental design criterion of the weighting matrix and the average model output sensitivity to the fuzzy rule, so that rule-bases can be effectively measured by their identifiability via the A-optimality experimental design criterion. The A-optimality experimental design criterion of the weighting matrices of fuzzy rules is used to construct an initial model rule-base. An extended Gram-Schmidt algorithm is then developed to estimate the parameter vector for each rule. This new algorithm decomposes the model rule-bases via an orthogonal subspace decomposition approach, so as to enhance model transparency with the capability of interpreting the derived rule-base energy level. This new approach is computationally simpler than the conventional Gram-Schmidt algorithm for resolving high dimensional regression problems, whereby it is computationally desirable to decompose complex models into a few submodels rather than a single model with large number of input variables and the associated curse of dimensionality problem. Numerical examples are included to demonstrate the effectiveness of the proposed new algorithm.

Establishing a connection between knowledge transfer and innovation diffusion

Successful innovation diffusion process may well take the form of knowledge transfer process. Therefore, the primary objectives of this paper include: first, to evaluate the interrelations between transfer of knowledge and diffusion of innovation; and second to develop a model to establish a connection between the two. This has been achieved using a four-step approach. The first step of the approach is to assess and discuss the theories relating to knowledge transfer (KT) and innovation diffusion (ID). The second step focuses on developing basic models for KT and ID, based on the key theories surrounding these areas. A considerable amount of literature has been written on the association between knowledge management and innovation, the respective fields of KT and ID. The next step, therefore, explores the relationship between innovation and knowledge management in order to identify the connections between the latter, i.e. KT and ID. Finally, step four proposes and develops an integrated model for KT and ID. As the developed model suggests the sub-processes of knowledge transfer can be connected to the innovation diffusion process in several instances as discussed and illustrated in the paper.

Towards a semiotic approach to practice-oriented knowledge transfer

With the rapid growth of information and technology, knowledge is a valuable asset in organisation which has become significant as a strategic resource. Many studies have focused on managing knowledge in organisations. In particular, knowledge transfer has become a significant issue concerned with the movement of knowledge across organisational boundaries. It enables the exploitation and application of existing knowledge for other organisations, reducing the time of creating knowledge, and minimising the cost of organisational learning. One way to capture knowledge in a transferrable form is through practice. In this paper, we discuss how organisations can transfer knowledge through practice effectively and propose a model for a semiotic approach to practice-oriented knowledge transfer. In this model, practice is treated as a sign that represents knowledge, and its localisation is analysed as a semiotic process.

Collaboration model for SSMEnetUK: a service science perspective

This paper aims to design a collaboration model for a Knowledge Community - SSMEnetUK. The research identifies SSMEnetUK as a socio-technical system and uses the core concepts of Service Science to explore the subject domain. The paper is positioned within the concept of Knowledge Management (KM) and utilising Web 2.0 tools for collaboration. A qualitative case study method was adopted and multiple data sources were used. In achieving that, the degree of co-relation between knowledge management activities and Web 2.0 tools for collaboration in the scenario are pitted against the concept of value propositions offered by both customer/user and service provider. The proposed model provides a better understanding of how Knowledge Management and Web 2.0 tools can enable effective collaboration within SSMEnetUK. This research is relevant to the wider service design and innovation community because it provides a basis for building a service-centric collaboration platform for the benefit of both customer/user and service provider.

WREN: electronic management system for facilities management

This paper describes a case study of an electronic data management system developed in-house by the Facilities Management Directorate (FMD) of an educational institution in the UK. The FMD Maintenance and Business Services department is responsible for the maintenance of the built-estate owned by the university. The department needs to have a clear definition of the type of work undertaken and the administration that enables any maintenance work to be carried out. These include the management of resources, budget, cash flow and workflow of reactive, preventative and planned maintenance of the campus. In order to be more efficient in supporting the business process, the FMD had decided to move from a paper-based information system to an electronic system, WREN, to support the business process of the FMD. Some of the main advantages of WREN are that it is tailor-made to fit the purpose of the users; it is cost effective when it comes to modifications on the system; and the database can also be used as a knowledge management tool. There is a trade-off; as WREN is tailored to the specific requirements of the FMD, it may not be easy to implement within a different institution without extensive modifications. However, WREN is successful in not only allowing the FMD to carry out the tasks of maintaining and looking after the built-estate of the university, but also has achieved its aim to minimise costs and maximise efficiency.