Data Flows and Engaging Visualisations for Your Repositories

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

A platform for assessing the current state of data repositories in Korea, Japan and China

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Practical Data Curation and Management for Institutional Repositories

Workshop at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

A Phase Model for Building a Customer Value Based Sales Tool – Case Mining and Metals Industry

The objective of this research is to observe the state of customer value management in Outotec Oyj, determine the key development areas and develop a phase model with which to guide the development of a customer value based sales tool. The study was conducted with a constructive research approach with the focus of identifying a problem and developing a solution for the problem. As a basis for the study, the current literature involving customer value assessment and solution and customer value selling was studied. The data was collected by conducting 16 interviews in two rounds within the company and it was analyzed by coding openly. First, seven important development areas were identified, out of which the most critical were “Customer value mindset inside the company” and “Coordination of customer value management activities”. Utilizing these seven areas three functionality requirements, “Preparation”, “Outotec’s value creation and communication” and “Documentation” and three development requirements for a customer value sales tool were identified. The study concluded with the formulation of a phase model for building a customer value based sales tool. The model included five steps that were defined as 1) Enable customer value utilization, 2) Connect with the customer, 3) Create customer value, 4) Define tool to facilitate value selling and 5) Develop sales tool. Further practical activities were also recommended as a guide for executing the phase model.

Heat Demand Forecasting Models’ Development: Use of Data Mining Tools in SQL Server Analysis Services

This thesis introduces heat demand forecasting models which are generated by using data mining algorithms. The forecast spans one full day and this forecast can be used in regulating heat consumption of buildings. For training the data mining models, two years of heat consumption data from a case building and weather measurement data from Finnish Meteorological Institute are used. The thesis utilizes Microsoft SQL Server Analysis Services data mining tools in generating the data mining models and CRISP-DM process framework to implement the research. Results show that the built models can predict heat demand at best with mean average percentage errors of 3.8% for 24-h profile and 5.9% for full day. A deployment model for integrating the generated data mining models into an existing building energy management system is also discussed.

Modelling the simultaneous effects of intellectual capital and knowledge management on the organisational performance of Finnish companies

The aim of this study was to contribute to the current knowledge-based theory by focusing on a research gap that exists in the empirically proven determination of the simultaneous but differentiable effects of intellectual capital (IC) assets and knowledge management (KM) practices on organisational performance (OP). The analysis was built on the past research and theoreticised interactions between the latent constructs specified using the survey-based items that were measured from a sample of Finnish companies for IC and KM and the dependent construct for OP determined using information available from financial databases. Two widely used and commonly recommended measures in the literature on management science, i.e. the return on total assets (ROA) and the return on equity (ROE), were calculated for OP. Thus the investigation of the relationship between IC and KM impacting OP in relation to the hypotheses founded was possible to conduct using objectively derived performance indicators. Using financial OP measures also strengthened the dynamic features of data needed in analysing simultaneous and causal dependences between the modelled constructs specified using structural path models. The estimates were obtained for the parameters of structural path models using a partial least squares-based regression estimator. Results showed that the path dependencies between IC and OP or KM and OP were always insignificant when analysed separate to any other interactions or indirect effects caused by simultaneous modelling and regardless of the OP measure used that was either ROA or ROE. The dependency between the constructs for KM and IC appeared to be very strong and was always significant when modelled simultaneously with other possible interactions between the constructs and using either ROA or ROE to define OP. This study, however, did not find statistically unambiguous evidence for proving the hypothesised causal mediation effects suggesting, for instance, that the effects of KM practices on OP are mediated by the IC assets. Due to the fact that some indication about the fluctuations of causal effects was assessed, it was concluded that further studies are needed for verifying the fundamental and likely hidden causal effects between the constructs of interest. Therefore, it was also recommended that complementary modelling and data processing measures be conducted for elucidating whether the mediation effects occur between IC, KM and OP, the verification of which requires further investigations of measured items and can be build on the findings of this study.

Governance of Healthcare Data: International Standards and Recommendations

In the global phenomenon, the aging population becomes a critical issue. Data and information concerning elderly citizens are increasing and are not well organized. In addition, these unstructured data and information cause the problems for decision makers. Since we live in a digital world, Information Technology is considered to be a tool in order to solve problems. Data, information, and knowledge are crucial components to facilitate success in IT service system. Therefore, it is necessary to study how to organize or to govern data from various sources related elderly citizens. The research is conducted due to the fact that there is no internationally accepted holistic framework for governance of data. The research limits the scope to study on the healthcare domain; however, the results can be applied to the other areas. The research starts with an ongoing research of Dahlberg and Nokkala (2015) as a theory. It explains the classification of existing data sources and their characteristics with the focus on managerial perspectives. Then the studies of existing frameworks at international and national level organizations have been performed to show the current frameworks, which have been used and are useful in compiling data on elderly citizens. The international organizations in this research are selected based on their reputations and the reliability to obtain information. The selected countries at national level provide different point of views between two countries. Australia is a forerunner in IT governance while Thailand is the country which the author has familiar knowledge of the current situation. Considered the discussions of frameworks at international and national organizations level illustrate the main characteristics of each framework. At international organization level gives precedence to the interoperability of exchanging data and information between different parties. Whereas at national level shows the importance of the acknowledgement of using frameworks throughout the country in order to make the frameworks to be effective. After the studies of both international and national organization levels, the thesis shows the summarized tables to answer the fitness to the proposed framework by Dahlberg and Nokkala whether the framework help to consolidate data from various sources with different formats, hierarchies, structures, velocities, and other attributes of data storages. In addition, suggestions and recommendations will be proposed for the future research.

Taenia solium transmission in a rural community in Honduras : an examination of risk factors and knowledge

Taenia soliurn taeniasis and cysticercosis are recognized as a major public health problem in Latin America. T. soliurn transmission not only affects the health of the individual, but also social and economic development, perpetuating the cycle of poverty. To determine prevalence rates, population knowledge and risk factors associated with transmission, an epidemiological study was undertaken in the rural community of Jalaca. Two standardized questionnaires were used to collect epidemiological and T. soli urn general knowledge data. Kato-Katz technique and an immunoblot assay (EITB) were used to determine taeniasis and seroprevalence, respectively. In total, 139 individuals belonging to 56 households participated in the study. Household characteristics were consistent with conditions of poverty of rural Honduras: 21.4% had no toilet or latrines, 19.6% had earthen floor, and 51.8% lacked indoor tap water. Pigs were raised in 46.4% of households, of which 70% allowed their pigs roaming freely. A human seroprevalence rate of 18.7% and a taeniasis prevalence rate of 2.4% were found. Only four persons answered correctly 2: 6 out of ten T. soliurn knowledge questions, for an average passing score of 2.9%. In general, a serious gap exists in knowledge regarding how humans acquire the infections, especially neurocysticercosis was identified. After regression analysis, the ability to recognize adult tapeworms and awareness of the clinical importance of taeniasis, were found to be significant risk factors for T. soliurn seropositivity. These results demonstrate a high level of transmission and a low level of kn~,wledge about Taenia soliurn in Jalaca. Consequently, intervention measures integrated with health education are necessary to decrease the burden caused by this parasite.

Organizational capacity and knowledge transfer : a qualitative case study of the 2007 Canada Winter Games host society

Understanding and managing the knowledge transfer process in sport organizations is an essential component to enhance organizational capacity. Very little research on either capacity or knowledge transfer within a sport organization exists. Consequently, the purpos e of this qualitative case study was to, examine the transfer of knowledge process within a major games host society. Specifically, two research goals guided the study: 1) To develop a model to explain a knowledge t r ans f e r process in a non-profit ma jor games hos t organization and 2) To examine the relevance of the model to a Canada Games Hos t Society. Data we r e collected from interviews with middle and senior level volunteers as well as senior s t a f f members (n= 27), document s and observations. The findings indicated three barriers to knowledge transfer: structural, systemic, and cultural. As a result of the findings a revised model for knowledge transfer wa s proposed that included modifications related to the direction of knowledge flow, timing of the knowledge transfer process, and group inter-relations. Implications identified the importance of intuition managers, time and organizational levels for successful knowledge transfer. Recommendations for future host societies and the Canada Games Council are presented.

Exploring Teacher Candidates’ Experience, Perception, and Knowledge of Multicultural Education in Two Ontario Universities

In this study, teacher candidates’ experiences, perceptions, and knowledge of multicultural education at 2 Ontario universities were used determine to the effectiveness of their teacher education programs in preparing them to teach in multicultural classrooms. The research also strived to highlight the most effective practices in these programs that contributed to the preparation of teacher candidates for employment in culturally, racially, and ethnically diverse classrooms in Ontario. A questionnaire and interviews were used to determine the effectiveness of the program in preparing them to teach in diverse classrooms. The findings revealed the need for a greater emphasis of multicultural education in teacher education programs at these universities. The data showed that teacher candidates were most critical of the courses and the delivery of the curriculum in relation to multicultural education. Teacher candidates were also concerned with the lack of multicultural education in their practicum placements. In addition, teacher candidates indicated in the questionnaire that they felt competent adapting instruction to the needs of students in multicultural classrooms. However, the results obtained from the interviews were more varied. The interviews highlighted that teacher candidates were hesitant about teaching in culturally diverse classrooms and less likely to state that they were prepared for these teaching environments. As well, many teacher candidates believed their peers were not prepared for multicultural issues. Teacher candidates believed the program could be improved in many ways including specific instruction across all classes, more diverse practicum experiences, guest speakers, case studies, and the creation of new courses that specifically address multicultural education.

Anxiety-Related Disorders in Primary-Junior Grades (K-3): Teacher Perceptions and Knowledge

This study used a descriptive case study design to analyze teachers’ experiences of anxiety-related conditions and emotions in the primary-junior grades (K-3). The study sought to examine (a) educators’ perceptions of anxiety conditions and how such interpretations influence their teaching practice; (b) teachers’ knowledge of the diagnostic processes, symptomology, and emotions related to anxiety disorders; (c) primary teachers’ knowledge of and experience with emotional regulation strategies and therapeutic approaches for anxiety; and (d) additional strategies and knowledge that should be available to help students. The study adopted Bronfenbrenner’s (1986) Ecological Model to frame participants’ experiences and perspectives, as well as the impact of several factors (e.g., school, home) and individuals (e.g. teachers, parents, students) on students’ anxiety and the participants’ perspectives. Through in-person interviews, participants shared their experiences with and knowledge about students in their teaching practice who had experienced anxiety-related conditions and emotions. Four major themes emerged from the data: symptoms and situational contexts; knowledge of strategies and interventions; understanding and perspectives of students; anxious emotional responses; and challenges. The study contributes to the literature by providing the real-life perspectives and experiences of primary-junior teachers (K-3) related to students experiencing anxiety. The study provides further information for educators, administrators, and research regarding any additional support and knowledge that should be implemented to further assist educators and students in regards to anxiety.

IR: Knowledge Creation, Knowledge Management and Knowledge Dissemination

Open access iiiovemerit and open source software movement plays an important role in creation of knowledge, knowledge management and knowledge dissemination. Scholarly communication and publishing are increasingly taking place in the electronic environment. With a growing proportion of the scholarly record now existing only in digital format, serious issues regarding access and preservation are being raised that are central to future scholarship. Institutional Repositories provide access to past. present and future scholarly literature and research documentation; ensures its preservation; assists users in discovery and use; and offers educational programs to enable users to develop lifelong literacy. This paper explores these aspects on how IR of Cochin University of Science & Technology supports scientific community for knowledge creation. knowledge Management, and knowledge dissemination.

Applying Data mining using Statistical Techniques for Career Selection

For years, choosing the right career by monitoring the trends and scope for different career paths have been a requirement for all youngsters all over the world. In this paper we provide a scientific, data mining based method for job absorption rate prediction and predicting the waiting time needed for 100% placement, for different engineering courses in India. This will help the students in India in a great deal in deciding the right discipline for them for a bright future. Information about passed out students are obtained from the NTMIS ( National technical manpower information system ) NODAL center in Kochi, India residing in Cochin University of science and technology

A Data Mining Approach for the Identification of Adverse Drug Events (ADE) resulting from Drug-Drug Interactions (DDI) to improve pharmacovigilance

In the current study, epidemiology study is done by means of literature survey in groups identified to be at higher potential for DDIs as well as in other cases to explore patterns of DDIs and the factors affecting them. The structure of the FDA Adverse Event Reporting System (FAERS) database is studied and analyzed in detail to identify issues and challenges in data mining the drug-drug interactions. The necessary pre-processing algorithms are developed based on the analysis and the Apriori algorithm is modified to suit the process. Finally, the modules are integrated into a tool to identify DDIs. The results are compared using standard drug interaction database for validation. 31% of the associations obtained were identified to be new and the match with existing interactions was 69%. This match clearly indicates the validity of the methodology and its applicability to similar databases. Formulation of the results using the generic names expanded the relevance of the results to a global scale. The global applicability helps the health care professionals worldwide to observe caution during various stages of drug administration thus considerably enhancing pharmacovigilance

Evolving Classifiers - Evolutionary Algorithms in Data Mining

Data mining means to summarize information from large amounts of raw data. It is one of the key technologies in many areas of economy, science, administration and the internet. In this report we introduce an approach for utilizing evolutionary algorithms to breed fuzzy classifier systems. This approach was exercised as part of a structured procedure by the students Achler, Göb and Voigtmann as contribution to the 2006 Data-Mining-Cup contest, yielding encouragingly positive results.