This paper analyzes connectivity and efficiency of a SME network across two industries. These characteristics are likely to be different for networks of various industries. The concept of 'small worlds' is used to judge overall network efficiency. The actual network can be classified as one in which a small world is present. Visualization of the results shows a single core group in the network. It was found that non-profit as well as science actors were overrepresented in the core of the field.
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This paper describes a project to explore the possibilities of virtual worlds in educating Green IT. In the project a virtual world has been created with various assignments which are meant to create awareness on sustainability aspects of IT. The world (and the assignments) will be incorporated in a course for first-year IT students. In order to measure the effects of the course, a questionnaire has been developed which can be used before and after the course to measure the attitude towards green IT.
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In the course of our supervisory work over the years, we have noticed that qualitative research tends to evoke a lot of questions and worries, so-called frequently asked questions (FAQs). This series of four articles intends to provide novice researchers with practical guidance for conducting high-quality qualitative research in primary care. By ‘novice’ we mean Master’s students and junior researchers, as well as experienced quantitative researchers who are engaging in qualitative research for the first time. This series addresses their questions and provides researchers, readers, reviewers and editors with references to criteria and tools for judging the quality of qualitative research papers. The second article focused on context, research questions and designs, and referred to publications for further reading. This third article addresses FAQs about sampling, data collection and analysis. The data collection plan needs to be broadly defined and open at first, and become flexible during data collection. Sampling strategies should be chosen in such a way that they yield rich information and are consistent with the methodological approach used. Data saturation determines sample size and will be different for each study. The most commonly used data collection methods are participant observation, face-to-face in-depth interviews and focus group discussions. Analyses in ethnographic, phenomenological, grounded theory, and content analysis studies yield different narrative findings: a detailed description of a culture, the essence of the lived experience, a theory, and a descriptive summary, respectively. The fourth and final article will focus on trustworthiness and publishing qualitative research.
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Within paediatric palliative care, it is essential for families and providers to have open, equal, and trusting relationships. In practice, however, building relationships can be challenging. Investing in better understanding the differences in each other's frames of reference and underlying values seems important. Wonder Lab practices provide a space to explore these differences by focusing together on life phenomena in curious and Socratic ways. Wonder Labs were organised with parents, healthcare professionals, and students involved in Dutch paediatric palliative care. The aim of this study was to develop an understanding of how participants experienced participating in Wonder Labs. We conducted twenty in-depth interviews with Wonder Lab participants and used inductive thematic analysis for data interpretation. Five themes were identified: Slowing down, Appreciating stories, Becoming vulnerable, Opening up and diving in, and Reframing perspectives. Participating in Wonder Labs allowed mothers, healthcare professionals, and students to contribute to deepening experiences and gain an expanded understanding of what is at play in caring for children with life-limiting and life-threatening conditions. Through working in pluralised groups, frames of reference and understandings complemented each other and could change. Participants often adopted a more open attitude towards others involved in care after participating and adapted day-to-day practices. Deliberating within paediatric palliative care on sensitive issues and their underlying personal and professional beliefs and values must be part of working together, without specific care situations being the catalyst. This may foster the mutual understanding needed in searching for quality of life, death, and bereavement.
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Societal developments show that future demands for visualization can be expected to grow. In many areas of organized human activities organizations may turn away from textual and numerical flatlands, and rely on the convenient and multidimensional digital worlds. Virtual worlds for facility management, design, and planning are no exception, it has an enormous potential to help organizations finding the right spaces that fit the human activities they perform. However, a major take-up of virtual worlds in this context allowing a comparison between present and future, is yet to come. Perhaps such applications, interweaving virtual and real worlds in order to design better facilities are at its beginning stages. One thing is clear: sophisticated applications may have remained absent until today, but it will come to us. Digital worlds start to normalize and the design of organizational spaces can benefit from that development. In this current article the effects of the proposed integrationof visualization with facilities were studied in a case study design. It was assessed whether the participants would actually change the design, without data on the organizational performance, and to what extent this affected staff satisfaction. This study however showed no design changes and no statistically significant changes in the affective responses ofparticipants between pre-test and post-test stages. However, in this current case the sample size may have been too small for generalization purposes. The connection of virtualworlds with organizational data, which were not applied in this current case but were in fact applied in our earlier studies, may be vital for the efficacy of interactive facility management, design, and planning. It is concluded that data on organizational performance serve as a linking pin between facility management and virtual worlds. Interaction can thus be improved by using organizational data as ‘subtitles’ which stimulate a more active use of the visualization.
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Abstract Despite the numerous business benefits of data science, the number of data science models in production is limited. Data science model deployment presents many challenges and many organisations have little model deployment knowledge. This research studied five model deployments in a Dutch government organisation. The study revealed that as a result of model deployment a data science subprocess is added into the target business process, the model itself can be adapted, model maintenance is incorporated in the model development process and a feedback loop is established between the target business process and the model development process. These model deployment effects and the related deployment challenges are different in strategic and operational target business processes. Based on these findings, guidelines are formulated which can form a basis for future principles how to successfully deploy data science models. Organisations can use these guidelines as suggestions to solve their own model deployment challenges.
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ackground and aim – Driven by new technologies and societal challenges, futureproof facility managers must enable sustainable housing by combining bricks and bytes into future-proof business support and workplace concepts. The Hague University of Applied Sciences (THUAS) acknowledges the urgency of educating students about this new reality. As part of a large-scale two-year study into sustainable business operations, a living lab has been created as a creative space on the campus of THUAS where (novel) business activities and future-proof workplace concepts are tested. The aim is to gain a better understanding amongst students, lecturers, and the university housing department of bricks, bytes, behavior, and business support. Results – Based on different focal points the outcomes of this research present guidelines for facility managers how data-driven facility management creates value and a better understanding of sustainable business operations. In addition, this practice based research presents how higher education in terms of taking the next step in creating digitized skilled facility professionals can add value to their curriculum. Practical or social implications – The facility management profession has an important role to play in the mitigation of sustainable and digitized business operations. However, implementing high-end technology within the workplace can help to create a sustainable work environment and better use of the workplace. These developments will result in a better understanding of sustainable business operations and future-proof capabilities. A living lab is the opportunity to teach students to work with big data and provides a playground for them to test their circular workplace, business support designs, and smart building technologies.
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The report from Inholland University is dedicated to the impacts of data-driven practices on non-journalistic media production and creative industries. It explores trends, showcases advancements, and highlights opportunities and threats in this dynamic landscape. Examining various stakeholders' perspectives provides actionable insights for navigating challenges and leveraging opportunities. Through curated showcases and analyses, the report underscores the transformative potential of data-driven work while addressing concerns such as copyright issues and AI's role in replacing human artists. The findings culminate in a comprehensive overview that guides informed decision-making in the creative industry.
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Trustworthy data-driven prognostics in gas turbine engines are crucial for safety, cost-efficiency, and sustainability. Accurate predictions depend on data quality, model accuracy, uncertainty estimation, and practical implementation. This work discusses data quality attributes to build trust using anonymized real-world engine data, focusing on traceability, completeness, and representativeness. A significant challenge is handling missing data, which introduces bias and affects training and predictions. The study compares the accuracy of predictions using Exhaust Gas Temperature (EGT) margin, a key health indicator, by keeping missing values, using KNN-imputation, and employing a Generalized Additive Model (GAM). Preliminary results indicate that while KNN-imputation can be useful for identifying general trends, it may not be as effective for specific predictions compared to GAM, which considers the context of missing data. The choice of method depends on the study’s objective: broad trend forecasting or specific event prediction, each requiring different approaches to manage missing data.
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Full tekst beschikbaar voor gebruikers van Linkedin. Driven by technological innovations such as cloud and mobile computing, big data, artificial intelligence, sensors, intelligent manufacturing, robots and drones, the foundations of organizations and sectors are changing rapidly. Many organizations do not yet have the skills needed to generate insights from data and to use data effectively. The success of analytics in an organization is not only determined by data scientists, but by cross-functional teams consisting of data engineers, data architects, data visualization experts, and ("perhaps most important"), Analytics Translators.
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