Abstract: With the adoption of values, principles, practices, tools and processes from Agile, Lean, and DevOps, knowledge preservation has become a serious issue because documentation is largely left out. We identify two questions that are relevant for knowledge acquisition and distribution concerning design decisions, rationales, or reasons for code change. The first concerns which knowledge is required upfront to start a project. The second question concerns continuation after initial development and addresses which knowledge is required by those who deploy, use or maintain a software product. We evaluate two relevant approaches for alleviating the issues, which are ‘Just enough Upfront’ and ‘Executable Documentation’ with a total of 25 related artifacts. For the evaluation, we conducted a case study supported by a literature review, organizational and project metrics, and a survey. We looked into closed source-code and closed classified source-code. We found two conclusive remarks. First, g it commit messages typically contain what has been changed but not why source-code has been changed. Design decisions, rationale, or reasons for code change should be saved as close as possible to the source-code with Git Pull Requests. Second, knowledge about a software product is not only written down in artifacts but is also a social construction between team members.
Does pervasive technology have a role to play in supporting the communication of busy couples? Especially when they are already living together and already have a high degree of awareness of each other's rhythms of daily life, their whereabouts and needs? A two week long field study of an awareness system allowed eight working couples to automatically exchange place, activity and calendar information as well as messages and photos. Data analysis provides both qualitative and quantitative evidence which suggest strongly that such a system can provide support for availability, coordination, reassurance and affection for this group. Findings which inform the design of such systems are: the need for transitions in places instead of location information to support coordination, the two tracks of daily communication of busy parents (reassurance and emergency) and usability barriers in current mobile applications which prevent this group from engaging in photo sharing. The contexts and unexpected uses that participants found in the system are described in detail.
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The principal aim of this study is to explore the relations between work domains and the work-related learning of workers. The article is intended to provide insight into the learning experiences of Dutch police officers during the course of their daily work. Interviews regarding actual learning events and subsequent changes in knowledge, skills or attitudes were conducted with police officers from different parts of the country and in different stages of their careers. Interpretative analyses grounded in the notion of intentionality and developmental relatedness revealed how and in what kinds of work domains police officers appear to learn. HOMALS analysis showed work-related learning activities to vary with different kinds of work domains. The implications for training and development involve the role of colleagues in different hierarchical positions for learning and they also concern the utility of the conceptualisation of work-related learning presented here.
This project develops a European network for transdisciplinary innovation in artistic engagement as a catalyst for societal transformation, focusing on immersive art. It responds to the professionals in the field’s call for research into immersive art’s unique capacity to ‘move’ people through its multisensory, technosocial qualities towards collective change. The project brings together experts leading state-of-the-art research and practice in related fields with an aim to develop trajectories for artistic, methodological, and conceptual innovation for societal transformation. The nascent field of immersive art, including its potential impact on society, has been identified as a priority research area on all local-to-EU levels, but often suffers from the common (mis)perception as being technological spectacle prioritising entertainment values. Many practitioners create immersive art to enable novel forms of creative engagement to address societal issues and enact change, but have difficulty gaining recognition and support for this endeavour. A critical challenge is the lack of knowledge about how their predominantly sensuous and aesthetic experience actually lead to collective change, which remains unrecognised in the current systems of impact evaluation predicated on quantitative analysis. Recent psychological insights on awe as a profoundly transformative emotion signals a possibility to address this challenge, offering a new way to make sense of the transformational effect of directly interacting with such affective qualities of immersive art. In parallel, there is a renewed interest in the practice of cultural mediation, which brings together different stakeholders to facilitate negotiation towards collective change in diverse domains of civic life, often through creative engagements. Our project forms strategic grounds for transdisciplinary research at the intersection between these two developments. We bring together experts in immersive art, psychology, cultural mediation, digital humanities, and design across Europe to explore: How can awe-experiences be enacted in immersive art and be extended towards societal transformation?
Huntington’s disease (HD) and various spinocerebellar ataxias (SCA) are autosomal dominantly inherited neurodegenerative disorders caused by a CAG repeat expansion in the disease-related gene1. The impact of HD and SCA on families and individuals is enormous and far reaching, as patients typically display first symptoms during midlife. HD is characterized by unwanted choreatic movements, behavioral and psychiatric disturbances and dementia. SCAs are mainly characterized by ataxia but also other symptoms including cognitive deficits, similarly affecting quality of life and leading to disability. These problems worsen as the disease progresses and affected individuals are no longer able to work, drive, or care for themselves. It places an enormous burden on their family and caregivers, and patients will require intensive nursing home care when disease progresses, and lifespan is reduced. Although the clinical and pathological phenotypes are distinct for each CAG repeat expansion disorder, it is thought that similar molecular mechanisms underlie the effect of expanded CAG repeats in different genes. The predicted Age of Onset (AO) for both HD, SCA1 and SCA3 (and 5 other CAG-repeat diseases) is based on the polyQ expansion, but the CAG/polyQ determines the AO only for 50% (see figure below). A large variety on AO is observed, especially for the most common range between 40 and 50 repeats11,12. Large differences in onset, especially in the range 40-50 CAGs not only imply that current individual predictions for AO are imprecise (affecting important life decisions that patients need to make and also hampering assessment of potential onset-delaying intervention) but also do offer optimism that (patient-related) factors exist that can delay the onset of disease.To address both items, we need to generate a better model, based on patient-derived cells that generates parameters that not only mirror the CAG-repeat length dependency of these diseases, but that also better predicts inter-patient variations in disease susceptibility and effectiveness of interventions. Hereto, we will use a staggered project design as explained in 5.1, in which we first will determine which cellular and molecular determinants (referred to as landscapes) in isogenic iPSC models are associated with increased CAG repeat lengths using deep-learning algorithms (DLA) (WP1). Hereto, we will use a well characterized control cell line in which we modify the CAG repeat length in the endogenous ataxin-1, Ataxin-3 and Huntingtin gene from wildtype Q repeats to intermediate to adult onset and juvenile polyQ repeats. We will next expand the model with cells from the 3 (SCA1, SCA3, and HD) existing and new cohorts of early-onset, adult-onset and late-onset/intermediate repeat patients for which, besides accurate AO information, also clinical parameters (MRI scans, liquor markers etc) will be (made) available. This will be used for validation and to fine-tune the molecular landscapes (again using DLA) towards the best prediction of individual patient related clinical markers and AO (WP3). The same models and (most relevant) landscapes will also be used for evaluations of novel mutant protein lowering strategies as will emerge from WP4.This overall development process of landscape prediction is an iterative process that involves (a) data processing (WP5) (b) unsupervised data exploration and dimensionality reduction to find patterns in data and create “labels” for similarity and (c) development of data supervised Deep Learning (DL) models for landscape prediction based on the labels from previous step. Each iteration starts with data that is generated and deployed according to FAIR principles, and the developed deep learning system will be instrumental to connect these WPs. Insights in algorithm sensitivity from the predictive models will form the basis for discussion with field experts on the distinction and phenotypic consequences. While full development of accurate diagnostics might go beyond the timespan of the 5 year project, ideally our final landscapes can be used for new genetic counselling: when somebody is positive for the gene, can we use his/her cells, feed it into the generated cell-based model and better predict the AO and severity? While this will answer questions from clinicians and patient communities, it will also generate new ones, which is why we will study the ethical implications of such improved diagnostics in advance (WP6).
There is increasing interest for the use of Virtual Reality (VR) in the field of sustainable transportation and urban development. Even though much has been said about the opportunities of using VR technology to enhance design and involve stakeholders in the process, implementations of VR technology are still limited. To bridge this gap, the urban intelligence team of NHTV Breda University of Applied Sciences developed CycleSPEX, a Virtual Reality (VR) simulator for cycling. CycleSpex enables researchers, planners and policy makers to shape a variety of scenarios around knowledge- and design questions and test their impact on users experiences and behaviour, in this case (potential) cyclists. The impact of infrastructure enhancements as well as changes in the surrounding built environment can be tested, analysed an evaluated. The main advantage for planners and policy makers is that the VR environment enables them to test scenarios ex-ante in a safe and controlled setting.“The key to a smart, healthy and safe urban environment lies in engaging mobility. Healthy cities are often characterized by high quality facilities for the active modes. But what contributes to a pleasant cycling experience? CycleSPEX helps us to understand the relations between cyclists on the move and (designed) urban environments”
