‘DIY’ Research Data Management Training Kit for Librarians

Abstract – This paper discusses extended professional development training in research data management for librarians piloted at the University of Edinburgh. This is framed by the evolving research data management Roadmap at the University, national and international initiatives in managing research data by bodies such as Jisc and LIBER, and the subsequent need to ‘up skill ’ information professionals in the emerging area of academic research data management. This knowledge-transfer exercise includes independent study based on the research data MANTRA course and reflective writing, face to face sessions with different speakers giving short presentations followed by discussion, and group exercises. The resultant training ‘kit ’ was released in Spring 2013 with an open licence for other institutions, particularly those without local research data management expertise, to utilise for ‘DIY ’ RDM training

Supporting Research Data Management and Open Science in Academic Libraries: a Data Librarian’s View

Die „Datenrevolution“ hat sich auf die WissenschaftlerInnen aller Disziplinen ausgewirkt. Als ob die traditionelle Arbeit in der Lehre, im Wettbewerb um Stipendien und Förderungen, in der Forschung und bei der Veröffentlichung von Forschungsergebnissen nicht schon anspruchsvoll genug wäre, müssen sie grundlegende Veränderungen in der Art und Weise vornehmen, wie sie all diese Dinge tun. Eine ähnliche Veränderung ist bei den wissenschaftlichen BibliothekarInnen zu beobachten. BibliothekarInnen, denen beigebracht wurde, die Bedürfnisse ihrer NutzerInnen aufgrund von Informationsknappheit zu befriedigen, müssen nun umlernen, um den NutzerInnen bei der Bewältigung der Informationsflut zu helfen. Darüber hinaus finden sich BibliothekarInnen bereits zunehmend im Forschungsprozess wieder und versuchen, ihre NutzerInnen bei der Verwaltung sperriger Datenmengen zu unterstützen. So verunsichernd dies auch sein mag, sind dies spannende Entwicklungen für den Bibliotheksberuf.The ‘data revolution’ has impacted researchers across the disciplines. As if the traditional work of teaching, competing for grants and promotion, doing research and publishing results was not challenging enough, researchers are required to make fundamental changes in the way they do all of these things. A similar shift can be seen for academic librarians. Librarians who were taught to meet the needs of their users based on information scarcity now need to retrain themselves to help users deal with information overload. Moreover, librarians increasingly find themselves ‘upstream’ in the research process, trying to assist their users in managing unwieldy amounts of data when their comfort zone is firmly ‘downstream’ in the post-publication stage. Unsettling as it may be, these are exciting developments for the library profession

El materialismo en Navidades de Madrid y noches entretenidas (1663) de Mariana de Carvajal y Saavedra: clase social y otras obsesiones

El texto Navidades de Madrid y noches entretenidas de Mariana de Carvajal es un compendio de costumbres y prácticas del siglo XVII español. En efecto, está repleto de descripciones detalladas del vestuario, etiqueta social, rangos aristocráticos y las costumbres cotidianas en el momento más álgido del Barroco. Es un friso que retrata una especie de cultura colectiva de la urbanidad madrileña incluyendo sus manías y preocupaciones. Mariana de Carvajal habrá sabido de la problemática de aquella época porque vivió sus propios conflictos que eran simulacros de ciertas obsesiones del Barroco todas relacionadas con la crisis social que caracterizó el reinado de los Austrias Menores (Felipe III, Felipe IV y Carlos II). El propósito de este estudio es de explorar cómo ilustra Mariana de Carvajal el nerviosismo secular sobre la situación económica, nobiliaria y de supervivencia social en sus novelas

Factors influencing student nurse decisions to report poor practice witnessed while on placement

Background: While it is commonly accepted that nursing care is generally of a good standard, it would be naïve to think that this is always the case. Over recent years concern about aspects of the quality of some nursing care has grown. In tandem with this, there is recognition that nurses do not always report poor practice. As future registrants, student nurses have a role to play in changing this culture. We know, however, relatively little about the factors that influence student decisions on whether or not to report. In the absence of a more nuanced understanding of this issue, we run the risk of assuming students will speak out simply because we say they should. Objectives: To explore influences on student decisions about whether or not to report poor clinical practice which is a result of deliberate action and which is witnessed while on placement. Methods: Qualitative interviews were conducted with thirteen pre-registration nursing students from the UK. Participants included both adult and mental health nurses with an age range from 20–47. Data were analysed to identify key themes. Category integrity and fit with data was confirmed by a team member following initial analysis. Results: Four themes emerged from the data. The first of these, ‘I had no choice’ described the personal and ethical drivers which influenced students to report. ‘Consequences for self’ and ‘Living with ambiguity’ provide an account of why some students struggle to report, while ‘Being prepared’ summarised arguments both for and against reporting concerns. Conclusion: While there is a drive to promote openness in health care settings and an expectation that staff will raise concerns about quality of care, the reality is that the decision to do this can be very difficult. This is certainly the case for some student nurses. Our results suggest ways in which educationalists might intervene to support students who witness poor practice to report

Social Network Based Substance Abuse Prevention via Network Modification (A Preliminary Study)

Substance use and abuse is a significant public health problem in the United States. Group-based intervention programs offer a promising means of preventing and reducing substance abuse. While effective, unfortunately, inappropriate intervention groups can result in an increase in deviant behaviors among participants, a process known as deviancy training. This paper investigates the problem of optimizing the social influence related to the deviant behavior via careful construction of the intervention groups. We propose a Mixed Integer Optimization formulation that decides on the intervention groups, captures the impact of the groups on the structure of the social network, and models the impact of these changes on behavior propagation. In addition, we propose a scalable hybrid meta-heuristic algorithm that combines Mixed Integer Programming and Large Neighborhood Search to find near-optimal network partitions. Our algorithm is packaged in the form of GUIDE, an AI-based decision aid that recommends intervention groups. Being the first quantitative decision aid of this kind, GUIDE is able to assist practitioners, in particular social workers, in three key areas: (a) GUIDE proposes near-optimal solutions that are shown, via extensive simulations, to significantly improve over the traditional qualitative practices for forming intervention groups; (b) GUIDE is able to identify circumstances when an intervention will lead to deviancy training, thus saving time, money, and effort; (c) GUIDE can evaluate current strategies of group formation and discard strategies that will lead to deviancy training. In developing GUIDE, we are primarily interested in substance use interventions among homeless youth as a high risk and vulnerable population. GUIDE is developed in collaboration with Urban Peak, a homeless-youth serving organization in Denver, CO, and is under preparation for deployment

Economic and psychological approaches to risk-bearing : theory and experimental evidence / BEBR No. 603

Title page includes summary.Includes bibliographical references (p. 44-45)