Open Data in Science

Open Data (OD) is an emerging term in the process of defining how scientific data may be published and re-used without price or permission barriers. Scientists generally see published data as belonging to the scientific community, but many publishers claim copyright over data and will not allow its re-use without permission. This is a major impediment to the progress of scholarship in the digital age. This article reviews the need for Open Data, shows examples of why Open Data are valuable, and summarizes some early initiatives in formalizing the right of access to and re-use of scientific data.     

Organization for corporate development

In this article the author emphasizes that there is no generally applicable organization for corporate development. Nonetheless, he stresses the need for whatever organization is set up to be staffed by very few very senior people who are willing to be judged by results.     

Integrating a Top‐Down and a Bottom‐Up Approach: Formal and Informal Risk‐Handling Strategies in a Utility Company

In this study, we bring together a top‐down and a bottom‐up approach of risk handling. We do so by conceptualizing and qualitatively and quantitatively measuring formal and informal risk‐handling strategies in a Dutch utility company. We conceive of formal risk handling as regulating, training, and educating safety and enforcing rule compliance, while we distinguish three different informal risk‐handling strategies: discretionary specialization, tacit knowledge, and taking personal responsibility. We show that the formal risk‐handling strategy and the three informal risk‐handling strategies can be measured separately. Hence, we have validated the measurement of all four strategies derived from two different risk‐handling approaches. Moreover, we have demonstrated that the perceived use of the four strategies has different effects on unsafe behavior: formal risk handling and tacit knowledge decrease it, discretion increases it, and taking personal responsibility has no effect on unsafe behavior.     

Learning in Public Sector Organizations: A Theory of Action Approach

The importance of learning has since long been acknowledged for both business and public sector organizations. However, learning theory and research have tended to neglect the differences between these organizations, and to develop in separate and unrelated directions. To address these developments, this paper purports, first, to develop a theoretical framework that integrates various concepts from the fields of public policy learning and organizational learning, and that is specifically directed at public sector organizations. Second, the paper purports to illustrate the utility of this framework by applying it to policy-making in a Dutch municipality, the Pegasustown prostitution case.     

Zustandsorientierte Maschinenzuordnungs- und Instandhaltungsplanung

Previous research focuses on preventive maintenance strategies which minimize the costs of break downs and of maintenance activities. Deteriorating machine conditions with the consequence of rising scrap rates and declining productivity are mostly neglected. This paper investigates simultaneous optimization of production and maintenance planning by applying the condition-based maintenance strategy with parallel machines and overlapping capabilities. The presented model allows exploitation of machine wear considering optimal order assignments to machines which is illustrated by a numerical example.     

Model weights for model choice and averaging

A method is suggested to estimate posterior model probabilities and model averaged parameters via MCMC sampling under a Bayesian approach. The estimates use pooled output for J models (J>1) whereby all models are updated at each iteration. Posterior probabilities are based on averages of continuous weights obtained for each model at each iteration, while samples of averaged parameters are obtained from iteration specific averages that are based on these weights. Parallel sampling of models assists in deriving posterior densities for parameter contrasts between models and in assessing hypotheses regarding model averaged parameters. Four worked examples illustrate application of the approach, two involving fixed effect regression, and two involving random effects.     

The identity career of the graduate student: Professional socialization to academic sociology

The pathway through graduate school is challenging and difficult. Nearly everyone, at one point or another, confronts the existential question of whether they want to drop out or to continue. Several challenges emerge as key to graduate students’ success in progressing through their programs. p]The first is moving from the secure but sometimes suffocating structure of a core graduate cohort into the role of independent student. This requires navigating an individual pathway into areas of specialization and a mentor. Programs can do no more than make faculty and courses available; from there, students must make connections and decisions on their own. The second critical transition involves moving from absorbing to creating knowledge. Accomplishing this requires that students grasp the conceptual foundation of the perspective (the “sociological eye”), learn how to gather data, to master the challenge of moving from immersion in the specificity of their research to contribute to more abstract theory, and to understand the conventions through which they must present their scholarly work. Along the way there are myriad interpersonal challenges for them to negotiate. Allegiances that they forge are then relinquished to make way for new, more stage-relevant ones. Students often undergo radical changes in their values and consciousness as they progress through their programs. They are bonded into an equalitarian model of evaluation and support in their cohesive, early years in the cohort. But as they forge scholarly accomplishments and turn their eyes increasingly toward the discipline, they recognize that their democratic ideals must yield to the meritocratic reality of the profession.