This study investigates the development of open access (OA) to journal articles from authors affiliated with German universities and non-university research institutions in the period 2010–2018. Beyond determining the overall share of openly available articles, a systematic classification of distinct categories of OA publishing allowed us to identify different patterns of adoption of OA. Taking into account the particularities of the German research landscape, variations in terms of productivity, OA uptake and approaches to OA are examined at the meso-level and possible explanations are discussed. The development of the OA uptake is analysed for the different research sectors in Germany (universities, non-university research institutes of the Helmholtz Association, Fraunhofer Society, Max Planck Society, Leibniz Association, and government research agencies). Combining several data sources (incl. Web of Science, Unpaywall, an authority file of standardised German affiliation information, the ISSN-Gold-OA 3.0 list, and OpenDOAR), the study confirms the growth of the OA share mirroring the international trend reported in related studies. We found that 45% of all considered articles during the observed period were openly available at the time of analysis. Our findings show that subject-specific repositories are the most prevalent type of OA. However, the percentages for publication in fully OA journals and OA via institutional repositories show similarly steep increases. Enabling data-driven decision-making regarding the implementation of OA in Germany at the institutional level, the results of this study furthermore can serve as a baseline to assess the impact recent transformative agreements with major publishers will likely have on scholarly communication.

Zusammenfassung Analysen im Bereich des Open-Access-Publizierens haben sich mit der Verfügbarkeit großer vernetzter Datensammlungen wie Unpaywall bedeutend vereinfacht. Der Artikel untersucht die Entwicklung des Datenbestands und der -struktur seit 2018. Eine Vollerhebung der Zeitschriftenartikel des Zeitraums 2008–2018 zeigt, dass der OA-Anteil kontinuierlich wächst. Allerdings variiert die OA-Kategorisierung, was methodische Fragen beim Publikationsmonitoring und in der bibliometrischen Forschung aufwirft.

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Light microscopy is an important instrument in life sciences. Over the last two decades, superresolution fluorescence microscopy techniques have been established, breaking the Abbé diffraction barrier, which before had posed a resolution limitation for over a century. The fundamentally new idea of these approaches is to use optically switchable fluorophores in order to detect features within the resolution limit imposed by the diffraction barrier consecutively instead of simultaneously. However, the relatively long imaging times needed in many modern superresolution fluorescence microscopy techniques at the nanoscale, one of them being single marker switching (SMS) microscopy, come with their own drawbacks. The challenge lies in the correct alignment of long sequences of sparse but spatially and temporally highly resolved images. This alignment is necessary due to rigid motion of the displayed object of interest or its supporting area during the observation process. In this thesis, a semiparametric model for motion correction, including drift, rotation and scaling of the imaged specimen, is used to estimate the motion and correct for it, reconstructing thereby the true underlying structure of interest. This technique is also applicable in many other scenarios, where an aggregation of a collection of sparse images is employed to obtain a good reconstruction of the underlying structure, like, for example, in real time magnetic resonance imaging (MRI).Further motivation and a more detailed description of the SMS imaging method are given in Chapter 1. In Chapter 2, a semiparametric model is developed and M-estimators for the parameters of the motion functions are derived, which are obtained by minimizing certain contrast functionals. The basic idea is to perform a two-step estimation, where the motion deformations are linearized by applying the Fourier-Mellin transform to the squared Fourier magnitudes of the obervations. This allows to estimate rotation and scaling in a first step, correct for it, and subsequently estimate translational drift. The main theoretical results, namely consistency as well as asymptotic normality of the motion parameter estimators are established in Chapter 3. Additionally, consistency of the final plug-in image estimator is obtained. The results of a simulation study and an application to real SMS microscopy data are presented in Chapter 4, demonstrating the practicability of this purely statistical method. It is shown to be competitive with state of the art calibration techniques which require to incorporate fiducial markers. Moreover, a simple bootstrap algorithm allows to quantify the precision of the motion estimate and visualize its effect on the final image estimation. A summary of the findings and outlook can be found in Chapter 5. We argue that purely statistical motion correction is even more robust than fiducial tracking rendering the latter superfluous in many applications. The proofs are presented separately in Chapter 6. Some auxiliary results are deferred to Appendix A viii ...