The members of the OSC, in alphabetical order:
I am professor for Quantitative Methods of Social Research at the Department of Sociology.
One of my research interests is publication bias and the low replicability of research. I am convinced that social institutions such as norms of transparency, sharing data and analyses codes, establishing good practices of replication, and further measures of OS are important to advance the quality of research. Analyses codes of my publications are available.
I am head of the Department of Radiation Oncology at the University Hospital Munich.
I am deputy head of the Core Facility Statistical Consulting at the Helmholtz Zentrum Munich.
I realized already at a very early stage of my career how scientific results can be affected by subjective / doubtful decisions made before, during or even after the data analysis process, such as lack of a clear pre-specified hypothesis, preliminary analysis during the time of data collection, data analysis without well-documented or even any program code, or p-hacking. In my current position, one of my responsibilities is to advocate PhD candidates and young postdocs in good scientific practice related to statistical analysis. Additionally, I am planning to make my program codes from previous and future projects publicly available, where possible.
I am professor for Computational Statistics at the Department of Statistics.
I have published about proper benchmarking in machine learning and optimization. Furthermore, I am one of the founders and core members of the OpenML platform for open and reproducible machine learning (www.openml.org).
I am professor for Computational Molecular Medicine at the Department of Medical Informatics, Biometry and Epidemiology.
Since 2009, I have been initiating and conducting projects on research reproducibility, validation, reporting, fishing for significance and false research findings, publication bias, benchmarking, and neutral comparisons of statistical methods; some of these activities are funded by the German Research Foundation (DFG). I am a Chair of the "simulation panel" of the STRATOS initiative and the Associate Editor for Europe of Briefings in Bioinformatics, a journal specialized in reviews and comparison studies.
I am professor for Empirical Communication Research at the Department of Communication Studies and Media Research.
In my field of research, Open Science, reproducibility, and replicability are intensively discussed. We are thinking about replication journals, regulations for data archiving, and Open Access. However, no structural decisions have been made so far, neither at our department nor in the field as far as I oversee it.
I am professor for Quantitative Methods and Social Inequality at the Department of Sociology.
Open Science has been essential for me since my first publication back in 1990 when I prepared a CD-ROM with reproducible analysis code (and wondered, why nobody asked for it). Today, my team gathers large-scale survey data (German Family Panel) which we provide to the research community as a service.
I am professor for Psychological Methods and Assessment at the Department of Psychology.
Research transparency is a core value of my working group. In my term as managing director of the Department Psychology, I supported the foundation of the department's Open Science Committee (https://osf.io/mgwk8/) in July 2015. Furthermore, many members of my working group signed the „Commitment to Research Transparency and Open Science“ (http://www.researchtransparency.org/signatories/).
I am professor for clinical psychology and psychotherapy.
I am professor for Finance and Banking at the Munich School of Management.
I consider data transparency and replicability of scientific studies as key elements of good scientific research practices. Therefore, jointly with the ifo Institute, we have established an IT infrastructure (https://www.cesifo-group.de/de/ifoHome/ facts/EBDC/EBDC-Archiv.html) at LMU’s Economics and Business Data Center (EBDC) which allows interested researchers on-site access to stored data for replication purposes. The structure also allows data to be anonymized (if necessary).
I am professor at the Institute of Stroke and Dementia Research. My research focus centers on identifying predictive models of disease progression in Alzheimer’s disease and understanding core brain changes that underlie dementia symptoms and cognitive resilience.
Sharing data, replicability and transparency are of key importance for successfully advancing clinical science. I am looking forward to the collaboration with the OSC.
I am the Medical Director of the University Hospital Munich.
Performing basic scientific and clinical studies in the field of schizophrenia research for the last 30 years, I am very interested in replicable findings and an openness for the community to work with our data. We have just been able to publish our first paper open-science and hope many more to come.
I am professor for Psychology of Excellence in Buisness and Education at the Department of Psychology.
My area of research is educational psychology and my passion is to understand basic psychological principles through exploring their relevance in the applied field of teaching and learning. I consider the Open Science movement a wonderful opportunity to focus again on the key prerequisites of high-quality scientific inquiry : In-depth theorizing, rigorous hypothesizing, precise operationalizing, stringent analyzing, and -- only then -- wrapping our heads around what the results may mean.
I am professor for Computational Biology at the Helmholtz Zentrum Munich.
I am professor of Social Psychology at the Department of Psychology. The recent discussions about the replicability of psychological effects gave me some pause. I hope (and somehow believe) that "open science" has the potential to increase replicability rates and to raise the quality of psychological research. As member of the executive board of the German Psychological Society, I have contributed to the development and implementation of recommendations regarding data sharing in the scientific community. In my own lab, I encourage the use of open science practices and a full commitment to openness and transparency in our research projects.
I am currently leading the Intercultural Communication Certificate Program at LMU.
I am convinced that social research always needs to be open resource in order to fit in into the international research community. Moreover, research must be discussed and verified by other scholars in order to become more validated. Discussions within OSC will give us, scientists a critical perspective, which will make our scholarship stronger and more creative. Therefore, I welcome the OSC at LMU-Munich and hope to stay an active member of it.
I am professor for Learning Sciences Research Methodlogies at the Department of Psychology.
We make reproducible analysis code available for every publication, see our „Commitment to Research Transparency and Open Science“ (http://www.researchtransparency.org/ signatories/). Starting 1 January 2017, I will not offer comprehensive review for, nor recommend the publication of, any manuscript that does not meet the minimum requirements of the „Peer Reviewers' Openness Initiative“ (https://opennessinitiative.org/signatories/). As acting director of the Doctoral Training Program of the Munich Center (DTP), I also work on incorporating research transparency into the DTP.
I am a postdoctoral researcher at the Institute for Medical Information Processing, Biometry, and Epidemiology.
As a statistician, I believe that we not only need to promote transparency in research, but also to provide
guidance on how to apply research methods in a way that will improve the replicability of research findings.
In my research, I engage in projects on the effects of fishing for significance on statistical inference and on methods that allow to handle the variability of results when applying alternative analytical strategies (involving for instance different data pre-processing steps and method choices). In my consulting activities, I try to convey these ideas in order to raise awareness on how common research practices can have devastating effects on the replicability of research findings.
I am postdoctoral researcher at the Department of Economics, Seminar of Economic Theory. My main research field is microeconomic theory and behavioral economics, but I also have several projects on replication and meta-analysis.
I am a physicist at the Department of Radiology, and I am interested in the application of data science methods in radiological and clinical research. By training, I am a magnetic resonance imaging physicist, with a focus on image post-processing and quantification of tissue perfusion. Recently, I have extended my technical portfolio towards automated image analysis and machine learning for classification and prognosis from medical images, such as computed tomography or magnetic resonance tomography. Open science and reproducible research in this field is highly relevant, especially with complicated image post-processing, deep learning or machine learning. While it is easy to share analyses and code, the sensitive nature of medical images and associated clinical data poses challenges with respect of public data sharing. I believe the Open Science Center provides the ideal framework to address these challenges.
I am research assistant and licenced psychologist at Department for Psychiatry and Psychotherapy at the University Hospital Munich.
I am professor for Computer Science at the Institute of Informatics.
I am professor for Romance Linguistics.
The framework for science communication has radically changed during my generation. But this has not only produced the complex questions of research data management; at the same time, strict ethical maxims have arisen which are very well expressed by the FAIR principles: Our data must be findable, accessible, interoperable and reusable. Reasonable rules for transparency and openness in research is to the benefit of the community of researchers and an obvious indicator of its vitality. Those who reject this social contract accept the disappearance of numerous, not least small, disciplines traditionally labelled with the (very German) name of 'Geisteswissenschaften'.
I am professor for Applied Physical Geography and Environmental Modeling at the Department of Geography.
I specialize in analyzing the impacts of climate change on water and land resources on regional scales. While I am aware of the broad acceptance of open science principles in the climate science community, I am also witnessing a considerable lack thereof in other areas of my research domain. With many years of experience in associate editing for high-level scientific journals, I am convinced that the need for research transparency, validation, code and data sharing is more necessary than ever.
I am professor for General Psychology (Emotion and Motivation) at the Department of Psychology.
Good scientific research practices require large sample studies as well as confirmatory studies. As such, the chair of General Psychology II established a lab that aims to help researchers to effectively and quickly run their studies under controlled conditions.
I am professor for Biometrics and Bioinformatics at the Institute of medical informatics, biometry and epidemiology.
We support data sharing and Open Science in the sense of the FAIR statement (https://www.dtls.nl/fair-data/): Data should be findable (unique and persistent identifier, description of metadata), accessible (retrievable in open formats with appropriate license and access conditions), interoperable (ready to be combined with other datasets), and reusable (offering documentation needed to understand the data and analysis).
I am an assistant professor at the Munich Center for Mathematical Philosophy.
I am a specialist in Psychiatry, Psychotherapy, and Neurology at the University Hospital Munich.
I am Professor of Macroeconomics and Public Finance at the Department of Economics, Director of the ifo Center for Macroeconomics and Surveys and in the Board of Directors of the LMU-ifo Economics & Business Data Center (EBDC).
Replicability of empirical studies is a must for “good scientific practice”. The EBDC is offering such opportunities (https://www.cesifo-group.de/ifoHome/facts/EBDC/EBDC-Archiv.html) and I hope that many researchers will make use of the opportunities that we offer.
I am head of the Alzheimer Treatment and Research Centre at the Department of Psychiatry and Psychotherapy at the University Hospital Munich.
I am professor for Experimental Stroke Research at the Institute for Stroke and Dementia Research.
I am interested in topics related to good scientific practice, particularly regarding data acquisition, analysis, and storage.
I am a postdoctoral researcher at the Munich Center for Mathematical Philosophy (MCMP).
I am a postdoctoral researcher at the Department of Statistics.
I support transparency and reproducibility in statistical methodology research by serving as the reproducible research editor at Biometrical Journal and by encouraging students and collaborators to utilize the great tools for reproducible data analysis we now have at our disposal in the form of public code repositories, permanent object identifiers for data sets and figures and literate programming frameworks that combine analyses and their description within a single document.
I am a postdoctoral researcher at the Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy.
For me, openness is intrinsically linked with high quality of research. Studies with open methods, materials, and data allow other researchers to find and correct potential mistakes and build on other labs' work rather than spending time and resources on re-developing methods and ideas. I make my own research, including materials, data, and analysis scripts, publicly available. I also promote Open Science in talks at workshops and seminars. Since April 2018, I organise a monthly event called Open Science Beers, which aims to bring together scientists across fields for informal conversations about Open Science.
I am principal investigator for Psychological Methods and Assessment at the Department of Psycholgoy.
The reproducibility of research findings is a core criterion of science, which however, has been challenged by the failure of recent large-scale replication projects. To foster open science practices, I teamed up with colleagues and established our department's "Open Science Committee" in 2015. The outcomes of this committee include an open science paragraph which we included in all recent professorship job descriptions, adding transparency criteria to the department's performance-based funding system, or introducing modules on preregistrations, open data, and reproducible scripts as mandatory components in undergraduate courses. ...
I am a Professor for Cardiovascular Immunology at the University Hospital Munich.
We focus on basic and translational research in cardiovascular diseases and inflammation. Research transparency and reproducibility are of pivotal importance in all areas of science. In addition to data availability and open access publishing, I am also committed to transparent peer review in order to improve trust and comprehensibility of review processes.
I am a Principle Investigator at the Department of Neurology in Klinikum Großhadern. My primary research interest is in how pain is processed in the human brain.
I have observed that not all study participants exhibited the effects that are reported in group statistics, indicating that results reported in publications are highly dependent on the study sample. In my experience results have been withheld because they were not in line with previously published findings.
Therefore I am planning to make my data and my code publicly available.
I am an Assistant Professor at the Geschwister Scholl Institute of Political Science.
As a Linux user myself, I support the use of open source software both in teaching and research. I am currently collecting historical tax and social policy data worldwide, that will be available for public use. My discipline, political science, is becoming much more open, but especially when it comes to open access publishing there is still a long way to go. I hope to positively contribute to this journey.
I do not only want to make my own research open and reproducible but want to help others do the same. This is why I am a contributor for the Journal of Statistical Software (a free open access journal), OpenML (an online tool for open machine learning), School of Data (a network for teaching data skills), and other projects.
I am a postdoctoral researcher at the Core Facility Statistical Consulting group of the Helmholtz Zentrum Munich.
I am medical doctor at the Department of Psychiatry at the University Hospital Munich.
I am Professor of Empirical Political Research and Policy Analysis at the Political Science Department, LMU.
Availability of data and routines of published work is key for scientific efficiency and progress.
Re-analysis of published work by students contributes to the development of new ideas and designs.
I am postdoctoral researcher at the Chair for Empirical Innovation Economics (http://www.inno.econ.uni-muenchen.de) and at the LMU-ifo Economics & Business Data Center (EBDC) (https://www.ifo.de/ebdc).
At the EBDC we offer guidance and courses on good scientific practices and research data management. In addition, researchers have the opportunity to archive their research data at EBDC and make it available for replication and secondary research projects.
I am professor for Empirical Economic Research at the Department of Economics.
I am professor for Molecular Animal Breeding and Biotechnology at the Department of Veterinary Sciences.
I am the Chair of Palaeontology & Geobiology in the Department of Earth and Environmental Sciences, Speaker of the GeoBio-Center, and currently Dean of the Faculty of Geosciences.
We have published open access since more than a decade and provide our data on open science repositories such as OpenDataLMU and GitHub, because open access to scientific results and the underlying data is imperative to enable reproducible research. Open science is the future!