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 a Research Associate and Lecturer at the Department of Statistics, LMU and part of the working groups Statistical Consulting Unit and Statistical Learning & Data Science.
As a consultant, I try to propagate good statistical practice in the applied sciences. As an educator, I try to raise awareness and sensitivity for open science issues like p-hacking and reproducibility. In my own research, I try to adhere to open science principles whenever possible, e.g., by sharing code and data, and by making manuscripts open access.
I am a statistician and epidemiologist at the Bavarian Health and Food Safety Authority, Privatdozent (Adjunct Lecturer) at TU München, and Academic Editor for PLOS ONE.
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. I make my program codes publicly available, wherever possible, and in the role of a reviewer or editor, I always ask the authors of submitted papers to do likewise.
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 a postdoctoral researcher at the Institute for Phonetics and Speech Processing. As a researcher, I wish to help increasing awareness within the Language sciences about the importance of openness, transparency, and reproducibility for ensuring replicability and accumulation of knowledge in the field. In particular, I am always on the look out for new methods that can streamline data processing and documentation, statistical models that can help us assess the degree of certainty of empirical results, and principles that can assist us in the formulation of statistical hypotheses that map more tightly to the research questions.
I am a principal investigator at the Institute for Cardiovascular Prevention (IPEK), University Hospital Munich and a lecturer at the Master Program Human Biology, LMU.
Open science is crucial to ameliorate reproducibility and replicability and to ultimately improve science. Changes in research are needed and I strongly believe that education is the way forward. As researchers not only should we implement good research practices such as integrity, transparency, and reliability in our own labs but also train the next generation of scientists and provide them the tools to progress the quality of science.
I am research group leader and Professor for Experimental Neurology at the Institute for Stroke and Dementia Research.
Research must always be performed in an open and reproducible fashion. This is especially true in the age of big data, which can facilitate questionable research practices, such as p-hacking. Sharing methodology, pre-specifying analyses and independent replication are the best tools to solve the reproducibility crisis. I’m looking forward to working with the Open Science center in order to promote Open Science.
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 Deputy 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 lecturer at the Geschwister-Scholl-Institut (GSI) for Political Science at the University of Munich (Ludwig-Maximilians-Universität).
For a free society to thrieve we need an open discussion of ideas. Our responsibility as a scienists is to do our part and be fully open with our procedures, tools and methods. Personally, I am commited to make it easy for others to replicate what I do, as it is the only way to review the procedures, to spot inconsistencies, and to provide new ideas to make science advance.
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 professor for epidemiology, specifically interested in successful ageing and the vestibular system, at the Department of Medical Informatics, Biometry and Epidemiology. In my team we try to adopt principles of Open Science into our daily work, e.g. by commenting code, verifying code and results, and by increasing awareness among project partners, collaborators and students.
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'm a postdoctoral researcher at the Chair for Statistics and Data Science in Social Sciences and the Humanities (SODA) at the Department of Statistics. I am mostly working on questions related to survey methodology and missing data.
I am very interested in open source software development and open data in statistics and sociology. I teach introductory and advanced statistical methods as well as statistical methods to sociology students and try to include topics on Open Science. In my own research, I try my best to publish reproducible analysis code and make available or use open data.
I am professor for Communication Science, especially Computational Communication Research, at the Department of Communication and Media.
While various principles of Open Science are embraced more in some parts of our field, others face severe challenges. The use of third-party data, for example, or working with individuals' personal data through surveys and in-depth interviews, stands in some contrast to the unlimited sharing of data and materials. In a recent DFG-funded project, we seek to identfy such challenges and potential solutions to them.
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 a professor for Biostatistics at the Department of Statistics. My research focuses on meta-analyses, compartment models and their application in medicine where I also want to strengthen replicability and reproducibility. I am also part of the reproducibility team of the Biometrical Journal to support transparency in statistical methodology.
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 leading the group for Clinical Data Science at the Department of Radiology. We employ advanced statistics, machine learning and computer vision techniques in the context of clinical radiology to enable fast and precise AI-supported diagnosis and prognostication. Open science and reproducible research in this field is highly relevant, especially with 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 head of the Statistical Consulting Unit (StaBLab) at the Department of Statistics, LMU. I want to integrate the ideas of open science and reproducable research into our consulting practice.
I am a principal investigator at the Munich Center for Mathematical Philosophy.
Imperfect data is a fact of life. I'm interested in drawing (causal) inferences from imperfect data. In particular, I'm interested in learning from biased data.
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 postdoctoral researcher in Developmental Psychology at the Department of Psychology. In my research I investigate the development of moral behavior and intergroup cognition. I try to follow the principles of Open Science as closely as possible, from preregistration to publishing of data and manuscripts.
I'm a group leader at the Institute of Computational Biology at the Helmholtz Zentrum München and a Professor for Biomedical Statistics and Data Science at the Department of Statistics.
I deeply care about open source software development in statistics and optimization and encourage students and collaborators to use public code repositories, open preprint servers, and permanent object identifiers for data sets for any of our research projects. In addition, I support fully reproducible open access analysis workflows accompanying any of our statistical or computational scientific articles.
I am currently a research scholar at the UC San Diego Health Department of Biomedical Informatics, USA, and a research assistant at the Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), LMU, Germany. I practice anesthesiology at the Medical Center of the University of Munich (LMU Klinikum), with additional experience in critical care. In December 2018, I joined the working group Anesthesia & Critical Care Informatics and Data Analysis Group (ACID).
My research interests are in perioperative medicine and developing predictive models for critically ill patients. In addition to exploring machine learning methods to personalize blood transfusion triggers, I am excited about being a team member of building an Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) data warehouse to establish a cross-institutional distributed ledger.
In my current project, Reliable Response Data Discovery for COVID-19 Clinical Consults using Patient Observations, many health institutions answer COVID-19 questions by consulting, in a privacy-protecting manner, data from electronic health records. We share concept definitions, query codes, and results to allow reproducibility. 'Open Science' can be the key for impactful research.
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 a postdoctoral researcher at the Chair of Psychological Methods and Assessment at the Department of Psychology.
I teach introductory and advanced statistical analysis to new psychologists, including topics on Open Science. In my own research, I try my best to publish reproducible analysis code, make available or use open data, and convince my coauthors to publish preprints or select journals with sustainable open access policies. In the future, I hope to contribute to meta scientific research to increase the replicability of psychological science.
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 a full professor at the Department of Media and Communications at the University of Klagenfurt. Before that, I was a researcher at the Department of Media and Communication at LMU. For me, open science is one of the most important and pressing issues for the scientific community as a whole. In my discipline, this topic has gained momentum in recent years, but there is still much to be done. Therefore, I would like to contribute to the promotion of open scientific practices within the communication community and help to make science more transparent, efficient and accessible to the public. Trust in science is of paramount importance for modern societies, and for me, open scientific practices are an indispensable part of this process.
I am a postdoctoral researcher at the Observatory of the LMU, working on planet formation. During my career I have come to understand how essential is openness into the scientific process, and how much it can help it to spur. I work with numerical simulations to recreate observations, in order to understand the physical processes at the base of planet formation. Many details can be hidden under the carpet, both from the observational and numerical side. In my work I am trying to explain all the assumptions made during my work, and I am planning to render more public all the codes and data used during the simulations and in the post-processing phase.
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 medical doctor and clinical researcher at the Department of Psychiatry of the University Hospital Munich.
I am a Principal Investigator and Professor at the Biomedical Center (BMC; LMU Munich). My research lab is interested in understanding the cellular principles, molecular mechanisms and mechanobiology of the immune system. I am convinced that research transparency, research reproducibility, and research data sharing is critical for the gain of knowledge in science. As my research frequently involves live-cell microscopy, I am further interested in the development of good scientific practices in data storage and data sharing of large imaging datasets.
I am a postdoctoral researcher at the Munich Center for Mathematical Philosophy (MCMP).
I’m a professor of marketing at the LMU Munich School of Management. While my main research interest is in the advancement of research methods to further the understanding of consumer behavior, I have gained interest in transferring principles of metrology—measurement science in the physical sciences—into the social sciences in an effort to improve replicability.
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 postdoctoral researcher at the chair of Quantitative Methods of Social Research (Department of Sociology). Besides my interest in researching the causes and contextual factors of social inequality using also meta-analytical tools I do methodological research on detection methods of publication bias and the assessment of scientific integrity. I am convinced that norms of transparency, sharing data and analysis files as well as establishing good practices of replication, and further interventions of open science are important to advance the quality as well as increase the efficiency of science.
My research is at the intersection of psychology and data-driven sciences. For my own work, it is very important to me to be transparent and to share analysis code, materials, and data (while respecting data privacy issues) to make a sustainable contribution to research in my field. In my teaching, I try to infect students with my enthusiasm for Open Science and thus to sensitize young people for 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 LMU Research Fellow at the Geschwister Scholl Institute of Political Science and an advocate of open science. I have been actively involved in teaching reproducible research. I am convinced that spreading knowledge about research transparency tools and practices helps to promote support for open science among students and the scientific community.
I am also a member of the catalyst network of the Berkeley Initiative for Transparency in the Social Sciences (BITSS).
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 Professor of International Comparative Public Policy at the Geschwister Scholl Institute of Political Science.
I am an elected member of the German Data Forum (RatSWD, 2020-2023) advising the government on expanding and improving the research data infrastructure for the empirical social, behavioural and economic sciences. My own discipline, political science, is becoming much more open, but compared to some other disciplines there is still a long way to go. I hope to positively contribute to this journey.
I am an advocate for open and reproducible research. I teach courses on good scientific practice and computational reproducibility and try to improve the way the research community operates.
I am a postdoctoral researcher at the Core Facility Statistical Consulting group of the Helmholtz Zentrum Munich.
I am heading the Bioinformatics Core Facility at the Biomedical Center, LMU.
Nowadays, first priority in my work as a scientist is to implement and teach reproducibility measures in basic life science. Looking back to 20 years of wet lab research I realized that I hardly ever designed an experiment properly. This is a common problem that will not be solved by top-down measures but by systematic education of new generations of scientists.
I am medical doctor at the Department of Psychiatry at the University Hospital Munich.
I am a principal investigator and associate senior researcher at the CVBE, Philosophy and the Munich Center for Neurosciences.
I am interested in trying to extend open science practices into areas of cognitive neuroscience where it is not established, such as in brain stimulation.
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 a postdoctoral researcher at the Department of Media and Communication. My field has been slowly but steadily adapting open science practices in the last few years. I try to promote open science by consequently following open science standards in my own research, by contributing to open-source research software development, and by integrating topics such as preregistration and reproducibility into my course syllabi. I am also part of an international multi-author team that suggests “An agenda for open science in Communication” in the Journal of Communication.
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!
I am professor emeritus for Theoretical Linguistics and German Linguistics.
In the first years of this century the extremely clever experimental design of Lera Boroditsky’s studies managed to undermine my deep skepticism about Neo-Whorfianism, so I encouraged my students to have a closer look. After several failed replications my skepticism regrew. Similarly with other early cases of experimental linguistics: a PhD dissertation I supervised dared to challenge a publication in the prestigious journal Language and got as much as five replication failures. Since then I am a strong supporter of OS (my recent study on new words includes a self-replication). I signed the Peer Reviewers’ Openness Initiative, and I encourage every student to observe Open Science practices.
I am a postdoctoral researcher at the Chair of Psychological Methods and Assessment at the Department of Psychology.
My research is at the intersection of motivational psychology, relationship research and psychological methods. As a signatory of the Commitment to Research Transparency and Open Science I am committed to implement openness and transparency in every step of my own research, and to encourage it in my reviews, as well as in cooperation with colleagues and students.