Die Workshops im Überblick

Workshop description:
Preregistration is becoming standard practice in various quantitative disciplines. Recently researchers have argued that preregistration might be applied to qualitative research as well. To develop a preregistration template that would provide a meaningful, common structure for a considerable range of qualitative approaches, we conducted a Delphi study among qualitative researchers. Join us to discuss the items included in the qualitative preregistration form, whether these items offer sufficient flexibility, and whether qualitative preregistration is relevant to all qualitative research.

Biography:
She is a PhD candidate at the VU University Amsterdam with a background in epidemiology, psychology and philosophy. In her PhD project, they focused on the role of the academic research climate in fostering research integrity Amsterdam (ARCA, see https://amsterdamresearchclimate.nl). From January until April 2020, she stayed at the Center for Open Science as a scholar in residence to develop a preregistration form for qualitative research. Her research interests include responsible conduct of research, research integrity, open science and meta science.

Workshop description:
In this two hour workshop, we will first have a brief look at a pre-registration: What is it, how and where can a study be pre-registered, and what purpose does it serve? We will then discuss reasons for pre-registration (and common misbeliefs against pre-registration) and will take the first steps towards a pre-registration on the Open Science Framework.

Biography:
Kai Horstmann is a Juniorprofessor of Psychology at Humboldt-Universität zu Berlin, where he also obtained his Ph.D. in 2018. His research focuses on the description, assessment, and prediction of momentary experiences and daily behavior. As a strong advocate for Open Science, he applies open science practices in his research such as pre-registration and the sharing of data and research materials. He has taught several workshops on Open Science, pre-registration, and data sharing. 

Workshop description:
Replication studies are pivotal to the advancement of science - but how can we plan a good one? This workshop will walk through how to pick a good study to replicate, what we can learn from different types of replication studies, and how to design a good replication study.

Biography: 
She is currently a postdoctoral researcher in the CoGDeV Lab at the University of Surrey on a project with Emily Farran and Camilla Gilmore. In this project they are studying the relationship between Lego construction ability, spatial thinking, and numeracy achievement.
She is committed to open science practice and passionate about methods for studying development, and how we can do better, more transparent, reproducible, and diverse science.
Her work includes pre-registration, Registered Reports, replication studies, open data and materials, reproducible analyses in R, and Bayes Factor Analysis of null results.

Find out more about Dr. Priya Silverstein on her website: https://priyasilverstein.wixsite.com/website or on Twitter: @priyasilverst

Workshop description:
“PhD students are the workhorses of academia, and are prone to abuse due to the extreme dependency from their supervisors. This workshop will cover which severe conflicts might arise (e.g., refusal of authorship, data fabrication), which structures universities offer to deal with these problems, and what else to keep in mind. Participants are encouraged to share their personal experiences and discuss how to change the system for the better”

Biography:
Martin is a meta-researcher at BIH QUEST Center, where he deals with incentive structures and metrics to assess the quality of biomedical research. He was trained as a psychologist and used to work in the field of clinical psychology at TU Dresden before he came to Berlin. Find Martin on twitter @MartinHolst9

Workshop description:
There’s no science without failure. Yet we are often led to believe this is not acceptable if we want to be good scientists. In this workshop we will explore failures in a safe and interactive way, with the CV of Failures history, a failure bingo, types of failures and ending with lessons about failure from 30+ researchers I interviewed for my How I Fail series. I will also address audience questions sent in before the workshop. 

Biography: 
Veronika Cheplygina received her Ph.D. in machine learning in 2015. After a posdoc at Erasmuc Medical Center, In 2017 she started as assistant professor of medical image analysis at Eindhoven University of Technology. Her research focuses on machine learning scenarios where few labels are available, such as transfer learning or meta-learning. In 2020 Veronika announced she is leaving her tenure track position in search of the next step where she can contribute to open & inclusive science. She blogs about these topics on https://www.veronikach.com, and gives talks and workshops to early career researchers. She also loves cats, which you will often encounter in her work.

Workshop description:

Today, more than ever, researchers play a crucial role in communicating science to the public, alongside professional communicators and journalists. To successfully reach broader audiences, it is important to focus on clear and comprehensible core messages.
During this science communication workshop, you can expect to learn the fundamentals of good communication, find out how to get involved and which paths are available to early career scientists.
Franziska will share her own journey as a science communicator as well as explain how researchers benefit from being present on social media. Participants will learn more about Berlin and Germany-based projects they can take part in and leave the workshop with a better understanding of why science communication is important.Workshop goals include building scientists’ communication skills and confidence in engaging with public audiences and providing best practices for use of different communication methods and mechanisms.

Biography: 
Franziska is a Vertebrate Paleontologist & Biology Master alumna of Freie Universität Berlin. She has always had a passion for science education and, communication, Open Access and the wish to give women in science a platform to showcase their research. Franziska studies dinosaur dentation and until recently worked on Tyrannosaurus rex tooth replacement at the Museum für Naturkunde Berlin, where she also has her own science education program, called "Kaffeeklatsch mit Wissenschaft" (Science Communication Café)  for which she invites speakers every month to talk about their research over coffee.
Website: https://franzisattler.com/
Twitter: https://twitter.com/ohyeahfranzi
Instagram: https://www.instagram.com/wisskommkaffee/

Workshop description:
Why should you care about reproducibility? In this workshop (2h), I will give you the answer and discuss the nuts and bolts of reproducibility. Spoiler: it is about getting the same results from the same analysis on the same data set. We discuss what can go wrong when trying to achieve reproducibility and derive some best practices to avoid common pitfalls. In the second half of the workshop, you'll have a chance to get your hands dirty with some practical examples in R using RStudio Cloud.

Workshop description:
This workshop aims to make explicit the various (and competing) philosophical assumptions that tacitly underlie scientific research. After all, without some working conception of what should count as evidence, what makes something a good theory, and how we should assess its successes and failures, science could not be functioning. Yet, there is often little time for researchers to systematically review these assumptions. Rather than thinking of philosophy as a fixed set of positions and debates, we will look at recurring themes and conceptual tools that can help better make sense of how science advances through controversies and the complex interplay of consensus and dissent.

Biography: 
Axel is a physicist-turned-philosopher of science and currently Professor of Theoretical Philosophy at Technische Universität Berlin, where he heads the Institute of History and Philosophy of Science, Technology, and Literature. Much of his work focuses on the question of how our knowledge practices influence conceptions of knowledge, justification, and responsibility. He is the author of two monographs (A Critical Introduction to Testimony, Bloomsbury 2014; How to Do Science With Models, Springer 2016) and has also published extensively on the epistemology of fake news (e.g., "Fake News: A Definition", 2018). 

Workshop description:
This workshop will equip participants with tools to conduct a transparent and reproducible meta-analysis. These tools include pre-registration, transparent analysis, and data sharing. A practical demonstration of a transparent meta-analysis using the free JAMOVI point-and-click program will also be included. Common pitfalls, such as dependent effect sizes and misinterpreting publication bias measures, will also be covered

Biography: 
Daniel S. Quintana is a researcher in biological psychiatry at the University of Oslo. His research interests include social behaviour, the oxytocin system, heart rate variability, autism spectrum disorder, and meta-analysis. He currently leads a project investigating the role of the oxytocin system in the development of severe mental illness and metabolic disorder, which is supported by an Excellence Project for Young Researchers grant from the Novo Nordisk Foundation.

Twitter: @dsquintana
Website: https://www.dsquintana.com/
 

Workshop description:
In this workshop we will go through the basics of a systematic review: What is a systematic review; how to frame your research question; what is the workflow of conducting a review, how and where to look for data; how do you interpret your findings and how do you ensure that your review is reproducible and transparently reported. The focus will be on systematic reviews in a biomedical context but the methods can be applied across disciplines. There will be plenty of time to discuss particular aspects depending on the participants’ interests.

Biography:
Kim is a Postdoctoral fellow at the Meta-Research Innovation Center Berlin (METRIC-Berlin) where he works with improving access to data from clinical trials. Kim has a medical degree from University of Copenhagen and did his PhD at the Nordic Cochrane Centre in evidence-based medicine.