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Data Conversations: Open Science, Team Science, Recognition and Rewards

Data Conversations: Open Science, Team Science, Recognition and Rewards Online

Open data, open methods, and reproducible and transparent research are increasingly endorsed by funders, publishers, institutions and learned societies. But what does making your research open, transparent and reproducible mean in practice? What are the advantages and the pitfalls?

This edition of the Data Conversations will focus on Team Science, Recognition & Rewards.

In this Data Conversations researchers from different Faculties, Institutes and disciplines will have a chance to hear and learn from each other about their experiences with opening up data and methods, failures, and setbacks.

Come and share your research data stories and hear others. Find the registration button at the bottom of this page.  At the moment, Data Conversations take place online. You will receive an email with a Zoom link after your registration.


12:50 - 13:00   Sign in; check your microphone

13:00   Data Conversations begin

Trynke Hoekstra "A team makes the dream or a dream makes the team? A talk about experiences with team science"

Anne Urai "The International Brain Laboratory: building a global collaboration for more reproducible neuroscience"

Q&A session

13:45 - 13: 55 Discussion in smaller groups

13:55 - 14:00   Wrap-up and closing

What to expect?

Data Conversations will feature a series of short talks from researchers or colleagues who support research. Each talk will be about 10 minutes long and there will be time for a Q&A session. There will be a discussion in smaller groups to give you an opportunity to meet like-minded colleagues across the VU.

Abstracts of the talks

Trynke Hoekstra: A team makes the dream or a dream makes the team? A talk about experiences with team science
We see a shift toward collaborative research, especially in applied sciences such as health sciences. Research is conducted more and more by teams, instead of by individuals only. Recently, the Dutch knowledge institutions and funders of research have addressed the wish to change how academics are rewarded and recognised. Amongst others, one of their suggestions is to change the balance between the individual and the collective; individual versus team performance. Trynke will share some of the experiences (both good and bad) she has had with team science over the years in her talk.

Anne Urai: The International Brain Laboratory: building a global collaboration for more reproducible neuroscience
The International Brain Laboratory (IBL) is a collaboration of ~20 laboratories worldwide. Its researchers are dedicated to standardizing mouse decision-making behavior, coordinating measurements of neural activity across the brain, and using theoretical approaches to formalize the neural computations that support decision-making. In contrast to traditional neuroscientific practice, in which individual laboratories each probe different behaviors and record from a few select brain areas, IBL aims to deliver a standardized, high-density approach to behavioral and neural assays. 
This approach relies on a highly distributed, collaborative network of ~50 researchers—postdocs, graduate students, and scientific staff—who coordinate the intellectual, administrative, and sociological aspects of the project. I will examine this network, elaborate on some lessons learned in the first two years of the project, and consider how IBL may represent a template for other team-based approaches in science.

About the speakers

Trynke Hoekstra  is appointed as an Assistant Professor at the Department of Health Sciences of the Vrije Universiteit. She is an experienced lecturer in epidemiology and applied biostatistics to BSc and MSc Students in Health Sciences and Epidemiology. Trynke has a broad research interest, probably because she enjoys collaborating in multidisciplinary research teams. She aims to inspire her students (and colleagues) to be(come) critical, constructive academics.

Anne Urai studied cognitive neuroscience and philosophy at University College Utrecht, Xiamen University in China, University College London and École Normale Supérieure, Paris. During her doctoral research in the lab of Tobias Donner at the Universitätsklinikum Hamburg-Eppendorf and University of Amsterdam, she investigated how our previous choices bias the way we interpret later information, and how this process is affected by the confidence in our decisions.
She joined Cold Spring Harbor Laboratory in New York as a postdoctoral fellow, investigating the neurophysiology of decision-making using high-density neural recordings in the mouse brain. During this time she was a core member of the International Brain Laboratory collaboration, working as part of a global team of systems and computational neuroscientists. Her research in general focuses on the neural basis of decision-making across mammalian species, the interaction between learning and perception, and the neural basis of cognitive aging.


Who should attend?

Data Conversations brings together researchers, research support staff, and data management, and data science experts from all subject areas. Early career researchers as well as experienced academics are welcome to attend.

About Data Conversations

Data Conversations started at the University of Lancaster in the UK. The Lancaster Data Conversations aim to bring data practitioners together to talk about how researchers create, collect, use and share data. The Data Conversations at the VU Amsterdam share the same aim and are intended to provide a forum for researchers from different subjects and disciplines to exchange practices and ideas around open data, FAIR data, research data management and related open science topics.

Thursday, November 26, 2020
13:00 - 14:00
Time Zone:
Central European Time (change)
This is an online event. Event URL will be sent via registration email.
  Library Staff     Master     PhD     Researchers  
  Research Support > Data Management  
Registration has closed.

Location in Google Maps

Event Organizer

Profile photo of Lena Karvovskaya
Lena Karvovskaya

Lena Karvovskaya is VU Amsterdam's Research Data Management (RDM) Community Manager. She visits RDM expertise meetings and conferences at home and abroad and takes care of the proper dissemination of the latest knowledge throughout VU Amsterdam. 

Lena has a PhD in theoretical linguistics and previously worked as a research data manager at Utrecht University Library. 

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