Scientific Coordination
André Ernst
Tel: +49 221 4703736
Tel: +49 221 4703736
Administrative Coordination
Janina Götsche
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Research Data Management and Open Science
About
Location:
Online via Zoom
Online via Zoom
General Topics
Course Level
Format
Software used
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Duration
Language
Fees
Students: 200 €
Academics: 300 €
Commercial: 600 €
Keywords
Additional links
Lecturer(s): Anja Perry, Sebastian Netscher
Course description
Have you ever searched for the right file but couldn't find it right away? Did you ever wonder why you coded a variable a certain way? Did you ever have doubts if it's actually legal to re-use research materials from someone else? Or did you ever think that data protection regulations are just too complex and restricting?
Working with research data can be challenging for various reasons. This workshop is designed to assist researchers in managing their research data within their research projects. Therefore, we introduce basic concepts of data organization, data cleaning, and data documentation. Moreover, we provide an insight into legal issues of data management in the social sciences, i.e., data protection regulations and intellectual property rights. These skills equip researchers to manage their data properly.
Having created and processed transparent and usable data within the project, it's just a few steps away from safely making data re-usable for others. Re-use of research data is of high relevance in the social sciences, generally labeled as Open Science. It enables others to re-use research materials, such as data, for new research purposes as well as for replicating research findings. We thus discuss concepts and ideas for digital preservation of research data beyond the research project as well as the workflows of data sharing to foster Open Science.
Target group
Participants will find the course useful if:
Learning objectives
By the end of the course, participants will:
Organisational Structure of the Course
This online workshop is structured around classroom instruction and hands-on exercises.
Prerequisites
Besides working with quantitative research data and being familiar with empirical research, this course has no further prerequisites.
Software and hardware requirements
This workshop is designed as an online course. Therefore, further hardware besides a computer is not needed. Participants should have a statistical software package ready that they are familiar with, such as R, Stata, or SPSS. We may need it for some of the exercises.