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--- skill-tree:k:6:1:b [2022/06/20 14:37] – [Background] ruben.kellner
+++ skill-tree:k:6:1:b [2022/06/27 12:30] (current) – external edit 127.0.0.1
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 # K6.1-B Introduction
+**Maintainer: Christian Löschen @ TU Dresden**
 # Background
 Research Data Management (RDM) has become a hype within the past years: Funding agencies demand for data management plans (DMP), research institutions set up data management policies and guidelines, and national projects aim on sustainably establishing research data infrastructures (NFDI). But why?
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 # Aim
+Participants should be aware about the risk of dark data and the benefits of data management. They should know about theoretical concepts of data management and practical strategies and techniques to implement aligned data management solutions. They should be able to describe and structure data, find and use metadata standards. They should know what to consider when publishing research data and how to find suitable data respositories.
 # Outcomes
+  * Understanding the risk of losing (knowledge about) data
+  * Knowing about RDM concepts
+  * Knowing techniques and abilities to minimize the risk of data loss
+  * Able to adequately describe and structure data
+  * Able to apply metadata schemas and create metadata profiles
+  * Knowing what to consider when publishing data
+  * Able to find suitable data repositories
 # Subskills