This course provides an introductory grounding in enriching research data with structured metadata and is primarily aimed at interested master's students, PhD students, and early career researchers. During the course, we will not only address how metadata can be important for one's own research data management, but also give an impression of how metadata in machine-readable structured form can make data more visible and more reusable for further research.
Does the following sound familiar to you in one way or another?
- You receive a research dataset from a colleague, but have difficulty understanding it correctly.
- You receive a request for the underlying data due to your own publication, you are able to provide it, but after the long time you are also unable to provide information on important details.
- When merging data tables from two different sources, you unfortunately discover that columns are incoherent in an incomprehensible way.
Enriching research data with adequate metadata can help to better understand research data, make it more visible and reusable, and thus promote scientific exchange and knowledge generation.
This course is primarily aimed at master's students, PhD students and early career researchers from the Helmholtz Research Field Energy, but can also be attended by others interested in this topic. The course contains a well-balanced combination of both theoretical presentations and hands-on sessions.
In the course you will learn:
- basic facts about the relationship between research data, metadata, and knowledge
- what types of metadata exist and what they are important for
- how research data can be enriched with structured metadata using basic markdown (XML, JSON)
- the role of metadata schemas and standards
- how machine-readable structured metadata can make data more visible and reusable, and which technologies and concepts play a role in this process
Registration period: until 20. March 2023
organized by HMC Hub Energy