Speakers
Description
In this course we will look at the intricate relationship between (digital) research data, metadata and knowledge, discuss why metadata is critical in today’s research, as well as explain some of the technologies and concepts related to structured machine-readable metadata.
Have you ever struggled to make sense of scientific data provided by a collaborator - or even understanding your own data 5 months after publication? Do you see difficulties in meeting the data description requirements of your funding agency? Do you want your data to have lasting value, but don’t know how to ensure that?
Precise and structured description of research data is key for scientific exchange and progress - and also for the recognition of your effort in data collection. The solution: make your data findable, accessible, interoperable and reusable by describing them with metadata.
You will learn:
- about the differences between and the importance of data & metadata
- to annotate your research data with structured metadata
- to find and evaluate a suitable metadata framework and data repository
- to use basic Markdown / JSON / XML
- which tools are already available to level up your metadata annotation game
- why structured metadata is important and how it can increase your scientific visibility
organized by HMC Hub Information
This is day two of the course starting on September 14 at 9 am.
| Target audience | PhD students, Postdocs, early career researchers |
|---|---|
| Previous experience | none |
| Maximum number of participants | 20 |
