Summary and Setup
to our entry-level introduction to the fundamentals of scientific metadata!
In this lesson 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.
This course is targeted at scientific staff and researchers from all
fields who are interested in annotating their research data with
well-structured and useful metadata.
This lesson is for you, if…
- … you are completely new to the topic of scientific metadata.
- … you are looking for alternatives for documenting your research data.
- … you have a basic understanding of metadata but want to gain some hands-on experience.
- … you want to get into the function and syntax of JSON and JSON schema.
- … you are looking for metadata standards and tools.
This lesson may not be what you are looking for if…
- … you know the difference between a metadata schema and a standard.
- … you annotate your research data with structured metadata (XML, JSON, YAML).
- … you have in-depth knowledge on web technologies and data exchange formats.
- … you are struggling with a specific metadata problem and just look for this one solution.
- … your main interest lies in linked data and semantic web technologies
This training course was created by the Hub Information of the Helmholtz Metadata Collaboration (HMC) at Forschungszentrum Jülich, an incubator-platform of the Helmholtz Association within the framework of the Information and Data Science strategic initiative
This lesson does not require any special setup.
All you need is a Web browser and a text editor and you are good to go.
Additional material will be provided throughout the challenges.