Hey All! Wanted to start a conversation centered on metadata.
Metadata is crucial to understanding data sets for reuse. It’s hard to find set standards for clinical or biological data for this overlooked component and I think it would be helpful to understand what sorts of metadata are useful for different situations and data types.
The point of metadata is that it is a high level document that shows a common way of structuring and understanding the data.
In terms of data sets, there are so many types and then subtypes of data : clinical, genomics, transcriptomics, proteomics, scRNA seq, metabolomics, lipidomics, imaging (microscopy or clinical imaging), etc. And within each of these, hardware and software used need to be taken into account.
Based on your experience with these types of datasets, what sort of information is useful to include in the metadata? What is crucial to your ability to reuse the data?
Will there be a universal standard for metadata or do you think standards will vary between fields and data types?