Notes from the NISO / DCMI webinar "Metadata for managing scientific research data".
General impression: it seems that people who research metadata (and larger information/knowledge organization issues) are so deep into their domains that they think everybody else knows nothing about data/metadata. Perhaps, the audience of this webinar consisted largely of people who are unaware of anything relate to this topic. And that's why the first half hour was spent on pretty simple and uninformative issues of "what is data-metadata-science".
I heard such conversations so many times without any progress, that I began to think we should just skip it and move on. No agreed upon definitions can ever be provided for any more-less complex concept. And still talking about metadata as "data about data" is almost embarrassing. It's better to emphasize that having a shared description of data, e.g., who created them, where they come from, what they are about, etc., helps to produce good and verifiable research and to (re)use the data in the future.
As for how to create metadata, it seems that it still needs to be figured out and systematized, so researchers and librarians are on their own. The metadata world is messy. Possible criteria for the selection and evaluation of metadata schemes include:
And below are some common schemes according to their level of complexity:
|Simple (interoperable, easy to generate, multidisciplinary, flat, 15-25 properties)||Moderate (requires some expertise, more domain focused, extensible via connecting to other schemes)||Complex (requires domain expertise, hierarchical, many properties):|
|Dublin Core||Darwin Core||FGDC Content standard for digital geospatial metadata|
|MARC||Access to biological collections data (ABCD)|
|DataCite||Ecological metadata language||Data Documentation Initiative (DDI)|
A couple of interesting questions/challenges: how to integrate metadata creation into social settings / workflows, automated generation of metadata, metadata as linked data.