The term metadata refers to " data about data". The term is ambiguous, as it is used for two fundamentally different concepts ( types). Structural metadata is about the design and specification of data structures and is more properly called "data about the containers of data"; descriptive metadata, on the other hand, is about individual instances of application data, the data content.
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Looking at data requires critical thinking skills just as reading fiction and nonfiction does. And it's not even restricted to statistics and statistical knowledge. "Data about data" is similar to the hunt for rigor and relevance of different kinds of research. However, it also includes how this data is stored, how it can be found, how it can be retrieved, in what format is the data stored/viewed, and what equipment/tools are needed to access and review the data. Metadata refers to other concerns as well. "Data about data" is a huge topic. It reminds me of what should be considered when evaluating research. It's not just about what is reported, but may also include the way something is reported, research tool decisions (choosing, appropriateness, measurement, etc). Granularity is another interesting element to data creation and capture.
from the article:
The degree to which the data or metadata are structured is referred to as their granularity. Metadata with a high granularity allow for deeper structured information and enable greater levels of technical manipulation however, a lower level of granularity means that metadata can be created for considerably lower costs but will not provide as detailed information. The major impact of granularity is not only on creation and capture, but moreover on maintenance. As soon as the metadata structures get outdated, the access to the referred data will get outdated. Hence granularity shall take into account the effort to create as well as the effort to maintain.