Metadata analysis: A complete guide to understanding and using digital metadata

What is metadata analysis?

Metadata analysis is the systematic process of examining and interpreting the descriptive information embedded in or associated with digital files to extract meaningful insight. It applies across a broad range of use cases — from aggregating findings across multiple research studies to uncovering hidden properties within images, emails, and other digital assets. Organizations use metadata analysis to improve how content is discovered, audited, and governed at scale.

Metadata management is the governance process that organizes and catalogs metadata to keep digital assets discoverable, trackable, and consistently labeled across your digital library.

A comprehensive approach to metadata analysis

Depending on what types of information you’re analyzing, chances are the best bet for success is something that brings together different sources and unifies them. That’s why a comprehensive approach to metadata analysis is so effective. It takes the available data, including the research about that data, and sifts through it, to find what’s relevant.

Here’s an example to demonstrate this effective approach. Let’s say there is a need to find out all there is to know about two particular objects: an email and an attachment on that email. Finding the metadata would be the first step. This would entail locating different parts of the email, and then downloading and reviewing the data from the attached file. After that, the information would need to be analyzed.

A comprehensive approach ensures that the analysis is complete, meaning users discover and explore all available data, and also they use the most valid analysis (especially if there are multiple “reports”).

Digital metadata analysis

Chances are, many problematic or at least complex metadata research attempts will come in the form of some type of digital object, particularly computer files that contain large amounts of information. Why is this the case? Consider this example: Let’s say you have a physical, print photograph in a photo album. If someone urged you to research and analyze the metadata of that picture, you could look at both the picture, and likely the back of it and gather all that is needed. The back of the photo has metadata visible for everyone, with things such as the “who” and the “when”’ either written by hand on or stamped on automatically by the camera.

Compare this to a digital image, and you see that analyzing the metadata for a computer file has the potential for immense complexities. It’s not just that the metadata is more difficult to find.Interpreting this data also requires a more unique skill set that extends further than reading a few bits of information.

It’s no surprise, then, that metadata analysis often requires specific approaches depending on the types of information being analyzed. Entire fields, such as computer forensics, are dedicated entirely to understanding the information on digital files.

Tools needed for successful metadata analysis

Because metadata analysis has such a wide ranging meaning from one application to the next, it becomes nearly impossible for a program to present itself as a metadata analysis tool. However, that doesn’t mean there aren’t programs and tools that can help in your own analysis of metadata.

The first type of tool you’ll want to check out are ones that help you read the metadata you’re after. Again, this will change depending on the situation, but metadata editors often come with helpful processes that allow users to view embedded metadata.

Another popular technology which paves the way for superior analysis is metadata management, which is technically designed to update and control metadata. This is important, because accurate data is a prerequisite for better analysis.

Whichever tools you end up selecting, make sure they’re a good fit for the type of research and analysis you require.

Final thoughts

Metadata is much too complex of a topic to address with a single fix or singular process. Instead, think of your analysis of the information through the scope of individual and specific needs. The results will be rewarding.