Data teams deal with different types of metadata on a regular basis. In a simple sense, metadata is data that describes other data. However, this doesn’t tell the whole story. The different types of metadata further explain what is being described and how that data can be used. Understanding the difference between the metadata types will help data teams make the most of the data they have available and leverage your company’s data sets to their maximum potential. In this blog, we’ll go over the eight different types of metadata you need to know.
First is descriptive metadata. This is a type of metadata that provides attributes about the data asset itself. Examples of descriptive metadata include titles, authors, dates, keywords that describe the content of your data and more. Descriptive metadata is primarily used for data identification, organization and discovery. Without descriptive metadata, it would be exceedingly difficult to find specific data assets.
For instance, the title of a data set distinguishes it from other data sets. If you have a data set about customer acquisition and a data set about your sales funnel, the title of that data set will allow you to tell the two apart. In another example, a date could help you find which data set is the most up-to-date. If you see two data sets with the same title, you’d want to choose the one that was updated most recently. This data set can be identified thanks to descriptive metadata.
In short, descriptive metadata keeps your data organized and searchable.
Administrative metadata is metadata that describes the management and technical aspects of data, such as the file format, size and location. This information shows who created the data, when that data was created and how the data was created.
Administrative metadata is used to help manage and understand data sets. Several other sub-types of metadata follow under the administrative metadata umbrella, including rights, technical and preservation metadata. Administrative metadata helps define the ownership information of data and the access rights of that data. It also helps with data maintenance and decoding.
Structural metadata is used to describe the organization and structure of the data, such as its table of contents, indexing and data relationships. Structural metadata is especially important for helping users locate data and understand the connections between different data sets or assets.
In other words, structural metadata helps you navigate your company data. You can see the relationship between data sets, allowing you to have more organized assets. Also, structural metadata helps define how data should be organized and stored, so it’s easily searchable and accessible for people that need it.
As mentioned, technical metadata is a subset of administrative metadata. However, it’s worth understanding this category on a deeper level. Technical metadata describes the technical specifications and requirements for the data, such as file format, compression, and resolution. This information can help ensure data is stored correctly. It also helps show how data can be used or presented.
Let’s take a look at some of our examples for technical metadata and how it can help. File format, for instance, shows if a file is a text, image or something else. This allows you to understand what type of data you’re working with and shows you where it should be stored. You can also see if compression or encryption is applied to the data, helping you better understand what is needed to access and use the data. Resolution can help you understand how data needs to be rendered. Overall, technical data helps you decode your files and use them properly.
Preservation metadata is another subset of administrative metadata we touched on earlier. Let’s take a closer look at preservation metadata and what it describes. As the name might imply, preservation metadata records information about the preservation and conservation of data. It can document the conditions of data, allowing users to retrieve the data in the same condition it was originally stored. Preservation metadata also describes if data has been migrated or digitized, helping you understand what storage medium it needs to be stored in. In summation, preservation metadata is essential for managing digital assets in the long term and ensuring integrity is maintained so the data assets are accessible from the archives in the future.
Finally, we have the third subset of administrative metadata – rights. Rights are the legal permissions associated with data, such as copyright and access restrictions. This is essential metadata, because it allows you to see if data can be legally used. In some cases, data is subject to copyright law. Another use case for rights metadata is when data is protected by confidentiality agreements. This allows you to see what users are allowed to access the data.
Data is shared and collected on a regular basis, so it’s important to know who owns the data and who is allowed to view it. An example of rights data in action would be if you see that a data asset is subject to a Creative Commons license. To use that data, a user would need to adhere to the rules of that license. In short, rights metadata helps to define your access protocols, user permissions and the legality of using or sharing certain assets.
Provenance metadata is metadata that tracks the history and lineage of the data, including data sources and transformations. With provenance metadata, you can see the relationship between two data objects, see where an asset started, see where it is stored now, find out if the data has been transformed in any way and more.
This also helps with documentation, as data teams can see the history of data and ensure that the data has been accurately recorded throughout its life cycle. By seeing how a dataset was created or changed, your organization can maintain a thorough and comprehensive data history. Along with helping you archive and document data, this also helps you identify any issues or inconsistencies with data sets.
Usage metadata records information about how data is being used. This can be highly useful metadata, as it can reveal to data teams how users interact with data, the challenges they may run into when using data and other useful insights. Usage metadata can also describe how data may be used. Some examples of usage metadata may include number of views, number of downloads, changes to the data, data sharing metrics and more.
Data usage metadata can help organizations learn what data sets are accessed frequently, allowing data teams to prioritize the organization of those data sets. Also, understanding the data your teams use most can help you optimize data collection by prioritizing these data types. In summation, usage data can provide context and insights into what data sets and assets your organization utilizes on a regular basis
Which Types of Metadata Are Most Important To Data Teams?
In truth, all the different types of metadata are important in their own way. While descriptive, administrative and structural metadata are considered the primary types of metadata, the subsets of metadata can be useful to data teams as well. Your data team can better organize and understand your organization’s data when they have a full understanding of the different metadata types.
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If you want to ensure your data is as organized and searchable as possible, Secoda can help. Secoda is a modern data management workspace that makes your data highly searchable. Our platform can also help you manage and document all of your data in one place. Secoda is truly an all-in-one platform for cataloging, documentation and data lineage. Learn more and try Secoda for free today.