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What is metadata? 

Metadata is a set of information that helps identify datasets, providing details and context to describe that particular data better.  It is an integral part of online content and data management which helps people select specific keywords when searching online and allows creators to tag their content to be easily indexed and captured by search engines and website usage trackers.

What is the definition of metadata?

The root word “meta” means “beyond” or “after,” which is an excellent way to describe how metadata digs into the different components of datasets to effectively categorize and index them for search engines and content management systems.

For images, these could be size, resolution, date of creation, color depth, and even location where the photo was taken.  Metadata can include author, length, type (Word, PDF, etc.), date of publication, tags, and content description for text. For videos, it can be length, genre, and topic.

The information creating a certain content is just as important as the content itself because it gives color and background to why that data exists.

Why is metadata important?

The primary Use of metadata is to categorize and index online content to be searchable accurately.  Manual metadata tends to be more detailed since it can be customized to the smallest piece of information.  On the other hand, automated metadata gives a general overview of the data and uses a set of basic fields that is consistent throughout.

Search engines can scan the metadata of online content by looking through its meta tags, which contain information that is not explicitly indicated on the content itself.  Examples of meta tags are the apps or software used to create that content and related keywords.

Metadata can also help standardize data management since its inputs are understandable to humans and computers, such as application programming interfaces (APIs).  This makes datasets more interoperable and integrates them into different systems or infrastructures. Industry standards have been put in place to ensure consistency in language, fields, format, and other specifications to create metadata even more helpful.  An example is Dublin Core, which lists 15 data elements, such as title, contributor, source, and rights.  Another example is schema.org which focuses on internet metadata, email, and other digital content.

Without metadata, content management is a lost cause as it would be impossible to find the right content in its right locations.  Consistency of tags and keywords goes a long way in organizing data and ensuring that everything is accounted for.

How to use metadata?

Different use cases for metadata depend on how the organization wants to group and manage its content. Here are the primary ones.

  1. Descriptive metadata includes author, size, format, date of publication, document type, and version control to help search engine algorithms scan which content is most relevant to a search term.   The completeness of metadata can also assist online users in deciding which content they would want to consume.
  2. Administrative metadata is particularly useful in content management systems, where files need to be accurately tagged, titled, and tracked for auditing and reporting purposes, including how many times a document has been updated and by whom.

Metadata is mainly utilized to track consumer behavior or patterns when accessing content or sites.  By having a system sort and analyze how many times a user clicks on a particular product image or how long they stay on a page, businesses can customize their website and how they present information.

  1. Statistical metadata is mainly used for data analysis by providing key information on numbers and processes found in reports, surveys, whitepapers, and other research-related documents.
  2. Legal metadata is anything related to licensing, copyrights, and royalties.
  3. Structural metadata describes how datasets are created or assembled.  This primarily can be found in digital libraries to detail how chapters of a book were organized and how a set of books were categorized into a volume.
  4. Provenance metadata captures how datasets have moved across different sectors of an organization.  This is particularly useful for data governance as this type of metadata can verify if the content has been reviewed and signed off as it changed hands across the company.

In general, the more detailed the metadata, the easier it is for users to find related content.  An excellent example of how metadata can be used to optimize information reach is in social media.  Each activity on Facebook, Twitter, Instagram, or Spotify is aided by metadata, including recommended songs, posts, and friends.  Even  though someone’s profile helps users make informed decisions on who to include or block in their network list.

What about enterprise usage of metadata?

Metadata can be applied to all industries, ranging from tech to healthcare to manufacturing.  This is because metadata management is a vital tool, especially for large companies with decades’ worth of data. Here are some ways that enterprises can use metadata.

Organizing and tracking vast amounts of available information.  By creating a structure to manage their databases efficiently, enterprises can better document and track processes, client details, expenditure, and customer behavior. 

Identifying data relevance, assigning and updating metadata on content can help firms identify which information is already outdated and which information has been recently updated.  This makes updating SOPs and running reports a lot easier.

Establishing data governance policies and audit trails.  By setting up a centralized metadata repository or glossary, companies can have a reliable source of information for accurate and timely data analytics and a tracker for all published content which can serve as evidence of policy compliance.  In addition, metadata management can also restrict access to the right user groups to prevent data leaks by having permissions in place.

There are many ways that firms can build their metadata repository, but having metadata management tools like APIs can help automate some of the processes.  By eliminating manual intervention, enterprises can have a real-time, updated system that stores, curates, evaluates, and analyses metadata and its usage across the business.

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