6 Types of Metadata and Their Uses – Spiceworks News and Insights
Metadata is data about data: i.e., its properties, history, origin, versions, and other information about a data asset.
Metadata refers to data about data, which essentially encapsulates the different properties, history, origin, versions, and other information about a data asset in highly structured fields – used primarily for tracking, classification, and analysis. This article explains the metadata types and their uses with examples.
Metadata is data about data, which essentially encapsulates the different properties, history, origin, versions, and other information about a data asset in highly structured fields – used primarily for tracking, classification, and analysis.
Metadata is roughly defined as data that offers information on some other content but not the data’s substance, such as the picture itself or the text message’s content. It helps users understand the meaning of the data and is essential in ensuring compliance with regulations and data governance initiatives.
Metadata provides information such as the origin of the data, its meaning, its location, its ownership, and its creation. For instance, the metadata within a digital image may consist of information such as its size, resolution, time of creation, and color depth. It is helpful in the classification, organization, labeling, sorting, and searching of data.
A metadata repository is a database that stores and manages metadata. One should provide content to a database to ensure that it is used as intended and appropriately identified—for example, a database of a collection of digital images.
The following are the functions of metadata:
However, metadata does pose a few challenges. Organizations could report little return on investment and thus prefer to stick to traditional methods, such as spreadsheets, instead of a proper database management system (DBMS). Further, it is scattered in hard-to-use forms such as databases and Excel sheets in large organizations. Metadata stored in this form is hard to track; sometimes, it’s not even updated.
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Metadata management software helps to evaluate, curate, capture, and store metadata. Ideally, organizations should automate data management to facilitate data tracking and accountability. The following are a few examples of this type of software:
The following are the benefits of centralizing metadata by using specialized software:
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Metadata can be of various types, depending on its functionality and source. The six key types of metadata to note, include the following:
Structural metadata provides valuable information that helps to establish the relationship between objects. This enables users to understand and make use of the data resource effectively. Structural metadata also provides information on the hierarchical structures between different data resources. This may include a table of contents, page, section, and chapter numbering.
Its principal purpose is to enhance the display and navigation of collected data, which is facilitated by a page-turning program specifying the order of page graphics. It is influenced by how photographs are given to the user and saved in the repository.
Descriptive metadata provides helpful information for discovering and identifying a data resource. It describes a resource’s what, when, where, and who. It consists of information about the content and context of the data. It is organized and often adheres to one or more recognized standard schemes, like Dublin Core or MARC. It may also define the resource’s physical characteristics, such as its medium type and dimensions.
It helps users search and retrieve information at the system level. At the Web level, it enables users to discover resources, for instance, through hyperlinking documents.
Preservation metadata refers to the information related to the preservation management of collections and information resources. It involves documentation of the process of preserving physical and digital versions of resources and encompasses all the necessary information to manage and protect digital assets over time.
In digital repositories, preservation metadata may deal with rights management and consist of information on rights holders that authorize such actions. It draws from other structures, such as structural and administrative metadata. It is mainly associated with the analysis and actions performed on a resource after it is submitted to a repository.
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Administrative metadata provides information that is useful in managing resources. It provides information related to governance, access controls, and security. It includes technical data on copyright information, rights management, and license agreements. It may consist of technical data on the creation and quality control of works, rights management, access control, user requirements, and preserving action information.
It is governed by project-specific procedures based on the project’s local requirements and may contain contract agreements and payment information. It includes both preservation and technical knowledge. One can use the archiving policy of administrative metadata for the internal management of resources.
Provenance metadata provides helpful information on the origins of a data resource. It includes information on the ownership, any transformation that the data may have undergone, the usage of the data, and the archival of the data resource. This information helps track the lifecycle of a resource.
Provenance metadata is generated whenever a new version of a data set is created and indicates the relationship between different versions of data objects. This allows users to query the relationship between versions and includes either or both fine- or coarse-grained provenance data on data resources.
Definitional metadata refers to the metadata that provides a common vocabulary that facilitates a shared understanding of the meaning of the data. The meaning of the data includes information on the definitions of the data, rules that govern the data’s context, and calculations. It may also include information on the logic used when creating derived data to understand its meaning entirely.
Definitional metadata is categorized into semantic and schematic. You can describe structured, and unstructured data sets semantically with a textual description or vocabulary. A database schema can present structured data sets.
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One may use various forms of metadata in various ways. Here are the top applications of metadata in an organization:
Metadata in a database management system (DBMS) consists of a column name and a row number that is attached to the piece of data. The SQL standard offers a standardized method for accessing the metadata referred to as the schema; however, not all databases implement this method. Metadata makes it easy to organize, interpret, and request data.
Metadata can be a directory in the database that allows users to easily sort and filter data by type and establish relationships between different data sets. A DBMS catalog is associated with data collection and contains information that defines database articles.
Websites are embedded with metadata that significantly affects their ranking and success. When building a webpage, it’s important to include metadata details such as a meta title and a meta description. A meta title briefly describes the page’s topic to give readers a preview of what to expect.
A meta description gives further information about the page’s contents, though it is brief. A meta tag only appears on a page’s code and helps search engines categorize the page. Search engines read this metadata to determine keywords and use it to categorize the website.
Metadata in social media allows users more control over how they want their content shared on platforms such as Facebook or Twitter. When users optimize their content, they get more interactions from their posts than from posts without optimization.
For instance, when users publish links on Facebook, it extracts metadata such as the title of the post, a brief description of the post and featured image, the URL of the post, and the name of the website. Users can leverage Open Graph on Facebook and Twitter Cards on Twitter to optimize and determine how their posts are displayed.
Markup languages allow users to identify individual elements of a document, such as a paragraph or a header. They include a standard generalized markup language (SGML) or extensible markup language (XML). SGML allowed the sharing of documents that were readable by machines. XML consists of standardized rules for attaching information to text to make it readable by machines.
It works by wrapping chunks of text such as words, sentences, or paragraphs in tags that describe what’s between them. Markup content allows users to search for keywords across many different documents.
Retail and online shopping websites often use metadata to track consumer habits and movements. They collect any data they are legally allowed to, such as their consumer’s device type, locations, purchases, clicks, and times they access the sites.
Using this information, they create a picture of their consumer’s preferences, associations, and habits and use it for marketing their products to them. This information can also segment consumers and send them targeted ads. Similarly, governments can use metadata from web pages and emails to monitor Web activity. This information can be used in mass surveillance.
Classification involves arranging information logically to find it when it’s needed. Putting this information into classes or categories is known as taxonomy, and the data associated with the items is metadata. Users can embed this information into the content or in an external content management system.
Understanding metadata is vital in creating an effective content management system (CMS). Within taxonomies, controlled vocabularies can promote an understanding of the intended purpose. Metadata tags can help with resource discovery and improve resource organization. Properly classified information makes it easy for users to analyze and interact with the data.
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Now that we have looked at the critical uses of metadata, here are a few examples to illustrate its application further.
Document metadata provides additional information on a document for additional context. This information is useful in classification, search, and retrieval. Metadata includes details such as the author of the document, size, and title.
Tags enable users to classify and categorize documents quickly. Information tags provide additional notes on a document, while security tags allow restricted access. Metadata on the version of the document enables users to track changes and view information on the date it was created and last modified.
Reliable content management systems and document management systems support document links. These links may establish relationships between one or more documents.
Social metadata refers to data added to a piece of content by others besides the content creator, such as tags, ratings, and comments.
Facebook meta tags on Open Graph consist of information like the title of a post, a brief description of the post and the featured image, the URL of the post, and the name of the website. Twitter meta tags on Twitter Cards consist of information such as a title, a brief description of the post, an image thumbnail, and Twitter account attribution. These tags are embedded in HTML code.
HTML code is embedded into a website to provide additional essential information to the website. A meta tag is used to provide this additional information. Meta tags are placed inside the header of the document. They can have information such as the title and author of the website.
Metatags can be used to specify important keywords related to the document. Keywords are useful to search engines while indexing webpages for search purposes. One can also use metatags can also be used to provide a short description of the document. Similarly, they can be used to provide information on when the document was updated last.
Relational databases are used to store and provide access to metadata in a structure known as a data dictionary. The data dictionary holds metadata information about tables, columns, data types, constraints, table relationships, views, and indexes.
The columns hold the attributes of the data, while the rows represent a record with a unique ID known as a key. Each record consists of a corresponding attribute value, which makes it easy to establish relationships among data points. Foreign keys allow for data searches and manipulation between databases.
The message headers of emails sent or received consist of metadata fields that are not visible in the mail client. Emails consist of metadata such as the date and time when the email was received – examples of this include the email addresses of the sender, the receiver, their names, the title, and the email’s subject.
They may also contain information on the full content of the document, including and excluding the HTML formatting. Additionally, it may include metadata on the original document, inclusive of the type of content, file size, and download URL. A list of all documents attached to the email, along with the URLs to retrieve them, may also be included, and this metadata plays a vital role in email security.
Geospatial metadata describes geographic objects such as maps and data sets. It often describes the who, when, where, what, why, and how of geographic information system (GIS) files.
Examples of geospatial metadata include details such as the creation date of the data, the author’s contact information, map projection and coordinate system, scales used on the data, any errors on the data, and a key containing explanations of various symbols and attributes that are used. It may also include a database schema for usage in a data system, data reproductions, and license information.
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Metadata forms the foundation of several advanced data-driven functionalities, from data meshes and fabrics to data lakes and warehouses. As more and more information is generated by users and machines worldwide, metadata helps keep track of these assets and assigns each data set a unique identity. Organizations can leverage this technology to improve operations in personalized services, data-driven security, and more.
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