3 Contract Metadata Extraction Best Practices
In general, metadata is a tidbit of information that defines a broader set of data. These tidbits are the essential information about a data set or data collection. Think of an author name or the title of a book or the year that a book was published — those are three examples of raw metadata.
The main purpose of metadata is to make tracking essential data faster and easier. That’s why it’s often used to organize and remodel complicated data into a practical and clear form. It’s a great way to sort and simplify important information and has consistently proven to be immensely beneficial in providing visible and accurate information.
Companies that process a large amount of digitized contract data rely on metadata to help sort the information they record. Let’s take a closer look at the three types of metadata available and what the best practices concerning contract metadata extraction are.
3 types of metadata
There are three types of metadata. They are:
- Structural metadata, which discloses how a digital asset or data is organized. As the name suggests, this type of metadata records information about how certain data may be categorized. This includes, for example, how the chapters of a book are organized. Structural metadata helps you determine if a relationship exists between two data sets.
- Administrative metadata, which relates to the technical source of the data. It allows you to control confusing data and simplify it for clearness. This kind of metadata extraction is typically used for intellectual property. It can help you find information about the owner of an asset or data. For digital images and pictures, for instance, metadata extraction includes the model of the device used to take the picture and the software used to edit it.
- Descriptive metadata, which describes and identifies data. This information helps identify a specific data set, like a book author or the date a medical article was published. Accessibility, visibility, and relevance are what make descriptive metadata the most popular and most commonly used type.
3 contract metadata extraction best practices
Companies all over the globe are automating and incorporating technological advancements into their work, developing best practices of contract metadata extraction in their management systems along the way. Here’s a closer look at the top three.
1. Automated metadata extraction
Best practices involve automated metadata extraction involve curating, managing, and storing existing data as well as properly disposing of information that’s no longer needed.
Automated metadata extraction relies extensively on technology and includes data cataloging, identifying relationships between multiple datasets, and linking business-relevant terms. There’s hardly — if any — manual integration involved here. This practice involves using more than one costly piece of software that isn’t easily accessible.
Because data is one of the most integral and crucial aspects of any firm, keeping the bulk of it at one location, like the company itself, increases your overall risk. By automating metadata extraction, companies significantly reduce potential data breaches and other risks through quality checks. These checks process your data automatically and eliminate the data that it considers as irrelevant for your work operations.
Regarding contract management, automated metadata systems ensure that contracts meet certain requirements before they’re processed or approved. The ones that don’t meet the requirements are automatically discarded by the system. In this way, automated metadata extraction systems manage your data usage and disposal, managing what’s relevant and eliminating what’s not needed.
2. Structured metadata
Structured metadata involves the actual structure of the data. This can include, for example, the version, the publisher, the number of pages, the search engine, the internal structure, and the organization of data. Because the flow of data involved in contract management is exceptionally large, it’s necessary to sequence the information in such a way that enables easy navigation between important contracts. That’s what makes structured data so handy.
A best practice regarding the use of structured data involves finding relationships between the internal and external structures of the information, including data content and relevant digital devices. This enables companies to navigate between important data easily, spotting patterns and relationships between data sets.
3. Metadata stored in a cloud-based repository
Data storage and accessibility is a cumbersome task, especially when there are bulks of information to contend with. At times, individuals need immediate access to a specific data set but retrieving this information is a timely, difficult task.
Commonly used for data storage and accessibility purposes, cloud-based technologies tend to be one of the advanced metadata repositories, serving as a database of metadata. Data and content stored on a cloud-based system may be accessed on any device when logged in. The repository itself is either stored in a physical location or as an online database.
Contract management systems, like Ironclad’s, access cloud-based repositories that organize metadata. These systems create efficiencies that have made adopting cloud-based repositories a best practice for contract metadata extraction.
Nowadays, a majority of executives, attorneys, and employees use contract management systems to access large, cloud-based repositories of contracts for key terms and data points. If there’s a high volume of contracts, assuring data accuracy can prove to be time-consuming and expensive.
Done right, contract metadata extraction creates efficiencies and minimizes costs. By implementing innovative contract management solutions that incorporate best practices, businesses can not only safeguard and secure data but also complete projects much more quickly and accurately.