What should you verify after importing metadata from one feature class to another?

After importing metadata from one feature class to another, it is essential to verify that the metadata is correct. Metadata provides critical information about the dataset, including its purpose, source, accuracy, and other descriptive attributes. Ensuring that this information is accurate is important for maintaining the integrity and usability of the data. Accurate metadata allows users to understand the dataset's context, making it easier to assess its appropriateness for various applications or analyses.

When metadata is simply transferred without verification, there is a risk of carrying over outdated or erroneous information that could misguide users about the dataset's quality or relevance. For example, if the source of the feature class or the date of collection is incorrect, it could significantly impact decision-making based on that data.

Furthermore, while it may be important to check that the item description matches, that data is backed up, and that feature classes are correctly linked, these actions do not directly address the integrity and correctness of the metadata itself. Therefore, verifying the correctness of the metadata should be prioritized to ensure that the new feature class meets the necessary standards for data management and usability.