Dataset Metadata
Dataset metadata provides essential information about the structure, content, and characteristics of a dataset. It serves as a "data dictionary" that helps users understand the dataset's context, features, and potential use cases. Metadata is critical for ensuring proper data management, reproducibility, and collaboration.
Key Components of Dataset Metadata
- General Information
- Dataset ID: A unique identifier for the dataset.
- Source: The origin of the dataset (e.g., internal database, public repository).
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Creation Date: The date when the dataset was created or last updated.
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Feature Descriptions
- Column Names: The names of all features (columns) in the dataset.
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Data Types: The type of data for each feature (e.g., integer, float, string, datetime).
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Statistical Properties
- Summary Statistics: Key metrics such as mean, median, standard deviation, and range for numerical features.
- Unique Values: The number of unique values for categorical features.
- Missing Values: The count or percentage of missing values for each feature.