Glossary

Plain-language definitions for dataset, AI training, and data licensing terms used across Datasets Maker.

  • AI Training Data

    The dataset used to teach a machine learning model the patterns it needs to perform its task.

  • API Access

    Programmatic access to a dataset through a defined interface, instead of downloading a static file export.

  • CSV

    Comma-Separated Values: a plain-text file format for tabular data, readable by nearly every spreadsheet and database tool.

  • Data Cleaning

    The process of fixing or removing inaccurate, duplicate, or inconsistently formatted records before a dataset is used.

  • Data Enrichment

    Adding additional fields or signals to an existing dataset to make it more useful than the original raw records.

  • Data Labeling

    Tagging records in a dataset with the category, classification, or value a model is meant to learn to predict.

  • Data License

    The terms defining how a dataset may legally be used, by whom, and for what purpose.

  • Data Schema

    The defined set of fields, types, and constraints that every record in a dataset is expected to follow.

  • Dataset

    A structured collection of data organized so it can be consistently read, queried, or processed by a person or a system.

  • JSON

    JavaScript Object Notation: a text-based data format that represents nested and hierarchical structures cleanly.

  • Structured Data

    Data organized into a defined schema of fields and types, as opposed to free-form text or unorganized files.

  • Synthetic Data

    Artificially generated data designed to resemble real-world records, often used to fill gaps real data cannot cover.