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MINT Data Catalog Primer and API Reference

Currently deployed at: https://api.mint-data-catalog.org/

Interactive Jupyter Notebook Demo

Play around with various api calls in a sanboxed environment (without affecting existing data) Binder

Documentation

The goal of MINT Data Catalog is to provide the data you need in the format you want. The high-level functionality can summarized with the following image

data_catalog_summary

More formally, the MINT Data Catalog is a system that provides a curated collection of datasets. Each dataset is a logical grouping of data about specific variables contained in one or more resources. The data in a dataset share metadata such as geospatial and temporal extent and provenance. Each dataset contains information about one or more variables, or scientific quantities of interest with a precise ontological definition. Variables are associated with one or more standard variable names, which are ontological classes in ontologies defined by domain scientists. Often a standard name is not sufficient to fully describe all of the metadata about a variable, so the data catalog defines a variable presentation capturing information about variables in datasets. Variable presentations include information about the variable’s representation such as the units of measure, handling of missing values, and metadata about collection. Data is physically located in one or more resources indexed by the data catalog. A resource can be a physical file, a web resource, or an API endpoint. For each resource, we define a layout, which captures the physical relationships between variables in the resource. For example, in a CSV file with columns corresponding to months and rows corresponding to different variables of interest (e.g., GDP, inflation rate, imports, exports, etc.), the layout specifies which row contains each variable and how those variables relate to the columns (time), while the variable presentation provides metadata such as units and how the variables were measured.

Below you can find more detailed documentation about the individual concepts.

Datasets

[TODO]

Standard Variables

[TODO]

Variables

Variables

Resources

Resources

About

Public-facing aspects of data catalog, such as documentation, demos, tracking issues, and feature requests

Resources

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