This dataset is released under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 licence (CC BY-NC-SA 4.0): research, academic, personal and other non-commercial use is permitted with attribution; adaptations must be shared under the same licence; commercial use is not permitted. The original public source data remains under the Government Open Data License - India (GODL-India). Commercial use: contact surya@judicialmind.ai or hello@judicialmind.ai.

India Data Catalog

Licence: CC BY-NC-SA 4.0 — research and non-commercial use only; derivatives must be shared under the same licence. Commercial use: contact surya@judicialmind.ai or hello@judicialmind.ai

Access is approved automatically when the email you enter matches your Hugging Face account email and belongs to the organisation you name; other requests are reviewed manually.

One clean, searchable metadata row for every resource on India's Open Government Data platform (data.gov.in) and every dataset on NITI Aayog's National Data and Analytics Platform (NDAP): 528,864 entries from 158 ministries and organisations, grouped into 20,786 catalogs and 32,544 template families (tables that share a column layout, such as one census table published per state).

It holds metadata only: titles, descriptions, ministry and department, sector, geographic level, years covered, row and column counts, column names, file formats, links, template ids and quality flags. No data rows; the tables themselves are in IndiaTables (same ids).

Quickstart

Input: a keyword and filters. Output: matching resources with their links.

import duckdb
from huggingface_hub import hf_hub_download

path = hf_hub_download("judicialmind/India-Data-Catalog", "resources.parquet", repo_type="dataset")
print(duckdb.sql(f"""SELECT id, title, ministry, geo_level, year_min, year_max, n_rows
                     FROM '{path}'
                     WHERE title ILIKE '%rainfall%' AND geo_level = 'district'
                     ORDER BY year_max DESC LIMIT 5"""))
print(duckdb.sql(f"SELECT quality, count(*) AS n FROM '{path}' GROUP BY quality ORDER BY n DESC"))

Expected output: five district-level rainfall resources (newest first; 1,686 match), then the headline-quality counts shown under Coverage (audit_clean 246,236, metadata_only 229,938, ...).

With pandas or datasets:

import pandas as pd
from datasets import load_dataset
from huggingface_hub import hf_hub_download

ministries = pd.read_parquet(hf_hub_download("judicialmind/India-Data-Catalog", "ministries.parquet",
                                             repo_type="dataset"))
print(ministries.sort_values("n_resources", ascending=False).head(3)[["source", "ministry", "n_resources"]])

ds = load_dataset("judicialmind/India-Data-Catalog", data_files="catalogs.parquet", split="train")
print(ds)

Files

File	What
`resources.parquet` (`resources.csv.gz`)	One row per resource or NDAP dataset (528,864)
`catalogs.parquet`	One row per data.gov.in catalog, a group of resources (20,786)
`templates.parquet`	One row per template family, with an example title and columns (32,544)
`ministries.parquet`	Counts per source and ministry

Schema

resources.parquet:

id: data.gov.in resource uuid, or ndap-<dataset id>. api_url, portal_url, datafile_url link to it; reference_url, external_ws_url as given by the portal.
source: data.gov.in, data.gov.in (legacy file), ndap or HMIS state reports (data.gov.in).
title, description, keywords, resource_category.
ministry, department, state_department, govt_type, sector, jurisdiction, catalog_uuid, catalog_title.
geo_level: national, state, district, subdistrict, block, village, city or unknown (detected from the table's columns; NDAP from its location granularity; for resources without a downloaded table, from title words, with geo_level_from = title).
year_min, year_max (years found in the table or NDAP's span), time_from, time_to (portal-declared), frequency, time_granularity; years_from says whether years came from the data, the portal's declared period or the title.
created, updated, published: portal dates.
n_rows (rows in the downloaded copy), api_total_rows (rows the API reported), n_cols, columns, file_format, file_size.
Portal flags and counters: high_value, api_available, active, view_count, download_count.
template_id, template_family and their sizes template_size, template_family_size: resources sharing a layout.
in_store, has_table: the resource has a cleaned table in IndiaTables.
Quality: truncated (the download stopped before the API total), empty, duplicated, excluded_pii (held back from table releases because it carries personal data), pii_policy, BharatData-Audit results (audit_tested, checks_evaluated, checks_held, audit_findings, audit_flags, audit_warns), the list quality_flags and a headline quality.

catalogs.parquet: catalog_uuid, catalog_title, keywords, ministry, sector, n_resources, rows_in_store, year_min, year_max, geo_level, n_template_families, n_audit_flag.

templates.parquet: template_family, n_resources, n_template_ids, example_title, ministry, geo_level, rows, year_min, year_max, example_columns.

ministries.parquet: source, ministry, n_resources, n_in_store, rows, n_catalogs, year_min, year_max, n_audit_flag, n_truncated.

Coverage

Snapshot May 2026; national to village level.

Entries by source:

Source	Entries
data.gov.in	512,698
data.gov.in (legacy file)	9,531
ndap	6,618
HMIS state reports (data.gov.in)	17

Headline quality:

quality	Entries
audit_clean	246,236
metadata_only	229,938
empty	20,859
not_audited	18,080
audit_flag	5,244
audit_warn	4,366
truncated	4,141

metadata_only means the resource is listed on the portal but no table was downloaded for it (file-only resources, API errors, or entries added after the May 2026 pull).

Source data

Built from the data.gov.in API catalogue snapshot (May 2026), the portal's resource and catalog listings, NDAP's dataset list, the cleaned tables of IndiaTables and the BharatData-Audit results. Contact e-mails in the portal listings were dropped.

Contains data from data.gov.in licensed under the Government Open Data License - India (https://data.gov.in/government-open-data-license-india). NDAP metadata from NITI Aayog (https://ndap.niti.gov.in), used under its terms of use.

Original data: published by the ministries, departments and State governments named per resource in ministry / department (data.gov.in), and NITI Aayog (NDAP) on the Open Government Data Platform India (data.gov.in) and, where marked, NITI Aayog's National Data and Analytics Platform (NDAP), under the Government Open Data License - India (GODL-India). The original public data remains under GODL-India; the CC BY-NC-SA 4.0 licence of this repository covers JudicialMind's compilation, derived fields, annotations, benchmarks and models.

Citation

@misc{judicialmind2026indiadatacatalog,
  title={India Data Catalog: metadata for every data.gov.in resource and NDAP dataset},
  author={JudicialMind},
  year={2026},
  publisher={Hugging Face},
  howpublished={\url{https://huggingface.co/datasets/judicialmind/India-Data-Catalog}}
}

License

CC BY-NC-SA 4.0 (see LICENSE): research, academic, personal and other non-commercial use, with attribution to JudicialMind and to the original data publishers; adaptations must be shared under the same licence. Commercial use requires a separate licence.

Commercial use: contact surya@judicialmind.ai or hello@judicialmind.ai.

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India Open Government Data — Bharat Tables Datasets

Collection

Research and non-commercial use (CC BY-NC-SA 4.0). Commercial: surya@judicialmind.ai / hello@judicialmind.ai • 5 items • Updated 3 days ago