Foundational data schemas, seed data, and queries for the OpenStacks ecosystem.
The database layer for OpenStacks — structured development data for India and South Asia.
RootStack provides a SQLite database with schemas, seed data, and ready-to-use queries covering three domains:
- Development Indicators — Health, education, gender, and climate data at state and district level (NFHS-5, SRS, UDISE+, CPCB)
- Government Schemes — Central and state schemes with budget allocation, spending, and coverage data
- Tools Catalog — Registry of all scripts, notebooks, and templates across the OpenStacks ecosystem
git clone https://github.com/Varnasr/RootStack.git
cd RootStack
bash scripts/setup.shThis creates rootstack.db with all tables seeded. Then run queries:
# Health indicators across states
sqlite3 -header -column rootstack.db < queries/01_health_dashboard.sql
# Government scheme budgets and spending
sqlite3 -header -column rootstack.db < queries/02_policy_analysis.sql
# Cross-cutting analysis (climate-health, tribal districts, tools search)
sqlite3 -header -column rootstack.db < queries/03_cross_cutting.sql- SQLite 3 (pre-installed on most systems;
brew install sqlite3on Mac,apt install sqlite3on Linux)
RootStack/
├── schemas/ # Table definitions (run in order)
│ ├── 001_geography.sql # States and districts of India
│ ├── 002_sectors.sql # Development sector taxonomy
│ ├── 003_indicators.sql # Indicator definitions and values
│ ├── 004_policies.sql # Government schemes and budgets
│ └── 005_tools_catalog.sql # OpenStacks tools registry
│
├── seed_data/ # Initial data (run in order)
│ ├── 001_sectors.sql # 19 sectors and sub-sectors
│ ├── 002_states.sql # 30 states and UTs
│ ├── 003_districts_sample.sql# 26 sample districts across tiers
│ ├── 004_indicators.sql # 20 indicators with 51 data points
│ ├── 005_schemes.sql # 16 major schemes with budgets
│ └── 006_tools_catalog.sql # 32 tools across 4 stacks
│
├── queries/ # Ready-to-use analysis queries
│ ├── 01_health_dashboard.sql # State scorecards, district rankings, gender gaps
│ ├── 02_policy_analysis.sql # Budget overview, utilization, sector spending
│ └── 03_cross_cutting.sql # Multi-sector profiles, climate-health nexus
│
├── scripts/
│ └── setup.sh # One-command database creation
│
└── docs/
└── data_dictionary.md # Table descriptions, field conventions, sources
states ──< districts
sectors ──< indicators ──< indicator_values >── districts
sectors ──< schemes ──< scheme_budgets
──< scheme_coverage >── states/districts
stacks ──< tools >── sectors
| Table | Records | Source |
|---|---|---|
| States | 30 | Census 2011 |
| Districts | 26 (sample) | Census 2011 |
| Sectors | 19 | OpenStacks taxonomy |
| Indicators | 20 definitions | NFHS-5, SRS, PLFS, CPCB |
| Indicator Values | 51 data points | Various (see data dictionary) |
| Schemes | 16 major schemes | Union Budget, Ministry reports |
| Budgets | 13 entries | Union Budget 2023-24 |
| Stacks | 4 registered | OpenStacks ecosystem |
| Tools | 32 cataloged | InsightStack, FieldStack, EquityStack |
State health scorecard:
State IMR Stunting Anaemia
Uttar Pradesh 40.0 39.7%
Bihar 38.0 42.9% 63.5%
Madhya Pradesh 36.0 35.7%
Kerala 6.0 23.4% 36.3%
Scheme budget utilization:
Scheme Allocated (Cr) Spent (Cr) Utilization
Jal Jeevan Mission 70,000 62,000 88.6%
MGNREGA 60,000 82,000 136.7%
National Health Mission 36,785 33,200 90.3%
NCAP (Clean Air) 460 350 76.1%
RootStack is the data foundation of the OpenStacks ecosystem:
| Stack | Role | Link |
|---|---|---|
| RootStack (this repo) | Database schemas & seed data | You are here |
| BridgeStack | API backend (FastAPI) | Will consume RootStack data |
| ViewStack | Frontend UI | Will display via BridgeStack |
| InsightStack | MEL tools (Stata/Python/R) | Tools cataloged here |
| FieldStack | R notebooks for fieldwork | Tools cataloged here |
| EquityStack | Python data workflows | Tools cataloged here |
Contributions welcome — especially:
- More district data — Expand from 26 to all 766 districts
- More indicators — Add UDISE+ education data, PLFS employment data
- More schemes — State-level schemes, historical budget data
- PostgreSQL port — Adapt schemas for PostgreSQL deployment
- Migration scripts — Schema versioning for production use
See CONTRIBUTING.md for guidelines.
MIT — free to use, modify, and share. See LICENSE.
Created by Varna Sri Raman — Development Economist & Social Researcher