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alterlab-datacommons

Resolve place names to Data Commons DCIDs and fetch statistical observations via Python API.

58|9|Updated Mar 16, 2026
Search Tags:#time-series#knowledge-graph#datacommons#entity-resolution#dcid-resolution#observation-fetch#api-python
One-click install
npx skills add https://github.com/AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-datacommons
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: alterlab-datacommons
Source: https://github.com/AlterLab-IEU/AlterLab-Academic-Skills/tree/main/skills/databases/alterlab-datacommons
Command: npx skills add https://github.com/AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-datacommons

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Resolve place names to Data Commons DCIDs and retrieve statistical observations across multiple domains.

Core Features & Use Cases

  • Resolve DCIDs from names, Wikidata IDs, and coordinates to enable downstream queries.
  • Fetch observations for multiple entities, time ranges, and variables, with optional facet filtering and hierarchical queries.
  • Explore the knowledge graph and perform entity resolution workflows to support research tasks.

Quick Start

Install the datacommons-client package, resolve place names to DCIDs, and fetch observations for those entities.

Frequently Asked Questions about alterlab-datacommons

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I resolve place names to Data Commons DCIDs for statistical queries?▼

You resolve place names to Data Commons DCIDs by using a Python API workflow that maps names, Wikidata IDs, and coordinates to unique identifiers for downstream statistical observations and knowledge-graph queries.

What statistical data can I retrieve using Data Commons DCID resolution?▼

Data Commons DCID resolution allows you to retrieve statistical observations across demographic, economic, health, and environmental domains, supporting time series analysis and geographic hierarchy queries.

How do I fetch time series observations for multiple entities in Data Commons?▼

You fetch time series observations for multiple entities by using a Python client to query resolved DCIDs across specified time ranges and variables, applying optional facet filtering and hierarchical queries.

Can I explore knowledge-graph relationships and perform entity resolution with Data Commons?▼

Yes, you can explore the knowledge graph and perform entity resolution workflows to support research tasks, discovering variables and fetching observations across geographic hierarchies.

Do I need to install the datacommons-client package to use this Data Commons workflow?▼

Yes, you need to install the datacommons-client package to enable the Python API workflow for resolving place names to DCIDs and fetching statistical observations across multiple domains.

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