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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

Ready to run

npx skills add https://github.com/AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-datacommons

💬 Prompt for ChatGPT / Claude Chat▼

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.