Queryless AI brings conversational data exploration to PortalJS. Users can discover datasets, analyze data, and generate charts simply by asking questions in plain English—making data portals easier and more accessible.
This guide walks through using the PortalJS Cloud API to programatically create datasets, add resources, upload and replace data files, and update metadata—showing how to build repeatable data update pipelines with code examples.
OpenMetadata is excellent for governance and power users, but difficult for broader audiences. Learn how PortalJS turns OpenMetadata into a user-friendly data portal focused on discovery and navigation.
Explore how the PortalJS MCP server unlocks AI-native discovery, metadata exploration, and data previews for modern portals — now open sourced and easy to integrate.
Empower your data portal with an insights catalog — a new way to explore, share, and communicate findings alongside your datasets.
How an MCP server bridges AI assistants and data portals, enabling seamless, efficient data discovery for ChatGPT, Claude, and other AI tools.
Migrating from a heavy CKAN 2.6 portal to a fast, fully static frontend — and the technical journey behind it.
Navigate the world of metadata standards from Dublin Core to DCAT to Frictionless Data. Learn which standards work best for government, academic, and enterprise data portals, and how to choose the right approach for your organization.
Learn how metadata transforms data discovery at scale—from search engines like Solr and Elasticsearch to standardized schemas that help users find exactly what they need among thousands of datasets.
Learn the basics of metadata—from built-in CSV attributes like filename and media type to simple external files—and see how it makes your data discoverable.