Originally posted here by Dan Wolfson, Founder, Pragmatic Data Research Ltd. and member of the LF AI & Data Context Intelligence Work Group
Enterprise data catalogs are rarely built in a vacuum. Most are created with deliberate purpose: to satisfy a regulatory mandate, support a critical data migration, power an executive analytics initiative, or unblock discovery. For those initial goals, cataloging known, curated digital assets delivers immediate return.
The challenge isn’t that initial catalogs were designed poorly; it’s that organizations and technologies never stay still.
New business priorities emerge. Engineering teams spin up new cloud frameworks, AI pipelines, and external integrations. Mergers and acquisitions bring un-indexed digital estates into view. As a consequence, what we govern, how we govern it, and where opportunity resides continually shifts.
Core Principle: Surveying is decoupled from cataloging: exploring what might be useful must never require cluttering the enterprise catalog with what isn’t.
To help organizations navigate this ongoing evolution, our approach to metadata governance with Egeria must adapt to four core realities:
- More is not always better: Flooding a catalog with every unvetted artifact ever touched produces noise and stale metadata, eroding user trust.
- Exploration demands an asymmetric strategy: Depth need not be uniform. When investigating a new use case, exhaustive analysis of every candidate is cost-prohibitive. We need an evaluation funnel that starts broad and cheap to winnow the field, reserving deep technical scrutiny for viable contenders.
- Context is in the eye of the stakeholder: A single resource must be evaluated through multiple viewpoints—active analytical lenses (such as Security, Architecture, Compliance, or App/AI Building) that care about fundamentally different details.
- Governance requires exploring the unknown: Maintaining what is already registered is essential, but supporting new initiatives requires surveying uncharted territory—scouting candidate assets that live outside the catalog’s existing perimeter.
This is the first in a series exploring the use, design, and implementation of Resource Explorer, with particular emphasis on the role of Context Intelligence.
Egeria Resource Explorer (packages/resource-explorer in the open-source egeria-trellis repository) is designed around this exact discipline: the Survey Funnel.
For the full article, please go to pdr-associates.com/egeria-resource-explorer-part-1-the-survey-funnel-enabling-growth-change-and-value-with-egeria
