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Metadata Strategy & Schema Design.

Make your content assets findable, consistently described, and governable at scale — with an information-layer metadata strategy and schema built on taxonomy and information architecture disciplines, not just data engineering conventions.

Information Management Services

The Situation — When Clients Come to Us

Organizations come to us for metadata strategy and schema design when:

  • Content assets — documents, web pages, digital assets, research outputs, product information — exist across the organization but can't be consistently found, understood, or compared because metadata fields are missing, inconsistently populated, or defined differently across repositories
  • A DAM, CMS, intranet, or content platform has been implemented with a default metadata schema that doesn't reflect how the organization's content is actually structured, described, or searched — and poor findability and inconsistent tagging are the result
  • AI, GenAI, or enterprise search programs are underperforming because the content and data they reason over lacks the semantic structure, classification, and metadata quality those systems require — and the metadata schema was never designed with AI use cases in mind
  • Organizations preparing to migrate content to a new platform and needing a metadata strategy, field mapping, and governance model designed before — not during — the migration
  • Content governance programs that require documented metadata standards, controlled value lists, and stewardship accountability that the organization currently cannot produce

What We Do — Our Approach

  1. // Phase 1

    Metadata Inventory & Gap Analysis

    We conduct a comprehensive audit of existing metadata across the organization's content estate — assessing current field definitions, controlled value lists, taxonomy mappings, and governance standards across all priority repositories. We distinguish between technical metadata (format, location, file properties), descriptive metadata (subject, creator, date, type), and administrative metadata (rights, retention, workflow status) — and identify where each is absent, inconsistent, or ungoverned.

  2. // Phase 2

    Metadata Strategy Design

    We develop the metadata strategy — defining the metadata framework scope, schema approach (Dublin Core, schema.org, custom, or hybrid), stewardship model, and the integration approach between the metadata schema and the organization's taxonomy, ontology, and content governance programs. We make explicit which metadata elements are mandatory, recommended, or optional for each content type.

  3. // Phase 3

    Metadata Schema Development

    We develop the metadata schema — specifying all metadata fields with names, definitions, data types, cardinality rules, controlled value lists (drawn from the taxonomy or other controlled sources), and application guidelines for each content type and repository. We design the crosswalk between systems where metadata must be consistent across platforms.

  4. // Phase 4

    Taxonomy Integration & Controlled Vocabulary Alignment

    We integrate the metadata schema with the organization's taxonomy and controlled vocabularies — ensuring that subject, theme, category, and classification fields draw from governed vocabulary sources rather than free-text entry. We design the technical integration between the metadata schema and the taxonomy management platform.

  5. // Phase 5

    Governance Framework & Stewardship Design

    We design the metadata governance model — field-level stewardship assignments, quality standards, population guidelines, validation rules, and the audit and monitoring processes that sustain metadata quality over time. We provide implementation guidance for the client team or technology partner.

What You Get — Deliverables

  • Metadata inventory and gap analysis report — field-by-field assessment across priority repositories
  • Metadata strategy document — framework scope, schema approach, and stewardship model
  • Complete metadata schema — all fields with names, definitions, data types, cardinality, controlled value lists, and application guidelines by content type
  • Taxonomy integration specifications — connecting schema fields to governed controlled vocabulary sources
  • System crosswalk documentation for cross-platform metadata consistency
  • Metadata governance model — stewardship roles, quality standards, population guidelines, and validation rules
  • Implementation guidance for the client team or technology partner
  • Metadata quality baseline metrics and improvement tracking framework

Your content is only as findable as its metadata allows.

Iknow brings the information architecture depth — taxonomy integration, controlled vocabulary alignment, governance design — that most metadata programs are missing. Let's assess your metadata environment.

Contact Iknow

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