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\nThe goal is to build a stateâofâtheâart crossâcollection discovery platform powered by the Linked Art data model (a profile of CIDOCâCRM) to unify cultural heritage data across museums, libraries, and archives.
\nThe platform emphasizes:
\n---
\nMuseum and library staff who need intuitive backend interfaces to create semantic relationships without touching raw JSONâLD.
\nTechnologists who require predictable, wellâstructured JSONâLD REST APIs for downstream apps, UI layers, and integrations.
\nEnd users who want visual, exploratory discovery tools that hide graph complexity while surfacing rich contextual connections across institutions.
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\nUse an Archesâbased framework (e.g., Ogee) to provide userâfriendly forms that automatically generate Linked Artâcompliant JSONâLD.
\nPipelines reconcile legacy strings against Getty AAT/ULAN/TGN, LoC, and Wikidata.
\nETL pipelines convert flat CMS exports (XML/JSON/CSV) into structured Linked Art nodes.
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\nSupport both:
\nEnable multiâentity, crossâcollection questions such as:
\nâFind works by European artists depicting the American West in the 19th century.â
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\nFirstâclass pages for people, places, and concepts enriched with Wikidata/dbPedia context.
\nDynamic browsing of large datasets (e.g., artists by birth year, exhibition histories).
\nZoomable timelines + map layers linked to gazetteers like PeriodO.
\nDeep zoom, highâresolution viewing, and sideâbyâside comparisons.
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\nShift from objectâcentric to activityâcentric modeling: production, provenance, exhibitions, etc.
\nDistinguish:
\nPrevents redundant data entry and improves reuse.
\nEnforce hierarchical concept vocabularies for seamless navigation and faceted filtering.
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\nIf you'd like, I can also generate:
\nThis is a very strong baseline PRD that accurately captures the core philosophy of Linked Art (CIDOC-CRM profile), its dual audience, and the necessary tech stack.
\nHowever, to make this truly State-of-the-Art (SOTA) for modern software development and current cultural heritage standards, we need to bridge the gap between traditional semantic web technologies and modern AI/data paradigms, while also filling out standard PRD structural gaps (KPIs, Risks, Out-of-Scope).
\nHere is how we can improve and elevate this PRD:
\nThe current PRD describes a standard 2020-era Linked Art implementation. To make it cutting-edge, integrate these features:
\nA professional PRD needs to define what success looks like and what could go wrong.
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\nAdd the following sections to your document to instantly elevate it:
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\nI recommend generating the Diagrammatic Architecture Map next.
\nBecause we are talking about a hybrid datastore (Triple Store + Document DB), an ETL pipeline from legacy CMS systems, IIIF servers, and a new AI query layer, visualizing how data flows from the Museum CMS âĄď¸ ETL Pipeline âĄď¸ Linked Art Graph âĄď¸ React/Next.js Frontend is the most crucial next step to get engineering buy-in.
\nWould you like me to map out that Architecture Diagram detailing the specific modern tech stack (e.g., Elasticsearch + Blazegraph/Neptune + Next.js + IIIF Image Server)?
\nHere is the upgraded 10/10 PRD.
\nI have removed the residual citation markers, added a concrete 3-phase rollout roadmap, explicitly defined the reconciliation logic (using external authorities), and established strict API security and rate-limiting requirements to protect the database from heavy graph queries.
\n!đ¨Â Linked Art Web Application â Product Requirements Document (PRD)
\n!đ§Â 1. Executive Summary
\nThe Linked Art Web Application is a modern, standardsâcompliant platform for ingesting, transforming, validating, and publishing cultural heritage data using the Linked Art profile, a JSONâLD implementation of the CIDOCâCRM ontology.
\nLinked Art intentionally reduces the complexity of CIDOCâCRM while retaining its expressive power â covering 90% of real museum use cases with ~10% of the complexity.
\nThis application enables museums, archives, libraries, and research institutions to publish interoperable, eventâbased cultural heritage data for public access, scholarly research, and crossâinstitutional aggregation.
\n!đ§ŠÂ 2. Problem Statement
\nCIDOCâCRM is powerful but extremely complex, containing dozens of classes and hundreds of relationships. Most institutions lack the resources to implement it directly.
\nLinked Art provides a practical, interoperable subset of CRM, but institutions still need:
\n A turnkey ingestion pipeline
\n A validation and mapping engine
\n A searchable public interface
\n A JSONâLD API
\n A graphâbased visualization layer
\nThis PRD defines a complete system that solves these gaps.
\n!đŻÂ 3. Goals & NonâGoals
\nGoals
\n Publish cultural heritage data in Linked Art JSONâLD format.
\n Provide a complete ETL pipeline: ingest â map â validate â publish.
\n Offer a public search and browsing interface.
\n Support eventâbased modeling (production, acquisition, attribution, etc.).
\n Ensure interoperability with other Linked Art and IIIF systems.
\n Provide developerâfriendly APIs for reuse and integration.
\n Enable research workflows through graph and timeline visualizations.
\nNonâGoals
\n Full implementation of the entire CIDOCâCRM ontology (intentionally avoided to maintain simplicity).
\n Acting as a collections management system (CMS).
\n Providing image hosting (integrates with IIIF instead).
\n!đĽÂ 4. User Personas
\n!đźď¸Â Museum Curator
\nNeeds to publish authoritative object metadata and provenance.
\n!đ§ŞÂ Digital Humanities Researcher
\nNeeds structured, eventâbased data for analysis and visualization.
\n!đ ď¸Â Software Developer
\nNeeds clean JSONâLD APIs for integration with external systems.
\n!đď¸Â Cultural Heritage Institution
\nNeeds a standardsâcompliant, lowâmaintenance publishing platform.
\n!đ 5. User Flows
\n5.1 Data Ingestion Flow
\n1 Upload source data (CSV, JSON API, XML).
\n2 System maps fields to Linked Art patterns.
\n3 Validation engine checks conformance.
\n4 User reviews and resolves any reconciliation conflicts.
\n5 Data is published as JSONâLD.
\n5.2 Public Browsing Flow
\n1 User searches for an object, person, or event.
\n2 Results appear with facets (type, date, location).
\n3 User opens a detail page.
\n4 Page displays Linked Art JSONâLD, images, events, relationships.
\n5 User explores graph or timeline views.
\n!đ§ąÂ 6. Functional Requirements
\n6.1 ETL Pipeline
\nBased on real Linked Art workflows, which include source â mapped â Linked Art JSONâLD stages.
\n Source ingestion: Accept JSON API, CSV, XML.
\n Mapping engine: Transform source data into intermediate model.
\n Linked Art generator: Produce final JSONâLD.
\n Validation: Ensure strict conformance with the Linked Art profile.
\n Reconciliation Engine: Deduplicate agents, places, and concepts by mapping against external authorities (Getty ULAN, AAT, TGN, Wikidata). Flag conflicts for manual review in the Admin UI.
\n Versioning: Track changes and updates over time.
\n6.2 JSONâLD API
\n REST endpoints for objects, agents, events, places.
\n JSONâLD â @contextâ support.
\n Pagination, filtering, faceting.
\n Graph expansion (â ?expand=events,actorsâ ).
\n IIIF image linking.
\n6.3 Search & Discovery
\n Fullâtext search.
\n Faceted navigation.
\n Autocomplete.
\n Timeline view.
\n Network graph view.
\n6.4 Admin Interface
\n Upload datasets.
\n Review validation errors and reconciliation conflicts.
\n Approve publication.
\n Manage field mappings.
\n!âď¸Â 7. NonâFunctional Requirements
\nPerformance
\n Ingest 10k objects under 5 minutes.
\n API responses < 200ms for common queries.
\nReliability
\n 99.9% uptime.
\n Automatic retries for ingestion jobs.
\nSecurity & API Governance
\n Access Control: Roleâbased access control (RBAC) for the Admin interface.
\n Audit Logs: Track all data ingestion and mapping changes.
\n Rate Limiting: Throttling policies (e.g., 100 requests/minute per IP) to protect the database from expensive SPARQL/Graph expansion queries.
\n CORS: Configurable Cross-Origin Resource Sharing policies for external web integrations.
\n API Keys: Provisioning for developer tiers allowing higher rate limits.
\nAccessibility
\n WCAG 2.1 AA compliance for all public UI views.
\n!đ§ŹÂ 8. Data Model
\n8.1 Standards
\n Linked Art: JSONâLD profile built on CIDOCâCRM.
\n CIDOCâCRM: Eventâbased ontology for cultural heritage.
\n JSONâLD: Serialization format for Linked Data.
\n8.2 Core Entities
\n HumanMadeObject
\n Person / Group
\n Production / Acquisition Events
\n Place
\n DigitalObject (IIIF)
\n8.3 Required Patterns
\n Eventâbased modeling.
\n Identifiers & references.
\n Multilingual labels.
\n Provenance chains.
\n!đ§Â 9. ETL Requirements (Detailed)
\nBased on real Linked Art workflows: source â mapped â Linked Art.
\nSource Data
\n JSON API (e.g., PIA API).
\n CSV exports from existing CMS.
\n XML from legacy systems.
\nMapping Layer
\n Extract relevant fields.
\n Normalize dates, names, identifiers.
\n Map to Linked Art patterns.
\nLinked Art Output
\n JSONâLD with correct â @contextâ .
\n Conformance to Linked Art profile.
\n Stable, dereferenceable URIs.
\n!đ ď¸Â 10. API Requirements
\nEndpoints
\n â /objectsâ
\n â /agentsâ
\n â /eventsâ
\n â /placesâ
\n â /searchâ
\nFeatures
\n JSONâLD framing.
\n Filtering (â ?type=painting&date=1500-1600â ).
\n Sorting.
\n Graph expansion.
\n!đĽď¸Â 11. Frontend Requirements
\nSearch Interface
\n Keyword search.
\n Facets: type, date, location, material.
\nObject Detail Page
\n Title, description, IIIF images.
\n Production event.
\n Attribution.
\n Provenance.
\n Related objects.
\nVisualizations
\n Timeline.
\n Network graph.
\n Map view.
\n!đşď¸Â 12. Implementation Roadmap & Phasing
\nPhase 1: MVP (Core Foundation)
\n Goal: Establish the underlying data architecture and public read access.
\n Deliverables: Core JSON-LD API, rigid CSV ingestion (pre-mapped), basic search interface, and IIIF image integration.
\nPhase 2: The Publishing Engine (ETL Focus)
\n Goal: Allow non-technical curators to ingest and publish data independently.
\n Deliverables: Full Admin interface, robust mapping engine, JSON/XML ingestion, automated validation checks, and the reconciliation engine (Getty ULAN/Wikidata).
\nPhase 3: Research & Discovery (Advanced UI)
\n Goal: Unlock the full potential of event-based semantic data.
\n Deliverables: Network graph views, interactive timelines, map views for geographic provenance, and advanced API graph expansion (â ?expand=â ).
\n!đ§ŞÂ 13. TDD Requirements
\nTest Coverage
\n ETL mapping tests.
\n JSONâLD validation tests.
\n API contract tests.
\n UI component tests.
\n Accessibility tests.
\nAcceptance Criteria
\n Every Linked Art entity must validate against the profile.
\n Every API endpoint must return valid JSONâLD.
\n Every ingestion must produce deterministic output.
\n!đ 14. Success Metrics
\nTechnical
\n 100% JSONâLD validation pass rate.
\n <1% ingestion error rate.
\n <200ms API response time.
\nUser Experience
\n 90% successful search rate.
\n 80% of users find the desired object within 3 clicks.
\nAdoption
\n Integration with at least 3 external Linked Art systems.
\n!â ď¸Â 15. Risks & Dependencies
\nRisks
\n Source data quality from legacy CMS varies widely and requires heavy normalization.
\n Institutions may lack compliant IIIF servers for image fetching.
\n CIDOCâCRM updates may require upstream model changes.
\nDependencies
\n Linked Art specification.
\n CIDOCâCRM ontology.
\n IIIF Image API.
\n External data sources and authority files (Getty Vocabularies, Wikidata).
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