Information
Overview
The Information domain encompasses data assets, knowledge resources, and information flows that enable decision-making and value creation across the enterprise. This domain integrates information assets into business architecture, connecting them with capabilities, processes, stakeholders, and strategic objectives across the organizational ecosystem.
The domain emphasizes real-time data governance and quality management to maintain current and accurate information, predictive analytics capabilities to anticipate information needs under different business conditions, and lifecycle management from creation through archival to support proactive information management and strategic positioning.
Schema Version: 2.2
Last Updated: August 2025
License: Creative Commons Attribution-ShareAlike 4.0 (CC BY-SA 4.0)
What is Information?
Information represents any data, knowledge, or intellectual asset that provides value to the organization through decision support, operational efficiency, compliance, or competitive advantage. Information can range from structured databases and analytical reports to unstructured documents and tacit knowledge. In the context of enterprise architecture, information serves as a key enabler that connects organizational capabilities with business outcomes.
Information is fundamentally about knowledge power - how to capture it, organize it, access it, analyze it, and leverage it for strategic advantage. This applies across all domains from operational data to strategic intelligence, from internal knowledge to external market insights, from historical records to predictive analytics.
Core Components
The Information domain includes essential elements that work together to provide comprehensive information management:
Information Elements: Specific data structures, datasets, or knowledge components that define what information is captured and how it delivers value
Information Architecture: Technical and logical structure of how information is organized, stored, and accessed
Data Governance: Policies, procedures, and controls that ensure information quality, security, and compliance
Information Flow: Processes and mechanisms through which information moves across the organization
Knowledge Management: Capabilities for capturing, organizing, and sharing organizational knowledge and expertise
Information Attributes
Attribute | Type | Description | Example | Required |
|---|---|---|---|---|
| String | The name or title of the Information asset | "Customer Transaction Database", "Market Intelligence Repository" | ✓ |
| String | A detailed explanation of what the Information asset contains | "Comprehensive database of all customer transactions and interactions" | ✓ |
| String | The intended purpose or function within the Organization | "Support customer analytics and personalization initiatives" | ✓ |
| String | The individual or team responsible for the Information asset | "Chief Data Officer", "Customer Analytics Team" | ✓ |
| String | The organization unit(s) to which the Information asset is linked | "Data and Analytics Division" |
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| Enum | Broad categorization of information type |
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| Enum | Specific type of information |
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| Enum | Security and sensitivity classification |
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| Enum | Quality level of the information |
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| String | Technical format or structure of the information | "PostgreSQL database, JSON API, Excel spreadsheets, PDF documents" |
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| String | Size or scale of the information asset | "2.5TB database, 50M records, 10K documents updated daily" |
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| Enum | How often the information is updated |
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| String | Data retention policies and schedules | "Active for 7 years, archived for 10 years, then deleted per compliance" |
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| String | Origin systems or processes that generate the information | "CRM system, transaction processing, customer surveys, market research" |
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| String | Systems, processes, or users that utilize the information | "Analytics platform, reporting tools, customer service, executive dashboards" |
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| String | Other information assets or systems this information depends on | "Customer master data, product catalog, transaction logs" |
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| String | Technical interfaces and access methods | "REST API, database views, file exports, real-time streaming" |
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| String | Data governance policies and procedures | "Data stewardship committee, quality monitoring, access controls" |
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| Array[Enum] | Regulatory and compliance requirements |
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| String | Security measures and access controls | "Role-based access, encryption at rest and transit, audit logging" |
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| String | Privacy protection measures and policies | "Data anonymization, consent management, right to erasure procedures" |
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| String | Data quality measures and monitoring | "99.5% accuracy, completeness checks, validation rules, quality dashboards" |
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| String | Data lineage and transformation history | "Source → ETL → Data warehouse → Analytics mart → Reports" |
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| String | Descriptive information about the data structure and meaning | "Data dictionary, business glossary, technical specifications" |
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| Enum | Current stage in information lifecycle |
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| String | Business value and impact of the information | "Enables $2M annual savings through customer insights and optimization" |
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| String | Costs associated with maintaining the information asset | "Storage: $50K annually, maintenance: $30K, licensing: $20K" |
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| String | Potential risks associated with the information | "Data breach exposure, quality degradation, system dependencies" |
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| Array[Enum] | Categories of risks |
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| String | How the information is typically accessed and used | "Batch processing nightly, real-time queries during business hours" |
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| String | Performance characteristics and requirements | "Sub-second query response, 99.9% availability, 10GB/hour throughput" |
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| String | Integration with other systems and platforms | "Native CRM integration, API connections to analytics tools" |
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| String | Analytical capabilities and use cases | "Customer segmentation, predictive modeling, trend analysis, KPI tracking" |
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| String | Archiving strategies and procedures | "Automated monthly archiving, compressed storage, searchable archives" |
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| String | Backup and recovery procedures | "Daily incremental, weekly full backup, 4-hour recovery time objective" |
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| String | Monitoring and alerting capabilities | "Quality monitoring, usage tracking, performance alerts, anomaly detection" |
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| String | Documentation and knowledge management | "Technical documentation, user guides, data dictionary, training materials" |
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| String | Training and skills development for information users | "Data literacy programs, tool training, best practices workshops" |
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| String | Innovation opportunities and emerging technologies | "AI/ML integration, real-time analytics, automated data discovery" |
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| String | External partnerships for data sharing or enrichment | "Third-party data providers, industry consortiums, research collaborations" |
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| String | Scaling capabilities and future growth plans | "Cloud-native architecture supports 10x growth, auto-scaling enabled" |
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| String | Adherence to data standards and frameworks | "ISO 8000 data quality, industry data models, enterprise standards" |
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| String | Alignment with organizational goals and strategies | "Supports digital transformation and customer-centric strategy" |
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| String | How this information provides competitive differentiation | "Unique customer insights enable personalized experiences" |
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| Array[Object] | Specific components or structures within the information asset | See Information Element Components below |
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Enhanced Enumeration Values
Information Category (informationCategory)
Value | Description | Example |
|---|---|---|
| Data generated from day-to-day business operations | Transaction records, system logs, sensor data |
| Data processed and structured for analysis | Data marts, analytical datasets, aggregated metrics |
| Stable data used for classification and categorization | Country codes, product categories, organizational structure |
| Core business entities shared across systems | Customer master, product master, employee directory |
| Data about data structures and definitions | Data dictionary, schema definitions, lineage information |
| Unstructured information and documents | Documents, images, videos, web content |
| Captured expertise and intellectual assets | Best practices, procedures, lessons learned |
| Processed information for strategic decision-making | Market intelligence, competitive analysis, forecasts |
Information Type (informationType)
Value | Description | Example |
|---|---|---|
| Structured data storage systems | Relational databases, NoSQL databases, data warehouses |
| Defined collections of related data | CSV files, data tables, research datasets |
| Formatted information presentations | Business reports, dashboards, analytics outputs |
| Text-based information assets | Policies, procedures, specifications, contracts |
| Organized knowledge repositories | Wiki systems, expert systems, FAQ databases |
| Data accessible through programming interfaces | REST APIs, GraphQL endpoints, web services |
| Continuous data flows | IoT sensor streams, transaction feeds, event streams |
| Historical data storage | Backup systems, historical records, compliance archives |
| Analytical or predictive models | Machine learning models, statistical models, simulations |
| Interactive data visualization | Executive dashboards, operational monitors, KPI displays |
Data Classification (dataClassification)
Value | Description | Example |
|---|---|---|
| Information that can be freely shared | Marketing materials, public announcements, general company information |
| Information for internal organizational use | Internal reports, employee directories, operational procedures |
| Sensitive information requiring protection | Customer data, financial records, strategic plans |
| Highly sensitive information with limited access | Personal information, trade secrets, merger discussions |
| Most sensitive information requiring highest protection | National security data, critical infrastructure details |
Data Quality (dataQuality)
Value | Description | Example |
|---|---|---|
| Accurate, complete, consistent, and timely | Validated customer records, certified financial data |
| Generally reliable with minor issues | Most operational data with occasional gaps |
| Usable but with known limitations | Legacy data with some inconsistencies |
| Significant quality issues affecting usability | Incomplete datasets, outdated information |
| Quality has not been assessed | New data sources, unvalidated imports |
Update Frequency (updateFrequency)
Value | Description | Example |
|---|---|---|
| Continuous updates as events occur | Live transaction feeds, sensor data streams |
| Updated every hour | Operational metrics, system status reports |
| Updated once per day | Daily sales reports, batch processing outputs |
| Updated weekly | Weekly performance summaries, trend reports |
| Updated monthly | Monthly financial statements, customer analytics |
| Updated quarterly | Quarterly business reviews, strategic assessments |
| Updated annually | Annual reports, compliance certifications |
| Updated as needed | Project reports, special analyses |
| Rarely or never updated | Historical archives, reference data |
Compliance (compliance)
Value | Description | Example |
|---|---|---|
| General Data Protection Regulation | EU data protection compliance |
| Health Insurance Portability and Accountability Act | Healthcare data privacy |
| Sarbanes-Oxley Act | Financial reporting compliance |
| Payment Card Industry Data Security Standard | Payment processing security |
| Sector-specific standards | Banking, healthcare, manufacturing standards |
| Organization-specific requirements | Company data policies, internal standards |
Risk Categories (riskCategories)
Value | Description | Example |
|---|---|---|
| Information security and cyber threats | Data breaches, unauthorized access, cyber attacks |
| Privacy protection and personal data risks | Privacy violations, consent management, data exposure |
| Data quality and accuracy risks | Data corruption, inconsistencies, validation failures |
| System availability and access risks | System downtime, network failures, access issues |
| Regulatory and legal compliance risks | Regulatory violations, audit failures, legal penalties |
| Technology and infrastructure risks | System failures, integration issues, scalability problems |
| Operational and process risks | Process failures, human errors, resource constraints |
Lifecycle (lifecycle)
Value | Description | Example |
|---|---|---|
| Information asset being created or developed | Data modeling, system development, content creation |
| Information in regular operational use | Production databases, active reports, current systems |
| Information being maintained and updated | Regular updates, quality monitoring, performance tuning |
| Information moved to long-term storage | Historical data, compliance archives, backup systems |
| Information being deleted or destroyed | Data deletion, system decommissioning, secure disposal |
| Information being moved or transformed | System migrations, data consolidation, format changes |
Information Element Components
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