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Information Security, Ethics, and Legislation - Coggle Diagram

- - - - Informed consent
      - Data controller responsibility
      - Privacy impact assessments
- - - - Discriminatory use of data
        
        Employee surveillance without justification
        
        Algorithmic bias and lack of transparency
- - - - Capture: Data collection (manual, automated, or hybrid).
        
        Importance: clear criteria, validation, avoid overload.
        
        Processing: Organize, clean, analyze, and visualize data.
        
        Use of AI and data mining.
        
        Storage: Secure and efficient data storage (servers, cloud, blockchain).
        
        Consider security, accessibility, and legal compliance.
        
        Dissemination: Provide relevant, timely, and secure information.
        
        Communication strategy, access levels, suitable formats.
  - - - Monitoring and evaluation (M&E) systems, KPIs.
      - Balanced Scorecard (integrates financial and non-financial indicators).
      - Process maps, traceability matrices, quality management tools (Six Sigma, Lean, ISO 9001).
    - - International standards: ISO 8000, ISO/IEC 25012, ISO/IEC 27001.
        
        Metrics:
        
        Objective: % incomplete records, errors, inconsistencies.
        
        Subjective: user perception of usefulness and reliability.
  - - - Vertical: top-down flow, rigid communication, limited feedback.
        Horizontal/matrix: bidirectional flow, collaboration, agility.
    - - Formal: regulated and documented (reports, databases, platforms).
        Informal: spontaneous (personal networks, chats, conversations).
  - - - Micro
      - Meso
      - Macro
- - - - Education: predict dropout, personalize learning.
      - Health: optimize resources, detect patterns.
      - Business: market segmentation, customer loyalty, ROI.
      - Public sector: evidence-based policies, impact evaluation.
  - - - High-quality, timely, and contextualized information.
      - Trained personnel in analysis and critical interpretation.
      - Data governance, ethics, transparency, and participation.