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References: Employee Event Streams

  1. Event-Driven Architecture - Wikipedia - Overview of event-driven system design patterns including event producers, consumers, channels, and processing. Provides architectural context for capturing organizational event streams.

  2. Complex Event Processing - Wikipedia - Explains how patterns are detected across streams of events in real time, including temporal correlation and event aggregation relevant to organizational activity analysis.

  3. Process Mining - Wikipedia - Covers techniques for discovering, monitoring, and improving real processes by extracting knowledge from event logs. Directly applicable to understanding how work actually flows through an organization.

  4. The Hidden Power of Social Networks - Rob Cross and Andrew Parker - Harvard Business Review Press (2004) - Chapter 3 covers data collection methods for organizational networks including email metadata, calendar data, and survey instruments that generate the event streams analyzed in this course.

  5. Process Mining: Data Science in Action (2nd Edition) - Wil van der Aalst - Springer (2016) - Definitive textbook on extracting process knowledge from event logs. Covers event log formats, discovery algorithms, and conformance checking applicable to organizational workflow analysis.

  6. RFC 5322 - Internet Message Format - Wikipedia - Technical specification of email message headers including From, To, CC, Date, and Message-ID fields that form the metadata backbone of email-based event streams.

  7. Apache Kafka Documentation - Apache Foundation - Documentation for the distributed event streaming platform commonly used to capture and transport organizational event streams at scale.

  8. ISO 8601 Date and Time Format - Wikipedia - International standard for date and time representation ensuring universal timestamps across event sources. Critical for correlating events from different systems.

  9. xAPI (Experience API) Specification - Wikipedia - Open standard for tracking learning experiences as event streams using actor-verb-object statements. Relevant to capturing training and development events in the organizational graph.

  10. Data Normalization - Wikipedia - Principles of organizing data to reduce redundancy and improve integrity. Applicable to normalizing heterogeneous event streams from email, chat, and device sources into consistent graph-ready formats.