Role: Creator & Lead Developer
Tech: Ruby on Rails, Node.js, AWS Lambda, PostgreSQL, NLP
The Non-Ordinary Reality Database (NORD) was an early attempt to systematically collect and classify reports of dreams, OBEs, and anomalous experiences as structured data. It sought to transform qualitative narratives into searchable, research-grade datasets.
Daniel built NORD’s backend and crawlers to aggregate over 100,000 experiences from public sources. He developed NLP pipelines to extract themes, entities, and emotional tone, while creating schemas flexible enough to evolve with new insights about consciousness.
This foundation now underpins the DSETI Dream Archive, demonstrating how large-scale experiential data can inform AI tools that analyze dreams and anomalous phenomena with nuance and respect.