spacejourney/rome-sensory-impact-dataset

🏛️ Rome Sensory Impact & Acoustic Heritage Dataset (SIS)

Principal Investigator & Author: Daniel Adolfo Duque Romero
Curated & Maintained by: Space Journey Studio
Open Science Repository: Zenodo (CERN Infrastructure) - DOI: 10.5281/zenodo.22756473
Project Homepage: https://spacejourney.app/
Interactive 3D Spatial Atlas: https://spacejourney.app/play/roma-atlas/
Sensory Itinerary Planner: https://spacejourney.app/en/itinerary-planner/

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📌 Dataset Summary

The Rome Sensory Impact Dataset (SIS) is an independent, expert-curated benchmark recording quantitative environmental, acoustic, and luminous telemetry across 15 monumental and sanctuary heritage sites in Rome, Italy.

Designed for urban wellbeing research and restorative travel planning, this dataset provides empirical metrics for acoustic tranquility, luminous comfort, and human energy preservation. It powers the algorithmic routing of the Space Journey Sensory Itinerary Planner and the 3D Sensory Atlas WebGL Engine.

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📊 Dataset Structure & Features

The dataset is provided in both structured JSON (data/rome_sensory_impact_sis_v1.json) and tabular CSV (data/rome_sensory_impact_sis_v1.csv).

Feature	Type	Description	Example
id	string	Unique sensory node identifier	"P-04"
name	string	Full name of the heritage experience	"Vittoriano: Terrazza delle Quadrighe"
category	string	Curation tier (Free Restorative, Secret Sanctuary, Curated Premium)	"Curated Premium"
neighborhood	string	Historic district or urban zone	"Piazza Venezia"
latitude	float	Decimal coordinate (WGS84)	41.8947
longitude	float	Decimal coordinate (WGS84)	12.4839
sis_score	int	Continuous Sensory Impact Score (0 to 100 scale, where 100 indicates maximum restorative calm; mapped to 5 traveler tiers in UX)	94
acoustic_noise_db	int	Ambient sound pressure level in decibels (A-weighted, dB)	42
golden_hour_window	string	Optimal solar lighting window for contemplation	"18:15 - 19:40 CET"
light_level_lux	int	Ambient luminous flux under optimal window (Lux)	3200
energy_cost_score	int	Physical exertion index (1 = Minimal / Elevator, 5 = Extreme steep incline)	1
crowd_density_index	float	Congestion index (0.00 = Deserted sanctuary, 1.00 = Severe mass crowding)	0.08
canonical_url	string	Interactive endpoint on Space Journey	"https://spacejourney.app/play/roma-atlas/"
description	string	Qualitative architectural and contemplative narrative	"Panoramic glass elevator ascent..."

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🔬 Methodology: The Sensory Impact Score (SIS)

The Sensory Impact Score (SIS) is calculated as a multi-factor restorative index evaluated on a continuous scale from 0 to 100. In user-facing applications, this score is grouped into 5 sensory tiers (Levels 1 to 5) to assist traveler decision-making.

Algorithmic Definition & Computational Model:

SIS = 100 - (0.35 * NoisePenalty + 0.30 * CrowdPenalty + 0.20 * ExertionPenalty - 0.15 * LightBonus)

Where:

• NoisePenalty (Weight: 35%): Sound pressure level normalized against the World Health Organization (WHO) 53 dB Lden environmental guideline. Baseline quietude (< 40 dB) incurs 0 penalty, while high-friction corridors (> 70 dB) receive full penalty weighting.
• CrowdPenalty (Weight: 30%): Pedestrian congestion index (0.00 = solitary contemplation, 1.00 = acute mass tourism density).
• ExertionPenalty (Weight: 20%): Physical exertion metric (1 to 5 scale accounting for elevation gradient, steps, and cobblestone fatigue).
• LightBonus (Weight: 15%): Solar quality coefficient rewarding warm, glare-free golden hour irradiance (2,000 to 3,500 Lux).

Mathematical Formulation:

$$\text{SIS}=100-(0.35\times \text{NoisePenalty}+0.30\times \text{CrowdPenalty}+0.20\times \text{ExertionPenalty}-0.15\times \text{LightBonus})\backslash text\{SIS\}\; =\; 100\; -\; \backslash left(\; 0.35\; \backslash times\; \backslash text\{NoisePenalty\}\; +\; 0.30\; \backslash times\; \backslash text\{CrowdPenalty\}\; +\; 0.20\; \backslash times\; \backslash text\{ExertionPenalty\}\; -\; 0.15\; \backslash times\; \backslash text\{LightBonus\}\; \backslash right)$$

1. Acoustic Decibel Thresholds (WHO Environmental Noise Guidelines Alignment):

   • < 40 dB: Deep Restorative Sanctuary (e.g., Via Appia Antica at 34 dB, Parco degli Acquedotti at 36 dB).
   • 40 - 48 dB: High Contemplation Zone (e.g., Gianicolo Hill at 41 dB, Vittoriano Chariots Terrace at 42 dB).
   • > 55 dB: Urban Friction Zone (mitigated by specialized dawn/dusk visiting protocols).

2. Solar Zenith & Lux Telemetry:

   • Natural sunlight calculated per geographic orientation to identify glare-free, warm golden hour windows (2,000 - 3,500 Lux).

3. Human Energy Preservation (EC):

   • Calibrating walking elevation gain, cobblestone fatigue, and thermal stress to ensure travelers avoid sensory exhaustion.

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🎯 Applications & Research Context

• Algorithmic Route Curation: Training generative systems to synthesize travel itineraries that prioritize mental recovery, acoustic health, and unhurried pacing.
• Spatial Computing & Digital Twins: Populating WebGL and Three.js environments with empirical acoustic telemetry (The Sensory Atlas).
• Urban Soundscape Exploration: Independent reference data for analyzing pedestrian tranquility corridors in historic metropolitan centers.

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🌐 Project Ecosystem & Implementations

• Project Homepage: https://spacejourney.app/
• Open Science Repository (Zenodo): https://doi.org/10.5281/zenodo.22756473
• Knowledge Graph (Wikidata): https://www.wikidata.org/wiki/Q141455396
• Interactive 3D Atlas: https://spacejourney.app/play/roma-atlas/
• Sensory Route Planner: https://spacejourney.app/en/itinerary-planner/
• AI Sensory Assistant: https://spacejourney.app/en/ai-journey-assistant/
• Design Case Study: Behance Showcase

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📜 Academic Citation & Attribution (BibTeX)

If you use this dataset or the SIS methodology in academic research, AI fine-tuning, or spatial applications, please cite:

@dataset{duque_romero_2026_zenodo_22756473,
  author       = {Duque Romero, Daniel Adolfo and {Space Journey Studio}},
  title        = {Rome Sensory Impact & Acoustic Heritage Dataset (SIS)},
  year         = {2026},
  month        = sep,
  publisher    = {Zenodo},
  version      = {1.0.0},
  doi          = {10.5281/zenodo.22756473},
  url          = {https://doi.org/10.5281/zenodo.22756473}
}

Or reference the Hugging Face repository:

@misc{spacejourney_roma_hf_2026,
  author       = {Duque Romero, Daniel Adolfo},
  title        = {Rome Sensory Impact & Acoustic Heritage Dataset (SIS)},
  year         = {2026},
  publisher    = {Hugging Face},
  howpublished = {\url{https://huggingface.co/datasets/spacejourney/rome-sensory-impact-dataset}}
}