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Office and Administrative Buildings

(Office and Administrative Buildings – Hourly Energy Dataset)

Dataset Purpose​

This dataset acts as a base data service for algorithms oriented towards the efficient energy management of office buildings and administrative spaces, such as town halls, municipal headquarters, and public administrative centers.

The dataset allows for monitoring and analyzing energy consumption associated with HVAC, lighting, and IT equipment, enabling algorithms for inefficiency detection, comparative analysis, and tracking of sustainability goals, all within a Compute-to-Data environment that guarantees data sovereignty and institutional control.

Scope and Technical Considerations​

Given the institutional nature of these buildings and the need for transparency and control, the dataset is designed to offer useful analysis without exposing sensitive information:

  • Data is filtered by a specific time period (day, week, or month)
  • The resolution is hourly
  • Only strictly necessary energy fields are included
  • No direct exposure of internal operational or security information

This approach allows for data-driven energy management, compatible with public governance requirements.

Dataset Type​

  • Private Dataset
  • Non-downloadable
  • Accessible only by authorized algorithms
  • Governed under public administration data policies
  • Executed via Compute-to-Data on Empower-X

Users do not access the raw data directly; only derived results.

Dataset Content​

The dataset contains hourly energy data associated with electrical supply points powering administrative buildings and public offices.

Each record represents the energy consumption of one supply point (CUPS) at a specific hour, without revealing sensitive information about the internal operation of the building.

Dataset Format​

The dataset follows a fixed tabular format, common to the rest of the ecosystem datasets.

Dataset Structure​

FieldDescription
cups_idSupply point identifier (anonymized if applicable)
timestampDate and time of the record (hourly resolution)
energy_consumed_kwhEnergy consumed in that hour (kWh)
energy_generated_kwhEnergy generated in that hour (kWh, if exists)
energy_exported_kwhEnergy exported to the grid in that hour (kWh, if exists)

In many administrative buildings, generation and export fields may be null.

What Each Field Represents​

  • cups_id Identifier of the supply point associated with an administrative building or public office, anonymizing the identity of the specific asset if necessary.

  • timestamp Allows for analysis of hourly patterns linked to working hours, equipment usage, and inactivity periods.

  • energy_consumed_kwh Electrical energy consumed by HVAC systems, lighting, and IT equipment during the indicated hour.

  • energy_generated_kwh Energy generated locally (e.g., photovoltaic in public buildings), when applicable.

  • energy_exported_kwh Energy exported to the grid, in case of existing local generation.

Relation to Algorithms​

This dataset feeds algorithms oriented towards:

  • Detection of energy inefficiencies
  • Analysis of anomalous patterns via AI
  • Optimization of operating schedules
  • Tracking of sustainability goals
  • Comparative analysis between administrative buildings
  • Support for public energy management dashboards

Algorithms access only the fields necessary for each analysis.

Security, Governance, and Audit​

  • The data does not leave the secure environment
  • Dataset download is not permitted
  • Access regulated by institutional policies
  • Auditable executions
  • Results always aggregated or derived

This design guarantees public control, traceability, and compliance with good governance principles.

Summary​

The office and administrative buildings dataset provides a secure, governed, and hourly view of energy consumption in public headquarters and administrative centers. Designed as a private data service for Compute-to-Data, it enables the execution of algorithms for optimization, inefficiency detection, and sustainability tracking, reducing operational costs and reinforcing the exemplary role of public administration in environmental responsibility.