IAQ Data Management

IAQ Data Management is the process of collecting, organizing, checking, storing, and sharing indoor air quality (IAQ) data. It helps turn sensor readings, laboratory results, and observations into reliable information for building managers, occupants, and researchers.

Good data management keeps measurements understandable and traceable, from their collection to their use in analysis and reporting.

Why IAQ Data Management Matters

Indoor air quality changes with activities such as cooking and cleaning, outdoor pollution, occupancy, and ventilation. Understanding these changes requires reliable measurements and information about the conditions in which they were collected.

Common data management challenges include:

• Data volume: Continuous monitoring can generate large numbers of records.
• Different data sources: Sensors, laboratory analyses, and occupant feedback may use different formats and methods.
• Data quality: Sensor drift, environmental conditions, and communication failures can affect readings or leave gaps.
• Context: Measurements are easier to interpret when linked to room characteristics, sensor locations, occupancy, and ventilation conditions.

The IAQ Data Lifecycle

Data management covers the following steps. Quality checks and documentation are needed throughout the process.

Stage	Main Tasks
1. Plan	Define the monitoring purpose, required data, responsibilities, and retention period.
2. Collect	Gather sensor readings, laboratory results, and relevant observations. Record units, locations, and measurement times or sampling periods.
3. Organize	Use consistent names, units, timestamps, and formats. Link measurements to information about the equipment and monitoring location.
4. Check	Identify missing records, duplicates, and questionable readings. Preserve original data and document any corrections, exclusions, or estimated values.
5. Store and Protect	Use organized storage, regular backups, and appropriate access controls.
6. Use and Share	Prepare data for analysis and reporting. Include documentation, known limitations, and conditions for reuse. Archive data according to the retention plan.

Key Principles

Consistent Formats and Definitions

Interoperability means that different systems can exchange and understand data. Shared parameter definitions, units, and identifiers help combine measurements from different sources.

EDIAQI's interoperability framework describes common data structures and standards, including the SensorThings API, to support data exchange between monitoring systems.

Metadata and Context

Metadata describes the data, including the sensor or sampling method, device identifier, calibration records, units, and time zone. Contextual information describes the monitored space and its use, such as room volume, sensor placement, occupancy, and ventilation operation.

Some information, such as room dimensions, changes rarely. Other information, such as occupancy and air exchange rates, can change over time and should be recorded accordingly.

FAIR Data

The FAIR principles support data that is:

• Findable: Identifiable and described with useful metadata.
• Accessible: Available through defined access methods, with authorization where needed.
• Interoperable: Organized using shared formats and definitions.
• Reusable: Accompanied by its source, processing history, limitations, and clear usage conditions.

FAIR data does not have to be publicly available without restrictions.

Privacy and Responsibilities

Indoor monitoring data can reveal information about people's presence and routines. Collect only the information needed, protect data during transfer and storage, and limit access appropriately. Before sharing, assess whether location details or other information could identify occupants.

Assign responsibility for maintaining the data, granting access, and deciding how long records should be kept.

Related Pages

• Measuring IAQ: Measurement approaches and practical monitoring considerations.
• Sensors: Sensor types, selection, calibration, and evaluation.
• Interpreting the Data: Understanding measurements and comparing results with guidelines.
• IAQ Data Reporting and Visualization: Communicating results through dashboards, reports, and alerts.