Data Source Overview
The Reverseau dataset draws from two distinct categories of information, each serving a different purpose within the platform. Neither source independently constitutes a complete picture — they are combined to provide contextual telecommunications intelligence.
Source 1: Community-Submitted Reports
The primary and most substantial data source is community-submitted reports. These reports represent first-hand accounts from individuals who have received phone calls or SMS messages.
Key characteristics of community report data:
- Submitted anonymously — no registration or personal identification required
- Structured fields include phone number, caller type classification, safety rating, and written description
- Reports are moderated through automated and human review processes
- Data volume has accumulated since 2014
Community reports reflect self-selected participation and do not represent a statistically random sample of all call recipients.
The pipeline for processing community reports is documented in Community Reporting & Processing Model.
Source 2: Public Telecommunications Allocation Records
Phone number allocation and service type information is sourced from publicly available records maintained by the Australian Communications and Media Authority (ACMA). This data provides:
- Carrier allocation — which telecommunications carrier has been assigned a number range
- Service type — whether a number range is classified as landline, mobile, VoIP, or special service
- Geographic region — the area code and associated state or territory for landline numbers
- Allocation status — whether a number range is allocated, quarantined, or available
This public data is refreshed periodically and supplements community reports with structural telecommunications context. Allocation records reflect number range assignments, not subscriber-level usage. They do not confirm caller identity or current ownership — see Number Classification System for the allocation vs. ownership distinction.
Cross-Referencing Approach
Reverseau combines these two data sources to produce the information displayed on phone number pages. The cross-referencing process includes:
- Number validation — submitted phone numbers are checked against known allocation ranges to determine whether they correspond to valid Australian numbering formats
- Service type enrichment — community reports are enriched with service type and carrier data from ACMA allocation records
- Geographic context — for landline numbers, area code data provides state and regional context
- Consistency checks — automated checks flag cases where submitted data appears inconsistent with known allocation records. Such checks assess structural consistency only and do not evaluate the factual accuracy of reported call content
Cross-referencing enhances structural accuracy but does not verify the substance of reported experiences.
What Reverseau Does Not Source
For clarity, the following data types are not sourced or available through this platform:
- Caller identity or personal information
- Business registration or ABN records
- Direct carrier feeds or real-time porting data
- Law enforcement or regulatory investigation data
- Call records, metadata, or interception data
- Subscriber account data held by telecommunications providers
Metadata Refresh Frequency
Community reports are processed and published in near-real-time, subject to the moderation pipeline. Public allocation data is refreshed periodically as ACMA updates its records. The refresh cycle means that recently ported or reallocated numbers may temporarily display outdated carrier information. Reverseau does not receive real-time carrier routing updates.
Identity & Subscriber Data Boundaries
Reverseau does not perform identity resolution, subscriber tracing, or investigative profiling of phone number users.
Related Documentation
- Community Reporting & Processing Model — submission and processing pipeline
- Number Classification System — numbering structure and allocation
- Transparency & Data Integrity — moderation and data quality processes