Collators aggregate parachain transactions block candidates and producing state transition proofs for validators based on those blocks.

Heima is a specialized identity and data verification blockchain powered by Polkadot Relay chain.

HEI holders own and govern the protocol. Heima’s investors include LD Capital, Digital Renaissance, Signum Capital, and others.

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Blockchains (L2)

Heima

# Heima Active addresses (weekly) Methodology

## 1. Overview

Weekly active addresses measures the number of unique addresses that have been active on the Heima network within a rolling 7-day window. This metric answers the business question "How many distinct users are actively using Heima each week?" and uses a rolling window approach where each day's value represents the count of unique addresses that were active in that day plus the preceding 6 days. The calculation supports both Heima's substrate blockchain and EVM execution environment.

## 2. Data sources

The calculation uses the following raw data sources:

- **Heima substrate extrinsics**: Transaction records from Heima's substrate blockchain containing sender address information in the `id` field and block timestamps
- **Heima EVM events**: Event logs from Heima's EVM execution environment, specifically ethereum pallet `Executed` events that contain user addresses in the first element of the `event_data` array
- **Chain availability data**: Metadata indicating which time periods have valid/supported data for different chains
- **Blockchain timestamps**: Block-level timestamp data used for daily aggregation boundaries

## 3. Step-by-step calculation

### Component A: User address extraction
- **Purpose**: Identifies unique user addresses from both Heima substrate and EVM activity
- **Logic**: Extracts user addresses from two distinct data sources. From substrate extrinsics, uses the `id` field directly as the user address. From EVM events, filters for ethereum pallet events with method `Executed` and extracts the user address from the first element of the `event_data` JSON array using `json_value(event_data[0])`. Each record is tagged with chain identifier ('heima' for substrate, 'heimaevm' for EVM), market sector ('blockchains_l2'), business segment ('blockchain'), and user type ('Transaction sender')
- **Key fields**: `block_timestamp` for temporal aggregation, `user_address` containing the extracted address, `chain` identifying the execution environment

### Component B: Daily active user calculation  
- **Purpose**: Calculates unique active users per day as the foundation for weekly aggregation
- **Logic**: Groups extracted user addresses by day using timestamp truncation to day granularity. Deduplicates user addresses within each day to count distinct active users. Maintains dimensional breakdown by chain, user type, market sector, business segment, and product. Creates the base daily active user dataset with `user_dau` field containing the unique address count
- **Key fields**: `timestamp` truncated to day, `user_dau` containing unique user addresses, dimensional fields for breakdown analysis

### Component C: Weekly active user aggregation using HyperLogLog
- **Purpose**: Efficiently calculates unique users over rolling 7-day windows using probabilistic counting
- **Logic**: Uses HyperLogLog (HLL) sketches to enable efficient distinct counting over time windows. Creates HLL sketches for each day's active users, then generates a complete datespine covering the full time range. For each day, creates a 7-day window by joining that day with the previous 6 days using interval arithmetic. Merges HLL sketches within each window and extracts the distinct count. Generates separate dimensional breakdowns for project level, chain level, user type level, and product level by grouping and merging sketches accordingly
- **Key fields**: `user_wau` containing the distinct user count over 7-day windows, `dimensions` indicating the breakdown level, dimensional identifier fields

### Final aggregation
- **Combining components**: The weekly active user counts are directly used as active addresses since user addresses and active addresses are synonymous in blockchain context
- **Currency conversion**: No currency conversion required as this is a count metric
- **Time aggregation**: Uses rolling 7-day windows where each day represents unique addresses active in that day plus the preceding 6 days
- **Final calculation**: Renames `user_wau` field to `active_addresses_weekly` and applies chain availability filters to ensure only data from supported time periods is included. The result is filtered to specific dimensional breakdowns ('chain' and 'project_dbt_tag') and formatted using standardized metric schema through the `finalize_metric_active_addresses_weekly` macro with zero-fill strategy for missing days

*This methodology was automatically generated by Token Terminal's methodology analyzer.*

Unique active addresses over a rolling 7-day window.

HeimaHEI

Active addresses (weekly)

Active addresses (weekly)

Competitive landscape

Chain breakdown