The Robonomics chain is a parachain in the Polkadot and Kusama ecosystems designed to provide a decentralized infrastructure for the Internet of Things (IoT) and cyber-physical systems.

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Blockchains (L2)

Robonomics Network

# Robonomics Network Token holders Methodology

## 1. Overview

Token holders measures the number of unique addresses that hold a non-zero balance of the native asset on Robonomics Substrate. This metric is used to track the growth and distribution of the network’s holder base over time. By monitoring the expansion of unique holding addresses, the adoption and decentralization of the Robonomics Network are quantified for institutional analysis.

## 2. Data sources

- **Blockchain events**: `NewAccount` and `KilledAccount` events from Robonomics Substrate
- **External data**: Asset metadata for canonical project identification

## 3. Step-by-step calculation

### Component A: Daily account change tracking

- **Purpose**: Quantify the net change in unique addresses with a non-zero balance on a daily basis.
- **Logic**: `NewAccount` and `KilledAccount` events are parsed from Robonomics Substrate system records. A value of positive one is assigned to each `NewAccount` event, representing the initiation of an address balance. A value of negative one is assigned to each `KilledAccount` event, representing an address balance falling below the existential deposit threshold. These values are aggregated by day to determine the net change in the holder base.
- **Key fields**: `block_timestamp`, `event_method`

### Component B: Cumulative holder aggregation

- **Purpose**: Calculate the total number of unique holders through a running sum of historical changes.
- **Logic**: A cumulative sum is applied to the net daily changes calculated in Component A across the entire history of the blockchain. This running total represents the aggregate number of unique addresses currently holding the native asset. For days where no account events are recorded, forward-filling logic is applied to maintain a continuous time series from the last known value.
- **Key fields**: `daily_change`, `timestamp`

### Component C: Normalization and final filtering

- **Purpose**: Finalize the metric for reporting and ensure data integrity.
- **Logic**: The cumulative counts are cast to high-precision numeric types to ensure accuracy. The dataset is filtered to include only records where the holder count is greater than zero. All values are mapped to UTC day boundaries and associated with the canonical identifier for the Robonomics Network.
- **Key fields**: `tokenholders`, `timestamp_grain`

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

Unique addresses holding a non-zero balance of the project's native token.

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