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cic-docs/TransactionDatasets.md
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TransactionDatasets

Data Sets from Blockchain Transactions and User Demographics

Datasets prior to 2020 are pulled from the POA blockchain for each user ex. https://blockscout.com/poa/core/address/0xcb55fc893000a984a5ad73011f93d1540a5f0895/tokens As well as user generated data and field surveys collected in Kenya. Fields described below.

Datasets Starting 2020 are pulled from the POA (xDAI) blockchain for each user ex. https://blockscout.com/poa/core/address/0xcb55fc893000a984a5ad73011f93d1540a5f0895/tokens As well as user generated data and field surveys collected in Kenya. Fields described below.

Brief description: Using a simple feature phone interface with USSD each user (people living below the poverty line in Kenya) starts with 400 Tokens and adverstises what they sell on a digital market place avalaible on the same interface. There are no transaction fees. The tokens are used often as a top-up to missing Kenyan shillings. Certian users / vendors were allowed to send 50% of their tokens to Grassroots Economics (GE) in return for Kenyan Shillings on a monthly basis. Each user only has one token assigned to them by GE based on where they live (Currently we have moved all users to the Sarafu token while we prepare for the next phase). When a user sends a token to another user that holds a different token a conversion is made automatically after receipt. This conversion uses a bonding curve (based on the Bancor Protocol) to adjust the token prices relative to eachother. Conversions can be seen as transactions to a contract address then that contract address sending the new token to the user. While the exchange rate information is avaliable to users, practially all the tokens are curently considered ~1:1 with the national currency as well as with eachother. For more information please contact us https://www.grassrootseconomics.org/contact

Post 2020 xDAI The Transaction csv fields:

  1. id - internal transaction ID number
  2. timeset - date and time of transaction
  3. transfer_subtype - internal typing: DISBURSMENT = from Grassroots Economics, RECLEMATION = Back to GE, STANDARD = a trade between users, AGENT = when a group account is cashing out
  4. transfer_use - The category the sender marked the transaction as - used for 'confidence' later for the user category - note this will be changed to boolean
  5. tx_hash - hashed transaction address on blockchain
  6. source - wallet ID of sender
  7. s_comm_tkn - Short name of Token that the source uses (each user should only have 1 token) - note that currently all users have Sarafu only
  8. s_gender - From user input
  9. s_location - Village name, From user input
  10. s_business_type - Entered by GE staff based on user inputed products or services
  11. target - wallet ID of recipent
  12. t_comm_tkn
  13. t_gender
  14. t_location
  15. t_business_type
  16. token_name - the token that was traded
  17. token_address - the blockchain address of token that was traded
  18. weight - How many tokens were traded

The user summary csv fields:

  1. id - Internal user id number
  2. xDAI_blockchain_address - Wallet ID on POA xDAI Blockchain
  3. old_POA__blockchain_address - Wallet ID on POA Blockchain if they had one
  4. comm_tkn - Their token name (each user only has 1 token) currenlty only Sarafu
  5. bal - current balance of [comm_tkn] as of file date
  6. location - User input (village name)
  7. gender
  8. business_type - Input by GE staff based on what the users sell
  9. ovol_in - total number of tokens that came into this account from non-STANDARD transactions
  10. ovol_out
  11. otxns_in - number of transactions incomming from non-STANDARD transactions
  12. otxns_out
  13. ounique_in - number of uniquie transactions incomming from non-STANDARD transactions
  14. ounique_in
  15. svol_in - total number of tokens that came into this account from STANDARD transactions
  16. svol_out
  17. stxns_in - number of transactions incomming from STANDARD transactions
  18. stxns_out
  19. sunique_in - number of uniquie transactions incomming from STANDARD transactions
  20. sunique_in
  21. start - day and time of first transaction (when the user account was setup)
  22. confidence - based on how many other purchasing users agree with the business_type

Pre 2020 POA The Transaction csv fields:

  1. timeset - date and time of transaction
  2. tx_hash - hashed transaction on blockchain can be found on https://blockscout.com/poa/core/a
  3. source - wallet ID of sender can be found on https://blockscout.com/poa/core/a - which could be a contract (for a conversion)
  4. s_comm_tkn - Short name of Token that the source uses (each user should only have 1 token)
  5. s_gender - From user input
  6. s_location - From user input
  7. s_business_type - Grassroots Economics Staff
  8. s_directory - From user input
  9. target - wallet ID of recipent - which could be a contract (for a conversion)
  10. t_comm_tkn
  11. t_gender
  12. t_location
  13. t_business_type
  14. t_directory
  15. tx_token - the token that was traded
  16. weight - How many tokens were traded
  17. id - test variable

The user summary csv fields:

  1. id - Wallet ID on POA Blockchain - can be found on https://blockscout.com/poa/core/a
  2. comm_tkn - Their token name (each user only has 1 token)
  3. bal - current balance of [comm_tkn] as of file date
  4. location - User input (village name)
  5. gender
  6. business_type - Input by staff based on what they sell
  7. directory - input by user a specific item they sell
  8. vol_trans_in - total number of tokens that came into this account
  9. vol_trans_out
  10. n_trans_in - number of transactions incomming
  11. n_trans_out
  12. n_in_unique - number of uniquie transactions incomming
  13. n_out_unique
  14. start - day and time of first transaction (when the user account was setup)