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DATA MANAGEMENT WITHIN DECENTRALIZED AUTONOMOUS
ORGANIZATIONS (DAO) – DECISION MAKING AND DOCUMENT EXCHANGE
Raimov Ulugbek Yorqinbek ugli
Teacher at Andijan State Technical Institute
ORCID: 0009-0009-9304-5980
ABSTRACT:
This article analyzes data management processes within Decentralized
Autonomous Organizations (DAOs), specifically focusing on decision-making and document
exchange. DAOs are decentralized, blockchain-based organizations whose effective functioning
depends on data transparency, security, and reliability. The study examines modern technologies
including smart contracts, on-chain voting mechanisms, and distributed storage systems as
foundations for data exchange and management processes. Governance models of various DAO
platforms and their capabilities are analyzed, highlighting existing limitations and possible
improvement directions. The research outcomes offer practical insights for enhancing DAO
operations and developing new governance mechanisms.
KEYWORDS:
DAO, Decentralized Autonomous Organization, data management, decision
making, document exchange, blockchain, smart contracts, on-chain voting, distributed storage
system, decentralized governance.
INTRODUCTION
In recent years, alongside the rapid development of blockchain technology, the concept of
Decentralized Autonomous Organizations (DAOs) has gained increasing relevance. Unlike
traditional centralized governance structures, DAOs autonomously manage decision-making and
resource allocation processes based on blockchain technology. Therefore, effective data
management—namely decision making and document exchange—within DAOs is crucial for
their success.
Data management in the DAO context encompasses not only secure and transparent storage of
information but also its efficient utilization and distribution. Particularly, information exchange
among members involved in decision-making processes has reached a new level through
blockchain technology, smart contracts, and distributed storage systems. Consequently,
analyzing and improving data management mechanisms to ensure DAO efficiency and reliability
is a pressing task.
This article investigates how data management, particularly decision-making processes and
document exchange, is organized in DAO systems using modern technologies. The study
reviews existing DAO platforms and their governance mechanisms, assessing their effectiveness
and security.
LITERATURE REVIEW
The concept of Decentralized Autonomous Organizations (DAO) was first proposed by Vitalik
Buterin and other blockchain researchers in 2013-2014, focusing on decentralized governance
and automated, transparent decision-making processes (Buterin, 2014). DAOs fundamentally
rely on blockchain technology and smart contracts to enable direct information exchange and
governance among participants (Wright & De Filippi, 2015)[1].
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From the perspective of data management, decision-making in DAOs differs significantly from
traditional organizations. The process is often carried out through on-chain voting mechanisms,
ensuring transparency and immutability of decisions (Jentzsch, 2016). For document storage and
exchange, distributed storage systems such as the InterPlanetary File System (IPFS) are
integrated with blockchain networks (Benet, 2014).
Recent research suggests improving DAO governance efficiency by adopting various consensus
algorithms and delegated voting models, which accelerate data exchange and decision-making
processes (Hassan & Kyriakou, 2021). Popular DAO platforms (Aragon, DAOstack,
MolochDAO) have been extensively analyzed regarding their governance models and data
management methods (Schwartz et al., 2020).
However, existing literature offers limited in-depth analysis of data security, document exchange
complexity, and challenges inherent to decentralized governance in DAOs. This article aims to
fill this gap by scientifically studying these aspects and proposing novel approaches[2].
METHODOLOGY
To conduct an in-depth study of data management and decision-making processes within
Decentralized Autonomous Organizations (DAOs), this research employed qualitative methods
including literature review, case studies, analytical approaches, and technical explanations.
These combined methodologies enable a comprehensive theoretical and practical investigation of
the topic[3].
1.
Literature Review
The initial phase involved extensive analysis of international scientific sources on blockchain
technology, DAO governance models, and data exchange, sourced from reputable databases such
as Scopus, Web of Science, IEEE Xplore, and Springer. Selected articles and books published
within the last 5-7 years focused on DAO development trends, smart contract-based decision-
making mechanisms, distributed storage, and data security. This review facilitated a deep
understanding of technical and governance aspects and helped identify existing research gaps.
2.
Case Studies
Following the theoretical review, practical examples of DAOs’ real-world operation and data
management processes were examined. Prominent DAO platforms including Aragon, DAOstack,
and MolochDAO were studied in detail to understand their governance models and technological
infrastructures. The voting process—where each member votes on proposals, smart contracts
tally votes, and decisions are executed automatically on the immutable blockchain—was
analyzed. Additionally, distributed storage systems such as IPFS integrated into DAO platforms
were explored for secure document exchange and persistence.
3.
Analytical Approach and Technical Demonstration
Based on collected theoretical and practical data, the study analyzed data management
workflows within DAOs. The effectiveness of on-chain voting via smart contracts and the
operational principles of distributed storage systems for document exchange were investigated.
A simple on-chain voting smart contract example written in Solidity demonstrates the technical
foundation of DAO decision-making (see below).
// SPDX-License-Identifier: MIT
pragma solidity ^0.8.0;
contract SimpleDAOVoting {
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struct Proposal {
string description;
uint voteCount;
bool executed;
}
Proposal[] public proposals;
mapping(address => mapping(uint => bool)) public hasVoted;
address public admin;
constructor() {
admin = msg.sender;
}
modifier onlyAdmin() {
require(msg.sender == admin, "Only admin can perform this action");
_;
}
function createProposal(string memory description) public onlyAdmin {
proposals.push(Proposal({
description: description,
voteCount: 0,
executed: false
}));
}
function vote(uint proposalIndex) public {
require(!hasVoted[msg.sender][proposalIndex], "You have already voted");
require(proposalIndex < proposals.length, "Invalid proposal index");
hasVoted[msg.sender][proposalIndex] = true;
proposals[proposalIndex].voteCount++;
}
function executeProposal(uint proposalIndex) public onlyAdmin {
Proposal storage proposal = proposals[proposalIndex];
require(!proposal.executed, "Proposal already executed");
require(proposal.voteCount > 0, "Not enough votes");
// Actions to be performed when executing the proposal
proposal.executed = true;
}
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function getProposalCount() public view returns (uint) {
return proposals.length;
}
}
This code example illustrates:
The admin creating proposals.
DAO members voting on proposals.
The admin executing approved proposals.
This technical demonstration enriches the article’s scientific level by elucidating DAO data
management and decision-making from a technical standpoint.
4.
Research Limitations
Although the study employs qualitative methodology, certain limitations exist. Only three well-
known DAO platforms were analyzed as case studies, limiting the scope of platform diversity.
Furthermore, the research relies on existing scientific literature and open resources, possibly
excluding rapidly evolving technologies[4].
DISCUSSION AND RESULTS
Decentralized Autonomous Organizations (DAOs) differ fundamentally from traditional
organizations due to their decentralized governance and automated decision-making mechanisms.
This section presents a comprehensive analysis of DAO data management, decision making, and
document exchange. Real-world practices of popular DAO platforms are examined in terms of
efficiency, security, and transparency, highlighting existing challenges and proposed solutions.
1.
Analysis of DAO Data Management and Decision-Making Processes
DAO data management significantly diverges from centralized administrative control by storing
and managing data in a decentralized manner, ensuring transparency and immutability. The
critical component of data management is the decision-making process, frequently implemented
through on-chain voting. Members cast votes recorded on the blockchain, with smart contracts
tallying votes and automatically executing decisions. This approach guarantees immutability,
transparency, and reliability (Jentzsch, 2016; Hassan & Kyriakou, 2021).
Advantages of on-chain voting include:
Transparency:
Every vote is recorded on the blockchain, preventing alterations or
forgery.
Equality:
Each member’s vote is accurately counted, reducing bias.
Automation:
Smart contracts automate decision enforcement, minimizing human errors.
However, on-chain voting also has drawbacks:
Scalability:
Voting in DAOs with many members burdens blockchain networks and
causes delays.
Participation:
Low member engagement can deteriorate decision quality.
Complexity:
Technical complexity of proposals may confuse voters, leading to
suboptimal decisions[5].
For data exchange and document management, distributed storage systems like IPFS are widely
used. Documents are not stored directly on the blockchain but via cryptographic hashes on-chain,
allowing secure and persistent storage off-chain[6][7].
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2.
Analysis of Popular DAO Platforms
The governance and data management mechanisms of Aragon, DAOstack, and MolochDAO
platforms were deeply analyzed.
Aragon
automates DAO governance via on-chain voting and smart contracts, providing
modular tools for managing documents and data. It offers customizable decentralized
governance models with high transparency and reliability but may face usability challenges due
to technical complexity.
DAOstack
implements delegated voting (holographic consensus), enhancing vote
allocation efficiency and speeding decision-making. It supports decentralized architecture and
integrates with various decentralized applications (dApps). Despite its scalability and
performance, DAOstack encounters occasional consensus difficulties and reduced voter
participation.
MolochDAO
features a lightweight and fast governance system within the Ethereum
ecosystem, facilitating quick proposal decisions with a focus on security and efficiency. It is
easier to manage and resource-efficient but has limited scalability and integration compared to
other platforms.
3.
Existing Challenges and Recommendations
Key challenges identified in DAO systems include:
Technical complexity:
Smart contracts and blockchain technologies can be difficult for
many users, hindering decision-making.
Security issues:
Vulnerabilities in smart contracts may threaten DAO operations.
Low participation:
Member disengagement reduces governance efficiency.
Scalability:
Large-member DAOs face network congestion and delays[8],[10].
Recommendations to address these challenges include:
Education and support:
Providing training resources to familiarize members with
blockchain and smart contracts.
Security audits:
Regular code audits and enhanced security protocols.
Incentive mechanisms:
Implementing tokens or other motivators to encourage active
participation.
Consensus improvements:
Refining delegated voting and other algorithms to alleviate
scalability issues[9],[10].
CONCLUSION
DAO data management and decision-making processes, built upon blockchain and smart
contract technologies, differ significantly from traditional governance systems. Their efficiency
and reliability depend on technological infrastructure and member engagement. Analysis of
popular platforms highlighted DAO strengths and weaknesses while identifying challenges and
solutions. Future DAO development requires technological innovation and enhanced user
education. Ongoing research in these areas remains essential.
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