Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
83
datasets available to search
ShareScore release 0.7.1
Dataset results
83 results for “blockchain”
Renoir: Accelerating Blockchain Validation using State Caching
<p>A Blockchain system such as Ethereum is a peer to peer network<br> where each node works in three phases: creation, mining, and validation phases. In the creation phase, it executes a subset of locally<br> cached transactions to form a new block. In the mining phase, the<br> node solves a cryptographic puzzle (Proof of Work - PoW) on the<br> block it formed. On receiving a block from another peer, it starts the<br> validation phase, where it executes the transactions in the received<br> block in order to validate it. Since transactions depend on the state<br> that previously executed transactions have created, a node must<br> validate each newly arrived block before creating a new block on<br> top of it. A long block validation time lowers the system’s overall<br> throughput and brings the well known Verifier’s dilemma into play.<br> Additionally, this leads to wasted mining power utilization (MPU).<br> <br> In this work, we present Renoir a novel mechanism that<br> caches state from transaction execution during the block creation<br> phase and reuses it to enable nodes to skip (re)executing these transactions during block validation. Renoir artifact consists of two parts: First, the extensive measurement from the production Ethereum network to check the extent of redundancy in the transaction execution during block creation and validation phase. Second, Evaluation of Renoir using different metrics(Throughput, Mining Power Utilization and Validation time) on a 50 node testbed mimicking the top 50 Ethereum miners.</p>
The Blockchain Trilemma: an Evaluation Framework (Replication Package)
<p>This repository contains essential data files used to generate graphs and statistics related to various blockchain ecosystems. These files are the result of aggregation and cleaning procedures applied to raw data collected from reputable sources within each respective blockchain network.<br> </p> <h2><strong>Transaction Per Second</strong></h2> <ol> <li><strong>Cardano</strong>: <ol> <li>Theoretical: 5.35</li> <li>Maximum: 5.74</li> </ol> </li> <li><strong>Solana</strong>:<br> <ol> <li>Theoretical: 710,000</li> <li>Maximum: 1763</li> </ol> </li> <li><strong>Arbitrum</strong>: <ol> <li>Theoretical: 40000</li> <li>Maximum: 3.09</li> </ol> </li> <li><strong>zkSync</strong>: <ol> <li>Theoretical: 2000</li> <li>Maximum: 0.521</li> </ol> </li> <li><strong>Polygon:</strong> <ol> <li>Theoretical: 7200</li> <li>Maximum: 101.97 </li> </ol> </li> <li><strong>Bitcoin</strong>: <ol> <li>Theoretical: 27</li> <li>Maximum: 4.53</li> </ol> </li> <li><strong>Ethereum</strong>: <ol> <li>Theoretical: 30</li> <li>Maximum: 19.86</li> </ol> </li> </ol> <h2>Nakamoto Coefficients</h2> <ol> <li><strong>arbitrum_aggregators.json</strong> <ol> <li><strong>Description:</strong> presents information on Arbitrum network aggregators' transaction count</li> <li><strong>Data Source: </strong>https://etherscan.io/apis</li> </ol> </li> <li><strong>cardano_stake.json</strong> <ol> <li><strong>Description:</strong> details stake-related data pertinent to the Cardano blockchain. For each exchange address the amount of holded stake</li> <li><strong>Data Source: </strong>https://pooltool.io/</li> </ol> </li> <li><strong>polygon_validators.json</strong> <ol> <li><strong>Description:</strong> provides insights into validators within the Polygon network. For each validator's name, the amount of held stake.</li> <li><strong>Data Source: </strong>https://wallet.polygon.technology</li> </ol> </li> <li><strong>solana_validators.json</strong> <ol> <li><strong>Description: </strong>provides information on validators operating within the Solana network. For each validator, the amount of held stake and details about the validator node.</li> <li><strong>Data Source: </strong>https://www.validators.app/</li> </ol> </li> <li><strong>zksync_validators.json</strong> <ol> <li><strong>Description: </strong>Contains data on validators associated with the zkSync protocol. For each validator's address, the amount of transactions processed.</li> <li><strong>Data Source: </strong>https://etherscan.io/apis</li> </ol> </li> </ol> <h2>Security Quantitative Evaluation</h2> <ol> <li><strong>Cardano</strong><br> <ol> <li>Cardinality of the smallest amount of nodes adding up to 33% of stake: 119</li> <li>33% Stake: 895,706,097.1264836 ADA</li> <li>ADA Value @ 13 Dec-2023 = 0.59</li> <li>Cost of Attack: 895,706,097.1264836 * 0.59 = 528,466,597.3046253 $</li> </ol> </li> <li><strong>Solana</strong> <ol> <li>Cardinality of the smallest amount of nodes adding up to 33% of stake: 18</li> <li>33% Stake: 126,950,233.4364128 SOL</li> <li>SOL Value @ 13 Dec-2023 = 71.78</li> <li>Cost of Attack: 126,950,233.4364128 * 71.78 = 9,112,487,756.06571 $</li> </ol> </li> <li><strong>Polygon</strong><br> <ol> <li>Cardinality of the smallest amount of nodes adding up to 33% of stake: 2</li> <li>33% Stake: 1,016,718,726.6246895 MATIC</li> <li>MATIC Value @ 13 Dec-2023 = 0.8317</li> <li>Cost of Attack: 1,016,718,726.6246895 * 71.78 = 845,604,964.9337542 $</li> </ol> </li> <li><strong>Ethereum</strong> <ol> <li>Cardinality of the smallest amount of nodes adding up to 33% of stake: 1</li> <li>33% Stake: 28907872.7327942/3 = 9,635,957.577598067 ETH</li> <li>ETH Value @ 08 Jan-2024 = 2133,90</li> <li>Cost of Attack: 9,635,957.577598067 * 2133,90 = 20,562,169,874.8365 $</li> </ol> </li> <li><strong>Bitcoin: </strong>$7.9 billion <a href="https://www.investopedia.com/terms/1/51-attack.asp#:~:text=4-,What%20Is%20a%2051%25%20Attack%3F,total%20hashing%20or%20validating%20power.">source</a></li> </ol>
Blockchain Topics in energy sector from CoinDesk
<p>This dataset includes articles related to blockchain technology used in energy application. The dataset includes section, title, timestamp, author, and corpus. This dataset is used to spot relevant topics discussed on CoinDesk. Please consider that this dataset will be extended with more information from other forum.</p>
Um Panorama do Conhecimento em Blockchain por Discentes
<p><strong>Descrição</strong></p> <p>Pesquisa sobre blockchain e educação.</p> <p><strong>Conteúdo</strong></p> <ul> <li>Questionário aplicado aos alunos</li> <li>Imagens com os gráficos gerados durante a pesquisa</li> </ul>
Formalising a Gateway-based Blockchain Interoperability Solution with Event-B (Replication package)
<p>This repository holds the artefacts that raised the results of our first paper <em>Formalising a Gateway-based Blockchain Interoperability Solution with Event-B</em> to be presented at the <a href="https://icbc2024.ieee-icbc.org/workshop/crosschain" target="_blank" rel="noopener">ICBC Cross-chain workshop</a>.</p> <p>In this paper, we explore the formalisation of a gateway-based interoperability solution with Event-B. The results showed that the method was suitable and that a straightforward specification could be developed considering Ethereum and Hyperledger Fabric as the involved blockchains. The Event-B specification was assessed with three strategies that enabled its verification and validation. In particular, formal verification (e.g. safety properties), functional validation, and functional utility. These promising results constitute a step forward in the development of formal specifications for blockchain interoperability solutions.</p> <p>The artefacts generated in this research were:</p> <ul> <li>An Event-B specification of the gateway-based interoperability solution proposed by <a href="https://ieeexplore.ieee.org/document/10346168" target="_blank" rel="nofollow noreferrer noopener">Pandolfi et al.</a>. This specification is composed of three machines: an abstract machine and two refinements. One refinement describes the behaviour of the gateway and smart contracts involved when the source blockchain is Ethereum and the target blockchain is Hyperledger Fabric. The second refinement describes the behaviour of the gateway and smart contracts when the source is Hyperledger Fabric and the target Ethereum.</li> <li>Animations of the three specifications (i.e. abstract and refinements) that enabled us to validate the functional behaviour of the specification and provided the means to understand the gateways' behaviour without Event-B knowledge.</li> <li>An Event-B specficiation of a use case scenario that shows the utility of the specification.</li> </ul>
Validation of MUISCA for Blockchain Interoperability: A Case Study in a Healthcare Environment
<p>This repository contains the questions asked to the 31 experts who participated in the study “Validation of MUISCA for Blockchain Interoperability: A Case Study in a Healthcare Environment”. It also contains the spreadsheet with the recorded answers.</p>
Literature Overview Blockchain Intermediation Concepts
<p>The dataset was created in a structured literature review (Webster and Watson, 2002). It provides a complete overview of the 90 identified articles.</p>
Dataset - Indonesian People's Readiness for Blockchain Adoption in E-Commerce - 2024
<p>The dataset on Indonesian blockchain adoption was collected through a questionnaire conducted over three months, from April to June 2024, gathering 422 responses. The survey had seven main sections, each designed to collect important data for the study.<br><br>The first section introduced the study’s purpose and asked demographic questions. Respondents were also asked about their experience with e-commerce and blockchain technology. The second section explored how ready Indonesians are to adopt blockchain infrastructure for e-commerce retail transactions.<br><br>The final sections focused on key study variables, including Transaction Security [BTS], Transparency [BT], Cost Efficiency [BCE], Transaction Speed [BS], Customer Trust [CT], and E-commerce Adoption [EA]. These variables were used to assess the overall readiness of Indonesians for integrating blockchain into the e-commerce sector.<br><br>This dataset offers valuable insights into the potential challenges and advantages of adopting blockchain technology in Indonesia's e-commerce transactions.</p>
A Collection of Papers on Blockchain Business Applications
<p>We performed a systematic literature review of 63 research papers reporting blockchain business applications, published between 2016 and 2020. These papers were selected through snowballing. There are 53 journal papers, 8 conference papers, and 2 book chapters. From these papers, we identified approximately 408 blockchain applications through qualitative content analysis. We classified these applications into three categories or types: IoT-Based, Enterprise-Centric and Consumer-Centric.</p>
Robot swarms neutralize harmful Byzantine robots using a blockchain-based token economy
Through cooperation, robot swarms can perform tasks or solve problems that a single robot from the swarm could not perform/solve by itself. However, it has been shown that a single Byzantine robot (e.g., a malfunctioning or malicious robot) can disrupt the coordination strategy of the entire swarm. Therefore, a versatile swarm robotics framework that addresses security issues in inter-robot communication and coordination is urgently needed. In this paper, we show that security issues can be addressed by setting up a token economy between the robots. To create and maintain the token economy, we use blockchain technology, originally developed for the digital currency Bitcoin. The robots are given crypto tokens that allow them to participate in the swarm's security-critical activities. The token economy is regulated via a smart contract that decides how to distribute crypto tokens among the robots depending on their contributions. We design the smart contract so that Byzantine robots soon run out of crypto tokens and can therefore no longer influence the rest of the swarm. In experiments with up to 24 physical robots, we demonstrate that our smart contract approach indeed works: the robots can maintain blockchain networks and a blockchain-based token economy can be used to neutralize the destructive actions of Byzantine robots in a collective-sensing scenario. In experiments with more than 100 simulated robots, we study the scalability and long-term behavior of our approach. The obtained results demonstrate the feasibility and viability of blockchain-based swarm robotics.
Intelligent approach for the rational use of a shared resource using blockchain.
<p>This dataset was created in the <em>Intelligent approach for the rational use of a shared resource using blockchain</em> dissertation of Federal University of Technology - Paraná (UTFPR), campus Curitiba, by Evandro Sestrem supervised by Prof. Marco Aurélio Wehrmeister and cosupervised by Prof. Alécio Binotto.</p>
Robot swarms neutralize harmful Byzantine robots using a blockchain-based token economy
Open the record for dataset details and reuse information.
Rational Behaviors in Committee-Based Blockchains (video)
Full video presentation of the paper: Rational Behaviors in Committee-Based Blockchains.<br><br>Appears in Session 3 of the 24th International Conference on Principles of Distributed Systems OPODIS 2020<br><a href="https://opodis2020.unistra.fr">https://opodis2020.unistra.fr</a>
Archetypes of Blockchain-Based Business Models - Analyzed Organizations
<p>Here we present a sample with the names of the analyzed organizations or projects and their websites.</p>
Enhancing Credit Risk Assessment in Digital Finance through a Hybrid Deep Learning Model Integrated with Blockchain on the Edge of Things F
<p><span>This work proposes a credit risk assessment model using deep learning models such as self-attention generative adversarial networks (SA-GAN) and deep multi-layer perceptron (DMLP). Blockchain is used to improve the security aspects of the model by employing Brakerski-Gentry-Vaikuntanathan (BKV) encryption technique. Further, the proposed system is implemented in Edge-of-things network and communications are enabled via LoRaWAN server.</span></p>
A Collection of Event Logs of Blockchain-based Applications
<p>A set of event logs of 101 blockchain-based applications (DApps). For each DApp, there are two event log files. The first one is a raw version where data is encoded by blockchain. The second file is a decoded version where data is decoded into a human-readable format. If a DApp has multiple versions on different blockchain networks, then there are two event log files (encoded and decoded) for each version. In addition, the event registry file includes a comprehensive list of event names and their corresponding signatures obtained from contract ABIs of the 101 DApps. </p>
Figure 1: Comparison of Redactable Blockchain Implementation for IoT Applications
<p>This figure presents a comparison of redactable blockchain implementations for IoT applications.</p> <p>This file contains a high-resolution version of figure 1 from the paper "Redactable Blockchain Solutions for IoT: A Review of Mechanisms and Applications". The file includes detailed data that is difficult to read in the main manuscript. For the full context and additional information, please refer to the main manuscript.</p> <p> </p>
The Hybrid Consensus Model Based on Blockchain Self-Executing Contract for Secure E-voting System
<p><strong>Data for Review</strong></p>
Blockchain in Procurement - Paper List
<p>Here we present the list of our analyzed papers.</p>
Transaction history of the first 10 million blocks of the Ethereum Blockchain
<p>This dataset contains the transaction history for the first 10,000,000 blocks of the Ethereum Blockchain. The dataset is structured into 10 consecutive CSV files, which sequentially hold the transactions of 1,000,000 blocks. The information stored for each transaction includes the sending and receiving addresses of the transaction, the transferred value, the corresponding block number, a timestamp, and further information about the target address.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.