BitcoinVis: Visualization of Bitcoin Blockchain Data
The goal of our BitcoinVis project is to devise visual analytics techniques to deeply explore data stored on the Bitcoin blockchain. Given the novel data storage nature of blockchains, they offer a unique opportunity to study the evolution of the stored data as well as data storage patterns. The volume and evolving nature of its data pose analysis challenges to explore diverse groups of users and different activities on the network. Over five years (2017-2021), we conducted a systematic review on blockchain data visualization and developed three visual analytics tools to explore and monitor Bitcoin transactions.
Systematic Review on Blockchain Data Visualization
by Natkamon Tovanich, Nicolas Heulot, Jean-Daniel Fekete, and Petra Isenberg
Abstract: We present a systematic review of visual analytics tools used for the analysis of blockchains-related data. The blockchain concept has recently received considerable attention and spurred applications in a variety of domains. We systematically and quantitatively assessed 76 analytics tools that have been proposed in research as well as online by professionals and blockchain enthusiasts. Our classification of these tools distinguishes (1) target blockchains, (2) blockchain data, (3) target audiences, (4) task domains, and (5) visualization types. Furthermore, we look at which aspects of blockchain data have already been explored and point out areas that deserve more investigation in the future.
Publications:
- Natkamon Tovanich, Nicolas Heulot, Jean-Daniel Fekete, Petra Isenberg. Visualization of Blockchain Data: A Systematic Review. IEEE Transactions on Visualization and Computer Graphics, 2019, ⟨10.1109/TVCG.2019.2963018⟩. ⟨hal-02426339⟩
- Natkamon Tovanich, Nicolas Heulot, Jean-Daniel Fekete, Petra Isenberg. A Systematic Review of Online Bitcoin Visualizations. Posters of the European Conference on Visualization (EuroVis), 2019, Porto, Portugal. ⟨10.2312/eurp.20191148⟩. ⟨hal-02155171⟩
MiningVis
by Natkamon Tovanich, Nicolas Soulié, Nicolas Heulot, and Petra Isenberg
Abstract: We present a visual analytics tool, MiningVis, to explore the long-term historical evolution and dynamics of the Bitcoin mining ecosystem. Bitcoin is a cryptocurrency that attracts much attention but remains difficult to understand. Particularly important to the success, stability, and security of Bitcoin is a component of the system called "mining.'' Miners are responsible for validating transactions and are incentivized to participate by the promise of a monetary reward. Mining pools have emerged as collectives of miners that ensure a more stable and predictable income. MiningVis aims to help analysts understand the evolution and dynamics of the Bitcoin mining ecosystem, including mining market statistics, multi-measure mining pool rankings, and pool hopping behavior. Each of these features can be compared to external data concerning pool characteristics and Bitcoin news. In order to assess the value of MiningVis, we conducted online interviews and insight-based user studies with Bitcoin miners. We describe research questions tackled and insights made by our participants and illustrate practical implications for visual analytics systems for Bitcoin mining.
Publications:
- Natkamon Tovanich, Nicolas Soulié, Nicolas Heulot, Petra Isenberg. MiningVis: Visual Analytics of the Bitcoin Mining Economy. IEEE Transactions on Visualization and Computer Graphics, 2022, 28 (1), pp.868-878. ⟨10.1109/TVCG.2021.3114821⟩. ⟨hal-03348145⟩
- Natkamon Tovanich, Nicolas Soulié, Nicolas Heulot, Petra Isenberg. An Empirical Analysis of Pool Hopping Behavior in the Bitcoin Blockchain. 2021 IEEE International Conference on Blockchain and Cryptocurrency (ICBC), May 2021, Sydney / Virtual, Australia. ⟨10.1109/ICBC51069.2021.9461118⟩. ⟨hal-03163006v3⟩
- Natkamon Tovanich, Nicolas Soulié, Petra Isenberg. Visual analytics of bitcoin mining pool evolution: on the road toward stability?. BSC 2020-2021 - 3rd International Workshop on Blockchains and Smart Contracts held in conjunction with the 11th IFIP International Conference on New Technologies, Mobility and Security, Apr 2021, Paris, France. ⟨10.1109/NTMS49979.2021.9432675⟩. ⟨hal-02902465v2⟩
BitConduite
by Christoph Kinkeldey, Jean-Daniel Fekete, Tanja Blascheck, and Petra Isenberg
Project Page: https://aviz.fr/Research/BitConduite
Abstract: We present BitConduite, a visual analytics approach for explorative analysis of financial activity within the Bitcoin network, offering a view on transactions aggregated by entities, i.e. by individuals, companies, or other groups actively using Bitcoin. BitConduitemakes Bitcoin data accessible to non-technical experts through a guided workflow around entities analyzed according to several activity metrics. Analyses can be conducted at different scales, from large groups of entities down to single entities. BitConduite also enables analysts to cluster entities to identify groups of similar activities as well as to explore characteristics and temporal patterns of transactions. To assess the value of our approach, we collected feedback from domain experts.
Publications:
- Christoph Kinkeldey, Jean-Daniel Fekete, Tanja Blascheck, Petra Isenberg. BitConduite: Exploratory Visual Analysis of Entity Activity on the Bitcoin Network. IEEE Computer Graphics and Applications, 2022, 42 (1), pp.84-94. ⟨10.1109/MCG.2021.3070303⟩. ⟨hal-03199547v2⟩
- Christoph Kinkeldey, Jean-Daniel Fekete, Petra Isenberg. BitConduite: Visualizing and Analyzing Activity on the Bitcoin Network. EuroVis 2017 - Eurographics Conference on Visualization, Posters Track, Jun 2017, Aire-la-Ville, Switzerland. pp.3, 2017. ⟨hal-01528605⟩
Bitcoin Entity Explorer
by Petra Isenberg, Christoph Kinkeldey, and Jean-Daniel Fekete
Abstract: We contribute a visual exploration system for analyzing the behavior of individual entities exchanging Bitcoins. Bitcoin is a cryptocurrency, popular for allowing pseudonymous financial transactions. The Bitcoin blockchain is the public ledger of the Bitcoin system holding data on millions of individual transactions between pseudonymous addresses. These addresses belong to individual entities such as people, services, or enterprises. Understanding how the Bitcoin system is used, however, is difficult because it is unclear which addresses belong to the same entities. Our tool addresses this problem by clustering addresses and displaying transaction detail for individual entities
Publications:
- Petra Isenberg, Christoph Kinkeldey, Jean-Daniel Fekete. Visual Analytics for Monitoring and Exploration of Blockchain Data With a Focus on the Bitcoin Blockchain. HCI for Blockchain: A CHI 2018 workshop on Studying, Critiquing, Designing and Envisioning Distributed Ledger Technologies, 2018, Montréal, Canada. ⟨hal-01950934⟩
- Petra Isenberg, Christoph Kinkeldey, Jean-Daniel Fekete. Exploring Entity Behavior on the Bitcoin Blockchain. VIS 2017 - IEEE Conference on Visualization, Oct 2017, Phoenix, United States. pp.1-2. ⟨hal-01658500⟩