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Dan McGinn Researcher - Data Science Institute Department of Computing +44 20 7594 8607 |
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PGP Public Key: 2A14 760E 5F3D 2F94 963A 5686 C067 3765 BD24 5E75 Bitcoin Node: imperialnza3tqgh.onion ZCash Node: 4n6oqeadf3s7ku72.onion Bitcoin Visualization: Bitviz Blockchain Graph Database: Neo4j (Please contact for a login.) Blockchain Visual History: Adjacency Matrix Interactive Tool |
William Penney Laboratory South Kensington Campus London SW7 2AZ In the best traditions of computing academics, here is my basic yet standards compliant html page of information and useful links. |
IC3RE site
— jack (@jack) June 11, 2019 |
@Jack Dorsey, twitter co-founder, tweeting the visualization work. 11 June 2019 |
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Towards open data blockchain analytics: a Bitcoin perspective D. McGinn, D. McIlwraith, Y. Guo R. Soc. open sci. 2018 5 180298; DOI: 10.1098/rsos.180298. Published 8 August 2018 |
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Toward Open Data Blockchain Analytics: A Bitcoin Perspective McGinn et al. Pre-print arXiv:1802.07523 - 21 February 2018 Research Article submitted for publication to the Royal Society Open Science journal. Exploring some of the prime open data benefits of 'public permissionless' blockchain architectures. |
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Data Stories Podcast 25 October 2017 - Episode 107: Visualizing Bitcoin with Dan McGinn |
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HRH Prince Andrew Duke of York 28 June 2017 On a personal visit to the DSI to expand his knowledge of Bitcoin, Cryptocurrency, Blockchain and Big Data pattern recognition. |
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Financial Times - Imperial College London maps bitcoin transactions across 64 screens 24 May 2017 |
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Professor Nick Jennings - Vice Provost (Research), formerly Government Chief Scientific Adviser (National Security) 23 February 2017 - High Performance Computing Conference at Imperial College London. |
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Guardian - Why data is the new coal 27 September 2016 |
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From Where do Bitcoins Come? 13 September 2016 Visualization querying Neo4j database of the whole blockchain transaction graph. For each block from 0-400,000, it shows the source of its inputs across all previous blocks (grey to red according to the percentage contribution). E.g. the highlighted point shows 61.08% of the inputs to block#392,193 come from block#103,165. Shows the expected high velocity of Bitcoin transactions demonstrated by the clear red region close to the diagonal, and also discrete Satoshi activity mopping up coins from early blocks. |
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Professor Sir Mark Walport - Government Chief Scientific Adviser 23 June 2016 - Wired Money Conference 2016. |
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Visualizing Dynamic Bitcoin Transaction Patterns McGinn et al. Big Data. Jun 2016, 4(2): 109-119. DOI:10.1089/big.2015.0056 |
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Understanding Blockchain Technologies Through Visualization Invited talk at Nordic Capital Markets Forum Den Sorte Diamant, Copenhagen 28 April 2016 |
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BBC Click 05 December 2015 |
