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Presentation . 2019
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Other literature type . 2019
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Presentation . 2019
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Data, Policies and Algorithms

Authors: Parfenov, Denis;

Data, Policies and Algorithms

Abstract

We live in an increasingly globalised world where citizens have no privacy, governments mimic transparency and algorithms know no borders. Global problems can be only addressed through global cooperation between citizens, governments and organisations. In our session, during the first Japanese Government run blockchain hackathon, which was sponsored by the Ministry of Economy, Trade and Industry (METI), in February 2019 in Tokyo, we discussed (1) how modest and persistent community efforts of Open Knowledge Ireland are helping citizens to keep their data private through education and making useful governmental data open, usable and used with advocacy. (2) Why through our work we realised that opened up data has trust issues and can disappear at any point of time and (3) why we started to work on distributed content-addressed solution for preservation of publicly funded data, known as Data Management Hub (DaMaHub). At DaMaHub we believe that for preservation of publicly funded (research) data we need architecture for global digital public infrastructure which provides cryptographic and institutional guarantees of persistent access to interoperable, verifiable and discoverable data to enable researchers and citizens to find data, to re-use data and to trust data they need. This content is also available on IPFS: https://ipfs.io/ipfs/QmfJwsUmcERrewAppv3QYBD7UibxVbr6amnwGthxnSAQyZ

{"references": ["https://zenodo.org/record/2548922", "https://www.meti.go.jp/press/2018/02/20190228004/20190228004.html", "https://web.archive.org/web/20190216052248/https://www.eventbrite.com/e/blockchain-hackathon-2019-tickets-55006472841", "https://ipfs.io/ipfs/QmfJwsUmcERrewAppv3QYBD7UibxVbr6amnwGthxnSAQyZ"]}

Keywords

DaMaHub, Open Knowledge Ireland, P2P, infrastructure, digital preservation, IPFS, Ireland

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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