Special Issue. Distributed Ledgers: Making Data Science More Open, Transparent, and Accountable

Guest Editors

  • Alexander Garcia, UPM, Spain
  • Maryann Martone, UCSD, USA
  • Michael Conlon, DuraSpace, VIVO, USA
  • Johannes Pfeffer, ConsenSys
  • Elena Simperl, University of Southampton
  • Melanie Swan, Purdue University, USA

Topic of the Special Issue

Distributed ledgers (DL) refer to a set of decentralised and distributed data management technologies that are used to maintain data in form of a growing list of connected records and keep track of transactions between different parties in an efficient, verifiable, and persistent way. The Blockchain, the DL underlying the bitcoin cryptocurrency, Ethereum, and Hyperledger are just some of the most prominent platforms in this space. This special issue will offer researchers and practitioners in data science the opportunity to present their work and ideas around this set of technologies, across different domains and DL platforms. We are seeking interdisciplinary contributions, as well as fundamental and applied research on DLs. Submissions that focus on the use of ledgers in a particular domain should discuss the positive and negative implications of using decentralised technologies and, when relevant, compare them against existing centralised solutions.

DLs are often praised for enabling more open, transparent and accountable processes in finance and beyond. For example, in e-science, they could disrupt scholarly publishing by allowing for a greater range of research outputs (publications, software, data, designs, requirements etc.) to be brought together into coherent, rich research objects, which could be identified, discovered, and used more easily; and by making scientific processes and contributions within a science team straightforward to trace and reward. They could potentially help with managing digital rights for research assets (via smart contracts), empower networks of researchers, and enable the technology of the common as well. Many other applications exist, including e-government, supply chain management, healthcare, and creative industries, to name just a few. We encourage submissions in all these, as well as other domains.

We welcome mature and ongoing work on algorithms, systems, experiments, benchmarks, and analyses, as well as position statements and visions of technology addressing, but not limited to, the following issues:

  • Architectures and implementations
  • Consensus algorithms for distributed ledgers
  • Smart contract languages and execution algorithms
  • Smart contract resilience and formal verification
  • Proof-of-work, proof-of-stake and other proof mechanisms
  • Scalability of distributed ledgers
  • Interoperability of DL platforms, and between DLs and other data management systems
  • Public and private ledgers
  • Algorithms and approaches to analyse DL data and transactions
  • Digital rights management on the blockchain
  • Distributed payment systems
  • Applications of DLs to facilitate reproducibility, scientific data reuse, and self-publishing.
  • Applications of DLs in other domains.

Submissions should comply with the guidelines for authors as outlined at https://datasciencehub.net/content/guidelines-authors For submitting please go to https://datasciencehub.net/content/submit-manuscript

Important Dates

Submissions will be accepted from 1 October 2017 until 30 April 2018.

We will assign three reviewers for each submitted paper. Reviewers will have 10 days for a first review, we aim for a first decision within less that 30 days.

Program Committee

  • Alan Third, Open University, UK
  • Kieron O'Hara, University of Southampton, UK
  • Max van Kleek, University of Oxford, UK
  • Luis Daniel Ibanez-Gonzalez, UK
  • Oliver N Oram, Chainvine LTD
  • Jesse Yli-Huumo, Aalto University, Department of Computer Science, Finland
  • Sujin Choi, Sogang University, Seoul, South Korea