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      Applying Distributed Ledgers to Manage Workflow Provenance

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          Abstract

          Sharing provenance across workflow management systems automatically is not currently possible, but the value of such a capability is high since it could greatly reduce the amount of duplicated workflows, accelerate the discovery of new knowledge, and verify the integrity of past and present analyses. Although numerous technological challenges exist to efficiently share provenance information across workflow management systems, permissioned distributed ledgers could surmount many of them. The primary benefit of permissioned distributed ledgers over other technologies is that their distribution is over a peer-to-peer network that encodes transactions across the network into an immutable hash list and achieves consensus on the validity of the new data through a common consensus mechanism. This work discusses provenance and distributed ledgers on their own and then presents an argument that distributed ledgers naturally satisfy many of the requirements of workflow provenance, that provenance information can exist in the ledger in multiple ways, and that a number of novel research areas exist based on this strategy.

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          Most cited references 5

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          AiiDA: Automated Interactive Infrastructure and Database for Computational Science

           ,  ,   (2015)
          Computational science has seen in the last decades a spectacular rise in the scope, breadth, and depth of its efforts. Notwithstanding this prevalence and impact, it is often still performed using the renaissance model of individual artisans gathered in a workshop, under the guidance of an established practitioner. Great benefits could follow instead from adopting concepts and tools coming from computer science to manage, preserve, and share these computational efforts. We illustrate here our paradigm sustaining such vision, based around the four pillars of Automation, Data, Environment, and Sharing. We then discuss its implementation in the open-source AiiDA platform (http://www.aiida.net), that has been tuned first to the demands of computational materials science. AiiDA's design is based on directed acyclic graphs to track the provenance of data and calculations, and ensure preservation and searchability. Remote computational resources are managed transparently, and automation is coupled with data storage to ensure reproducibility. Last, complex sequences of calculations can be encoded into scientific workflows. We believe that AiiDA's design and its sharing capabilities will encourage the creation of social ecosystems to disseminate codes, data, and scientific workflows.
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            A Digital Signature Based on a Conventional Encryption Function

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              The Open Provenance Model core specification (v1.1)

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                Author and article information

                Journal
                15 April 2018
                Article
                1804.05395

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

                Custom metadata
                Submitted to P-RECS 2018
                cs.DC

                Networking & Internet architecture

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