DARE Platform: a Developer-Friendly and Self-Optimising Workflows-as-a-Service Framework for e-Science on the Cloud

Klampanos, Iraklis A.; Themeli, Chrysoula; Spinuso, Alessandro; Filgueira, Rosa; Atkinson, Malcolm; Gemünd, André; Karkaletsis, Vangelis

doi:10.21105/joss.02664

Cited by 4 publications

(3 citation statements)

References 8 publications

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“…As of 2013, over 60 datasets or frameworks implemented the PROV model. Indeed recently, the F-UJI tool [13] developed under the FAIRsFAIR [14] project assumes the use of a machine-readable version of PROV (or PAV [15] which is just a specialisation of PROV) when assessing a datasets compliance to FAIR principles, and the DARE [16] platform provides support for automating the output of PROV formatted provenance.…”

Section: The W3c-prov Standard For Provenancementioning

confidence: 99%

A FAIR based approach to data sharing in Europe

Strand

Coster

Płóciennik

et al. 2022

Plasma Phys. Control. Fusion

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The European fusion research activities have over the last decades generated a vast and varied set of data. The volume and diversity of the data that need to be catalogued and annotated make the task of organising and making the data available within a broader environment very challenging. Nevertheless, there are strong scientific drivers as well as incentives and mandates from national research agencies suggesting that a more coherent approach to data referencing, dissemination and sharing would provide strong benefits to the fusion research community and beyond. Here we discuss the technical requirements and developments needed to transition the current, and future, range of fusion research data to an open and FAIR (Findable, Accessible, Interoperable, and Reusable) data sharing structure guided by the principle “as open as possible, as closed as necessary”. Here we propose a set of recommendations and technical implementations needed to form a European data sharing environment for the fusion research programmes. Consistency with the emerging IMAS (ITER Integrated Modelling and Analysis Suite) infrastructure is considered to facilitate future deployments.

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Section: The W3c-prov Standard For Provenancementioning

confidence: 99%

A FAIR based approach to data sharing in Europe

Strand

Coster

Płóciennik

et al. 2022

Plasma Phys. Control. Fusion

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“…The framework evaluation tests the capability of the whole framework with use cases that involve typical collaborative use of data and computational methods for global research addressing environmental hazards [24,45]. It considers the language encoding, the system implementation, the extracted information, the reasoning result, etc.…”

Section: Framework Evaluationmentioning

confidence: 99%

Dr.Aid: Supporting Data-governance Rule Compliance for Decentralized Collaboration in an Automated Way

Rui

Atkinson

Papapanagiotou

et al. 2021

Proc. ACM Hum.-Comput. Interact.

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Collaboration across institutional boundaries is widespread and increasing today. It depends on federations sharing data that often have governance rules or external regulations restricting their use. However, the handling of data governance rules (aka. data-use policies) remains manual, time-consuming and error-prone, limiting the rate at which collaborations can form and respond to challenges and opportunities, inhibiting citizen science and reducing data providers' trust in compliance. Using an automated system to facilitate compliance handling reduces substantially the time needed for such non-mission work, thereby accelerating collaboration and improving productivity. We present a framework, Dr.Aid, that helps individuals, organisations and federations comply with data rules, using automation to track which rules are applicable as data is passed between processes and as derived data is generated. It encodes data-governance rules using a formal language and performs reasoning on multi-input-multi-output data-flow graphs in decentralised contexts. We test its power and utility by working with users performing cyclone tracking and earthquake modelling to support mitigation and emergency response. We query standard provenance traces to detach Dr.Aid from details of the tools and systems they are using, as these inevitably vary across members of a federation and through time. We evaluate the model in three aspects by encoding real-life data-use policies from diverse fields, showing its capability for real-world usage and its advantages compared with traditional frameworks. We argue that this approach will lead to more agile, more productive and more trustworthy collaborations and show that the approach can be adopted incrementally. This, in-turn, will allow more appropriate data policies to emerge opening up new forms of collaboration.

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“…Applying static optimizations to DARE workflows DARE[33] 19 project focused on empowering domain experts to invent and improve their methods and models by providing a new platform and a working environment, in which analysis tools and workflow systems are readily available. DARE worked with two scientific communities: Seismology (EPOS20 ) and Climate (IS-ENES 21 ) Research Infrastructures.…”

mentioning

confidence: 99%