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R4R: Reproducible Data Analyses for All

Project description

A program analysis tool for non-programmers ensuring reproducibility of analyses

Scientific conclusions are typically based on the detailed and complex analyses of voluminous experimental data. As datasets grow larger and the programmes to analyse them get more complicated, reproducibility of the analyses – the necessary requirement for scientific success, recognition and funding – becomes harder to test. The ERC-funded R4R project plans to address this important challenge with its ‘R4R’ tool for non-programmers that will streamline ensuring that data analysis pipelines are reproducible. Focusing on data analysis software written in R, they plan to use dynamic program analysis techniques to track dependencies, data inputs, and other sources of non-determinism that impact reproducibility.

Objective

Unevaluated science is not worth funding. Gone are the days where a scientific breakthrough could be based on scribbles made on a few loose sheets of paper reviewed by a single attentive reader. Most disciplines rely on experimental data that is collected, analyzed, and presented using powerful computational tools. The scientific adventure hinges on our ability to openly and widely share and reproduce such results.
The goal of this PoC is to market a tool, R4R, for non-programmer scientists to make their archival work easily reproducible and offer it to them through a non-expensive licence. Affordable reproducibility is key to independent evaluation of previously published results.

We will focus on reproducibility of data analysis pipelines written in R with RMarkdown or Jupyter. Creating a reproducible environment is hard, labor-intensive and error-prone, and requires expertise that data analysts lack. We propose to use dynamic program analysis techniques to track dependencies, data inputs, and other sources of non-determinism needed for reproducibility. R4R will synthesize metadata to generate self-contained, portable, fully reproducible environments, based on Docker images.

Programme(s)

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Topic(s)

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Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

HORIZON-ERC-POC - HORIZON ERC Proof of Concept Grants

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) ERC-2022-POC2

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Host institution

CESKE VYSOKE UCENI TECHNICKE V PRAZE
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 150 000,00
Address
JUGOSLAVSKYCH PARTYZANU 1580/3
160 00 PRAHA
Czechia

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Region
Česko Praha Hlavní město Praha
Activity type
Higher or Secondary Education Establishments
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Total cost

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Beneficiaries (1)

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