Tag Archives: Open computation

Call for Papers: Recomputability 2014

I am co-chairing Recomputability 2014, the first workshop to focus explicitly on recomputability and reproducibility in the context of utility and cloud computing and is open to all members of the cloud, big data, grid, cluster computing and open science communities. Recomputability 2014 is an affiliated workshop of the 7th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2014), to be held in London in December 2014.

Recomputability 2014 will provide an interdisciplinary forum for academic and industrial researchers, practitioners and developers to discuss challenges, ideas, policy and practical experience in reproducibility, recomputation, reusability and reliability across utility and cloud computing. It will provide an opportunity to share and showcase best practice, as well as to provide a platform to further develop policy, initiatives and practical techniques for researchers in this domain. Participation by early career researchers is strongly encouraged.

Proposed topics of interest include (but are not limited to):

  • infrastructure, tools and environments for recomputabilty and reproducibility in the cloud;
  • recomputability for virtual machines;
  • virtual machines as self-contained research objects or demonstrators;
  • describing and cataloging cloud setups;
  • the role of community/open access experimental frameworks and repositories for virtual machines and data, their operation and sustainability;
  • validation and verification of experimental results by the community;
  • sharing and publication issues;
  • recommending policy changes for recomputability and reproducibility;
  • improving education and training: best practice, novel uses, case studies;
  • encouraging industry‚Äôs role in recomputability and reproducibility.

Please see the full call for papers; deadline for submissions (online via EasyChair) is 10 August 2014 17 August 2014.

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2014 Software Sustainability Institute Fellowship

SSI

I’m delighted to have been named today as one of the sixteen Software Sustainability Institute Fellows for 2014.

The Software Sustainability Institute (SSI) is an EPSRC-funded project based at the universities of Edinburgh, Manchester, Oxford and Southampton, and draws on a team of experts with a breadth of experience in software development, project and programme management, research facilitation, publicity and community engagement. It’s a national facility for cultivating world-class research through software, whose goal is to make it easier to rely on software as a foundation of research; see their manifesto. The SSI works with researchers, developers, funders and infrastructure providers to identify the key issues and best practice surrounding scientific software.

During my fellowship, I’m particularly keen to work closely with Software Carpentry and Mozilla Science Lab to highlight the importance of software skills across the STEM disciplines. I’m also interested in a broader open science/open computation agenda; see the Recomputation Manifesto and the recently established recomputation.org project.

More to follow in 2014!

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Ten Simple Rules for Reproducible Computational Research

In a paper published last week in PLoS Computational Biology, Sandve, Nekrutenko, Taylor and Hovig highlight the issue of replication across the computational sciences. The dependence on software libraries, APIs and toolchains, coupled with massive amounts of data, interdisciplinary approaches and the increasing complexity of the questions being asked are complicating replication efforts.

To address this, they present ten simple rules for reproducibility of computational research:

Rule 1: For Every Result, Keep Track of How It Was Produced

Rule 2: Avoid Manual Data Manipulation Steps

Rule 3: Archive the Exact Versions of All External Programs Used

Rule 4: Version Control All Custom Scripts

Rule 5: Record All Intermediate Results, When Possible in Standardized Formats

Rule 6: For Analyses That Include Randomness, Note Underlying Random Seeds

Rule 7: Always Store Raw Data behind Plots

Rule 8: Generate Hierarchical Analysis Output, Allowing Layers of Increasing Detail to Be Inspected

Rule 9: Connect Textual Statements to Underlying Results

Rule 10: Provide Public Access to Scripts, Runs, and Results

The rationale underpinning these rules clearly resonates with the work of the Software Sustainability Institute: better science through superior software. Based at the universities of Edinburgh, Manchester, Oxford and Southampton, it is a national facility for cultivating world-class research through software (for example, Software Carpentry). An article that caught my eye in July was the Recomputation Manifesto: computational experiments should be recomputable for all time. In light of the wider open data and open science agenda, should we also be thinking about open software and open computation?

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