Raniere Silva

Advances in Data ScienceBy Raniere Silva, Software Sustainability Institute.

Manchester hosted the Advances in Data Science 2017 meeting organised by the Data Science Institute on 15-16 May 2017. It was an opening eyes meeting for privacy and inspiring for ways that researchers can analyse and visualise their data.

The meeting started with a talk by Mark Girolami covering the use case of inference and prediction of the London retail development. It was interesting to discover how retail development is important to plan the future of any city since it’s one of the main reasons why people travel across their cities. The introduction of drones and self-driven cars would completely change why and when we travel across our cities, which will create many opportunities for researchers in this area. Following Mark's talk, Raia Hadsell exposed ways to overcome catastrophic forgetting; i.e., when a machine learning entity forgets what it’s learnt when it starts learning  a new problem in neural nets. Raia used Atari Games played by an artificial intelligence…

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The Software Sustainability Institute are very pleased to announce Microsoft as the primary sponsor of the Docker Containers for Reproducible Research Workshop (C4RR). They have offered very kindly Azure Cloud time to every attendee! Azure Container Service supports Docker and can be used to improve reproducible research.

Kenji Takeda, Director, Azure for Research, Microsoft (UK) will present on 28th June. Kenji was one of the speakers at Collaborations Workshop 2017—you can watch the recording of his talk here—and we are very happy to have the opportunity to listen him talking about containers.

Register today! The C4RR will take place at the University of Cambridge from the 28th-29th June 2017.

Docker Containers & Reproducible ResearchBy Raniere Silva, Community Officer

The Docker Containers for Reproducible Research Workshop (C4RR) is nearly upon us. It will take place from the 27th to 28th June 2017 at the Department of Engineering, University of Cambridge.

The latest changes and additions to the agenda are now live. Tuesday 27th June will be filled most with talks. 28th June will start with two demos. Delegates will need to select one to attend since they will be run in parallel and are responsible to configure their machine in advance with the requirements of the demo they plan to attend.

28th June afternoon will kick-off with the Sponsored Keynote Talk by Kenji Takeda from Microsoft. Kenji was one of the speakers at Collaborations Workshop 2017—you can watch the recording of his talk here—and we are very happy to have the opportunity to listen him talking about containers.

The workshop dinner will happen at the end of the first day, 27th June. We will be waiting delegates at The Cambridge Brew House for a informal curry night. Before the dinner…

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The Docker Containers for Reproducible Research Workshop is attracting people from a broad range of backgrounds. To have an idea of who is attending we provide their organisation details on the list below.

  • BP Institute
  • British Library
  • Cancer Research UK - Cambridge Institute
  • CERN
  • Diagnostic Image Analysis Group- Radboudumc Nijmegen
  • Earlham Institute
  • ECMWF
  • EMBL-EBI
  • EPCC
  • First Light Fusion Ltd
  • GigaScience
  • Institute of Cancer Research
  • Institute of Nuclear Medicine - UCL
  • John Innes Centre
  • Newcastle University
  • Oxford University
  • Quadram Institute Biosciences
  • RadiaSoft LLC
  • RosettaHUB Ltd
  • Software Sustainability Institute
  • STFC
  • Tecgraf PUC-RIo
  • University of Cambridge
  • University of Edinburgh
  • University of Exeter
  • University of Manchester
  • University of Münster
  • University of Reading
  • University of St Andrews
  • Univesity of Barcelona - Barcelona Supercomputing Center
  • Weatherall Institute of Molecular…
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Docker Containers & Reproducible ResearchBy Raniere Silva, Community Officer.

Docker Containers for Reproducible Research Workshop (C4RR) is only a month away, 27-28th of June 2017 at the University of Cambridge. This workshop offers many talks on the use of containers applied to improve reproducibility on desktop, cloud and HPC environments and some practical sessions.

For those interested in HPC, some talks will surely make the workshop worth for all our attendees, Michael Bauer's one about Singularity, Matthew Hartley's one about ways to make the transition from the desktop to the HPC smother and Jeroen Schot's one describing how the Dutch National e-Infrastructure is empowering containers.

Meanwhile, the talks from Nick James, David Mawdsley and Matthew Upson are aimed at attendees who are more interested in reproducibility. Nick will talk about an open source data analysis pipeline from the European Bioinformatics Institute that employs containers. If you are an R user and are looking for ways to use Knitr with Docker to make easy for your colleagues to reproduce your R Markdown documents, David's talk is for you. And Matthew will take the attendees through a journey…

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This procedure has been adopted from the Ada Initiative's guide titled "workshop anti-harassment/Responding to Reports”.

  1. Contact any of the following staff

The staff will also be prepared to handle the incident. All of our staff members are informed of the code of conduct policy and guide for handling harassment at the workshop. There will be a mandatory staff meeting just prior to the workshop when this will be reiterated as well.

  1. Report the harassment incident (preferably in writing, e.g. on paper or via email). All reports are confidential.

  2. When reporting the event to staff, try to gather as much information as available, but do not interview people about the incident. Staff will assist you in writing the report/collecting information.

  3. The important information consists…

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The Docker Containers for Reproducible Research Workshop brings together researchers, developers and educators to explore best practices when using containers, not only Docker, and the future of research software with containers.

We value the participation of each stakeholder and want all attendees to have an enjoyable and fulfilling experience. Accordingly, all attendees are expected to show respect and courtesy to other attendees throughout the workshop and at all workshop events, including online.

To make clear what is expected, all attendees, speakers, exhibitors, organisers and volunteers at Docker Containers for Reproducible Research Workshop 2017 are required to conform to the following Code of Conduct. Organisers will enforce this code throughout the workshop.

Summary

Docker Containers for Reproducible Research Workshop is dedicated to providing a harassment-free workshop experience for everyone. We do not tolerate harassment of workshop participants in any form.

All communication should be appropriate for a professional audience including people of many different backgrounds.

Be kind to others. Do not insult or put down other attendees.

Behave professionally. Remember that harassment and exclusionary jokes are not appropriate at  the Docker Containers for Reproducible Research Workshop.

Attendees violating these rules may be asked to leave the workshop without a refund at the sole discretion of the workshop organisers.

Thank you for helping make this a welcoming, friendly event for all.

Clarifications

Harassment includes…

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Abstracts of lightning talks sorted by last name of the first author.

The lightning talks will take place in the afternoon of the second day, 28 June, starting at 15:00.


Using Containers to drive reproducibility best practices in Bioinformatics training

Mark Fernandes, Quadram Institute Biosciences

At Quadram Institute Biosciences, we have implemented an innovative training programme called ‘Bite-sized Bioinformatics’.

These are regular short (60-90 minute) sessions where there is a short single-topic talk followed by an applied practical exercise.

A key requirement is to have a means of easily & quickly deploying the training environments to users machines inside and outside of the Institute premises. This enables learners to complete the practicals at their own time, location and pace outside of the sessions.

Along with some use of VMs, we have increasingly used Docker containers. We contend that actively engaging with containers for learning environments is a powerful advocacy for further usage in their research work. The strengths and limitations of the technology can be experienced first-hand.

The containers have also been used to facilitate exposure to other good practices with regard to reproducibility e.g. Jupyter Notebooks


Containing infrastructure models for testing and scale

Tom Russell, Oxford University, Environmental Change Institute, ITRC Mistral project

NISMOD (National Infrastructure Systems MODel) is a system-of-systems model which couples simulation models of the energy, water, waste water, transport and solid waste systems in order to evaluate long-term plans, risk and resilience under…

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Abstracts of demos sorted by last name of the first author.

The demos will take place in the morning of the second day, 28 June, between 9:00 and 12:00.


RosettaHUB, connecting the dots between clouds, containers and research software

Karim Chine, RosettaHUB Ltd.

The RosettaHUB platform connects the dots between clouds, containers, research software, real-time collaboration frameworks and social portals. It delivers a virtual environment of considerable flexibility and power that fosters usability, reproducibility, shareability and auditability at all layers of interactions between scientists and the research tools and infrastructures.

The workshop will give an overview of the new platform and hub for open data science and will highlight the essential role played by docker in this new ecosystem.

RosettaHUB makes public and private clouds easy to use by everyone. RosettaHUB's federation platform allows higher education institutions and research laboratories to create virtual organizations within the hub. Members receive active AWS accounts supervised in terms of budget and cloud resources usage, protected and monitored/managed centrally by the institution’s administrator. 

RosettaHUB allows users to work with docker containers seamlessly. Simple web interfaces allow users to create those containers, connect them to data storages, snapshot them, share snapshots with collaborators and migrate them from one cloud to another. The RosettaHUB perspectives make it possible to use the containers to serve securely noVNC, RStudio, Jupyter, Zeppelin and Spark-notebook, Shiny Apps and to enable those tools for real-time collaboration.

The RosettaHUB…

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Abstracts of talks sorted by last name of the first author.


Singularity Containers for Reproducible Research

Michael Bauer, University of Michigan / Lawrence Berkeley National Lab

In scientific research it is imperative that methods and data used for those methods be preserved to allow for the reproduction of results. Unfortunately, some results are also dependent on the computing environment in which they are run. For example, a random number generator may depend not just on the seed used, but the version of the random number generator library and the compiler used to generate the executable. Singularity is an open source container solution designed to mitigate these reproducibility problems. Singularity was initially developed at Lawrence Berkeley National Laboratory and is now maintained by collaborators from institutions across the globe. With Singularity a scientist can package the entire computing environment (compiler, libraries, data, etc..) used to generate their results into a single file that runs independently of the Linux distribution, without the need to create a virtual machine. This file can then be archived alongside a published research paper to allow others to independently verify the published results with the guarantee that they will be running the exact same executable as the researcher.


Docker Containers for Deep Learning Experiments

Paul K. Gerke, Diagnostic Image Analysis Group, Radboudumc Nijmegen

Deep learning is a powerful tool to solve problems in the area of image analysis. The dominant compute platform for deep learning is Nvidia’s proprietary CUDA, which can only be used together with Nvidia…

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