CERN@school and GridPP: harnessing the power of the Worldwide LHC Computing Grid for research in schools and beyond

Lead Research Organisation: Queen Mary University of London
Department Name: Physics

Abstract

CERN@school is a programme that brings CERN into the classroom. It offers school students access to research-grade detector technology, data analysis and storage facilities, and a nationwide collaboration of fellow students, teachers and academics so that they can pursue their own investigation-driven research and experience being a scientist before making important career choices. This fellowship will support Tom over three years as the programme evolves to incorporate the Worldwide LHC Computing Grid (WLCG), harnessing the 485,000 processing cores and 270 petabytes of storage used to discover the Higgs boson to bring cutting-edge research techniques to schools and others through the GridPP Collaboration's new user engagement programme. The fellowship will support:

* Managing the CERN@school experimental facilities: the Timepix hybrid silicon pixel detector, developed by the Medipix2 Collaboration, can visualise and measure ionising radiation via a ~2cm^2 silicon sensor divided into a 256 x 256 pixel grid. CERN@school features a number of experimental facilities based around the Timepix detector. These include the CERN@school detector network (currently reaching 42 schools, outreach groups and science centres via the Institute of Physics' Physics Teacher Network and SEPnet), the Langton Ultimate Cosmic ray Intensity Detector (LUCID) experiment, launched aboard Surrey Satellite Technology Limited's (SSTL's) TechDemoSat-1 in July 2014, and the Langton Star Centre's Timepix detectors in the Monopole and Exotics Detector at the LHC (MoEDAL) at CERN. Thanks to Tom's work to date, datasets from these facilities are accessible to members of the CERN@school Collaboration. The fellowship will support the continued management of these facilities;

* Facilitating usage of GridPP resources for schools research: the GridPP New User Engagement programme makes use of a number of STFC-backed technologies such as DIRAC (for grid processing and storage management) and the CERN Virtual Machine File System (CVMFS) software deployment mechanism. The fellowship will exploit these technologies to bring schools - particularly those in deprived areas - onto the grid so that the excitement of data-driven physics research is accessible to all. The CERN Virtual Machine (VM) service can be used to instantly deploy research software into schools and connect to the grid. Where school IT infrastructure requires it, the "GridPPi", a Raspberry Pi developed by Tom to run with CERN@school and GridPP software, may be used instead to engage harder-to-reach audiences with the data analysis techniques used by scientists at CERN.

* The CERN@school Research Symposia: the first CERN@school Research Symposium was held in September 2014 in conjunction with the 10th International Conference for Position Sensitive Detectors (PSD10) at the University of Surrey, Guildford. Over one hundred students and teachers from around the country attended the joint plenary and poster sessions to share progress on research projects. Workshops for detector usage and data analysis were also held. The fellowship will support these for the next three years.

* Training and development for the IOP Physics Teacher Network: the fellowship will support the development of a training and CPD programme for teachers, outreach officers, science centre staff, and Physics Network Coordinators (PNCs) in collaboration with the National Centre for Science and Engineering Research in Schools (NCSERS) and the Science Learning Centres. This includes lesson plans for using the detectors in class. This will allow students from all schools to benefit from the CERN@school programme.

Publications

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Whyntie T (2017) The GridPP UserGuide

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Pinfold JL (2019) The MoEDAL experiment: a new light on the high-energy frontier. in Philosophical transactions. Series A, Mathematical, physical, and engineering sciences

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Whyntie T (2016) CERN@school: bringing CERN into the classroom in Nuclear and Particle Physics Proceedings

 
Description Programmes such as CERN@school, where school students carry out novel scientific research under the supervision of practising scientists, can have a positive impact on STEM educational outcomes and practices for both students and teaching practioners. See (Walkington & Rushton 2019) for further details: https://doi.org/10.5539/hes.v9n4p133
Exploitation Route The legacy of this Award is its contribution to the Institute for Research In Schools (IRIS). See http://www.researchinschools.org/ for more details.
Sectors Education

URL http://www.researchinschools.org/
 
Description The outcomes of this Award have contributed to a new paradigm in the teaching of STEM subjects for both students and teaching practioners, championed by the Institute for Research in Schools (IRIS). These findings are summarised in (Walkington & Rushton 2019): https://doi.org/10.5539/hes.v9n4p133
First Year Of Impact 2019
Sector Education
Impact Types Policy & public services

 
Description The GridPP Collaboration 
Organisation GridPP Collaboration
Country United Kingdom 
Sector Learned Society 
PI Contribution CERN@school acted as a technology demonstrator Virtual Organisation (VO) for software and tools in GridPP's New User Engagement Programme. By testing things like the GridPP DIRAC job management system, the Ganga User Interface, and CernVM-File System for remote software distribution, it could be ensured that these were production ready for when other new user communities from astrophysics, medical physics, and industry wanted to engage with GridPP resources. The results of this programme are reported in [1]. CERN@school users also provided feedback for the GridPP UserGuide [2], a document that was key to the process of engaging new users. [1] http://doi.org/10.5281/zenodo.220995 [2] http://doi.org/10.5281/zenodo.222702
Collaborator Contribution The GridPP Collaboration, which represents the UK's contribution to the Worldwide LHC Computing Grid (WLCG), offers up to 10% of its resources to users not associated with the Large Hadron Collider (LHC) experiments. CERN@school, and the MoEDAL Collaboration (as part of CERN@school research), made use of GridPP resources in carrying out research associated with the programme. CERN@school (and IRIS) also benefitted significantly from the technical expertise provided by members of the GridPP Collaboration via support mechanisms like the UserGuide, the TB-SUPPORT and GRID-SUPPORT JiscMAIL mailing lists, and attendance at GridPP Collaboration meetings.
Impact Please refer to [1] and [2] for a list of the outputs and case studies from CERN@school and the GridPP New User Engagement Programme respectively. New user communities from astrophysics (including the Large Synoptic Survey Telescope), computational biology, medical physics, and space science were successfully engaged with GridPP as a result of the programme. [1] http://doi.org/10.5281/zenodo.227090 [2] http://doi.org/10.5281/zenodo.220995
Start Year 2012
 
Description The Institute for Research in Schools (IRIS) 
Organisation The Institute For Research In Schools
Country United Kingdom 
Sector Charity/Non Profit 
PI Contribution The Fellow acted as "Researcher in Residence" for the Institute for Research in Schools, initially for the wider CERN@school programme (i.e. supporting the detector network and LUCID experiments) but from January 2016 with more of a focus on the Monopole and Exotics Detector at the LHC (MoEDAL). Full details may be found in [1]. [1] [1] http://doi.org/10.5281/zenodo.227090
Collaborator Contribution IRIS absorbed CERN@school into its programme of research activities when it came into existence in December 2015. This provided substantial support for the programme in the form of administrative and technical support for the detector network. IRIS also supported the involvement of L. F. Thomas (LFT Consulting, ESERO Space Ambassador) and the Scottish Schools Education Research Centre (SSERC) to develop and expand the educational resources available for CERN@school activities.
Impact Please refer to "The CERN@school Programme: Document Index" [1] for a full list of all documents, presentations, events, and code repositories that were produced in association with the Fellowship. [1] http://doi.org/10.5281/zenodo.227090
Start Year 2015
 
Title CERN@school analysis code: beta-attenuation 
Description This repository contains the code and data needed to recreate the analysis carried out for the beta radiation attenuation experiment described in Section 5 of the CERN@school Contemporary Physics paper (doi:10.1080/00107514.2015.1045193). The datasets featured in the paper are included with the code, but may also be found on FigShare (doi:10.6084/m9.figshare.867659.v2). 
Type Of Technology Software 
Year Produced 2017 
Open Source License? Yes  
Impact This software was and continues to be used as part of the Institute for Research in Schools CERN@school programme. Please refer to doi:10.5281/zenodo.227090 for a summary of the impact of the programme. 
URL https://github.com/CERNatschool/beta-attenuation
 
Title CERN@school analysis code: cluster-sorter 
Description This repository contains code for analysing, visualising and sorting clusters of pixels measured by the Timepix detector using the techniques described in (Whyntie, T. 2015, doi:10.1080/00107514.2015.1045193). 
Type Of Technology Software 
Year Produced 2017 
Open Source License? Yes  
Impact This software was and continues to be used as part of the Institute for Research in Schools CERN@school programme. Please refer to doi:10.5281/zenodo.227090 for a summary of the impact of the programme. 
URL https://github.com/CERNatschool/cluster-sorter
 
Title CERN@school analysis code: fast-cluster-analysis 
Description The code in this repository can be used to perform a fast cluster analysis on data collected with a Timepix detector for use in research conducted as part of the CERN@school programme. An example analysis using the radiation profile methods described in Section 4 of the CERN@school Contemporary Physics paper (Whyntie, T. 2015 doi:10.1080/00107514.2015.1045193) is included. The datasets featured in the paper are included with the code, but may also be found on FigShare (doi:10.6084/m9.figshare.4588276.v2). 
Type Of Technology Software 
Year Produced 2017 
Open Source License? Yes  
Impact This software was and continues to be used as part of the Institute for Research in Schools CERN@school programme. Please refer to doi:10.5281/zenodo.227090 for a summary of the impact of the programme. 
URL https://github.com/CERNatschool/fast-cluster-analysis
 
Title CERN@school analysis code: frame-viewer 
Description This repository contains some simple Python code for displaying CERN@school Timepix frame data using a GridPP CernVM and the matplotlib software suite. 
Type Of Technology Software 
Year Produced 2017 
Open Source License? Yes  
Impact This software was and continues to be used as part of the Institute for Research in Schools CERN@school programme. Please refer to doi:10.5281/zenodo.227090 for a summary of the impact of the programme. 
URL https://github.com/CERNatschool/frame-viewer
 
Title CERN@school analysis code: get-coding 
Description This repository contains the Jupyter notebooks and code associated with the prototype CERN@school coding course. It contains one lesson that may be used as a basis for others and further development of the course. The lesson displays in GitHub as a Jupyter notebook, but also may be used interactively when downloaded and run on (for example) a GridPP CernVM. 
Type Of Technology Software 
Year Produced 2017 
Open Source License? Yes  
Impact This software was and continues to be used as part of the Institute for Research in Schools CERN@school programme. Please refer to doi:10.5281/zenodo.227090 for a summary of the impact of the programme. 
URL https://github.com/CERNatschool/get-coding
 
Title CERN@school analysis code: inverse-square-law 
Description This repository contains the code required for performing the analysis described in the CERN@school inverse square law experiment, as described in (Whyntie, T. et al. 2013 - doi:10.1088/0031-9120/48/3/344). The dataset used in the paper is available separately on FigShare (doi:10.6084/m9.figshare.949631.v1). 
Type Of Technology Software 
Year Produced 2017 
Open Source License? Yes  
Impact This software was and continues to be used as part of the Institute for Research in Schools CERN@school programme. Please refer to doi:10.5281/zenodo.227090 for a summary of the impact of the programme. 
URL https://github.com/CERNatschool/inverse-square-law
 
Title CERN@school analysis code: particle-rate-plotter 
Description This code is for estimating the mean rate of particles detected with a Timepix detector using the method described in Section 3 of the CERN@school Contemporary Physics paper (Whyntie, T. et al. 2015 - doi:10.1080/00107514.2015.1045193) and the accompanying background radiation measurement how-to guide on FigShare (doi:10.6084/m9.figshare.895961.v1). There is also code for plotting the time profile (i.e. the number of pixels detected over a time series) for a given dataset for a given day. The datasets featured in the paper are included with the code, but may also be found on FigShare (doi:10.6084/m9.figshare.1618851.v2). 
Type Of Technology Software 
Year Produced 2017 
Open Source License? Yes  
Impact This software was and continues to be used as part of the Institute for Research in Schools CERN@school programme. Please refer to doi:10.5281/zenodo.227090 for a summary of the impact of the programme. 
URL https://github.com/CERNatschool/particle-rate-plotter
 
Title CERN@school training and analysis code: getting-started 
Description This repository contains legacy code associated with training material for the CERN@school programme; see, for example, "Plotting with CERN@school: an introduction to functions" (doi:10.6084/m9.figshare.1136052.v1). This initial release has been updated to reflect CERN@school's move to the Institute for Research in Schools (IRIS). 
Type Of Technology Software 
Year Produced 2017 
Open Source License? Yes  
Impact This software was and continues to be used as part of the Institute for Research in Schools CERN@school programme. Please refer to doi:10.5281/zenodo.227090 for a summary of the impact of the programme. 
URL https://github.com/CERNatschool/getting-started
 
Title LUCIDITY 
Description The Langton Ultimate Cosmic ray Inetensity Detector Interactive Test sYstem (LUCIDITY) is a web app for running and managing simulations of the LUCID detector. It is based on the Hobo Ruby on Rails framework and was used to carry out the research reported in "Simulation and analysis of the LUCID experiment in the Low Earth Orbit radiation environment" (Whyntie, T. 2014 - doi:10.1088/1742-6596/513/2/022038). 
Type Of Technology Webtool/Application 
Year Produced 2017 
Impact This software was used to estimate the data rates expected from the Langton Ultimate Cosmic ray Intensity Detector (LUCID). The results were reported in doi:10.1088/1742-6596/513/2/022038. The expected data rates were estimated to be within the capabilities of TechDemoSat-1's systems, and the successful operation of the detector since its launch in July 2014 has shown that these estimates were justified. 
URL https://github.com/CERNatschool/LUCIDITY
 
Title SimLUCID-lite 
Description SimLUCID-lite is a simple GEANT4-based simulation of the Langton Ultimate Cosmic ray Intensity Detector (LUCID) experiment, used to estimate the expected data rates observed in Low Earth Orbit (LEO). This is the official initial release of the SimLUCID-lite code that accompanies the CHEP 2013 conference proceedings reported in (Whyntie, T. 2014, doi:10.1088/1742-6596/513/2/022038), with an updated README.md to link CERN@school with the Institute for Research in Schools (IRIS). 
Type Of Technology Software 
Year Produced 2017 
Open Source License? Yes  
Impact This software was used to provide estimates of the data rates expected from the Langton Ultimate Cosmic ray Intensity Detector (LUCID). The results were reported in doi:10.1088/1742-6596/513/2/022038. The expected data rates were estimated to be within the capabilities of TechDemoSat-1's systems, and the successful operation of the detector since its launch in July 2014 has shown that these estimates were justified. 
URL https://github.com/CERNatschool/SimLUCID-lite