Third ASTERICS-OBELICS Workshop

Europe/Amsterdam
Postdoc Centre, Eddington

Postdoc Centre, Eddington

Postdoc Centre @ Eddington 105 Eddington Place Cambridge CB3 1AS Tel: +44 (0)1223 336661
Description
Third ASTERICS-OBELICS Workshop : New paths in data analysis and open data provision in Astronomy and Astroparticle Physics
23-26 October 2018, Cambridge, UK.

This workshop is organized in the framework of OBELICS (Observatory E-environments LINked by common ChallengeS) work package of H2020-ASTERICS. OBELICS activities aim at encouraging common developments and adoption of common solutions for data processing, archive, analysis and access among ESFRI and world class projects in Astronomy and Astroparticle Physics, such as CTA, SKA, KM3NeT, EUCLID, LSST, EGO-Virgo, E-ELT.

The ASTERICS – OBELICS workshops aim at building bridges between ESFRI projects, concerned scientific communities, e-infrastructures, industries and consortia. The 3rd ASTERICS – OBELICS Workshop will survey the development of new software analysis methods in Astronomy and Astroparticle Physics. Follow-up discussions about potential connections between the ESFRI projects and the implementation of EOSC will be part of the programme.

This third edition of the workshop is being organised by the French CNRS LAPP (Laboratoire d’Annecy de Physique de Particules) laboratory, the leading OBELICS institute and hosted locally by the University of Cambridge, UK one of the partner of H2020-ASTERICS project.
Participants
  • Aard Keimpema
  • Alessandro Costa
  • Bjorn Backeberg
  • Brian Matthews
  • Chiara De Sio
  • Chris Atherton
  • Daniel Nieto Castaño
  • Danielle Fenech
  • Elena Cuoco
  • Florian Gaté
  • Fred Moolekamp
  • Giovanni Lamanna
  • Ian Bird
  • J. B. Raymond Oonk
  • Jayesh WAGH
  • Joris Verstappen
  • Jose Luis Contreras
  • Juan Bicarregui
  • Kingsley Gale-Sides
  • L. Angelo Antonelli
  • Matthew Viljoen
  • Michael Kagan
  • Michal Bejger
  • Mikael Jacquemont
  • Miles Deegan
  • Niccolò Zazzeri
  • Peter Hague
  • RITA SOFIA MENESES
  • Rob van der Meer
  • Sebastian Hoch
  • Simona Maria Stellacci
  • Tamas Gal
  • Tammo Jan Dijkema
  • Thomas Vuillaume
  • Tiziana Ferrari
  • Tony Wildish
  • Vladislav Stolyarov
  • Will Handley
    • 08:45 09:15
      Registration 30m
    • 09:15 09:30
      Welcome Address 15m
      Speaker: Prof. Paul Alexander (University of Cambridge)
    • 09:30 10:00
      WP-3 OBELICS overview 30m
      Speakers: Dr Giovanni Lamanna (LAPP/IN2P3/CNRS), Mr Jayesh WAGH (Programme Coordinator-Obelics-Asterics)
    • 10:00 11:05
      Presentations from D-GEX

      Data generation task

      Conveners: Prof. Jose Luis Contreras (Universidad Complutense de Madrid), Dr Lucio Angelo Antonelli (INAF Osservatorio Astronomico di Roma)
      • 10:00
        Work on DL3 and Gammpy 10m
        Speaker: Prof. Jose Luis Contreras (Universidad Complutense de Madrid)
        Slides
      • 10:10
        Update on benchmarking of data formats for VHE 10m
        Speaker: Prof. Jose Luis Contreras (Universidad Complutense de Madrid)
        Slides
      • 10:20
        Data Format Generator 10m
        Speakers: Dr Pierre Aubert (LAPP, CNRS), Dr Thomas Vuillaume (LAPP)
        Slides
      • 10:30
        HERA data management and Recipe minimal recomputation 15m
        Speaker: Dr Kingsley Gale-Sides
      • 10:45
        Casacore data storage 10m
        Speaker: Dr Tammo Jan Dijkema (Astron)
        Slides
      • 10:55
        Real-Time Data Streaming Architecture Survey 10m
        Speaker: Dr Lucio Angelo Antonelli (INAF Osservatorio Astronomico di Roma)
        Slides
    • 11:05 11:30
      Coffee break 25m
    • 11:30 12:30
      Presentations from D-INT
      Conveners: Dr Tammo Jan Dijkema (Astron), Dr Thomas Vuillaume (LAPP)
      • 11:30
        Data and software preservation through containerisation 15m
        Speaker: Mr Tamas Gal (Friedrich-Alexander-University Erlangen)
        Slides
      • 11:45
        INAF Data integration Services for the Cherenkov Telescope Array 10m
        Speaker: Dr Alessandro Costa (INAF)
        Slides
      • 11:55
        Polynomial data compression for large-scale physics experiments 10m
        Speaker: Dr Thomas Vuillaume (LAPP)
        Slides
      • 12:05
        First experience with Common Workflow Language for LOFAR and Apertif data reduction 15m
        Speaker: Dr Tammo Jan Dijkema (Astron)
        Slides
      • 12:20
        Update on STOA workflow management system and its applications 10m
        Speaker: Dr Peter Hague (University of Cambridge)
        Slides
    • 12:30 14:00
      Lunch break 1h 30m
    • 14:00 15:30
      Presentations from D-ANA

      Data Analysis task

      Conveners: Dr Bojan Nikolic (University of Cambridge), Dr Fabio Pasian (INAF - OATs)
      • 14:00
        hipeCTA, high-performance algorithms for CTA 10m
        Speaker: Dr Florian Gate (LAPP, CNRS)
        Slides
      • 14:10
        INAF Data Analysis Services for the Cherenkov Telescope Array 10m
        Speaker: Dr Alessandro Costa
        Slides
      • 14:20
        Recent advances in LOFAR calibration and imaging 10m
        Speaker: Dr Tammo Jan Dijkema (Astron)
        Slides
      • 14:30
        GammaLearner: a Deep Learning framework for CTA 10m
        Speaker: Mr Mikael Jacquemont (LAPP, CNRS)
        Slides
      • 14:40
        Efficient remote processing using CASA and Jupyter 10m
        Speaker: Dr Aard Keimpema
        Slides
      • 14:50
        DNN classification of signals and glitches in time-domain gravitational-wave data 10m
        Speaker: Dr Michal Bejger
        Slides
      • 15:00
        Accelerating Science by Repurposing Machine Learning Software 10m
        Speakers: Dr Bojan Nikolic (University of Cambridge), Dr Vladislav STOLYAROV
        Slides
      • 15:10
        Bayesian source finding for interferometers with BaSC 10m
        Speaker: Dr Peter Hague (University of Cambridge)
        Slides
    • 15:30 16:00
      Coffee break 30m
    • 16:00 17:00
      Panel discussion: OBELICS review and conclusion 1h
    • 17:00 18:00
      Internal meeting - tasks leaders: Preparing OBELICS blue print
    • 18:30 20:30
      Welcome Reception 2h
    • 09:00 09:30
      Machine Learning applications in Gravitational Wave research 30m
      Noise of non-astrophysical origin contaminates science data taken by the gravitational-wave detectors. Characterization of instrumental and environmental noise has proven critical in identifying false positives in the first observing runs. In this context the application of different machine learning methods can help in achieving, for example, a fast classification of transient events to disentangle noise from gravitational signals helping a fast real time analysis. Moreover, these approaches could be used to disentangle Gravitational signals from noise. Deep Learning techniques could even be used to the aim of non linear noise cancellation to condition the data before any detection algorithm will be used and there are promising on-going studies on simulated data.
      Speaker: Dr Elena Cuoco
      Slides
    • 09:30 10:00
      Time-domain Machine Learning - Opportunities and Challenges for the SKA 30m
      To harness the discovery potential of data collected by the SKA, we require efficient and effective automated data processing methods. Machine learning tools have the potential to deliver this capability, as evidenced via their successful application to similar problems in the astronomy domain. This talk introduces the machine learning required for successful time-domain data processing (pulsar / transient discovery), and the infrastructure required to support it. Here the overriding aim is to increase awareness of what is required to facilitate the execution of automated learning methods, which we’ll need if we are to achieve the SKA's ambitious science goals.
      Speaker: Dr Robert Lyon (University of Manchester)
      Slides
    • 10:00 10:30
      Applications of Machine Learning to Deblending in LSST 30m
      It is estimated that at least 63% of sources observed in the 10 year LSST survey will have at least 2% of their flux blended with another object. Achieving many of the LSST science goals requires a working deblender to separate the flux from overlapping stars and galaxies by extracting morphological and spectral data for each source. The primary focus of this talk will be on scarlet, the python package I have been developing with Peter Melchior that will soon be implemented in the HSC and LSST software pipelines. Time permitted I will also mention more ambitious efforts by other members of the Dark Energy Science Collaboration (DESC) using neural networks to solve the blending problem.
      Speaker: Dr Fred Moolekamp
      Slides
    • 10:30 11:00
      Coffee break 30m
    • 11:00 11:30
      Machine learning in the Cherenkov Telescope Array 30m
      The sensitivity of ground-based gamma-ray telescopes based on the imaging atmospheric Cherenkov technique (IACTs) is driven by, among other factors, our ability to reconstruct the primary particles that originate the extended atmospheric showers that are imaged by the telescopes: this particle reconstruction enables us to classify gamma-ray events from the much more frequent background of cosmic-ray events. Supervised machine learning algorithms, like random forest or boosted decision trees, have been successfully applied to the task of event reconstruction by current generation IACTs, substantially improving their sensitivity. In this talk we will briefly review the state-of-the-art of machine-learning based event reconstruction for current-generation IACTs and will present an overview of the novel approaches, like deep learning, currently being explored for the Cherenkov Telescope Array, the next-generation gamma-ray observatory.
      Speaker: Dr Daniel Nieto
      Slides
    • 11:30 12:00
      Machine learning in High Energy Physics 30m
      High Energy Physics probes the mysteries of the universe using some of the worlds largest experiments and datasets. To interpret and analyze this data in search of new physical phenomena, a wide array of domain specific algorithms have been developed. At the same time, recent advances in deep learning have seen great success in the realms of computer vision, natural language processing, and broadly in data science. By connecting the challenges in the HEP domain with those in deep learning, new and powerful approaches to analyzing HEP data are being developed. In this talk, I will discuss developments in the application of machine learning techniques to the analysis and interpretation of High Energy Physics data, with a focus on the Large Hadron Collider.
      Speaker: Dr Michael Kagan
      Slides
    • 12:00 12:30
      Machine learning in KM3NeT 30m
      Speaker: Ms Chiara De Sio (University of Salerno)
      Slides
    • 12:30 14:00
      Lunch break 1h 30m
    • 14:00 14:30
      Machine learning in solar physics 30m
      Speaker: Dr Sebastian Hoch
    • 14:30 15:00
      Bayesian statistics 30m
      Speaker: Dr Will Handley
      Slides
    • 15:00 15:30
      A summary of the workshop "AI at CERN and SKA" 30m
      The two-day workshop was held in the Alan Turing Institute in London (17-18.09.2018) where ATI staff members, AI researches from industry as well as CERN and SKA scientists discussed the application of Artificial Intelligence (AI) and Machine Learning (ML) for scientific discovery in High Energy Physics, astrophysics, cosmology and radio astronomy. An overview of the presentations will be given in this summary talk.
      Speaker: Dr Vlad Stolyarov
      Slides
    • 15:30 16:00
      Coffee break 30m
    • 16:00 17:30
      Uniformisation in machine learning: Panel Discussion
      Convener: Dr Thomas Vuillaume (LAPP)
      slides
    • 19:30 21:30
      Social Dinner 2h
    • 09:00 09:25
      DATA LAKE - WLCG computing model evolution 25m
      Speaker: Dr Ian Bird (CERN)
      Slides
    • 09:25 09:50
      EOSC overview and paths 25m
      Speaker: Dr Brian Matthews
      Slides
    • 09:50 10:15
      ASTERICS-OBELICS software and services contribution to EOSC needs 25m
      Speaker: Dr Giovanni Lamanna (LAPP/IN2P3/CNRS)
      Slides
    • 10:15 10:40
      EOSC-hub: project status and plans, presentation of service catalogue 25m
      Speakers: Matthew Viljoen (EGI Foundation), Dr Tiziana Ferrari (EGI Foundation)
      Slides
    • 10:40 11:00
      Coffee Break 20m
    • 11:00 11:25
      Rules of participation (state of play) for service providers: EOSCpilot outcome and EOSC-hub experience 25m
      Speaker: Matthew Viljoen (EGI Foundation)
      Slides
    • 11:25 12:25
      Interactive group discussion - Shaping the European Open Science Cloud service roadmap 1h
      During this session representatives from the European Open Science Cloud (EOSC) will introduce EOSC and provide an overview of existing services and then engage with the Asterics meeting participants in an interactive world cafe-style session on prospective future service provisioning, access models and concrete services that the RI would like to bring into EOSC. EOSC is an ambitious initiative aiming at the federation of existing and planned digital infrastructures for research. It seeks to remove barriers among disciplines and countries and make it easier for researchers to share and access the digital resources they need. Looking forward to the evolution of EOSC, it is essential to understand and prioritise what services are most needed and that should be added to the future EOSC service portfolio and importantly, what criteria are to be used for uptake in the service portfolio. The goal of this session is to take advantage of the collective knowledge of the audience to extract high-level needs for services and identify priorities for the coming years to develop a service roadmap. The outcome of the session will help us draw a more detailed picture of the European Open Science Cloud roadmap, and the services that ESFRI RIs, such as Asterics, would need and bring into it.
      Speakers: Dr Bjorn Backeberg, Dr J B Raymond Oonk, Matthew Viljoen (EGI Foundation), Dr Tiziana Ferrari (EGI Foundation)
    • 12:25 13:55
      Lunch Break 1h 30m
    • 13:55 14:20
      H2020-HNSCiCloud project update and future directions 25m
      Speaker: Dr Tony Wildish
      Slides
    • 14:20 14:45
      H2020 AENEAS results and objectives 25m
      Speaker: Dr Rob van der Meer (ASTRON)
      Slides
    • 14:45 15:15
      Coffee Break 30m
    • 15:15 17:00
      Panel Discussion 1h 45m
      Slides