Challenges Posed by Processing Scientific Data at Extreme Light Infrastructures Tams Gaizer September 27th, 2016 ELI in a Nutshell ELI = Extreme Light Infrastructure: pan-European research institution Three pillars (cutting edge research institutions):

ELI-ALPS (Szeged, Hungary): ELI-BL (Doln Beany, Czech Republic): PW-power laser with high repetition rate ELI-NP (Mgurele, Romania): Ultrahigh intensity laser beam Transition from construction to operation: All pillars are close to completion ELITRANS H2020 Project on the ELI roadmap Transition from distributed implementations towards integrated and unified operation Parallel implementation

initiation 2008 PP 2011 2013 MoU joint operation 2017 ELI Delivery Consortium ELI-ERIC ELITrans

Main ELITRANS objectives Developing concepts for ELI-ERICs business model: essential elements of the future ELI-ERICs organisation, legal constitution, financial sustainability, governance, user relations, and international integration Preparing ELI-ERICs business plan, adapted to the operation as the worlds first international laser user facility corporate-wide concepts for a VRME, definition and standardisation of user-facility interfaces, health and safety regulations, specialized experiment preparation techniques, computing and big-data management, innovation and technology transfer aspects Preparing and undertaking the merger of formally independent national construction projects towards one unified research infrastructure of pan-European importance. ELITRANS Facts and Figures

Key objectives: Developing concepts for ELI-ERICs business model Preparing ELI-ERICs business plan Manage the merger of independent developments into one unified RI Timescale, budget: September 2015 August 2018 (36 months) 11 workpackages, one devoted to Data and computing

EC funding of 3.4 mEUR Consortium members: Coordinator: Extreme Light Delivery Consortium ASBL Global View of ELI Research Process The model is partially based on: J. Bicarregui: Building an Open Data Infrastructure for Science: Turning Policy into Practice. Franco-British Workshop on Big Data in Science, November 2012 Data and Computing WP: Goal and Challenges Goal of Data and Computing:

Prepare the implementation of a common, ELI-wide data management service layer Define interfaces, integrate to e-infrastructure, manage big data, provide unified access to users, recommend data models, conduct pilot projects Challenges: State-of-the art research tools open new perspective for acquiring raw data -> quantity and complexity increases

Exact needs are being assessed now / making predictions is challenging Expected quantity: 1 5 PB scientific data / year / pillar Different endpoints require different acquisition, management and computation tools and How to Achieve Tasks within Data and Computing WP: Task 1: Develop common concepts for data management, identify requirements Task 2: Survey and identify e-infrastructure solutions

Task 3: Define the common ELI-wide data management service layer Envisaged User Scenarios (1): Generic Data Management Workflow Envisaged User Scenarios (2) Would-be users: scientists researchers from the field of physics, chemistry, biology, nanotechnology

General public: data might be made available some time after the experiment Expected number of users: 500-1000 / year Access to the system: on-site during the experiment, remote access in certain cases System: different systems for different endpoints! Needs are changing from traditional scientific computation to HPC Current Status

Every pillar is under development yet Step-by-step installation of experiment endpoints during 2017 First friendly user test are expected to start in 2017 Live operation: during 2018 Components related to data and computing: still in the design phase. Equipment supporting

the DAQ process definitely will be kept in-house Closing Remarks: Benefits for Scientific Community A unified, ELI-wide data management framework will be applied at every pillar Controlled data management processes, transparent service rules Experimental data and related metadata will be maintained according to international standards

Access to a wide range of state-of-the-art data management and computation tools Availability of e-infrastructure solutions to support processing and curation of scientific data THANK YOU FOR YOUR ATTENTION!

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