1. 1 11/09/2015 Final Reflections APA Conference 2011 John Wood

2. 2 ERA 2030: ERAB’s STRATEGIC VIEW October 2009

3. 3 Commissioner Janez Potocnik... holistic thinking and approach epitomized the first ‘Renaissance’, where scholars and artists moved relatively freely around Europe among the centres of learning and culture. While this privilege was the domain of a few at that time, it should be our ambition, in the new ‘Renaissance’, that this should be the expectation of all citizens, especially in the field of research and innovation.

4. 4 An ERA driven by societal needs to address the ‘Grand Challenges’

5. 5 11/09/2015 Highlights - CANFAR connects astronomical dots July 1, 2009 — Victoria, British Columbia Astronomers were once stereotyped as lone insomniacs tending optical telescopes. But now they do most of their research in "virtual organizations" - far-flung national and international collaborations of diverse people and institutions that use the Internet to exchange and crunch vast stores of digital data fed by telescopes of many kinds around the planet.

6. Scenario IV: Science and the st udent Roger is working on an international PhD. It’s a relatively new programme, in which a student applies to become a member of an international team working on a big problem that affects all people. His group is comparing many forms of nonverbal communications between cultures. It has several hundred members and his university tutor is one of the nodal points contributing expertise in ‘synergistic communication between biological components.’ Others in the network are using archaeological evidence to study communications between ancient Mesopotamian and Hellenic cultures; some are studying computer-computer interactions between different systems; yet more are studying communications in refugee camps. Each node contributes to the whole. Results are communicated as they happen, and there are daily, virtual-presence planning sessions. Roger had to sign a contract not to misuse data or contribute anything that is not for the common good – such as externally sourced information that he has not checked for provenance

8. Data Services Community Support Services Astronomy Climatology Chemistry History Biology Computing Infrastructure Persistent Storage Capacity Integrity Authentication & Security API Data Discovery & Navigation Workflows Generation Demography Scientific Data (Discipline Specific) Other Data Researcher 1 Non Scientific World Scientific World Researcher 2 Aggregated Data Sets (Temporary or Permanent) Workflows Aggregation Path Source: High-level Group on Scientific Data

9. 9  Data ingest  Managing petabytes+  Common schema(s)  How to organize?  How to re-organize?  How to coexist & cooperate with other scientists and researchers?  Data query and visualization tools  Support/training  Performance  Execute queries in a minute  Batch (big) query scheduling Experiments & Instruments Simulations facts answers questions ? Literature Other Archives facts

10. 10 CESSDA Council of European Social Science Data Archives Till December 2009 CLARIN Common Language Resources and Technology Infrastructure Till December 2010 DARIAH Digital Research Infrastructure for the Arts and Humanities Till September 2010 ESS European Social Survey Till May 2010 SHARE Survey on Health, Ageing and Retirement in Europe Till December 2009 Social Science and Humanities Projects Copyright © 2009 Norwegian Social Sciences Data Services Grenoble, September 10, 2009

11. 11 Common Language Resources and technology Initiative - CLARIN large-scale pan-European coordinated infrastructure language resources and technology to scholars of all disciplines based on a Grid-type infrastructure using Semantic Web technology Estimated costs Preparation: 4.1 M€ (2008 – 2010) Construction: 104 M€ (2011 - 2013) Operation: 38 M€ (2014 - 2018) Decommissioning: not applicable www.clarin.eu Brussels, 25 September 2008

12. 12 RAMIRI HamburgSept 2009 - Steven Krauwer12 What is CLARIN? Common Language Resources and Technology Infrastructure (http://www.clarin.eu) Basic idea: –European federation of digital archives with language data and tools (text, speech, multimodal, gesture …) –target audience humanities and social sciences scholars –with uniform single sign-on access to the archives –with access to language and speech technology tools to retrieve, manipulate, enhance, explore and exploit data –all languages are equally important –to cover all EU and associated countries

13. 13 RAMIRI HamburgSept 2009 - Steven Krauwer13 Main challenges Take-up Take-up by target audience: –aim at humanities and social sciences scholars –who have no technical background –who have very little tradition in using technological tools Special challenges: –discovering what they need –making them aware of the potential benefits of the infrastructure, e.g. to speed up or innovate their research

14. 14 RAMIRI HamburgSept 2009 - Steven Krauwer14 Main challenges Legal and ethical Legal challenges: –making a light access and licensing system for the users –protecting owners’ rights and interests –respecting national IPR legislation Special problems: –transnational access and diversity of national IPR and data legislation –repurposed data (e.g. using novels or TV news for linguistic studies) –ethical & privacy considerations (e.g. use recorded phone calls to train speech recognition systems)

15. 15 Large-scale e-Infrastructures for Biodiversity Research

16. 16 Experimentation on a few parameters is not enough: Limitations to scaling up results for understanding system properties The biodiversity system is complex and cannot be described by the simple sum of its components and relations LifeWatch adds a new technology to support the generation and analysis of large-scale data-sets on biodiversity. Find patterns and learn processes.

17. 17 Distributed data generation Continental ecological monitoring sites Marine monitoring sites Biological collections Greenhouse gas measurements Plate observing system

18. 18 Data + users from other infrastructures

19. 19 XFEL: Office and Laboratory Building

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22. 22 3 rd Gen. SR 2 nd Gen. SR Laser Slicing SPPS Initial H.-D. Nuhn, H. Winick Peak Brightness [Phot./(s · mrad 2 · mm 2 · 0.1%bandw.)] FWHM X-Ray Pulse Duration [ps] Future ERLs X-Ray FELs Initial Ultrafast x-ray sources will probe space and time with atomic resolution. Peak brightness of pulsed X-ray sources what do we do today and what tomorrow?

23. 23 R. Neutze, R. Wouts, D. van der Spoerl, E. Weckert, J. Hajdu: Nature 406 (2000) 752-757 t=0 t=50 fsec t=100 fsec Coulomb Explosion von Lyzosym

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25. 25 DAQ Challenge: 2D X-Ray Detector Systems  10 6 pixels per frame for one detector O(400-500) frames per train (goal, likely will start with less) 10 trains per second (machine allows up to 30 Hz…) With 2 Byte/pixel  average rate 10 Gbyte/sec for one 2D detector! Time between frames as short as 200ns  buffering needed 600  s 99.4 ms 100 ms 200 ns LPD

26. 26 Technology Forecast – Storage at DESY YearRate Capability [Gbyte/sec] Storage Space [Petabyte] 200913 2012526 201640 200 not a technology problem money and manpower issues to be determined: user behaviour compression and accept/reject algorithms potentially critical: access to data!

27. 27 GÉANT: connecting Europe  Pan-European coverage (40+ countries /3900 universities / 30+ million students)  Hybrid architecture:  connectivity at 10 Gb/s (aggregated traffic)  dark fiber wavelengths (demanding communities)

28. 28 GÉANT: global reach

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31. 31 The role of the Data Scientist? Extension of Library or Archive Personnel? Where are the data scientists now? The role of current large data users in training Part of a larger problem in how to manage large research infrastructures including virtual 11/09/2015

32. 32 Bernd Panzer-Steindel, CERN Creating conditions similar to the Big Bang The most powerful microscope in the world ‘snapshot of nature’ Particle Accelerator one snapshot == one event == 1.5 MByte 322/17/2010

33. 33 RAW data copies Enhanced copies RAW data Sub-samples Enhanced copies Data and Bookkeeping 10 PB RAW data per year + derived data, extracted physics data sets, filtered data sets, artificial data sets (Monte-Carlo), multiple versions, Multiple copies  20 PB of data at CERN per year  50 PB of data in addition transferred and stored world-wide per year Data copies  safety and access/performance 33Bernd Panzer-Steindel, CERN2/17/2010

34. The Bellagio Declaration Conclusions The group of experts concluded that the following joint activities would provide a strong basis for the development of a common framework that would help demonstrate the overall power of investments in science. Aligning efforts to develop and implement common approaches. Examples could include collaboration in the development of persistent researcher identifiers; extending the accessibility, usability and interoperability of U.S. and European publication and patent databases; development of interoperable and authenticated research datasets as well as common analysis tools; and identification of quantitative and qualitative information concerning the contributions of various actors to science, innovation and economic growth beyond existing and emerging national and transnational data sets.

35. Travel Safely!