1. The Global Scene Wouter Los University of Amsterdam The Netherlands

3. Courtesy: psfk.com

4. Data sustainability Data quality Orphan data The data desert

5. A cottage industry in the desert Data generator User Data generator User Data storage Data storage Data generator User Data generator User Data generators User Data generators User Data generators User Data generators User Data storage Data storage Data storage Data storage Data storage Data storage Tool Interdisciplinary challenges Data infrastructure Support services

7. A collaborative Data Infrastructure Data Generators Data Generators Users Community Support Services Persistant storage, identification, authencity, workflow execution Data discovery & navigation, workflow generation, annotation, interpretability User functionalities, data capture and transfer, virtual research environments Trust & Curation

9. Vision 2030 high-level experts group on Scientific Data “Our vision is a scientific e-Infrastructure that supports seamless access, use, re- use and trust of data. In a sense, the physical and technical infrastructure becomes invisible and the data themselves become the infrastructure – a valuable asset, on which science, technology, the economy and society can advance.” High-Level Group on Scientific Data “Riding the Wave: how Europe can gain from the raising tide of scientific data”

10. US Report of the Blue Ribbon Task Force on Sustainable Digital Preservation and Access

11. Global collaboratories With a proper scientific e-Infrastructure, researchers in different domains can collaborate on the same data set, finding new insights. They can share the data across the globe, protecting its integrity and checking its provenance. They can use, re-use and combine data, increasing productivity. They can engage in whole new forms of scientific inquiry and treat information at a scale we are only beginning to see. … and help us solving today’s Grand Challenges such as climate change and energy supply.

12. The laboratory of environmental research infrastructures Deep Earth, land and sea, the atmosphere Living and dead environments

13. Distributed measurements and monitoring observatories, sensors, radars, human eyes... physical, chemical and biological parameters Laboratories and experimental facilities in fixed monitoring stations on research vehicles, ships, floats and buoys from aircraft and satellites A variety of data complex and sometimes fuzzy heterogeneous and distributed primary and processed data Analytical and modelling platforms data exchange and integration high performance computing and Grid services e-Laboratories

14. ESFRI Projects for Env. Sciences LIFEWATCH EMSO IAGOS-ERI AURORA BOREALIS EUFAR-COPAL ICOS EURO-ARGO EPOS EISCAT-3D SIOS Status 2009

15. ENVRI Common operations of Environmental Research Infrastructures

16. Facilitating interoperability of data and methods Experiments – Controlled parameters Long-term monitoring – 20+ years for a many parameters – In different systems Modelling – Covering environmental complexity Simulations – Understanding parameter changes – Scenarios

17. Data from various origins in different spatial and temporal scales

18. Example: Oceans and CO2 sequestration The role of fytoplankton

20. Andrew D. Barton et al, Patterns of Diversity in Marine Phytoplankton, Science online 25 Feb 2010 A single vizualized result. But we would like to see thousands of these.

21. A community driven cyber infrastructure User create their own collaborative virtual laboratories or services, sharing data and models with others, while controlling access. Composition allows for making preferred work flows or clouds. E-Infrastructure integrates resources and provides grid computing power. Resources: data and software Research Infrastructure for Biodiversity and Ecosystem Research

22. Requirements to study complexity in collaborative projects – Access to interoperable data and workflows – Capabilities to (re) use workflows: support to manage a (analytical and modelling) toolbox for different research communities – Options for fast computation of the effect of changes in parameter data – Virtual collaborative environments, allowing scientists to do experiments in silica – Visualisation of (intermediate) results with 4D resolution – Export to publications

23. Thank you for your attention w.los@uva.nl