European Grid Initiative The EGI Federated Cloud as Educational and Training Infrastructure for Data Science Tiziana Ferrari/ EGI.eu Technical Director S. Diego, 10 March /28/2016 IG Education and Training, RDA V Plenary1

Problem statement Availability of eLearning tools to support high education and professional training of the data scientist profession Online discoverability and access On-demand access Relying on the EGI publicly-funded federated cloud infrastructure Distribution and management of scientific codes, big data analytic tools etc., open datasets Packaging of these in an integrated environemet Sharing of these between educators and trainers Federation of community effort Library of maintained learning objects supporting the Data Science Body of Knowledge Reuse 6/28/2016 IG Education and Training, RDA V Plenary2

Solution Learning objects library providing access, distribution and management of virtual appliances and software appliances Virtual Appliance => bundle of one or more Virtual Machine Images ready to be used either on a cloud infrastructure (i.e. EGI FedCloud) or even to be downloaded for personal use Software Appliance: a pair of a Virtual Appliance and a contextualization script which can be used for adhoc software installations at the Virtual Appliance during its boot time i.e. a base Virtual Appliance of a Centos6 and a contextualization script that downloads and installs the latest version e.g. of an application, on boot time. EGI Federated IaaS cloud infrastructure – open cloud standards, scaling-up, migration Training marketplace Coupling eLearning platform with access to other educational and training material Federation and Certification 6/28/2016 IG Education and Training, RDA V Plenary3

EGI Federated Cloud 1/3 6/28/2016 IG Education and Training, RDA V Plenary4 Singe sign-on Standards and validation: Recommended and common open standards for the interfaces and images – OCCI, CDMI, OVF, GLUE2, AAI Resource integration: Cloud Computing to be integrated into the existing production infrastructure. Heterogeneous implementation: no mandate on the cloud technology. Provider agnosticism: the only condition to federate resources is to expose the chosen interfaces and services.

EGI Federated Cloud 2/3 6/28/2016 IG Education and Training, RDA V Plenary5 Cloud Compute Cloud Storage IdentifyResearchManage Monitoring Manage apps Reuse appsShare appsAuthn & Authz Accounting Brokers & Portals

EGI Federated Cloud 3/3 6/28/2016 IG Education and Training, RDA V Plenary6 Resources 12 NGIs provide 21 certified resources 5 NGIs currently integrating resources 5 NGIs with interested resource providers Worldwide interest & integration Australia* (NeCTAR) South Africa* (SAGrid) South Korea* (KISTI) United States* (NIST, NSF A.C. Centres) Usage in period -244,913 (397,128) VMs certified (uncertified) -10.6M (12.3M) CPU hours (wall time)

Learning objects library Based on the EGI AppDB tool: appdb.egi.eu/ Based on EGI AppDB: A community driven central service that stores and provides:  software solutions (of any form, native software and/or virtual appliances), originated from almost every scientific area/discipline  reference of scientific datasets (under development)  the programmers and scientists responsible for them  the publications derived from the registered items (SW, VA & datasets) Acts as distribution medium, for:  native software packages (RPMs, DEBs, TARs) exposed through the UMD Community Repository to the public  virtual machine images by using the HEPiX virtualization vmcatcher/vmcaster technology 6/28/2016 IG Education and Training, RDA V Plenary7

EGI AppDB 6/28/2016 IG Education and Training, RDA V Plenary8

Policy context: The Open Science Commons 6/28/2016 IG Education and Training, RDA V Plenary9 Researchers from all disciplines have easy, integrated and open access to the advanced digital services, scientific instruments, data, knowledge and expertise they need to collaborate to achieve excellence in science, research and innovation

Knowledge commons The human networks, understanding and material capturing skills and experience required to carry out open science using data, instrumentation, cyberinfrastructures Objective  Share Open Science Knowledge without barriers and accessible to all user groups including Industry and SMEs 6/28/2016 IG Education and Training, RDA V Plenary10

What do you think about the knowledge commons? Your feedback matters: Policy paper: Feedback: 6/28/2016 IG Education and Training, RDA V Plenary11