ENSURE : E nabling k N owledge S ustainability, U sability and R ecovery for E conomic value

1. ENSURE: Enabling kNowledge Sustainability, Usability and Recovery for Economic value Presenter: Michael Factor factor@il.ibm.com The research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 270000

2. EVALUATECost and Value AUTOMATEPreservation Lifecycle SCALE using ICT innovations PROTECTContent-aware data protection 3 Enabling kNowledge Sustainability, Usability and Recovery for Economic value 4 Healthcare INNOVATIONS USE CASES Clinical Studies Financial Services • A 3-year IP project started Feb 2011 • www.ensure-fp7.eu

3. ENSURE: Key Technical Innovations Evaluate  Automate  Scale  Protect Requirements External Events CloudVirtualappliance Anonymi-zation Evaluate Automate Scale Protect Deploy Cost ValueQuality FlowEventsOntology Access

4. ENSURE: Key Technical Innovations Evaluate  Automate  Scale  Protect Requirements External Events CloudVirtualappliance Anonymi-zation Evaluate Automate Scale Protect Deploy Cost ValueQuality FlowEventsOntology Access

5. Evaluate Cost and Value – Output Evaluate Cost and Value – Input 5

6. ENSURE (Re)Deploy Solution Evaluate Cost and Value – Process Requirements Translation Rules Configurator Administrator Data Repositories Configuration Selection Preservation Plan Optimizer Cost/risk Engine Economic Performance Engine Quality Engine Automate

7. Evaluate cost and value: Preservation Plan Optimizer Quality • Genetic algorithm generates results based upon engines • Really n-dimensions • The user chooses a solution from the Pareto frontier • No dimension can be improved without degrading at least one other dimension QOE COE Cost

8. ENSURE: Key Technical Innovations Evaluate  Automate  Scale  Protect Requirements External Events CloudVirtualappliance Anonymi-zation Evaluate Automate Scale Protect Deploy Cost ValueQuality FlowEventsOntology Access

9. Automate Preservation Lifecycle: Preservation Data Aware Lifecycle Management (PDALM) Workflow Engine PDALM: Controls system activities Manage workflow of the information being preserved Execute preservation plan (built by the Configurator) Handle notifications and interaction with the administrator Example: Workflow for ingest 9

10. Economic Data/format Monitored system behavior PDALM Standards Feeds Regulatory Automate Preservation Lifecycle: Event engine • Event Engine • Manages, concurrency, priority and impact/severity of events • Listens for preservation related events • Notifies relevant ENSURE components EventEngine Configurator Scale

11. Automate preservation lifecycle: ontology update Upload a new version and display potential system impacts Apply new ontology and update system Select ontology to update

12. ENSURE: Key Technical Innovations Evaluate  Automate  Scale  Protect Requirements External Events CloudVirtualappliance Anonymi-zation Evaluate Automate Scale Protect Deploy Cost ValueQuality FlowEventsOntology Access

13. Enterprise A Enterprise Data Center User A User B User C Enterprise B User D User E Enterprise C Private Cloud Community Cloud Services Public Cloud Services Scale: What is a cloud, why is it interesting, and what are the issues? “Cloud computing is a model for enabling convenient, on-demandnetwork access to a shared pool of configurable computing resources … that can be rapidly provisioned and released with minimal management effort or service provider interaction.” • US National Institute of Standards and Technology, Information Technology Laboratory Benefits • Cost Savings • Economies of scale, utilization improvement and standardization • Speed and Agility • Pay-as-you-go for usage Cloud Delivery Models Issues for preservation • Rich metadata support, e.g., no search • Differences in security models • Encryption may limit preservation actions • Compute near the storage (storlets) • Logical connections among objects in the same and different clouds • Standards

14. Map OAIS AIPs and the links among AIPs to the cloud data model Manage object’s inter-relationship and referential integrity Map objects to one or more clouds Scale: Mapping Data to Multiple Clouds Cloud A Cloud B Protect

15. Scale: Accessing Content with a Virtual Appliance (VA) ENSURE Request to access content with VA Instantiate VA Give user access to VA with content Compute Cloud Storage Cloud Extract content Into VA Private Application Library

16. ENSURE: Key Technical Innovations Evaluate  Automate  Scale  Protect Requirements External Events CloudVirtualappliance Anonymi-zation Evaluate Automate Scale Protect Deploy Cost ValueQuality FlowEventsOntology Access

17. Content-aware data protection: Masked/Anonymized Data Data Owner Requirement: Data should be anonymized and cannot be associated with a specific individual Example: Living people from London who fought in WWII is becoming more and more identifiable Data Owners Masking Services Data Receivers Masked data Full data hospital Medical Research Pharma Research factory Telco Software testing bank Statistical Analysis

18. Summary • Architect and build the next generation preservation system, ensuring knowledge is sustained and can be recovered for future value • Key Innovations: • Evaluate Cost and Value supporting business decisions • Automate Preservation Lifecycle • Scale using ICT innovations • Content-aware data protection • Three use cases to demonstrate future preservation • Healthcare, clinical trials, and finance use • Status • Initial end to end demo of two use cases in the first year • Emphasis on evolution along time for the second year www.ensure-fp7.eu

19. Thank You

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