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Prof. Richard O. Sinnott National e-Science Centre University of Glasgow, Scotland

Supporting Security-Oriented Interdisciplinary Research: Crossing the Social, Clinical and Geospatial Domains. Prof. Richard O. Sinnott National e-Science Centre University of Glasgow, Scotland r.sinnott@nesc.gla.ac.uk. The Context. Many Grids EGEE, NGS, D-Grid, Naregi, OSG,…

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Prof. Richard O. Sinnott National e-Science Centre University of Glasgow, Scotland

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  1. Supporting Security-Oriented Interdisciplinary Research: Crossing the Social, Clinical and Geospatial Domains Prof. Richard O. Sinnott National e-Science Centre University of Glasgow, Scotland r.sinnott@nesc.gla.ac.uk

  2. The Context • Many Grids • EGEE, NGS, D-Grid, Naregi, OSG,… • Many definitions and standards • OGSA, OGSI, WSRF, WS-I, WS-ACRONYM-GOES-HERE… • Many solutions • Semantic web/Grid, ... • Web 2.0, wikis, mash-ups, collaboratories, clouds (fluffy/ill defined!)… • Unicore, Globus, gLite, WS-…, OGSA-DAI, … • Tis all a bit (a lot!!!) of a mess… • couple that with the data and knowledge explosion in many (all?) domains, and we have a recipe for chaos • “Grid” to me is solution that supports • (simple) seamless access to a heterogeneous variety of compute and data resources • Often domain specific – especially data! • (simple) single sign-on • support researchers and research, especially inter-, trans- disciplinary research • often at the risk of being non-sexy!

  3. + environmental, social, geographic … Interdisciplinary e-Health Example biologists, bioinformaticians, statisticians, clinicians, pharmacists, epidemiologists, physicists, chemists, ... VOTES Researchers should do their research and not become Grid middleware experts Focus here is Data Grids Solutions have to be multi-disciplinary! Tissues Solutions have to support scientists - not interfere/confuse Cell Organs Protein functions Protein Structures Organisms Physiology Gene expressions Populations Nucleotide structures Cell signalling Nucleotide sequences Protein-protein interaction (pathways) Security-oriented Middleware DAMES SeeGEO

  4. Example of Inter-disciplinary Research • Typical Query • What is the correlation between living adult males over 50 years of age in Scotland who have had type-2 diabetes for 5 years or more and those employed in manual versus office jobs, i.e. does having the type-2 diabetes condition imply that those afflicted are more likely to be employed in manual or office jobs? Where in Scotland is this most prevalent? • Why? • Health inequalities, impacts of policies,… • For example… • Male life expectancy for the whole of Glasgow averages 70.7 years • In East Glasgow, it goes right down to 53.9 years in the Calton ward • UK National Average 77 years, Mongolia 65, Ghana 59, Gambia 54

  5. Data, Data, Data • No magic bullet for data management on the Grid • You can use data if you • a/ know where it is, • b/ are allowed to access it, • c/ know its format, • d/ trust it is authentic, • e/ are sure of its quality, • f/ have the right local widget to talk to the right remote widget • z/… • a/ there are MANY, MANY, MANY resources out there • Tis scary just how big the internet is! (see later) • b/ there are MANY, MANY, MANY ways to define and enforce access policies • Grid sexy security stuff vs real world of NHS, • Range of data stakeholders, • Ethics, • Information governance, • Sys-admin/user perspectives…

  6. Data Grids • There is no single solution • Why? • Things change • Science revolution • Grid technology revolution • General principles/patterns are what we need • How do I set up a Virtual Organisation to do research into X? • Connecting users/software/resources across sites • Seamless access, End-end security, … • How do I connect multiple Virtual Organisations to do research into X, Y and Z? • Clinical VOs vs other VOs

  7. AAAA • Grid Security • AAAA • Users like usernames/passwords • Provide them (once!) • Users don’t like/understand X.509 based PKI • Forget training, education for most users! • $> openssl pkcs12 -in cert.p12 -clcerts -nokeys -out usercert.pem! • The vast majority most certainly won’t jump through hoops to get on the Grid • “me-Science” culture • Should all be transparent to end users and aligned with the way that want to work/access resources • Access Management Federation (Shibboleth) + authZ technologies

  8. AuthZ Identity Provider AuthN Home Institution 4. Home site authenticates user and pushes attributes totheservice provider 3.User selects their home institution 4. Home site authenticates user and pushes attributes totheservice provider 2. Shibboleth redirects userto W.A.Y.F. service LDAP LDAP LDAP LDAP 1. User points browser at Grid resource/portal User points browser at Grid resource/ portal Shibboleth Decentralised Approach ? uid AuthZ Identity Provider Service provider Shib Frontend AuthN ? VOMS, push/pull attribute models, international federations Home Institution 6. Make final AuthZ decision Federation Grid Application ? 5. Pass authentication info and attributestoauthZ function ? W.A.Y.F. User Grid Portal User Log-in once and roam

  9. Inter-disciplinary Data • Data, data everywhere… • Or better yet, services, services everywhere… • Clinical Data • VOTES project • Primary care data, • Secondary care data, • Disease registries, … • Social Science Data • DAMES project • Occupational data • Social classification • Census data (educational, housing, family, ...) • Survey data sets • Ethnicity … • Geospatial data • SeeGEO project • EDINA UK Borders • DigiMap

  10. Others Security-oriented Socio-, Geo-, Clinical Data Infrastructures Or many portals and services that are co-ordinated across federations Licenses, privileges

  11. VOTES • Virtual Organisations for Trials and Epidemiological Studies • 3 year (£2.8M) MRC funded project started October 2005 • Plans to develop framework for producing Grid infrastructures to address key components of clinical trial/observational study • Recruitment of potentially eligible participants • Data collection during the study • Study administration and coordination • Involves Glasgow, Oxford, Leicester/Nottingham, Manchester, Imperial • Strong links with UK Biobank

  12. VOTES Scottish Experiences • Scottish Data Space… up to now • Scottish Care Information (SCI) Store • Hospital batch system rolled out across Scotland (lab data, patient records…) • Scottish Morbidity Records (SMR) • Aggregated clinical records from last 40 years across Scotland • We have been given pseudo-anonymised • SMR01A General acute inpatient and day case discharges (3,719,206 records) • SMR04A Psychiatric and mental handicap hospitals and units: admissions, residents and discharges   (241,599 records) • SMR06A Scottish cancer registrations (171,167 records)           • SMR99A Deaths (173,615 records)            • General Practitioners Administration System for Scotland (GPASS) • Used by 85% of GPs across Scotland • Consent • Opt-in/opt-out trial, study, disease area, … • Applied in range of areas/projects: • UK Biobank, Congenital anomaly, Brain trauma, Diabetes, Knee pain/obesity, Prostate cance.… • Community Health Index (CHI) number key to this!

  13. DAMES • NCeSS Data Management through e-Social Science node • Lead by Stirling • NeSC Glasgow involvement started August 2008 • Occupational data • Social classification • Census data (educational, housing, family, ...) • Survey data sets • Ethnicity • …

  14. DAMES::GEODE

  15. DAMES::GEODE

  16. DAMES::EuroOccupations

  17. DAMES::UK Data Archives

  18. DAMES::CESSDA

  19. DAMES::ONS

  20. SeeGEO::EDINA

  21. SeeGEO Project Changes in UK Borders Census data 1991 and 2001

  22. Demo Walk Through. 1. User attempts to access clinical trials portal

  23. enough records returned?

  24. 2. User redirects browser to geospatial portal

  25. single sign-on

  26. SeeGEO Project

  27. 3. User redirects browser to DAMES portal

  28. still single sign-on

  29. Conclusions • Systems driven by Information Governance/Ethics • MREC, LREC, PAC, PIAG, Caldicott Guardians, Joe Public • Once defined have tools/techniques to rapidly roll-out e-Infrastructures to support researchers • Diabetes? • Cancer? • Obesity? • Smoking? • Health/Wealth? • Genetics and Healthcare? • Nature / Nurture? • Focus not on single VO but supporting many VOs that have their own access/usage policies • Understanding data models are ESSENTIAL to make any of this work!!! I am not sure how we cope with all of the information!

  30. A Final Word

  31. DAMES::SCROL

  32. DAMES::SCROL

  33. DAMES::SCROL

  34. Questions …?

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