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E-Infrastructure Use Cases and Service Usage Models (eIUS) Project Michael Fraser, Mercedes Arguello Casteleiro, Gabriel Hanganu Community Engagement Steering.

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Presentation on theme: "E-Infrastructure Use Cases and Service Usage Models (eIUS) Project Michael Fraser, Mercedes Arguello Casteleiro, Gabriel Hanganu Community Engagement Steering."— Presentation transcript:

1 e-Infrastructure Use Cases and Service Usage Models (eIUS) Project Michael Fraser, Mercedes Arguello Casteleiro, Gabriel Hanganu Community Engagement Steering Group 14 October 2008, London

2 Slide: 2 eIUS Progress Report,Community Engagement Steering Group, 17 April, London. Last 6 months –WP 1 Project Management recruitment –WP 3-4,7 Experience reports/Use cases 8 onsite interviews conducted and analysed; 5-6 uses cases drafted –WP 5 SUMs Refined methodology; generated 2-3 SUMs; engaged with e- Framework individuals –WP 6,9 Community Engagement/Dissemination In collaboration with Engage and e-Uptake; Presentations at e- Social Science 2008; JISC Innovation Forum; AHM 2008; eResearch08 –WP 8 Interactive website Publishing material via Engage portal; planning for primary portal

3 Slide: 3 eIUS Progress Report,Community Engagement Steering Group, 17 April, London. Project management –Staffing Sue Fenley, Project Manager (0.2FTE, from May 08)‏ Gabriel Hanganu, Senior Analyst (0.5 FTE, from Jun 08)‏ Mercedes Arguello Casteleiro (1 FTE)‏ Seeking up to 1 FTE addition 'casual' (from Nov 08)‏

4 Slide: 4 eIUS Progress Report,Community Engagement Steering Group, 17 April, London. Experience reports –Interviews in this period (14 interviewed in 8 activities)‏ 5VERA (AHRC)‏ 2 Humanities computing (AHRC)‏ 1Taverna (BBSRC)‏ 1Condor (disease control) (BBSRC)‏ 1Comb-e-Chem (EPSRC)‏ 1Condor (quantum chemistry) (EPSRC)‏ 1 + 1ESDS International (ESRC)‏ 1eMinerals (NERC)‏ –Agreed but not yet scheduled Via Landmap Via NaCTeM –In planning consenting e-Uptake/Engage interviewees of interest

5 Slide: 5 eIUS Progress Report,Community Engagement Steering Group, 17 April, London. Use Cases Drafts –Archaeology (VERA)‏ –Bioinformatics (Taverna)‏ –Physics (eMinerals (compute))‏ –Physics (eMinerals (data))‏ –Chemistry (Comb-e-Chem)‏

6 Slide: 6 eIUS Progress Report,Community Engagement Steering Group, 17 April, London. SUMs Draft SUMS –Grid Enabled Microeconomic Data Analysis (GEMEDA)‏ –Modelling and Simulation for e-Social Science (MoSeS) –Grid Enabling MIMAS Services (GEMS): a grid enabled Census data querying service Developing Service Genres Meetings with e-Framework representatives

7 Slide: 7 eIUS Progress Report,Community Engagement Steering Group, 17 April, London. Dissemination Towards a collective knowledge base: sharing the expertise acquired on developing grid-based e-science and e-social science applications. Oxford e-Research Conference, Oxford, Sept 2008 Highlighting e-Infrastructure patterns in Grid-based e-Social Science applications. AHM 2008, Edinburgh, Sept 2008 A case study about how e-Infrastructure is used within the Social Sciences. 4th International Conference on e-Social Science, Manchester, June 2008 eIUS: e-Infrastructure Use Cases and Service Usage Models, JISC Innovation Forum, July 2008 Publication of materials via with further portal planninghttp://engage.ac.uk/eIUS

8 Slide: 8 eIUS Progress Report,Community Engagement Steering Group, 17 April, London. eIUS Videos 'Additional resources' project in collaboration with Engage Create ~10 three minute videos –Derived from, and support, use cases –Consider as 'trailers for research' – to encourage further engagement Work will be out-sourced –Use cases selected on basis of consent, visual appeal, cross-section of subjects First videos published by Feb 2009

9 Slide: 9 eIUS Progress Report,Community Engagement Steering Group, 17 April, London. Interviews and Use Cases Gabriel Hanganu

10 Slide: 10 eIUS Progress Report,Community Engagement Steering Group, 17 April, London. Outline Use case production process –Interviewing –Experience report –Draft use case –Feedback –Dissemination What we learn –Overall (rather than just research) benefits –Personalisation and co-ownership

11 Slide: 11 eIUS Progress Report,Community Engagement Steering Group, 17 April, London. Process - interviews Interviewing –Selection of interviewees –Locations –Structure –Style

12 Slide: 12 eIUS Progress Report,Community Engagement Steering Group, 17 April, London. Process - experience reports Experience report –Read transcript + listen to audio –Read related interviews if available (eUptake, Engage)‏ –Select relevant interview data –Organise them according to research cycle –Allow tangents & misc

13 Slide: 13 eIUS Progress Report,Community Engagement Steering Group, 17 April, London. Process - draft use cases Analysis and distillation –Identify characters –Sketch narrative –Flesh out, select key quotes –Check logical & temporal coherence

14 Slide: 14 eIUS Progress Report,Community Engagement Steering Group, 17 April, London. Process - feedback Feedback –Circulate draft use cases to interviewees –Elicit feedback –Edit draft use case –Check overall coherence –Create feedback report

15 Slide: 15 eIUS Progress Report,Community Engagement Steering Group, 17 April, London. Process - dissemination Dissemination –Project report –Standalone narratives in CE portal –Links to experience reports –Video use cases

16 Slide: 16 eIUS Progress Report,Community Engagement Steering Group, 17 April, London. What we learn – overall benefits Researchers adopt e-infrastructure tools if these provide overall, rather than just research, benefits These benefits overcome the effort of appropriating the tools

17 Slide: 17 eIUS Progress Report,Community Engagement Steering Group, 17 April, London. What we learn - co-ownership Personalisation and sense of co-ownership are key for the successful adoption of e-infrastructure tools

18 Slide: 18 eIUS Progress Report,Community Engagement Steering Group, 17 April, London. Engaging with the e-Framework Service Usage Models Mercedes Arguello Casteleiro,

19 e-Framework e-Framework Knowledge Base Framework Knowledge Base Phil Nicholls

20 Grid Enabled Microeconometric Data AnalysisGEMEDA Grid-based e-Social Science application

21 GEMEDA (Grid Enabled Micro-econometric Data Analysis) a Grid based demonstrator Yuette activates her GEMEDA logon (single sign-on)‏ Yuette monitors the progress of Grid operations Yuette has an e-certificate and is a registered user of GEMEDA that supports empirical economic modelling using secondary information Yuette is an econometrician that has an e-certificate. She wants to determine the UK ethnic minority welfare which requires cross-analysis of multiple datasets (statistical data fusion)‏ Yuette visualises the results within the Web browser Yuette initiates the modelling process by choosing appropriate parameters (e.g. ethnic category, geographic location, etc)‏ Based on Yuette instructions, the Grid extracts the required data, and uses it to perform the econometric computations When Grid operations are completed the results are returned for visualisation

22 GEMEDA business process ♣ Single sign-on ♣ Authentication and authorisation ♣ Set-up and launch a job ♣ Job execution ♣ Job monitoring ♣ Access jobs ♣ Analysing the results

23 GEMEDA (Grid Enabled Micro-econometric Data Analysis) a Grid based demonstrator Authentication and Authorisation Set a Job Launch job Job execution and Job monitoring (Result presentation or Visualisation)‏ Set-up Analysing the results

24 GEMEDA e-Framework SUM

25 Modelling and Simulation for e-Social SciencesMoSeS Grid-based e-Social Science application

26 MoSeS e-Framework SUM

27 Grid Enabling MIMAS Services projectGEMS-I Grid-based e-Social Science application

28 GEMS-I e-Framework SUM

29 Concluding remarks Highlighting e-Infrastructure patterns found in Grid-based e-Social Science applications


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