Grammars of Collaboration: Designing for e-Science

1. Grammars of Collaboration:Designing for e-Science Mark Hartswood, Roger Slack, Kate Ho, Marina Jirotka, Rob Proctor, Jenny Ure, Alex Voss

2. Vision and Reality • One role of visions is to provide a future orientation for research and practice; they can sometimes, however, be blind to the sorts of practical problems on the ground which impact on its realisation

3. Quantitative and qualitative changes • Scientific work and scientific communication • Situated and virtual • Local and Global • Social and Technical • Everyday interactions on the ground that shape and are shaped by these new ‘virtual organisations’ and in many cases hinder the realisation of the vision • Examples from a number of Grid based projects

4. Examples from eHealth and others • eDiamond • GS: Scottish Family Health Study • MRC NeuroGrid • NTRAC: National Translational Cancer Research Network (Edinburgh Centre)

5. So-called ‘joined-up’ systems envisage services being delivered through virtual organisational structures (VOs) Flexible VOs formed around networks within, and across, multiple service units and administrative domains

6. The Vision of the Virtual Organisation • Across disciplines • Across organisations • Across CoPs • Across complex distributed human and technical networks

7. Translational Medicine Patient Care Clinical Trials Bench Science Drug Development Epidemiology ‘From bench science to clinical practice’

8. Edinburgh NTRAC Centre Integrating clinical, molecular and trial data

9. Vision of Benefits • Shorter start-up periods for studies, cost-effectiveness and earlier realisation of outcomes • Feeding the virtuous circle of translational research • Getting benefits of e-Science projects realised in practice • Technologies that are ‘in working order’: • in line with NHS infrastructure • in line with research infrastructure • usable in clinical and research contexts • Platform for eHealth innovations • Direct benefits for patients through trials and feedback of research results

10. Gap between vision and reality Relating ‘bleeding edge’ research to established, routine, accepted practice requires (among other things)negotiation of obligations, expectations, reciprocities associated with sharing of data and resources in local communities

11. Data Integration : the NeuroGrid Vision-the social life of information • Integration of data collected for very different purposes • Reliability of data collected across multiple sites – or even across the same research lab • Myth of shared protocols!

12. Subject groups, Trial purposes, Trial data Longitudinal studies over several years Different scanners, protocols, clinical/cognitive tests Different data formats Varying methods and regions of interest Algorithms such as Freesurfer, SPM, auto-Gyrification Index Varying clinical diagnoses and demographics Differences across CoPs Disciplines -Psychiatry, Psychology, Computer Science, Neuroscience, Physics, Radiology, Nursing Aims -funding Strategies – competition vs collaboration -Criteria – cost, time, usability

13. Implications for Grid-based VOs ‘One might say that Grid technologies represent a shift from data and resource sharing in collaboration as a craft or cottage industry, to something that can be routinely engineered and expected to behave in a well mannered way’ Implications for making collaborative work visible in virtual organisations

14. Local Grammars The articulation of local community structures is an intrinsic part of the social process in natural communities • Shared understanding • Shared aims and criteria • Shared and visible mechanisms for carrying out, Providing additional technical infrastructure can make performance worse if the social, technical and socio-technical articulation of the complex is not in alignment. Increasingly, system design reflects the need to generate a similar process for larger ensembles that do not have the shared spaces in which to do so.

15. Supporting project collaboration • Developing embryonic community infrastructure as basis for co-creating a socio-technical one. • Shared spaces • Shared frames of reference Nokia Arrabianranta

16. Socio-technical & Socio-political Grammars • Vision of Grid science dependent on socio-political, legal and contractual infrastructures not yet in place (NH Records) • Resulting tensions affect realisation of the translational science vision e.g. tensions between ethical consent and research access to patient records in eHealth

17. e-Science & scientific process Gives rise to new ‘virtual organisations’ (Foster & Kesselman, 2004) More heterogeneous More interdisciplinary More potential for alignment and misalignment (examples) Opportunities for rethinking the nature of scientific work Recurring problem: solution scenarios

18. Aligning the whole and the parts: visualisation Interest in the different ways in which VOs can shape or be shaped by the grammar of collaborative processes in local contexts • Role of mapping these (often invisible) local processes to inform design • Role of designers in making the processes in the VO more visible for the users

19. Visualising systems: allowing users to ‘see’ the implications of action in the system

20. Visualising data architecture for users Building systems around the cognitive process. • WebSOMs • Shneiderman • Bush • Pask • Hitchens

21. Visualising local processes for designers eDiamond Involved ethnographic studies of collaborative process ‘in the wild’ with implications for a virtual infrastructure to extend that

22. The collaborative process in the wild • Computer-aided Detection (CAD) • Use image analysis software to detect potential abnormalities • Draw these to the reader’s attention using a ‘prompt’ • Designed to prevent readers from overlooking a possible abnormality • Has a number of potential roles: • Making screening more sensitive • Supporting single reading • Supporting less experienced reader

23. Decision-aids in mammography • The idea is for prompting systems to act as attention cues • Look at the images and reach own conclusion before looking at the prompts • However, we saw evidence of prompts being used as decision-aids: “I’m not really that worried about it. [At all?]. But as CAD’s marked it now, it’s a case of – do I really take more notice of it? … I’ll mark it. I’m going to mark it down - as possibly being something.” (transcript from video)

24. VOs heighten the need for synergy & alignment to common ends • One size fits all • Global and Local Requirements • Federated Local Requirements

25. Local and Global collaboration • Software designed to standardise safety compliance procedures globally, was actually increasing risk in some local operating sites

26. Aligning heterogeneous and distributed communities of interest

27. Collaboration can add value

28. Or cost and risk • Challenger • Iraq procurement system was deemed a success - technically

29. Tension Interviewer: You’ve mentioned the problem of requirements ‘creep’ late in the design. Can you think of anything that might have helped avoid this? Technical Manager: ‘A cluster bomb perhaps?’

30. Grammars of consent, liability,reward • Grid protocols for acceptable use of resource • Ethical consent for use, reuse, repurposing • New or varied conversations became possible for which these rights, permissions and potential benefits or penalties have not been negotiated and for which a process is required

31. The e-Science bundle of new paradigms, technologies and concepts has challenged the accepted order that is seen to govern how collaborations conventionally unfold in less distributed contexts. • Making the collaborative process more visible to designers and users is part of realising the Grid vision

32. Barriers to Grid Vision Collaboration in designing systems was about criteria and reward within particular communities as much as knowledge transfer Many of the problems were recurrent scenarios found in other Grid projects, and in other distributed socio-technical systems

35. Visions of eScience: the ‘third way’ • Buetow (2005) suggests that the cyber-infrastructure provided by and for e-science can reconfigure our perceptions of what doing scientific research in distributed settings might be • Laurillard • VLE ebusiness experience

36. Users face problems understanding • Provenance of data • Reliability of data • Security of data • Implications of action – who sees the data etc • Dependability of service • Shape of the organisation

37. Transformational Technologies? • Emergent work practices and requirements may only become evident as users attempt to apply the system to their work • Requirements capture and design are currently separated off from the deployment of the system. • Through ‘learning by doing’ and ‘learning by interacting’, users are able to experiment, share and appropriate the innovations of others, mobilising their collective resources to evolve systems, to continue ‘design-in-use Nokia and Arrabianranta

38. Visualising systems: allowing users to ‘see’ the implications of action in the system

39. Future Work • Policies that govern the VO are codified and embedded in the collaborating systems, and interactions between the organisation are audited. • This provides an opportunity to visualise the VO to end users • aim is to explore how existing e-Science infrastructures could be used to meet these usability requirements

41. Recurring Collaborative Strategies in other Systems • Map existing process • co create a new one

42. Building Technology Around Social Processes • Local Scenario • SSM • CATWOE • Amazon • Limewire • eBAY - brokerage

43. Using the Architecture of Social Networks • Brokerage • Closure • Burt • Sense-making • Social Capital

44. Pre-requisites for Collaboration • Shared spaces • Shared frames & terms of reference • Shared aims • The ‘file’‘programme’ analogy

47. Open Social Technical Te Closed