SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Cross Cutting Themes Jonathan Grudin John Walsh Deb Agarwal

SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Issues Why people collaborate, build a collaboratory –What happens when people are forced to collaborate long distance (GAN, others) –Readiness Collaboration vs. competition Where are the constraints, stresses, contention Technical history

SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Issues (continued) Evolution of Collaboratories –Going through the types –Garnering best practices Changes as the population grows –Natural size (people and instruments) –Idea size, more participation –“Rich get richer” Value in being flexible –CFAR, UARC, EMSL

SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Issues, continued What is domain specific, what is general What taxonomies/dimensions will be useful What is success –The role of collaboratories in the research value chain –How are collabs changing science Going from research or first adopters to production –How to you insure success the second time. –Sustainability

SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Issues (continued) Tension between –Science policy –Collab technology –Social studies of scientists –Evaluation of scientific efforts Incentives for participation How important is security really

SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Issues (continued) How do we generalize from these instances How do we be prescriptive

SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Theories (cause and effect) Diffusion of Innovation –Trialability (EMSL) –First adopters get burned (UARC) –Who adopts, transmission to new people Cost/benefit as conditions of adoption Lifecycle –Access, collaboration, integration, community Legitimate peripheral participation –Other issues of mentoring, growth of a field

SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Opportunities Track the relationships between collaboratories –UARC-SPARC-others –Chickscope-Bugscope Shared technologies –EMSL-GAN eLog others Why isn’t more collaboration happening among collaboratories Glue to multiple online environments

SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Methodological issues Collect a standard set of things over all collaboratories on internal and external impacts Getting people to respond to evaluation surveys Can we quantify –Data flow –Infor flow –Money

SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Methodological issues Resource Diagram –Capture change over time –Break them up –Create prototypical What should we add to the Get more data on failure Who should the control groups be?

SCHOOL OF INFORMATION UNIVERSITY OF MICHIGAN Other What are the priorities for funding Workshop proceedings (this workshop) –Tools, social science, big science projects, shared facilities