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Re-thinking Distributed Work in Distributed Research Centers Gloria Mark University of California, Irvine Discussant, AfCS collaboratory.

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Presentation on theme: "Re-thinking Distributed Work in Distributed Research Centers Gloria Mark University of California, Irvine Discussant, AfCS collaboratory."— Presentation transcript:

1 Re-thinking Distributed Work in Distributed Research Centers Gloria Mark University of California, Irvine Discussant, AfCS collaboratory

2 Distributed teams (results and issues) Distributed Research Centers Collaborative structure Different configurations possible: individual nodes small groups group-individual collaborations Generally larger scale: more nodes, more people per node More often group-to- group collaboration; introduces Different type of dynamics Can “team” technologies scale up?

3 Distributed teams (results and issues) Distributed Research Centers Information filters Information filters (I.e. team leaders, facilitators) at each site primarily govern information flow What role do information filters (I.e. lab directors?) have on information and data sharing

4 Distributed teams (results and issues) Distributed Research Centers Technology adoption All in team must adopt to effectively participate Unique barriers to adoption in distributed orgs: Different org.policies Different technology standards Rich and poor sites: hw and infrastructure Adoption more complex Can subgroups adopt and effectively collaborate? (Depends on interdependencies) What barriers exist? Org policies, standards, etc.

5 Distributed teams (results and issues) Distributed Research Centers Working spheres People are members of multiple working spheres (teams); wear multiple hats How does collaboratory work relate to, and is affected by member’s other working spheres? How can people maintain a topic thread while switching spheres

6 Distributed teams (results and issues) Distributed Research Centers Technology choice Collaboration can range from mostly/all synchronous to mostly/all asynchronous Most (?) teams use combination of technologies Lack of integration of technologies AfSC, Intermed, NEESgrid: Combination of synchr/asynchr technologies Lack of integration of technologies How to achieve uniform use/perspective on technology purpose and activity?

7 Distributed teams (results and issues) Distributed Research Centers Awareness: of others’ task activities others’ expertise when people are reachable Technologies tend to be compartmentalized What kind of awareness information is needed? How can technology support this?

8 Distributed teams (results and issues) Distributed Research Centers Transformation of technology and work practice Emerging work practices occur, esp when technology is introduced from one team to another (some technologies more malleable than others for multiple kinds of uses ) What is the process by which emerging work practices with technology occurs? How is technology transformed? How are emerging work practices diffused throughout collaboratory community?

9 Distributed teams (results and issues) Distributed Research Centers Standardizing protocols/ methodologies Need to achieve standardized methods of collaboration and scientific methodologies when collaborating, e.g. different algorithms used by teams AfSC: standardized protocols? Must common methodology be achieved? Harder to achieve with different teams. Results are visible, but methodologies are invisible across distance

10 Distributed teams (results and issues) Distributed Research Centers Sharing and reuse of rationale and information In design collaboration, subgroups formed; results (esp. rationale) not shared to rest of group To what extent is rationale shared (and not just data)?

11 Distributed teams (results and issues) Distributed Research Centers Public and private data Team requirement: electronic workspace must store private as well as public information, common agreement when information becomes public IP policy of AfCS What kind of model for public/private data? (e..g. NEESgrid: individuals free to provide data) When to provide data?? Data-checking can be incorporated into collaboratory work Implications for motivation to collaborate


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