Understanding Collaboration Using Social Network Analysis

Diana RhotenOffice of CyberinfrastructureNational Science Foundation

Inte

grat

ion

[col

labo

ratio

n]

Diversity [Interdisciplinarity]

HIGH

LOW

Breakthroughs

From isolation to collaboration

Source: Hollingsworth (2001). Research Organizations and Major Discoveries in Twentieth Century Science: A Case Study of Excellence in Biomedical Research. Research Paper 02–003. Berlin: Wissenschaftszentrum Berlin für Sozialforschung.

Rudi

Ike

Saul

Ed

Jun

Axel

• Model the structure of research networks in different “interdisciplinary” research centers

• Assess the effect of individual, organizational, and relational factors on the structure of these research networks

• Analyze the dynamics and outcomes of the network’s interdisciplinary collaboration

Interdisciplinary research center study

Degree of Interdisciplinarity Across all research centers and labs, the networks tend to be more multidisciplinary than interdisciplinary and to demonstrate pockets of disciplinary collaborations connected by fewer cross-disciplinary ties

A few key findings

Network MeasuresNetwork MeasuresDensity = 8%Density = 8%

Cohesion = 2.6Cohesion = 2.6Ave. Centrality = 5Ave. Centrality = 5

= Hydro Engineering= Hydro Engineering

DisciplineDiscipline

= Civil/Enviro Engineering= Civil/Enviro Engineering= Mechanical Engineering= Mechanical Engineering

= Ecology= Ecology

= Chemical Engineering= Chemical Engineering

= Applied Mathematics= Applied Mathematics

= Industrial Engineering= Industrial Engineering

= Eng Public Policy= Eng Public Policy= Sustain/ Resource Mgt= Sustain/ Resource Mgt

= Applied Anthropology= Applied Anthropology= History of Science= History of Science= Decision Science= Decision Science

= Applied Physics= Applied Physics

= Epidemiology= Epidemiology

= Land Use Geography= Land Use Geography

= Env Soc Sci Policy= Env Soc Sci Policy= Resource Economics= Resource Economics

= Behavioral Economics= Behavioral Economics

= Risk Analysis/Assess= Risk Analysis/Assess

Multi- more than Inter- disciplinary

Center 2 demonstrates “disciplinary pocket” pattern found in most centers, particularly at level of knowledge producing

Shows all CLOSE connections by DISCIPLINE/FIELD based on responses to the following survey item:

“Please indicate the strength of your relationship with other center affiliates.”

= Physical Sciences= Physical Sciences

Science FieldScience Field

= Life Sciences= Life Sciences= Social Sciences= Social Sciences

= Environmental Sci Eng= Environmental Sci Eng

= Engineering= Engineering

= Comp & Math Sciences= Comp & Math Sciences

= Environmental Soc Sci= Environmental Soc Sci= Arts & Humanities= Arts & Humanities

Network MeasuresNetwork MeasuresDensity = 10%Density = 10%Cohesion = 2.6Cohesion = 2.6

Ave. Centrality = 6Ave. Centrality = 6

Shows all CLOSE connections by SCIENCE based on responses to the following survey item:

“Please indicate the strength of your relationship with other center affiliates.”

Center 3 demonstrates the even more dramatic pattern of segregation of researchers by fields of science

Multi- more than Inter- disciplinary

Degree of CollaborationAcross all centers, researchers average approximately 8 information sharing vs. 6 knowledge producing collaborations, and 5 interdisciplinary information sharing vs. 3 interdisciplinary knowledge producing collaborations

Degree of Interdisciplinarity Across all research centers and labs, the networks tend to be more

multidisciplinary than interdisciplinary and to demonstrate pockets of disciplinary collaborations connected by fewer cross-disciplinary ties

A few key findings

Network MeasuresNetwork MeasuresDensity = 47%Density = 47%Cohesion = 1.6Cohesion = 1.6

Ave. Centrality = 8Ave. Centrality = 8

= Physical Sciences= Physical Sciences

ScienceScience

= Life Sciences= Life Sciences= Social Sciences= Social Sciences

= Environmental Sci Eng= Environmental Sci Eng

= Engineering= Engineering

= Comp & Math Sciences= Comp & Math Sciences

= Environmental Soc Sci= Environmental Soc Sci= Arts & Humanities= Arts & Humanities

Interdisciplinary information sharing and knowledge production

Shows all CLOSE and COLLEGIAL INTERDISCIPLINARY connections by SCIENCE based on responses to the following survey item:

“Please indicate the strength of your relationship with other center affiliates.”

Center 1 networks illustrate the role of information sharing collaborations …

Network MeasuresNetwork MeasuresDensity = 16%Density = 16%Cohesion = 2.3Cohesion = 2.3

Ave. Centrality = 3Ave. Centrality = 3

= Physical Sciences= Physical Sciences

ScienceScience

= Life Sciences= Life Sciences= Social Sciences= Social Sciences

= Environmental Sci Eng= Environmental Sci Eng

= Engineering= Engineering

= Comp & Math Sciences= Comp & Math Sciences

= Environmental Soc Sci= Environmental Soc Sci= Arts & Humanities= Arts & Humanities

… in the density of the interdisciplinary research networks in most centers

Shows all CLOSE INTERDISCIPLINARY connections by SCIENCE based on responses to the following survey item:

“Please indicate the strength of your relationship with other center affiliates.”

Interdisciplinary knowledge production

Organizational form and spatial distribution

Frequency and mode of interaction

Foci of collaboration

Personalities and positions

Variation in Interdisciplinarity and Collaboration

Intraorganizational – concentrated

Interorganizational – distributed (F2F)

Transorganizational – distributed (F2F, V)

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20

Density

A mean density score of 50% compared to an approx. mean of 35% for other organizational types

1 SD above Mean

Mean

1 SD below Mean

Density metrics across all groups (close and collegial)

Distance can enhance integration …

TimeSame

(synchronous)Different

(asynchronous)G

eogr

aphi

c Pl

ace

Sam

eD

iffer

ent

75.75% 65.50%

58.75% 56.50%

… but collaboration still depends on F2F

Foci of collaborationCollaboration practices and products benefit from a unifying vision, a common problem, a shared tool (methodological, technological) – “boundary object” – that could ground and guide the work

Personalities and positionsProductive interdisciplinary collaborations require the “right”

scientific and technical expertise as well as the “right” social and management skills to serve the project and evolve the process.

A few key findings

Network “Hubs”But it is not just about the leaders. While center or lab directors tend to be network “hubs”, research assistants are among the most central researchers in the networks -- particularly at the level of knowledge production

A few key findings

= Associate Professor= Associate Professor

PositionPosition

= Assistant Professor= Assistant Professor= Post Doc= Post Doc

= Non-Tenure Researcher= Non-Tenure Researcher

= Professor= Professor

= Graduate Research Asst= Graduate Research Asst

= Center Director= Center Director

Network MeasuresNetwork MeasuresDensity = 39%Density = 39%Cohesion = 1.6Cohesion = 1.6

Ave. Centrality = 15Ave. Centrality = 15

Shows all CLOSE and COLLEGIAL connections by POSITIONbased on responses to the following survey item:

“Please indicate the strength of your relationship with other center affiliates.”

Center 4 demonstrates the common network pattern in which “hub” positions are occupied by center or lab directors and the central “core” is

dominated by research assistants

Network “hubs”

Network “Bridges” Research assistants and non-tenure track scientists also tend to serve as the interdisciplinary “bridges” in the center networks. They often come from “hybrid” disciplines, have higher rates of previous interdisciplinary exposure, and/or are methodologists/ technicians versus content experts

Network “Hubs” But it is not just about the leaders. While center or lab directors tend to be network “hubs”, research assistants are among the most central researchers in the network -- particularly at the level of knowledge production

A few key findings

Network MeasuresDensity = 5%

Cohesion = 3.4Ave. Centrality = 3

= Physical Sciences

Scientific Field

= Life Sciences= Social Sciences

= Environ Sci/Eng Pol

= Engineering

= Arts & Humanities

s

Shows all CLOSE INTERDISCIPLINARY ties by SCIENTIFIC FIELDbased on responses to the following survey item:

“Please indicate the strength of your relationship with other center affiliates.”

= Environmental Soc Sci

= Comp & Math Sciences

Again, using center 4, it demonstrates the common network pattern in which “bridges” tend to be students more than faculty …

Network “bridges”

Network MeasuresDensity = 5%

Cohesion = 3.4Ave. Centrality = 3

= Physical Sciences

Scientific Field

= Life Sciences= Social Sciences

= Environ Sci/Eng Pol

= Engineering

= Arts & Humanities

s

Shows all CLOSE INTERDISCIPLINARY ties by SCIENTIFIC FIELDbased on responses to the following survey item:

“Please indicate the strength of your relationship with other center affiliates.”

= Environmental Soc Sci

= Comp & Math Sciences

Removing them demonstrates their importance to the overall connectivity of an interdisciplinary research network

Network “bridges”

59% of respondents report collaboration “has enabled individual’s research in new ways”

62% report that it “has advanced individual’s thinking”

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20

40

60

80

Publications andPresentations

Tools andInstrumentation

Projects andExperiments

Project Planningand Proposals

Collaborationenabled

individual'sresearch in new

w ays

Collaboration hasadvanced

individual's thinking

Perc

enta

geProduction & innovation

Source: Rhoten and Parker (2006). Study commissioned by National Center for Atmospheric Research.

Inte

grat

ion

[Col

labo

ratio

n]

Diversity [Interdisciplinarity]

HIGH

LOW

Breakthroughs

Leveraging interdisciplinary collaboration

Source: Hollingsworth (2001). Research Organizations and Major Discoveries in Twentieth Century Science: A Case Study of Excellence in Biomedical Research. Research Paper 02–003. Berlin: Wissenschaftszentrum Berlin für Sozialforschung.

Engineered, concentrated, roster-driven, single generational

Organic, distributed, problem-based, multi-generational

Office of Cyberinfrastructure(est. July 2005)

Virtual Organizations

Virtual organizations offer a community of practice the opportunity to work together - sharing expertise, tools, information and facilities.

Instances of Virtual Organizations (VOs)

ComputationData,

information management

Sensing, observation,

activation in the world

Distributed, heterogeneous services for:

Mechanisms for flexible secure, coordinated resource/services sharing among dynamic collections of

individuals, institutions, and resources (the Grid or service layer problem)

Interfaces for interaction, workflow, visualization and collaboration for individuals & distributed teams

People* People* People*

Alternate Names for VOs:• Co-laboratory• Collaboratory• Grid (community)• Network• Portal• Gateway• Hub• Virtual Research Environment * People engaged in discovery and learning as individuals and in teams

Virtual Organizations