Collaborative Research@CWN: Who do Scientists Network with?
NETWORK MAPPING STUDY
Prepared for the Canadian Water Network
Dimitrina Dimitrova, University of Toronto
Emmanuel Koku, Drexel University
Barry Wellman, University of Toronto
Howard White, Drexel University
Date: June 2007
We are indebted to numerous people for their support and assistance in conducting the
study and preparing this report.
Lee Weisser has been an invaluable member of the team. She has seen the project
through from start to finish, assisting it in numerous ways. She worked as project
administrator, interviewer, and editor, and in all of these capacities she excelled. Jeremy
Birnholtz contributed incisive comments and ideas to the research design and the
preliminary report of the study. He also conducted a number of the interviews, bringing
his competence and experience to the process. June Pollard transcribed even the most
difficult interviews with accuracy and speed. Kristen Mandziuk and Dolores Figueroa
coded them expertly in NVivo. Kristen, in addition, spent many hours helping in the
orderly wrap up of the project, sorting, verifying and cleaning records. A group of smart
students assisted with numerous tasks: they transcribed interviews, entered data, searched
the Internet, and hunted down articles and books. Glasha Romanovska, Lindsay Cai,
Jackie D’Sa, Natalie Zinko, and Nazila Rostami were all a pleasure to work with.
Few research projects receive as much support and assistance from their funding
organization as this one has. We have benefited tremendously from the visionary ideas
and sage advice of Don Brookes, the professionalism and engaging personality of Monica
Escamilla, and the technical skills and hard work of Corban Riley. Other CWN staff
including David Cotter, Bernadette Conant, and Karen Van Sickle, have also lent a hand
Finally, this project was only possible because busy people working in the area of water
generously shared their time and their insights with us. Working with them has been a
privilege and a delight.
Our sincere thanks to all!
TABLE OF CONTENTS
Executive summary...................................................................................................... i
Part I. Respondents ......................................................................................................... 3
1.1. Demographics: Who are the respondents?........................................................... 3
1.2. Personal networks: To whom are the respondents connected?............................ 4
1.3. Ties: Another look at the water community ........................................................ 6
Part II: Connections in the Water Network..................................................................... 9
2.1. Centrality Analysis............................................................................................... 9
2.2. Clique Analysis.................................................................................................. 13
2.3. Citation analysis................................................................................................. 21
Part III. The context of collaborative work................................................................... 27
3.1. Barriers and incentives for collaborative work.................................................. 27
3.2. Challenges on a project and strategies for overcoming them ............................ 29
3.3. Strategies for coping: team selection and independent work............................. 32
3.4. Impact of CWN on the work of academics and practitioners............................ 36
Part IV. Conclusions ..................................................................................................... 41
Appendix 1: Tables ...............................................................................................................
Appendix 2: Figures..............................................................................................................
Appendix 3: Survey Data Collection and Available Data ....................................................
Appendix 4: Document and Interview Data .........................................................................
Appendix 1: Tables
Appendix 2: Figures
Appendix 3: Survey Data collection and Available Data
Appendix 4: Document and Interview Data
The Network Mapping project is a social network study of the academics and
practitioners working in the area of water commissioned by the Canadian Water Network
of Centres of Excellence (CWN). The objectives of the study were to map the relations
among the stakeholders in the area of water, describe the collaboration and knowledge
exchanges among them, and examine the context in which they worked.
The study included four components: a web based network survey (N=173), semi-
structured interviews (N=65), citation analysis of a small subgroup of academics central
in the CWN (N=31), and review of documents. Several key findings emerged in the
analysis of these complementary bodies of data.
Socio-demographic characteristics and personal networks
The survey respondents have two salient characteristics: diversity and maturity.
• Water issues are very broad, not easily captured within a discipline, and jurisdiction
over water is fragmented among numerous government agencies. Hence, participants
in the water network come from a range of sectors and disciplines and have different
involvement in water issues. Engineers and natural scientists such as biology and
earth/environmental sciences are most numerous while health, social and policy
scientists are fewer. Such disciplinary and sectoral diversity provides the prerequisites
for the cross-sectoral and multi-disciplinary research needed in the area.
• At the same time, developing cross-sectoral and multidisciplinary ties strong enough
to sustain collaboration is difficult. This precludes dense connections in the water
network and makes water issues the playing field of experienced academics and
practitioners, who have developed diverse networks. The majority of the people
working in the area are mature professionals with well established networks, many of
them in senior positions. In addition, despite some changes, universities tend to
reward traditional work within a single discipline. This discourages junior academics
building careers from doing complex collaborative research and further reinforces the
maturity and seniority of the participants in the area.
Water community (whole network)
Briefly put, the water network is sparsely connected yet well structured and capable of
supporting multidisciplinary and cross-sectoral collaboration.
• The network has a small core of well connected central participants and a large
periphery of sparsely connected participants less involved in water issues. About
three quarters of these central participants are CWN members. This suggests that the
agency either attracts central participants to the water network or helps its members to
develop their networks and become central. Among these central participants, those
who actively network and reach out to others are junior academics, a few senior
academics, and practitioners from various sectors. By comparison, other central
participants play the role of experts who attract others. These are mostly senior
academics all of whom are involved in the work of CWN.
• About two dozen participants actively work and exchange ideas with others, typically
in small cliques of two to three colleagues. Some of them collaborate with colleagues
from several cliques and act as bridges that connect the cliques and preclude the
fragmentation of the network. Notably, people in bridge positions are academics in
mid career who have already developed their networks to some extent but are still
actively networking. Three quarters of the active collaborators are CWN members,
confirming the key role of the agency in fostering collaboration in the area of water.
• The composition of the cliques suggests that collaboration in the network is
multidisciplinary and often cross-sectoral. Most of the work cliques include members
from biology and earth/environmental sciences while the health, policy and social
sciences are less represented.
• The small size of the cliques arises from the independent work practices on the
research projects. Since collaboration across disciplines, sectors, and organizations is
difficult, one of the strategies to avoid problems and decrease efforts for coordination
is for researchers to work independently or in small groups. Only in a very few cases
do project participants work as integrated teams.
• A second strategy to facilitate coordination and communication is for project leads to
put together teams of people they know. While project teams include some
newcomers recommended by other team members, researchers tend to work with a
few long-term collaborators. Such teams of long-term collaborators increase
commitment and decrease the efforts for developing common practices and trust —
trust, commitment, and common practices have already been developed. Pre-existing
ties thus facilitated the formation of teams and the work on a project.
• Despite many multidisciplinary connections, the citation practices more closely
follow disciplinary boundaries. Scientists in the water network are perceived as
working in the same area and cited together. Often they are cited together with
colleagues from different disciplines. This suggests that their work has
multidisciplinary relevance. However, scientists in the water network do not readily
see the relevance of their colleagues’ publications for their own work, rarely cite each
other directly, and such direct citations more closely follow disciplinary boundaries.
Such citation practices are consistent with the publication criteria of most scholarly
journals which encourage working within a single discipline.
CWN impact on the work of academics and practitioners
• The main impact of CWN on the work of academics is networking with the right
people. Academics interested in multidisciplinary and cross-sectoral research might
be hard to find in a more traditional university environment and CWN helps such
academics connect to each other and find partners.
• In turn, practitioners emphasized — in addition to networking — the role of the CWN
as a focus of expertise in the area and as a link to academics. Even outsiders without
formal partnerships with CWN turn to it when they need information.
In short, the results of the study show that CWN is successfully achieving its mission: to
provide expert knowledge on critical water issues in Canada, to build scientific and
human resources to address them, and to create a network of stakeholders in the area of
water that serves as a catalyst for research and technology development. CWN plays a
key role in holding the water network together and fostering cross-sectoral
multidisciplinary collaboration: the majority of central participants and active
collaborators in the area of water are CWN members. In turn, the presence of outsiders,
who reach out to CWN members or already collaborate with them, suggests possibilities
for creating new partnerships. Although the overall water network is sparsely knit and the
core of well connected active participants is small, the ties are structured and the network
is capable of supporting multidisciplinary cross-sectoral collaboration. The water network
can be further improved by expanding the core, maintaining healthy balance between
junior and senior academics, increasing the number of bridges, and improving the
representation of health, social and policy sciences. Nonetheless, in the diverse and
inherently fragmented area of water, CWN has created a viable network, established its
reputation, and became a “brand name” in the area.
The Canadian Water Network (CWN) was created with the mandate to support
multidisciplinary research, cross-sectoral partnerships that link academics, government
and industry staff, and cross-country collaboration in the area of water. CWN supports
knowledge transfer and innovation by connecting researchers and practitioners across the
country. Crucial to its work is a comprehensive understanding of the existing
relationships among people working in the area of water that can facilitate the
management and planning of CWN activities in support of the water community.
In the fall of 2005, CWN hired a team of researchers to conduct a social network study of
the scholars, industry partners, public sector users and regulators whose work is directly
related to water. The goal of the study was to map the existing relationships among them,
describe the processes of collaboration and the exchange of advice and innovative ideas,
and delineate key individuals and research clusters within the network. The study
addresses the following questions:
• Who are the academics and practitioners in the area of water and what are their
• With whom are they connected?
• With whom do they exchange ideas?
• What is the internal structure of the network arising out of the ties among the
academics and practitioners in the area of water?
• Who is connected to whom?
• What activities do they do together in their networks?
• What is the context in which the academics and practitioners in the area of
water collaborate? In other words, what are the barriers to and the challenges
in collaborative research?
• What are the strategies used to overcome these challenges?
• What is the impact of CWN on the work of the academics and practitioners in
the area of water?
• How do they see the role of CWN in the area?
Data collection, described below and in further detail in the Appendices, consisted of a
web based national survey, semi-structured interviews, citation analysis, and a review of
documents. In brief, the data collected in the study include:
• 173 surveys. Among the participants are 94 academics and partners involved in
CWN funded projects. They are referred to as “CWN members”. The
remaining 79 respondents are academics and practitioners who are part of the
water community but who have never been involved in CWN funded research.
They are referred to as “outsiders.”
• 65 interviews, including 56 interviews with CWN members and nine interviews
with outsiders. Among all respondents, 39 were both interviewed and
completed the survey.
• Citation analysis results for a small group of 31 CWN members.
• Several dozen organizational and personal documents, including 39 research
proposals, internal analyses and presentations, and several dozen resumes.
Although the survey is not a representative sample of all practitioners and researchers
working in the area of water, a profile of the respondents provides some understanding of
the characteristics of this part of the water community. Furthermore, both the survey and
the interviews include academics and practitioners working on CWN funded projects as
well as individuals who are not currently involved in the work of CWN. This
composition of the survey respondents reflects the overall community of people working
in the area of water and enables a comparison of CWN members with other researchers
and practitioners working in the area of water. The interview data, where CWN members
are proportionately much more numerous, also provide opportunities for a comparison.
Part I creates a profile of the participants in the area of water based on individual level
data from the survey. Part II maps the internal structure of the whole network using the
aggregated survey data. Part III draws on the interviews to describe how participants
collaborate, thus placing the network in context and suggesting explanations for its
characteristics. Throughout the report, the interpretation of the results is informed by data
from several available sources.
Part I. Respondents
The analysis below draws on both survey and interview data to describe the respondents,
their networks in the area of water, and the way they use their networks for knowledge
and information exchange. The discussion introduces patterns visible in the overall
survey sample and then follows with comparisons between CWN members and outsiders.
1.1. Demographics: Who are the respondents?
The typical respondent is a mature professional in mid-career who holds a Ph.D., works
at a university, and is male.
The demographic data presented show that over two thirds (69.9%) of all our respondents
are men (Table 2, Section A) 1 . The mean age is 47.7 years, and the majority of the
respondents are between 40 and 60 years (Table 1; Table 2, Section B). Most of the
respondents have considerable work experience. On average, they have worked nearly 15
years (Table 1). More than a quarter have worked for more than 20 years (Table 2,
This is a well-educated sample. All respondents who provided information on their
education have a university degree, and the most common highest degree is Ph.D. Among
the respondents, 40.0% hold doctoral degrees, 20.8% Master’s degrees, and 18.5%
Bachelor’s degrees (Table 2, Section D). The largest group of respondents (40.5%)
comes from academia, followed by government employees at various levels (37.6%),
industry (11.6%), and NGOs (7.5%, see Table 2, Section F).
By discipline, the largest group are engineers (Table 3). They are followed by
respondents from a cluster of natural sciences: earth/environmental
science/geology/ecology (Table 3). The next most sizable groups are social scientists
(12.1%) and biology/microbiology (9.8%).
A comparison between the CWN members and the outsiders among our respondents is
presented in Table 4. As the table shows, CWN members tend to work in academia, hold
doctoral degrees, be older and have longer work experience. Such differences are
consistent with the focus of CWN activities and are an indication of the calibre of the
people the Network works with. For instance, the majority of CWN members hold
doctoral degrees and have worked over 10 years (Table 2, Sections C and D). By
comparison, the majority of outsiders hold either Master’s or Bachelor’s degrees and are
concentrated in the lower categories of work experience (Table 2, Sections C and D).
In short, the typical CWN member among the survey respondents is an experienced
academic, while the typical outsider is a slightly younger government employee. There
are no significant differences between men and women although there are slightly more
women among CWN members.
All tables are in Appendix 1.
1.2. Personal networks: To whom are the respondents connected?
The survey data enable us to describe the water networks of the 173 respondents. The
network level data characterize the network of individual respondents: they show who
each respondent knows in the area of water—this group of people is referred to as their
“water network”—and how they communicate and exchange information with them.
Alternatively, it is possible to combine all the 1,904 ties for which respondents provide
information, and discuss their overall characteristics regardless of who has provided the
information. This “tie-level” data describes the entire community rather than individual
When focusing on the individual respondents and their water networks, the data show
that all our respondents have well-established networks in the water community and they
tend to work directly with many of their ties. These network patterns are similar for CWN
members and outsiders, although they are slightly more pronounced for CWN members.
The typical respondent has known his network members in the area of water between five
and ten years, contacts them a few times a year, works and exchanges ideas with the
majority of them, and considers them acquaintances.
Further, the data on work ties shows that for a large group of the respondents, the people
they know in the area of water tend to be colleagues, partners, and collaborators. The
respondents work directly with them, as opposed to simply knowing them or being aware
of them. Almost half of the respondents (46.2%) work directly with the majority of the
people in their water networks (Table 5, Section E). This group of respondents is actively
working with members of their network in the area of water. Another sizable group of the
respondents, 37.0%, works with fewer network members (Table 5, Section E). A
relatively small group among all respondents,16.8%, works with just a fraction—less
than one third—of their network members on their water issues (Table 5, Section E).
These respondents know people in the area of water but work with only a fraction of
This importance of work ties in the networks of the respondents reflects the selection of
the respondents and the effort the survey requires for completion. We contacted people
who are actively working and have connections in the area of water. Further, the
respondents chose to describe their ties with colleagues and collaborators rather than their
ties with people they simply know but do not work with directly. In other words, the
survey captures the strong professional ties of the respondents. In that sense, the
interesting result is not the importance of work ties but the differences among the
respondents: some are actively working with their network members while others are
only marginally involved with them. This suggests a diversity of the respondents which is
consistent with the diversity of the stakeholders in the area of water: water issues cover a
very broad content area, they are regulated under multiple jurisdictions, and concern a
range of government, community, industry and academic organizations. Priorities, needs,
and level of involvement in water issues of these diverse stakeholders vary.
A cross tabulation with sectoral data shows that the pattern of direct work with the
majority of network members is common for some federal government employees and
academics. By comparison, the provincial and local government staff work with fewer
(between 30% and 70%) of their network members (Table 6). These are people whose
main work responsibilities are in the area of water.
In contrast, working with a small fraction of their network members is common for other
federal employees and some industry staff (Table 6). Since federal agencies and
businesses are very diverse, their involvement in the area is very different. Some federal
agencies and businesses are actively working in the area, others are connected to—but do
not work in—the area. The main work activities of such respondents likely require
awareness and information gathering rather than direct contact with others in the water
community. These three groups with different network characteristics will need and
benefit from different CWN activities.
Comparing CWN members and outsiders reveals only slight differences in their
networks. When asked how close they are to each of their network members, both CWN
members and outsiders show similar patterns. There are no differences between them in
how many friends they have in their networks. Consistent with their older average age,
CWN members tend to have known their water network members longer than outsiders,
work with more of them, and contact each of them less frequently. For instance, many
more CWN members work directly with most of their water network members compared
to outsiders (Table 7, Section E). The majority of CWN members (55.0%) contact their
network members a few times a year (Table 7, Section A). Outsiders, in contrast, are not
concentrated in one modality of communication frequency: one third of them contact
their network members a few times a year but almost as many contact their network
members monthly. For a sizable group of outsiders, the average frequency of contact is
weekly (Table 7, Section A).
Overall, outsiders tend to contact their water network members more often. This is
surprising. Because CWN members work with more of their network members compared
to outsiders, they might be expected to contact them more often. Yet the opposite is true.
A possible explanation is the long-term work schedules of CWN members. It is likely
that their work ties are with colleagues and partners participating in CWN-funded
projects, which have a relatively long duration. Further, the majority of CWN members
are academics whose work also has long-term schedules. Indeed, the interview data with
CWN members suggest that working with others on a project, whether CWN funded or
not, does not require constant communication. Instead, project communication is
concentrated in specific stages: writing the application and the reports, discussing the
research design, or solving problems. Despite this burst of communication at certain
stages, the average frequency of communication is not high.
In contrast, outsiders tend to be government employees, most often from municipalities
(Table 4, Section E). The comments of interviewees, which touch upon the different time
constraints for government and academia, suggest shorter duration and quick turnaround
time for government employees compared to academics.
In short, the work network characteristics of the overall sample—the large number of
respondents working with the majority of their network members, five to 10-year
duration of ties, majority acquaintances rather than friends—are more pronounced in the
CWN sub-group than in the overall sample of respondents. On the average, academics
contact their colleagues less frequently. But the average is misleading. Ties between
academics vary greatly in their frequency of contact. The typical academic has few ties of
frequent, intense collaboration and many less intensive ties with other academics—
occasional interactions at conferences, etc.
The survey data also show whether, in addition to working, respondents also exchange
ideas with other participants in the water community. People often work and exchange
ideas with the same colleagues, but it is not always the case. Compared to work ties,
exchanging ideas is a more informal tie and at the same time requires trust. Hence, work
and innovation ties may be quite different.
Social psychologists often find disjunctions between what people say and what they do.
That is the case with CWN. The data show an interesting dynamic: the actual and
potential exchanges of ideas have different, almost opposite patterns. Table 8, Section A
shows that over half of the respondents have discussed innovative ideas with a majority
of their network members, suggesting a pattern of active exchanges of ideas. This is
particularly common for CWN members who are mostly academics; tossing around ideas
is common for them. At the same time, when asked whether they would exchange
innovative ideas with others, respondents reveal a completely different pattern (Table 8,
Section B): the majority of the respondents say they would share ideas with a very small
proportion of their network members. They focus on obtaining ideas from a small set of
other academics whom they trust as well as from grant-giving industry and government
partners. Thus, when it comes to sharing ideas in the future, selectivity is the major
By contrast, the respondents do not expect such selectivity on the part of their network
members. They expect a sizable proportion of their network members to exchange ideas
with them (Table 8, Section C). In other words, they believe they have the trust and
respect of their colleagues, and they want to gather ideas—but not share them—with a
wide range of network members.
1.3. Ties: Another look at the water community
What do these relational characteristics mean for the community of people working in the
area of water? Investigating all the ties of the survey respondents together provides a
picture of the community.
The analysis now turns to the ties, or those 1,904 people for whom our respondents
provide information in their surveys. These tie level data capture additional
characteristics of the entire water community. The analysis suggests that the ties in the
water community are dominated by academics and local government: these two groups
are the backbone of the community.
As previously discussed, the largest group of respondents is in academia. The proportion
of all government employees combined (37.6%) is close but does not reach the
proportion of academics (40.5%, see Table 2, Section F). Among all government
respondents, those from municipalities are the most numerous (21.4%, see Table 2,
The ties of the respondents are principally directed to other government staff and
academics. The distribution of ties is not as strongly dominated by academics and by
local government staff as the sectoral characteristics of the respondents suggest. For
instance, the ties directed to academics comprise only 31.1% of the entire set of ties, even
though academics are 40.5% of the respondents (Table 2, Section F; Table 9, Section A).
Similarly, the ties directed to local government employees are only 16.1%, compared to a
much stronger presence of such officials in the sample: 21.4% (Table 2, Section F; Table
7, Section A). Conversely, while industry employees as well as federal and provincial
government staff are a smaller proportion of the sample, they comprise a larger
proportion of the ties (Table 9, Section A; Table 2, Section F). These findings suggest
that academics and local government staff have diverse networks that connect also to
other government officials, industry practitioners, and members of non-governmental
organizations (NGOs). The importance of academic and local government ties comes
from their diversity as well as their sheer numbers.
This is consistent with the data about who works with whom. A cross tabulation of
sectoral data and the direction of ties (Table 10) more clearly shows who works with
whom. Most of the ties of all respondents are within their own sector. This could only be
expected: government employees work mostly with government employees, academics
work mostly with academics and so on. Yet there are distinct patterns by sector.
Academics are the most inward-looking group; they have ties above all with other
academics, in fact half of their ties are directed to other academics (Table 10). Far behind
their ties in academia are their ties to the federal government (14.0%) and industry
(10.0%, see Table 10).
Federal government staff is at the other end of the continuum. In fact, they are an
exception: their ties with academics are more numerous than their ties with colleagues in
other federal agencies, provincial or local government (Table 8). Local and provincial
government, industry and NGO employees are in between academics and federal
government: they work mostly with people in their own sector but are not as locked
within it as academics.
Further, the distribution of respondents’ ties suggests that the ties of academics to other
sectors are strongest in the federal government; academics are relatively weakly
connected to provincial and local governments as well as NGOs. This is consistent with
the ties of the federal government and municipalities. Federal government staff is
connected strongly to academics. Local government, in turn, is connected to industry but
to a much less extent than to academics. NGOs have the most evenly distributed ties with
various sectors. However, they are well-connected to industry but weakly connected to
the federal government (Table 10).
To summarize, academics and local government have strong presence in the area of water
and ties directed to them dominate the community. Since respondents from each sector
except federal government work mostly with their own sector, we can expect a
fragmentation of the community along sectoral lines. When academics do work on water
issues with partners outside academia, they work mostly with federal government.
Part II: Connections in the Water Network
This section examines the connections in the water network as a whole. The discussion
first examines the overall connectivity of the network and identifies the well connected
members in the network, those who are most central. The analysis then turns to the
internal divisions in the network drawing on “clique” analysis. The clique analysis
describes the internal structure of the network, revealing sub-groups and connections
between them. Finally, the discussion examines the ways researchers in the network cite
the scholarly articles of colleagues. Citing other scholars can be treated as a specific type
of tie. The citation analysis, therefore, provides an additional avenue to examine the
connections among academics in the water network.
2.1. Centrality Analysis
Network centrality, the number of connections a person has in a network, is the most
common way to capture the connectivity of the overall network and the role of specific
persons in it. The more connections each member of the network has, the higher the
connectivity in the network. In highly connected networks, ideas travel quickly, members
influence each other strongly, and resources can be mobilized easily. In turn, individuals
with many connections, or with high centrality, are well-positioned to collaborate or
exchange information with others. For instance, network members who are central are on
communication paths that keep them in contact with others in the network; they receive
information sooner than those who are less connected and benefit more from
Further, respondents may be connected to others either because they work with them or
they may be connected because they exchange ideas with them. Respondents working
with many collaborators may not be exchanging ideas with the same number of people,
or they may be exchanging ideas with a very different set of people. The centrality of
respondents is therefore calculated separately for working ties and for the ties that discuss
In a network, people connect to others either when they initiate a contact or when others
seek them out and contact them. Thus, we can distinguish between two types of
centrality. Outdegree centrality shows the extent to which a person is actively reaching
out to others and initiating contacts with them. People with high outdegree centrality are
the active networkers. By comparison, indegree centrality shows the extent to which
other members of the network contact a particular person. People with high indegree
centrality have prestige and status; they can be considered the established experts in the
network. Both types of centrality reflect connectivity and are crucial for maintaining the
network. Whether reaching out or responding to others, centrally located individuals hold
the network together.
The analysis suggests that the connectivity in the network is low 2 . Centrality varies
depending on the particular measure (indegree or outdegree) and the types of ties
examined (work ties or exchanging innovative ideas). The highest number of connections
a respondent has, for instance, varies from a mean of 6 (work outdegree) to 10 (work
indegree). Yet in each type of measurement, only about a dozen respondents are linked to
the network by three or more ties. The network is sparse.
Why is the connectivity so low? These results should be viewed in the context of the way
researchers work and the diversity of the water community. All the respondents report the
most important professional ties they have with people working in the area of water.
Thus, the survey captures relatively strong professional ties and people have few such
ties. Previous research shows, and our interview data confirm, that academics—who are
almost half of the survey respondents—work closely with only a few colleagues. This is
particularly visible on large research projects; even when the project team includes a
dozen or more people, each project team member works closely with just a few people
(see also clique analysis). These fewer but stronger ties are the type of ties captured in the
survey. In contrast, the survey disregards weak professional ties. For instance, several
members of a large research project have filled in the survey and listed their strong
professional ties. However, they do not work closely with each other, and the analysis
found no ties among them.
For non-academics (over half of the sample), such strong professional ties in the area of
water are likely to be even fewer. The area of water is known for the breadth of issues
and the diversity of stakeholders in it. As some respondents indicate, water issues are
“everybody’s concern.” The responsibility for policy and management in this area is
shared by all levels of government and several agencies. A number of NGOs and
industries are also involved in water issues. The points of common interest among such
diverse stakeholders are likely to be few; the practitioners are therefore likely to work
separately from each other. In turn, their connections to academics depend on their job
and the specific needs of their organization at the moment. For many of them, their main
work responsibilities are unrelated to research activities and outside of the area of water.
In short, the diversity of the stakeholders fragments the community and decreases the
overall connectivity. The results show that many of these non-academic respondents,
especially those not involved in CWN, neither work closely together nor share ideas with
others in the water network.
Finally, the low connectivity in the water network is also affected by the fact that the 173
respondents who filled in the survey are just a sample of all the people working in the
area of water. The analysis looks for connections among the 173 respondents who filled
in the survey. Some respondents work and exchange ideas with collaborators in the area
Construction of the network data was derived from the survey results of personal networks in which
relations with others in the water community were described. The connections of each respondent reported
here are connections to the 173 people who filled in the survey. See Appendix 3 for details.
of water, but their collaborators have not filled in the survey. Therefore, these
connections are not reflected in the analysis.
In short, strong professional ties in the water network are likely to be few. The analysis
captures this low connectivity. The sampling further emphasizes it.
Who are the most connected respondents in the survey and what are their connections?
The discussion next examines those respondents who are better connected to others and
are thus the most active in the water community. These are the respondents central to the
The results of the survey show that the respondents most actively working with others are
not always those who most actively exchange innovative ideas (Table 11). The two
groups only partially overlap. Similarly, those who most actively contact others (high
outdegree) are not necessarily those who are most often sought out by others (high
indegree); the two groups only partially overlap. This pattern of asymmetric ties, quite
common for network studies, holds true for both working ties and sharing innovative
ideas. That is why it is important to examine them separately.
About a dozen respondents are actively working with others in the water network, or they
have high outdegree centrality (Table 11). These are the respondents who have strong
interest in collaboration and are focusing their networking in the area. The interview data
show that among those seeking out collaborators are several senior academics strongly
involved in CWN work; two of them are project leads. At the same time, some of these
active networkers are junior researchers and outsiders not who are not currently involved
in CWN. In other words, the interest and focus on collaborators in the area is stronger
among junior academics—those still building careers and expanding their personal
The presence of outsiders is particularly interesting. The person who is most central of all
the active networkers is an outsider, a senior government official from the federal
government; he works with six other respondents in the water network. The presence of
outsiders among the active networkers is a good indication of their interest in
collaborative research and the potential for developing new connections.
Roughly the same number of respondents—about a dozen—are named as collaborators
by at least three others members in the network (indegree). But this is a different group of
people: only four of the people actively reaching to work with others are also among
those most often sought by others; these four people do not have the highest indegree
centrality scores. In other words, there is a low overlap between the respondents with
high outdegree and those with high indegree. If the first group of respondents with high
outdegree includes respondents interested in collaborative work, this second group of
respondents with high indegree consists of experts with established reputations in the area
who are attractive collaborators for others. There are no outsiders among them. All but
one are academics. About half of them lead CWN projects. The most central person
(indegree), named by 10 other members in the network, is the project lead of a large
The connections among respondents who exchange innovative ideas show similar
patterns to the connections among those working together (See Table 11). A small group
of slightly more than a dozen respondents is connected to the networks by three or more
ties. Those who seek out others to share their ideas are not necessarily the recipients of
such ideas; only five respondents with high outdegree also have high indegree. Notably,
over half (7) of those who initiate contact to discuss innovative ideas are not academics:
they are government, NGO and industry staff. Almost as many (6) are outsiders to CWN.
These are people with ideas who seek out the experts in the water network. In contrast,
the majority of the established experts who attract the interest and trust of others are
senior academics who lead CWN projects. All are involved in CWN.
Comparisons across type of ties and types of centrality
Comparing work ties with ties for exchanging innovative ideas shows that the
respondents who actively contact others for work are often the same people who contact
others to share their innovative ideas with them. Alternatively, those who are named by
others as collaborators are often the same people with whom others want to share ideas.
The overlap suggests that people behave consistently across their ties. Active networkers
tend to be well connected in the water network because they both work and exchange
ideas with others in the water network. Similarly, high status experts attract others as both
work collaborators and consultants on innovative ideas. Where differences between work
and sharing innovative ideas do emerge, it points to higher proportion of non-academics
and outsiders. Sharing innovative ideas, in other words, evokes diverse participants.
Summary of centrality analysis
In sum, the water network is only sparsely connected. Only a small group of the
respondents (29) are better connected to the network, either because they initiate or
attract connections by others. CWN members comprise the majority of these central
network members (22) and therefore contribute most to the connectivity in the network.
The respondents who hold the network together through their connections are divided
into two relatively different groups. The active networkers, who are interested in
collaborative work, include a sizable number of non-academics and people outside CWN.
Young academics building their careers as well as some established academics are also
looking for collaborators in the network. The presence of outsiders in the group—people
who reach out to CWN researchers—is evidence of their interest in the work of CWN. By
comparison, the second group of central people who contribute to the connectivity in the
network by attracting others, or the established experts, are overwhelmingly CWN
members and academics. Their centrality to others suggests the role of CWN in the water
community as a focus of expertise.
2.2. Clique Analysis
Understanding how a network functions is impossible without examining the internal
structure. All networks have their own internal divisions and typically include several
sub-groups of people who are closely connected. In turn, sub-groups may be connected to
each other to a different degree. The number and size of the internal sub-groups as well
as their connections affect the processes unfolding in the network. They determine how
information travels within the network or how resources are mobilized. For example, if a
network consists of many small groups that are not connected to each other, information
and resources are not easily shared across the network. In such networks, information
spreads slowly and resources available in the sub-groups are not pooled together. In
contrast, if a network includes people who are members of more than one sub-group and
thus can connect the subgroups, information and resources travel more easily across the
network. Information spreads rapidly throughout such a network, jumping from one sub-
group to another with the help of overlapping members.
This section examines the results of analyses that identify a specific type of sub-group
within the network—cliques, or groups of individuals who are closely connected. They
might be working together, exchanging information and ideas, or pooling resources. In all
cases, they interact directly and are more strongly connected to each other than they are
to the rest of the network. Clique analysis, in other words, identifies the groups of people
who are strongly connected to each other.
The analysis examined two types of cliques: cliques based on working ties, in which
members work closely with each other, and cliques based on exchanging innovative
ideas, in which members extensively discuss their ideas. The results of the clique analysis
address several questions: How many cliques of close collaborators and discussants are
there in the water network? How big are they? Who works with whom in a clique? Are
the existing cliques connected, i.e., are there individuals who are members of more than
one clique? Finally, do the people who work closely together also exchange ideas or do
people work with some colleagues but exchange ideas with others? In other words, are
work cliques similar to cliques discussing innovative ideas?
The analysis found 12 small cliques, or groups of close collaborators, in the water
network. Figure 1A and 1B 3 are sociograms of the work relations, i.e., they are visual
representation of the ties among network members who work together (Appendix 2). The
graph includes 86 respondents who work with at least one other person in the network.
The analysis showed that these respondents tend to work closely with only one or two
other collaborators. There are many dyads but no groups of close collaborators that are
larger than three members. The small size of work cliques is consistent with the
qualitative data on project practices. While projects may include numerous researchers
and partners, most of them work independently from each other. Daily work is done in
All figures are in Appendix 2. Figure 1A and 1B both represent the same work relations; the symbols used
in Figure 1A indicate the sector of the respondents while the symbols used in Figure 1B indicate whether
the respondents are members of CWN or outsiders.
small groups of close collaborators. Researchers switch from one small group to another
depending on the stage of the project.
A dozen such three-member work cliques exist in the networks (Table 12). Half of the
respondents involved in cliques (8) are members of more than one clique; three of them
are members of five or six cliques of closely related members. Because of these
overlapping members, all 12 work cliques taken together include 16 people (Table 12).
In short, a small number of the active collaborators in the water network (16) are
involved in closely collaborating groups. Such respondents always work with two close
collaborators in a group but are often involved in more than one group. These are the
active collaborators in the network. The rest of the respondents might have close
collaborators, but their close collaborators are either outside the water network or simply
did not complete the survey.
Who are the active collaborators in the network?
The majority of the 16 members of the existing work cliques are CWN members (13 out
of 16) and academics (11 out of 16). More than half of them are over 50 years old and
have long work experience. In other words, the typical active collaborator in the water
network, as captured in the survey, is a senior academic with a lot of experience who is
working on a CWN project(s). However, five of the respondents who are closely working
with others in the area of water, are employees from various levels of government. While
academics dominate, one third of the active collaborators are government employees.
What is even more interesting, three of the government employees are outsiders to CWN.
One of these outsiders, a federal government employee, is involved in three work cliques.
This suggests that some of the key collaborators in the water network are outside CWN
and that there are still important partnerships to be built between CWN and the federal
Who works closely with whom in a clique?
Who works closely with whom is the next key question in understanding the network. If
academics work with each other, or government employees keep to themselves, or work
cliques are drawn by a single discipline, this tell us that their research is hardly cross-
sectoral or multidisciplinary. A closer look inside the work cliques reveals, however, that
the opposite is the case.
The analysis showed that work cliques in the water network cut across sectors and
disciplines. In other words, collaborative research in the area of water tends to be cross-
sectoral and multidisciplinary. This finding is all the more significant since the work
cliques include only three members. Despite this, cliques bring together collaborators
with diverse backgrounds.
Table 13 shows that more than half (7) of the work cliques are cross-sectoral; they
include two academics and a non-academic (#1, #3, #5, #9, #10, #11, #12). The non-
academic collaborators are government employees at the three levels of government.
Most of the collaboration, in other words, takes place among academic and government
employees. The most sought after collaborator is a federal employee: he is a member of
three different cliques, each in a different part of the country. Since he is also the outsider
mentioned above this result reinforces the idea that there are untapped connections
between CWN and the federal government.
Equally important, the composition of the work cliques is multidisciplinary, with a heavy
representation of biology, followed by earth/environmental science/geology, and
engineering. By contrast, there is a poor representation of social sciences (Table 13). The
analysis found that none of the work cliques draws its members from a single discipline.
Instead, virtually all work cliques are multidisciplinary; in half of them each member
comes from a different disciplinary background.
Biology is the most prominent discipline in the network. Two thirds of the cliques
include at least one biologist (#3, #4; #5, #6, #7, #8, #9, #11); all of them include either a
biologist or an epidemiologist. In several cliques, two of the members are biologists. As a
result, in most of the work cliques, members are involved in research projects related to
There are four to five biologists who participate in the work cliques (four biologists and
one microbiologist). Two of them are much more active collaborators: they are involved
in five and six cliques respectively. Both of them are CWN members who have been
invited to participate in a number of research projects. It is through their collaborative
work that biology takes such a central place in the work cliques.
The next two areas that figure prominently in the work cliques are earth/environmental
science/geology (multidisciplinary by nature) and engineering. Two thirds of the cliques
include earth/environmental scientists (#1, #2, #4, #5, #6, #8, #9, #12). There are five
people with earth/environmental sciences backgrounds who participate in the work
cliques. None of them, however, is a member of more than two work cliques; they do not
contribute to the same extent as biologists to the water network. Engineering is
represented in half of the work cliques (#1, #2, #3, #10, #11, #12) even though there are
only two engineers. Both of them participate in several cliques, ensuring the high
representation of their discipline.
The social sciences are not well represented in the work cliques. Out of the 12 existing
cliques, only three contain a single collaborator with a background in social sciences (#3,
#10, #7). They collaborate with biologists and engineers. Each of the collaborators—a
geographer and two economists—participates in a single clique.
The cliques in the network are various configurations drawing on these three popular
disciplines. The most common combinations include epidemiology, biology and
environmental sciences, or biology with environmental sciences and engineering. For
instance, one of the well-connected researchers is an engineer who appears in three
cliques along with a biologist, epidemiologist, and environmental scientist.
In short, there is no doubt that the active collaborators in the water network, most of
whom are CWN researchers, are doing cross-sectoral and multidisciplinary research.
They work closely with government employees (although some of their partnerships are
outside CWN) and collaborate with other academics outside their own discipline.
However, the disciplines from which they draw their collaborators are limited and social
sciences are underrepresented in the collaborations.
Are the work cliques connected?
It is important to examine the connections among cliques. Without such connections, the
larger water network would be only a collection of independent groups, in which
members work only among themselves and do not have common work interests. Given
that the work cliques are quite small—only three members—such a situation would mean
there was a very limited circulation of information and resources within the larger
network. In turn, with only a few connections among the cliques, the network would be
vulnerable to slipping back to a disconnected state. If only a few members collaborate in
several groups, all these connections would be removed if they were to leave the network.
The analysis showed that eight of the active collaborators in the network are members of
more than one work clique. In other words, there is a significant overlap in the
membership of the work cliques and this ensures that many of the work cliques are
interconnected. This suggests that active collaborators in the network have common work
interests that link them together in various configurations. Further, the active
collaborators contribute to different degrees to these interconnections. Three of them are
involved in as many as five or six work cliques while five other collaborators are in two
or three work cliques. The remaining eight participants in work cliques are working with
members of only one clique.
In short, there are connections that cut across the work cliques and hold the overall water
network together. People working in the area of water are thus a network and not a
collection of independent groups. Yet the people contributing to these integrative
connections are relatively few. Among them, an even smaller number contributes
disproportionately to these connections. While for the active collaborators themselves
such connections mean access to resources and information, for the network as a whole
this dependence on a few key participants reveals a weakness.
What brings work cliques together?
How active collaborators come together to create work cliques is important not only for
the understanding of the network but also for possible interventions in the network. This
is not a matter that the survey can answer. However, documents and interview data
provide some clues.
About one third of the work cliques identified in the analysis are most likely based on
CWN projects. Such work cliques consist of people who work together on the same
CWN project (Cliques #2, #4, #8, #5). Most of them include the project lead, senior
researcher, or partners. These groups of collaborators have come together because of their
CWN project. To put it differently, in these groups the membership in the work cliques is
a function of the membership in CWN.
A surprisingly sizable number (6) of work cliques, however, includes two academics
working on the same CWN project and a government employee who is not formally
listed as a partner on their project (#1, #3, #9, #10, #11, #12). It is unclear in these cases
whether members work together on a CWN project or on a project funded by a different
agency. In the first scenario, it is possible that the third member of the clique, the
government employee, may not be listed as a partner on the CWN project for reasons of
authority. The formal proposals often include high ranking contact persons from the
government who do not necessarily do the everyday work. In contrast, the clique analysis
captures the government employee who works on a day-to-day basis with the academics.
Personnel changes in the government can also change the members of a work clique
without changing the nature of the partnership and the collaborative work.
Alternatively, in the second scenario, the members of the clique are working on a project
unrelated to CWN. Their relationship goes beyond CWN. It is not clear which of the two
scenarios corresponds to reality in each of the cliques with such composition. In both
cases, however, the active collaborators demonstrate a commitment to cross-sectoral
research and solid connections to the government.
Finally, a third set of work cliques cuts across projects; it includes members from two
CWN project teams (#6, #7, # 9). Such groups most likely work together on projects not
funded by CWN. They extend their collaborative relationship across several projects.
This is consistent with what the interview data reveal about the way researchers work
together. Researchers are typically involved in several projects and thus work with
collaborators from several formal work groups. At the same time, most researchers
consciously build a group of close collaborators, and they invite them to participate in
multiple projects. This is particularly true for senior researchers. Their close collaborators
get involved in different configurations, and in several projects. Collaborative ties with
them transfer across several formal projects.
To summarize, the membership in a work clique does not closely follow CWN project
teams. While the majority of active collaborators in the water network are CWN
members, they are not necessarily working on a CWN funded project. These results
reflect the fact that research in the area of water is funded by many agencies including
CWN. The collaborative ties in the water network do not all arise in CWN projects and
are not entirely dependent on the work of CWN. These results are consistent with the
existence of active collaborators outside of CWN.
On the other hand, CWN plays a crucial role in the water network; the majority of the
active collaborators in the network, and certainly all of the academics among them, are
CWN members. Whether CWN attracted active collaborators or, alternatively, helped its
members expand their collaborative ties (interview data suggests that both processes are
taking place), it has been able to link those academics who are interested in collaborative
work in the area of water.
Innovative ideas can be interpreted as a distinct resource in networks. The way that
innovative ideas travel in a network does not necessarily follow work ties. In some cases,
collaborators are experts with complementary expertise who can bring a fresh look to an
issue; in others, they are close collaborators who act as sounding boards. In such cases,
collaborators from a work clique not only work together but also exchange innovative
ideas. Work cliques coincide with the innovation cliques.
Yet there are also good reasons to expect differences between the two types of cliques.
Innovative ideas are often cross-sectoral in nature. Further, people outside one’s own
work group and outside one’s own discipline can bring unexpected ideas. We would
expect, therefore, exchanges of innovative ideas to occur more across sectors and
How do work cliques and innovation cliques in the water network compare?
Figures 2A and 2B present the innovation exchanges in the network 4 . The clique analysis
found 12 small innovation cliques with three members each (Table 14). Despite the
opportunities for different networks, in practice, most of the cliques coincide with work
cliques (#1, #2, #3, #5, #7, #10, #11, #12). Just a third of the cliques contain one or two
new members (#4, #6, #8, #9). In other words, respondents not only work with their close
collaborators but also discuss their innovative ideas with them. Nonetheless, there are
some interesting differences between innovation and work cliques.
Who exchanges ideas with whom?
Compared to work cliques, the data in Table 14 reveal that the participants in innovation
cliques have fewer outsiders (2 out of 19) and more non-academics; almost half of the
participants are outside academia (9 out of 19). Such changes in the background of the
participants in innovation cliques can be expected; the sharing and implementation of
innovative work and ideas involves collaboration between academics and non-academics,
whereas collaborative research work is more limited to ties among academics.
What is perhaps unexpected is that the non-academic participants in the innovative
cliques are somewhat different than those in work cliques. Innovative cliques, non-
academic participants are more evenly distributed across various sectors: there are
employees from the federal government (2), provincial government (1), local government
Figure 2A and 2B both represent the same innovative relations; the symbols used in Figure 2A indicate
the sector of the respondents while the symbols used in Figure 2B indicate whether the respondents are
members of CWN or outsiders.
(1), as well as representatives from industry (2) and NGOs (2). Notably, some of the local
government participants from work cliques are not present. Thus, industry and NGO
representatives not present in work cliques become members of innovation cliques.
Disciplinary characteristics of the innovation cliques also slightly change compared to
work cliques. Biology retains its prominence: just as in work groups, two-thirds of the
cliques include a biologist and some are entirely based on biologists. However, the role of
environmental sciences and engineering decreases. The number of social scientists in the
group slightly increases due to the participation of more non-academics from government
Are innovation cliques connected?
Connections between such innovative cliques are especially important since such
connections facilitate the spread of ideas in the larger network. Yet it is much easier to
share ideas with only close collaborators.
The analysis shows that the innovation cliques are connected albeit to a lesser degree
compared to work groups. Out of 19 participants in innovation cliques who exchange
ideas, five are involved in two cliques. An additional two are involved in five and six
cliques respectively. With a few exceptions, the clique members who connect the
innovation cliques are the same clique members who connect the work cliques in the
network. In other words, respondents who are most actively working with collaborators
from different work groups are also most actively exchanging innovative ideas with their
collaborators from different groups. It is significant that the two members involved in the
highest number of innovation cliques are the same two members involved in the highest
number of work cliques. Since they are both biologists, they reinforce the centrality of
biological sciences in the innovation network.
Bridges: Who are the people connecting the cliques?
The analysis of cliques showed that some respondents are members of more than one
group. Two of them are also cutpoints in the data, meaning they are central to both the
work and innovation networks, connecting and acting as bridges between cliques (the
people identified as 146; 122, Figures 1 and 2). Such network members are known as
bridges connecting otherwise disconnected groups. People in such positions act as
information or resource brokers and boundary spanners within the group. They are a key
to the “health” of the network; their removal could result in fragmentation of the network.
Demographic information, as well as the clique analysis and centrality scores, can
identify who are the important bridges and how they behave in the network. The two
respondents in bridge positions are academics in mid-career. Both are biologists, the most
prevalent discipline in the network. Both work on a CWN funded project although neither
of them is a project lead. In other words, they are not junior researchers; they have had
time to develop their professional ties in the network. Neither are they among the most
senior members of the network who have less time for networking, get more easily
funded by various agencies, and work on many projects whose participants may be
unconnected to CWN.
The clique analysis also shows that the two bridges work and exchange ideas with
academics and partners across the country, i.e., they have developed broad networks of
distant collaborators and partners. Quite likely, in addition to their CWN project, they
have research projects not funded by CWN. In turn, centrality analysis shows that they
are among the few people who both reach out to others and are named by others who
want to collaborate and exchange ideas with them. Their indegree and outdegree
centrality scores are quite similar.
Finally, they are involved not only in CWN but also in other organizations in the area of
water. There is a significant overlap in the membership of the two organizations. This
helps them develop and strengthen their ties to other researchers in the area.
Several findings emerge in the clique analysis. First, the research taking place in the
network is cross-sectoral and multidisciplinary. The composition of the work and
innovation cliques bears evidence to that. The finding is all the more important given the
small size of the cliques.
Second, CWN plays a central role in supporting these partnerships and research although
it is not the only player in the area of water. The clique composition shows that it is CWN
members and especially academics who dominate research collaboration. Not all of their
work is on CWN projects—other funding agencies also support such complex
collaborations—but CWN members are always a strong presence in these collaborative
groups. Work and innovation cliques have similar memberships, although outsiders are
more active in exchanging innovative ideas than in work cliques.
Third, clique analysis confirms the opportunities for expansion of CWN memberships in
government and industry. Outsiders from industry, federal and local government are
already collaborating and exchanging ideas with CWN academics. This is consistent with
the centrality analysis which shows industry and government employees actively
reaching out to the networks. In this respect, the federal and provincial employees are
particularly active. Notably, the analysis of personal level networks (Table 10) confirms
that the largest proportion (26%) of the ties of federal employees is directed to academics
in universities and not to people in their own sector. The interview data also show that
some federal employees feel an affinity to academics. In short, if local government
employees are already involved in research and exchanging ideas, federal employees
seem to be the most important, albeit not the only, untapped resource for expanding
Finally, the analysis suggests two weaknesses in addition to the overall low connectivity
discussed in the previous section. Multidisciplinary research draws on a limited range of
disciplines; biology dominates collaboration, followed by environmental science and
engineering, while social sciences are not well represented. Next, there are only two
significant bridges in the network, making it vulnerable to changes.
2.3. Citation analysis
Citation analysis is a technique that examines how scholars cite each other. Citing
another scholar is interpreted as a specific type of tie. A group of authors citing each
other is thus seen as a network of scholars who have common interests, work in the same
area, and read each other’s publications. In a university environment, publications
measure the value of academic work and citing is the most common recognition of this
value. Citation analysis therefore captures the most significant as well as the most
traditional professional tie among scholars.
The discussion below presents the result of citation analysis for a small group of 31
scholars 5 . Applied to CWN members, citation analysis can show whether scholars in the
network are connected by this traditional professional tie. The analysis can tell a lot about
what is happening in the network by answering questions such as: do scholars in the
group cite each other? In other words, does their collaboration end with the report for the
project or do they continue to follow each other’s publications? Citing indicates that their
publications are related and relevant for their colleagues. Who are the most often cited?
In others words, who are the most visible and influential scholars? Alternatively, who
cites others most often? Such scholars are familiar with the work of their colleagues and
are able to link it to their own work.
Citation analysis is particularly important for the CWN by revealing who cites whom in a
group of scholars and thus mapping the internal structure of the group. Combined with
information on the disciplinary background of scholars, this can show whether scholars
from different disciplines work on common issues and find each other’s publications
relevant in their own work.
The analysis includes several types of measures, each of which examines a distinct
citation behaviour and adds to our understanding of the network. The first measure is
cocitation, or how many times any two authors in the group are cited together by anyone
in any field, whether in the group or not. It is a pairwise measure. Repeatedly cocited
authors are perceived to work on related issues; their work is either similar or
complementary in some respect. Cocitation captures opportunities for collaboration.
By comparison, intercitation shows how many times scholars from the selected group
cite each other directly. The role of a scholar who frequently cites others in the group
differs from that of the scholar whom others frequently cite. Scholars who cite others in
the group are familiar with their work, find it relevant to their own, and recognize its
Citation analysis is only feasible for small groups. This analysis includes the 31scholars who are among
the most central people in the network. Compared to the group of people who are central in working and
exchanging ideas, this 31-member group excludes respondents outside CWN. Details of methodological
issues are available in Appendix 5.
importance. Senior scholars citing others act as integrators of the intellectual
contributions of their colleagues.
In contrast, scholars who are widely cited have prestige and influence with their
colleagues but may not be citing them; they may not even be familiar with their
colleagues’ work at all. Such scholars are thought leaders in the group.
Intercitation thus includes two separate measures. The first captures the instances in
which a scholar cites others in his or her group. The second captures instances in which a
scholar is cited by others in his or her group 6 .
Centrality of Authors in Citation Networks: Do Scholars Cite Each Other?
The scholars included in the citation analysis are all members of CWN and represent over
a dozen CWN projects. Most are either biologists (10) or earth scientists (7); the rest are
almost evenly distributed among chemistry, health, engineering, geography and business.
The multidisciplinary composition of the group makes dense citation within the group
Most scholarly journals publish work in a single discipline and their criteria for
acceptance reinforce disciplinary boundaries (Section 2). Citing the scholars you work
with cannot be taken for granted: even for people working in multidisciplinary teams,
publishing and citing can fold back within one’s discipline to increase the likelihood of
publication. Citing, therefore, is the most rigorous test for the existence of cross-
disciplinary connections. At the same time, citing across disciplines may strongly
indicate the interdisciplinary nature of the work being done in the group.
Do scholars cite their colleagues?
The analysis suggests several salient patterns. First, scholars in the group do not cite their
colleagues very often. Citations within the group are not frequent and connectivity in the
citation network is low. This is consistent with the low connectivity found in the survey.
To be sure, the majority of the scholars are in some measure connected to the group: they
are cocited with others in it, and they cite or are cited by others in it (Table 15). However,
most of the citation counts are small and some scholars neither cite nor are cited within
the group. Individual scholars, though, differ considerably in terms of citation.
Second, the scholars in the group are more often cited together (cocitation) than they cite
each other (intercitation). Almost everyone is cocited with at least one other group
member: there are relatively few zeros indicating that the scholar has not been cocited at
all. This suggests that the work of the scholars in the group is perceived as having a
certain measure of coherence; they are seen as working on the same issues.
These measures are similar to the centrality measures in any other type of tie and have already been used
in Section 4 to show the active networkers (outdegree) and established experts (indegree).
Table 15 compares the number of other persons in the group that each member is cocited
with (Cocite Degree), the number of persons each cites (Intercite Outdegree), and the
number each is cited by (Intercite Indegree). Values above 4 are shaded. Intercitation
among members is responsible for some of the cocitation they receive. As indicated by
the zeros, two scholars in the group have not been cocited, and four neither cite nor are
cited by their colleagues. This is consistent with the diverse disciplines from which the
scholars in the group come.
In sum, scholars in the group do not cite their colleagues very often. While they can see
the connections between their work and the publications of a few other colleagues, they
have trouble relating most of their colleagues’ publications to their own research.
Cocitation Centrality: Who is most frequently cited together with other colleagues?
As noted, cocitation refers to the instances in which pairs of authors are cited together by
any citer in any field. Scholars with high cocitation scores usually write on similar topics
and use methods in common. Almost all of the scholars in the group are cocited with at
least one of their colleagues, and one is cocited with 11 others (Table 15). Such
differences may be linked both to individual characteristics, such as the career trajectory
of the scholar, and to contextual characteristics, such as the disciplinary composition of
the group and the established practices in it.
When the articles that cocite pairs of CWN authors are counted, the analysis shows that
the scholars who are most often cited together tend to be biologists and earth scientists.
The top scholar on the list, who is cocited with other group members in a total of 60
articles, is a biologist, works in large projects, and participates in more than one CWN
project. Participating in several projects underscores the fact that his work is related and
fits well with the work of his colleagues. The centrality analysis in Section 2.1 shows that
he is often named by others as a collaborator and a person with whom others want to
share ideas. His project participation reinforces his visibility in the group, makes him a
familiar name to others, and increases the likelihood that that his work will be seen as
related to the work of other colleagues.
Yet, this is not the full explanation: there are other scholars who are also senior and
participate in several projects but are not cocited so frequently. To understand better what
is happening, the analysis needs to take into account the broader characteristics and
internal structure of the networks. The discussion turns to the question of particular
Cocitation Map: Whom are they cited together with?
Figure 3 is a map of the cocitation links that shows which scholars are cited together. A
link between any two scholars indicates that they have been cocited in at least one article.
The thickness of the link indicates the frequency of cocitation: scholars joined with
heavier lines are cocited in many more articles than those with lighter lines. The heaviest
link is between a pair of authors who were cocited in 23 articles. Disciplinary background
is indicated by colour.
The map shows that the central people are cited together with scholars from several
disciplines. For instance, one of the two most central people is cited together with
biologists, engineers, chemists, and health scientists. This is what leads to his centrality.
The second person is cited more often with people in his own discipline, but there is still
disciplinary diversity. This pattern of diversity is common for many of the scholars, even
though they are less frequently cocited.
Figure 3 shows an internal structure in the group that further suggests patterns of
cocitation across disciplinary boundaries. The cocitation map indicates that scholars tend
link up in groups of three. The majority of these groups are composed of authors from
different disciplinary backgrounds. In other words, their works are perceived as relevant
to issues in several other disciplines and cited together. This pattern is an indication of the
multidisciplinary relevance of the publications of these scholars.
On the other hand, several patterns suggest the impact of disciplinary boundaries. Some
of the scholars, who are cited together, include only biologists (#164, #122, #152) or only
economists (129, 126, 149). Some of the biologists have very strong connections among
themselves. Scientists in economics, geography, and health tend to be at the periphery of
the network. In short, while there are many cross-disciplinary connections, disciplinary
boundaries remain important.
These patterns suggest an interesting dynamic of the disciplines in the group, best
illustrated in a comparison between biology and economics. Biologists are the most
numerous in the group of scholars included in the citation analysis. They dominate the
work cliques (Section 2.2) and are highly visible in the network. Given this wide
participation and visibility, it is easy to perceive their publications as relevant to many
disciplines; biologists are therefore often cited together with scholars from other
disciplines. At the same time, the sheer numbers of biologists is a temptation to cite
biologists only. This accounts for the strong cocitation links between several of the
biologists in the group.
In contrast, social scientists are not well represented in the group included for citation
analysis. They are less central in work cliques and less visible (Section 2.2). Other
scholars have trouble finding the links between a social sciences discipline such as
economics and others more popular in the CWN disciplines. Economists, therefore, tend
to be cited together with other economists; their participation in cross-disciplinary
cocitation is very low.
In short, cocitation suggests that, with a couple of exceptions, all scientists are perceived
as having at least minimal ties with colleagues in the group. There is a perception that
scholars in the network work on common issues. Working actively in the network
facilitates such perception of relevance but it is not the only factor that affects it.
Individual participation in CWN projects interacts with discipline to determine who is
most visible and most often cited with others. Further, cocitation indicates many cross-
disciplinary connections, but also that disciplinary boundaries remain important. This is
particularly important for the social sciences and to some extent for the health sciences,
which remain locked in their own disciplines.
Intercitation Centrality: Who cites other colleagues?
Intercitation occurs when scholars cite each other directly. Scholars who often cite their
colleagues within this set are familiar with their publications and recognize their
relevance and importance. Typically, they may be junior to these colleagues and are
citing to establish the credibility of their own work. However, there are no junior scholars
in the CWN group. All members are well-established in their careers and are often
leading scientists in their disciplines. This, together with publication pressures to cite
people within one’s own discipline, is part of the explanation why there are relatively few
instances in which scholars in the group cite their colleagues, despite the many
opportunities to do so.
The more interesting finding is that in this group, scholars who cite their colleagues most
frequently are not juniors. The person who cites group colleagues in the most articles is
indisputably a senior scholar (127). He is also actively working and highly visible in
CWN. He has cited colleagues in 48 articles. (By contrast, seven scholars in the group
have not cited anyone at all.) The average outcitation score is 6. Notably, the next person
on the list, who has cited others in 22 articles, is also a well-established scientist. These
scholars are not only familiar with the work of their colleagues, but are also able to find
the connections between the work of others and their own. They synthesize and integrate
diverse contributions. Figure 4 shows that the scholar on the top of the list cites not only
colleagues from his own discipline (biology), but also colleagues from several other
disciplines. In short, he integrates the intellectual contributions of the other scholars in
Who is cited by colleagues?
In contrast, scholars who are cited by their colleagues are visible and influential. This
different role in the group is played by different people. Despite some overlap, the
scholars who are cited by colleagues in the most articles are not the scholars who most
often cite colleagues in articles of their own.
The person most often cited by others in this group is, not surprisingly, another biologist
in a senior position who is actively involved in CWN (164, Figure 4). He is highly visible
among colleagues, often being named by them as a collaborator and as a person with
whom they want to share ideas (Section 2.2). They cite him much more often than other
members—in some 48 of their articles. (That his 48 incitations match the other leader’s
48 outcitations is a coincidence.) Although he is cited by scholars in his own discipline,
scholars from different disciplines also cite him (Figure 4). In other words, they find his
publications relevant in their own work—a strong recognition of his importance. (He is
also the group member most highly cocited with other members.) This scholar, hence, is
in a position to influence his colleagues—he is a thought leader. His closest competitor
in this role is cited in 17 articles. The average number of articles in which the group cites
a member is 6.
Thought leaders are all the more important because being cited by colleagues does not
happen very often: while these scholars are leading scientists in their areas, publication
criteria strengthen disciplinary boundaries and limit within-group citations. This
eliminates one of the major channels for influence among scholars. Moreover,
disciplinary boundaries are reinforced by organizational boundaries, which further
decrease opportunities for influence.
Who cites whom? Who is cited by whom?
The two scholars leading the intercitation lists in sending and receiving citations are both
connected to colleagues from different disciplines. Is this pattern of citing across
disciplinary boundaries common for other members of the group? In other words, do
intercitation patterns indicate multidisciplinary connections?
Figure 4 maps the structure of the intercitation connections in the group. Direct citation is
less frequent, and more scholars become disconnected from the group. The remaining
connections are quite similar to the cocitation map, but they seem to follow disciplinary
boundaries more closely. Direct citation happens in groups of two and three scholars and
many of the groups are familiar from the cocitation analysis. The three economists
remain connected among themselves at the periphery of the map. The biologists around
the central person in the cocitation map are still closely connected to each other. In other
words, scholars who are cited together also tend to cite each other. If they work on
common problems, as evidenced in the cocitation map, they will cite each other and will
have a link in the intercitation map.
At the same time, the multidisciplinary nature of the connections decreases. Many of the
scholars continue to have connections to other disciplines. However, compared to the
cocitation map, some groups in the intercitation map have lost the member who
contributed to their diversity; a few of the scholars are now connected to a single
colleague from their own discipline. In other words, scholars tend to cite and be cited by
colleagues in their own discipline. This holds true even when they work on common
problems with colleagues outside their discipline and are cited together with them. In
several cases, scholars from different disciplines are working together on a CWN project
yet do not cite each other.
In short, when it comes to directly citing their colleagues, scholars tend to follow
disciplinary boundaries. Current publication practices in most scholarly journals reinforce
such preferences. This confirms the patterns mentioned earlier: while scholars in the
group are perceived as working on common problems and cited together, these scholars
themselves find it difficult to integrate the work of their colleagues from other disciplines
in their own work.
Part III. The context of collaborative work
To understand why the researchers and practitioners in the area of water connect to each
other the way they do, it is necessary to look at the broader context of their work. In the
previous sections of the report, the analysis has on occasion referred to interview and
documentary data to explain results. The next sections draw heavily on interview data to
discuss in more detail several themes that have emerged in the comments of interviewees.
First, the analysis examines barriers and incentives for complex collaborative work of the
type fostered by CWN that explain the age and status composition of CWN membership.
Second, it looks at the challenges in doing collaborative work and the strategies for
overcoming them. These are related to connectivity in the network, the characteristics of
work cliques, and the role of personal networks in the collaboration. In sum, networking
practices lead to the third theme—the impact of CWN on the work of its members and its
role in the area of water.
3.1. Barriers and incentives for collaborative work
Barriers for academics
Existing research shows and the interview data concur that the organizational
arrangements in universities are the major barrier that discourages academics to engage in
cross-sectoral and multidisciplinary research. Most of the academics admit that cross-
sectoral and multidisciplinary collaboration is not rewarded through the formal promotion
and evaluation procedures in their universities. Even universities that “pay lip service” 7
to the importance of such research rarely provide support and recognition of it. Neither
are the difficulties of such work recognized. Traditionally, the evaluation of academics is
based, in addition to teaching and community service, on the number of publications and
the prestige of the journals in which they publish—the “publish or perish” criteria.
Multidisciplinary and cross-sectoral research is not conducive for these traditional
outcomes. Working with partners does not necessarily generate opportunities for
scholarly publications: its outcomes might be manuals, software tools, website
information—“very informative but not peer-reviewed publications”. Integrating results
from empirical research across disciplines faces significant challenges: the methods,
interpretation, even the scale of empirical research are different.
Several researchers interviewed point to this integration of results as the major challenge
they face and link it to the multidisciplinary nature of the research. When an article is
produced by collaborators, publishing is less likely because multidisciplinary work is
hard to assess and not many journals are willing to undertake this evaluation and thus
publish such work. Finally, even when multidisciplinary work is published, such
publications are not highly valued in universities. Applied journals are considered less
All quotations are from the interviews.
prestigious. These works tend to have several co-authors and some departments interpret
multiple authors as inability to do independent work.
The interview data therefore show that doing cross-sectoral and multidisciplinary work of
the type CWN fosters is more difficult and at the same time less valued in academia. To
quote the researchers themselves, “There is no real incentive” for complex collaborative
work. If academics collaborate, they may be considered “tainted in some way.” Or, to put
it bluntly, “individual researchers get involved in these projects at their peril.” To be sure,
there is some evidence for a shift to a more positive attitude to multidisciplinary
collaborative research. The establishment of new multidisciplinary programs is the best
indicator for this even though multidisciplinary programs might be a result of external
pressures that universities cannot ignore. In addition, two of the respondents mention that
their departments or universities do not penalize or even value collaborative work
although they are quick to add that this is the exception rather than the rule. Only one
academic reports that continued success in partnerships carries recognition, including the
intangible support and goodwill of university executives, “more latitude in decision-
making,” and it most likely contributed to the funding for new facilities. In short, while
cross-sectoral and multidisciplinary collaboration carries penalties, the rewards for it are
more uncertain and intangible.
The unfavourable organizational context in academia has a particularly dampening effect
on the collaborative work of junior academics in the early stages of their careers.
Pressures to build careers combine with the more rigorous application of traditional
criteria for evaluation. Many of the senior academics volunteered comments on this issue.
University criteria do not account for the value or innovativeness of research and resort to
“metrics” when evaluating young academics: they count research dollars and
publications. For academics with 20-25 years of experience, such criteria may not be so
rigorously applied. Young academics, however, cannot expect such latitude. They often
think that getting involved in multidisciplinary work is “the kiss of death.” One of the
students echoed these concerns by comparing a writing a thesis based on a CWN research
project to doing two Ph.D.s—one doctoral thesis satisfying university requirements and a
second one meeting the needs of the partners.
As a result, multidisciplinary cross-sectoral collaboration involves above all academics
who have at least 20 -25 years of experience or may be close to retirement. Alternatively,
collaborative projects do not include “anybody who has the pressure to build a career.”
These interview data are consistent with the demographic characteristics of the CWN
members who filled in the survey: about half of them are over 40 years old and have had
more than 10 years of work experience.
Incentives for academics
Given this unfavourable organizational context and the relatively limited changes in it,
one begins to wonder why academics get involved in multidisciplinary cross-sectoral
research at all. The short answer is: academics, or at least a selected group of them, find
intrinsic value in collaborative work, appreciate the intangible benefits of such research,
and look at it as an opportunity to find like-minded collaborators. Several respondents
shared their interest and excitement in doing interesting research that contributes to real
life outcomes. Such intellectual benefits play an important guiding role in the behaviour
of academics. Some argue that CWN projects provide higher exposure compared to other
agencies. In addition, CWN projects have some intangible benefits for researchers: CWN
funding “is tough money to get” and might bring kudos from colleagues and university
officials. Moreover, CWN funding may be a welcome increment to the funding within
their own discipline. Even when they do not translate into tangible benefits, academics
value the prestige such projects bring.
To summarize, the barriers for academics doing cross-sectoral multidisciplinary work are
to a great extent structural, although any structural constraints are typically accompanied
by cultural characteristics. It is the evaluation procedures in universities and publication
criteria that discourage such complex collaboration. Traditional academic culture
reinforces this effect. By comparison, what attracts researchers to such research are its
intrinsic value and intangible benefits such as prestige. The dampening effect is
particularly strong for junior researchers in the early stage of their careers. This set of
barriers and incentives is consistent with the results of the citation analysis, which
confirms that researchers tend to follow disciplinary boundaries when citing their other
scholars. As well, it is one of the reasons for the prevalence of senior researchers in
CWN. This balance in favour of senior academics may become even more pronounced in
the future: as CWN develops and fine tunes its funding criteria to focus further on
multidisciplinary and cross-sectoral research, it will further depart from the traditional
evaluation criteria of universities that impact young academics. Paradoxically, the more
successfully CWN achieves its goals to promote multidisciplinary and cross-sectoral
research, the less likely it “can expect to involve young academics.” If CWN is to include
junior academics, a participant suggested, its application criteria need to be more flexible
and to account for the constraints faced by young academics.
3.2. Challenges on a project and strategies for overcoming them
While the university barriers can prevent academics from participating in cross-sectoral
and multidisciplinary research, things do not get easier once academics are committed to
such research. Collaborative projects have significant coordination and communication
difficulties. In the words of the respondents, they are known for their “high transaction
cost” and “much frustration.” Each project has its war stories of unique difficulties and
challenges. What is common for all of them, however, are the challenges that arise from
the cross-sectoral and multidisciplinary nature of the projects: different work styles, the
need to establish common practices, and delays. These common challenges as well as the
strategies for overcoming them are the focus of this section.