Teamwork has long been a part of computing research, but now advanced technologies and widespread proficiency with collaboration technologies are creating new opportunities. The capacity to share data, computing resources, and research instruments has been growing steadily, just as predicted when Bill Wulf coined the term "collaboratories" a quarter of a century ago.2,15,16
Teamwork has become the overwhelmingly dominant form of research, so rewarding effective teams, teaching our students how to collaborate, and supporting research on what works and what doesn't have taken on new importance.
In recent years, the tools for locating relevant documents, finding team members with special skills, coordinating schedules, and refining reports collaboratively has grown substantially.7 In addition to these technology advances, the willingness and fluency with which young researchers appear to use video and audio conferencing, curated datasets, shared document editors, task managers, and other collaboration tools grows steadily.
Another driving force for teamwork and larger group collaborations is what I see as the increased ambition of team members and the growing expectations from research leaders. Teamwork brings more than larger capacity for work; it opens new possibilities when different disciplines, research methods, and personalities are fruitfully combined.6 In short, research teams of two to 10 members and larger groups of hundreds of researchers, can accomplish much more and conduct higher quality work than they could just two decades ago when the Internet was a novelty.10
The growth of research teams was well documented in a series of papers by Wuchty, Jones, and Uzzi.5,13,14 They reported that from the 1950s to 2000 the average number of journal paper co-authors in science and engineering grew from 1.9 to 3.5. They also showed that the impact as measured by journal citation counts increased as the number of authors grew. Furthermore, the benefit of teamwork grew over time. In 1955, team papers attracted 1.7 times as many citations as solo-authored papers, but by 2000 the advantage grew to 2.1 times as many citations, suggesting that technologies and teamwork skills had enabled teams to be more effective than they were in the past.
A study of the papers for the ACM SIG-KDD 2014 Conference, by program chairs Jure Leskovec and Wei Wang, added evidence of the benefits of teamwork. The reviewer ratings of the 1,036 submitted papers increased steadily for papers with up to five co-authors, then remained level. Reviewer ratings may be imperfect, but this bit of evidence seems potent, especially since this conference had an impressively rigorous acceptance rate of approximately 14%. Another outcome was tied to the ratings for papers. Those papers whose authors included a mix of academics and business practitioners had statistically significantly higher ratings than papers whose authors were either all academics or all business practitioners. This added to the evidence that diversity in teams is a catalyst for high quality.8
However, teamwork has downsides, requiring extra coordination among collaborators, learning new disciplines, adjusting to fresh research methods, and accommodating different personalities.4 These downsides mean that those who engage in teamwork will need to learn how to do it effectively, so as to attain the full benefits.
The interest in research teams and larger groups has now accelerated with the publication of the National Academies report Enhancing the Effectiveness of Team Science.3 This report adds recent evidence that teams and larger groups are a growing phenomenon in science and engineering research, where multiple authorship has risen to 90% of all papers in 2013.
The report makes another useful contribution by characterizing seven dimensions that challenge today's research teams (see the accompanying table). Teams on the left side of the range are easier to manage, while teams on the right side of the range are more difficult to manage, suggesting that these deserve more study.3 The report offers suggestions of how to improve team processes and calls for increased research on teams and larger groups.
Teams and larger groups of academics and practitioners seem likely to be more effective in choosing meaningful problems, forming successful research plans, and in testing hypotheses in living laboratories at scale. Teaming between applied and basic researchers is likely to be a growing trend, as indicated by a recent National Science Foundation program announcement, Algorithms in the Field:11 "Algorithms in the Field encourages closer collaboration between two groups of researchers: (i) theoretical computer science researchers, who focus on the design and analysis of provably efficient and provably accurate algorithms for various computational models; and (ii) applied researchers including a combination of systems and domain experts."
Teamwork between academics and practitioners can have strong benefits, as does multidisciplinary collaboration within academic communities. A clear testimonial for joint research bridging computer science and other disciplines comes from David Patterson's review of his 35-plus years running research labs on computer systems: "The psychological support of others also increases the collective courage of a group. Multidisciplinary teams, which increasingly involve disciplines outside computer science, have greater opportunity if they are willing to take chances that individuals and companies will not."9
Patterson concludes with his vision of the growth of multidisciplinary teams: "Whereas early computing problems were more likely to be solved by a single investigator within a single discipline, I believe the fraction of computing problems requiring multidisciplinary teams will increase."
There is always room for solitary researchers who wish to pursue their own projects. There are substantial advantages to working alone, but those who learn team skills are more likely to become part of breakthroughs than those who go it alone.
A near-term impediment to teamwork is the difficulty that researchers expect to have when facing hiring, tenure, and promotion committees, who are perceived as having trouble in assessing individuals who contribute to teams. Even team members who have participated in many award-winning papers fear they will find it difficult to convince review committees of their contributions. Being a first author helps gain recognition, as does documenting the role of each team member in the acknowledgments section. Writing a single-author paper, when this is warranted, may also help in many disciplines.
In light of the growing interest in teamwork, appointment, promotion, and tenure committees would do well to update their methods for documenting and assessing teamwork, so as to encourage and reward effective team participation and leadership. One example to follow is the University of Southern California, which has developed guidelines to emphasize a variety of forms of collaborative scholarship and to introduce attribution standards for contributions to larger projects.12
A second step, for computing educators, would be to increase teamwork training and experiences, so as to raise the quality of students' work. Team projects in undergraduate and graduate courses would train students in using collaboration tools and nurture their communication skills for future professional or research jobs. The National Academies report makes many recommendations that need to be tailored to fit local computing cultures and the seven dimensions on which today's research teams differ in complexity.
A third step, for government agencies, would be to increase funding to study computing research teams so as to enable leaders to form and manage successful teams. Teamwork is difficult since it requires different skills than working alone, but the potential for greater impact makes teamwork attractive. A strong research agenda would include applied and basic components to understand which incentives and rewards best amplify success within the seven dimensions of the National Academies report.
1. ACM 2014 Conference on Knowledge Discovery and Data Mining (ACM-KDD); www.kdd2014.org
3. Cooke, N.J. and Hilton, M.L., Eds. Enhancing the Effectiveness of Team Science. National Academies Press, Washington, D.C. (2015); http://www.nap.edu/19007
11. U.S. National Science Foundation Program on Algorithms in the Field (AitF); http://www.nsf.gov/pubs/2015/nsf15515/nsf15515.htm
12. University of Southern California, Guidelines for Assigning Authorship and for Attributing Contributions to Research Products and Creative Works (Sept. 16, 2011); http://www.usc.edu/academe/acsen/Documents/senate%20news/URC_on_Authorship_and_Attribution_20110916.pdf
16. Wulf, W.A. The National CollaboratoryA White Paper. In Towards a National Collaboratory, the unpublished report of a workshop held at Rockefeller University, March 1718, 1989 (Joshua Lederberg and Keith Uncapher, co-chairs).
Thanks to the anonymous reviewers and readers of early drafts, including Nancy Cooke, Gerhard Fischer, Kara Hall, Margaret Hilton, Judy Olson, Scott Page, Dave Patterson, and Jennifer Preece.
The Digital Library is published by the Association for Computing Machinery. Copyright © 2016 ACM, Inc.
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