Writing a grant proposal as a team has many pluses—a plenitude of viewpoints, a wider wealth of knowledge to pull from, and a larger pool of resources to help edit and finalize the proposal. Too often, however, a team-written proposal turns out as “Frankenstein’s monster”: a mess of disparate parts, thrown onto the page. Agreement is missing throughout, with no consistency in terms of vocabulary, style, or even tense. So how can a team work together, from day one, to write a successful, cohesive proposal—how do we avoid Frankenstein’s monster?
Interdisciplinary collaboration to tackle complex problems is challenging! In particular, interdisciplinary communication can be very difficult – how do we bridge the gulf of mutual incomprehension when we are working with people who think and talk so very differently from us? What skills are required when mutual incomprehension escalates into conflict, or thwarts decision making on important issues?
It is often at this point that collaborations lose momentum. In the absence of constructive or productive exchange, working relationships stagnate and people retreat to the places where they feel safest: their own disciplines, their offices, or the colleagues who are on their ‘side’. As a consequence, prospects for meaningful collaboration and integration dwindle.
How can conflict be minimised in long-term collaborations where there is the potential to change priorities over time?
Partners who contributed to creating a collaborative initiative or who joined it early might, quite naturally, prefer to look back at the times when they were most influential and able to shape priorities and contribute significantly to achievements in which they believed.
Also, quite naturally, those who joined a collaborative initiative later may prefer to look forwards towards new approaches and ways of doing things that might increase their influence and enable them to shape priorities and achieve things important to them.
What are the key lessons for building a successful collaborative team? A new version of the Collaboration and Team Science Field Guide (Bennett et al., 2018) provides ten top take aways:
It is almost impossible to imagine a successful collaboration without trust. Trust provides the foundation for a team. Trust is necessary for establishing other aspects of a successful collaboration such as psychological safety, candid conversation, a positive team dynamic, and successful conflict management.
How can we improve interdisciplinary collaborations? There are many lessons to be learned from the Science of Team Science. The following ten lessons summarize many of the ideas that were shared at the International Science of Team Science Conference in Galveston, Texas, in May 2018.
1. Team up with the right people
On the most basic level, scientists working on teams should be willing to integrate their thoughts with their teammates’ ideas. Participants should also possess a variety of social skills, such as negotiation and social perceptiveness. The most successful teams also encompass a moderate degree of deep-level diversity (values, perspectives, cognitive styles) and include women in leadership roles.
How can undergraduate and graduate students be helped to build their interdisciplinary collaboration capacity? In particular, how do they build capacity between the arts and other disciplines?
In 2018, I co-facilitated the annual, 3-day Emerging Creatives Student Summit, an event for approximately 100 undergraduate and graduate students from 26 universities organized by the Alliance for the Arts in Research Universities. Students’ majors ranged from the sciences, engineering, music, arts, and design.
By Sanford D. Eigenbrode, Lois Wright Morton, and Timothy Martin
What’s required to lead exceptionally large projects involving many dozens of participants from various scientific disciplines (including biophysical, social, and economic), multiple stakeholders, and efforts spanning a gamut from discovery to implementation? Such projects are common when investigating social-ecological systems which are inherently complex and large in spatial and temporal scales. Problems are commonly multifaceted, with incomplete or apparently contradictory knowledge, stakeholders with divergent positions, and large economic or social consequences.
Leaders of such very large projects confront unique challenges in addition to those inherent to directing interdisciplinary efforts:
By Dena Fam, Abby Mellick Lopes, Alexandra Crosby and Katie Ross
How can transdisciplinary educators help students reflexively understand their position in the field of research? Often this means giving students the opportunity to go beyond being observers of social reality to experience themselves as potential agents of change.
To enable this opportunity, we developed a model for a ‘Transdisciplinary Living Lab’ (Fam et al., forthcoming).
By Katrine Lindvig, Line Hillersdal and David Earle
How can we resolve the stark disparity between theoretical knowledge about interdisciplinary approaches and practical applications? How can we get from written guidelines to actual practices, especially taking into account the contextual nature of knowledge production; not least when the collaborating partners come from different disciplinary fields with diverse expectations and concerns?
For the past few years, we have been developing ways in which academic theory and physical interactions can be combined. The result is CoNavigator – a hands-on, 3-dimensional and gamified tool which can be used:
for learning purposes in educational settings
as a fast-tracking tool for interdisciplinary problem solving.
CoNavigator is a tool which allows groups to collaborate on a 3-dimensional visualisation of the interdisciplinary topography of a given field or theme. It addresses the contextual and local circumstances and the unique combinations of members in collaborative teams. CoNavigator is therefore short for both Context Navigation and Collaboration Navigation. The process of applying the tool takes around 3 hours.
CoNavigator is composed of writable tiles and cubes to enable rapid, collaborative visualisation, as shown in the first figure below. The tactile nature of the tool is designed to encourage collaboration and negotiation over a series of defined steps.
Making the Tacit Visible and Tangible
Each participant makes a personal tool swatch. By explaining their skills to a person with a completely different background, the participant is forced to re-evaluate, re-formulate, and translate skills in a way that increases their own disciplinary awareness. Each competency that is identified is written onto a separate tool swatch.
Human groups and societies have built many kinds of bridges for centuries. Since the 19th century, engineers have designed complex physical structures that were intended to serve one or more purposes in precise situations. In essence, the construction of a bridge is meant to join two places together. What may appear as a mundane functional structure is built only after numerous decisions have been made about its appearance, cost, functions, location and structure. Will a bridge serve only as a link and passage, or will it serve other functions?
In discussing three things the transdisciplinary research community can do to build bridges, I use “building bridges” as a metaphor. I discuss a bridge as a human-made artefact that is attributed meaningful form. It is created intentionally for one or more purposes.
One toolkit provides concepts and methods relevant to the full range of transdisciplinary research, while the others cover four key aspects: (i) collaboration, (ii) synthesis of knowledge from relevant disciplines and stakeholders, (iii) thinking systemically, and (iv) making change happen.
How can you improve your thinking – alone or in a group? How can mapping ideas help you understand the relationships among them? How can mapping a conversation create a new reality for those involved?
In what follows, I draw on the work of Daniel Kahneman’s (2011) best-selling book Thinking, Fast and Slow, which explains how human thinking occurs at different speeds, from the very fast thinking associated with face-to-face conversation to the very slow thinking associated with assembling information resources into encyclopedias. I use those ideas in my descriptions of knowledge maps.