IEEE Systems, Man and Cybernetics Magazine - October 2019 - 12

and taught to think about problems in a transdisciplinary
Foundational Recommendations for
manner. In some ways, this training lowers the barrier for
Transdisciplinary SMC Research
entry into transdisciplinary work because it allows trans-
The following eight recommendations are foundational to
disciplinary cognition to become second nature.
ensuring that SMC sustainably promotes transdisci-
The interdisciplinary training of
plinary work (Table 1). Almost all
future SMC scientists is not a want
of these recommendations stem
but a need. The work conducted in
from my own experiences. They
this community often requires a
are not meant to be exhaustive.
The interdisciplinary
working knowledge about multiple
During the preparation of this
training of future SMC
domains of a particular problem. A
article, many more were generat-
researcher could certainly collabo-
ed, but these are viewed as the
scientists is not a
rate with others who have different
most critical.
want but a need.
expertise, but there will be issues
that stem from that. Instead, hav-
Academic Training
ing someone who was formally
There is a reason for presenting
trained to possess expertise in
academic training first. Simply, the
multiple areas will most likely lessen the overhead often
question of how we train the next generation of scientists
required for collaboration. Take, for example, high level,
should be our starting point. More specifically, we need
human-computer interaction. Only having knowledge per-
more scientists whose educational training is interdisci-
taining to the human/social aspects without a working
plinary to begin with. This means that we need more peo-
knowledge of associated technology is not enough. Failing
ple who specifically study one area for one degree and
to understand the back end of a piece of software will lead
then study another area for their next degree, and more
to inadequately designing a humancentric front end due to
people who seek out specific degree programs that are
lack of knowledge pertaining to the limitations or chal-
interdisciplinary are also imperative. In recent years, there
lenges of the back end. Scholars do not have to be experts
has been a push to create more of these interdisciplinary
in both, but there is value in having a working knowledge
educational degrees, but there is a severe need for more
of each aspect.
(for additional information on new models of academic
In general, we need leaders in the SMC community to
training, see [4] and [5]; and for a historical review of these
promote the importance of interdisciplinary academic
types of programs, see [6]). There is something to be said
training. For the most part, we must move away from
about someone who is trained on interdisciplinary content

Table 1. Eight foundational recommendations for transdisciplinary SMC research.
Recommendation

High-Level Description

Academic training

Students need to be trained from an early age to think from the perspective of multiple
disciplines, and more specific programs must be developed that seek to do this at all
educational levels.

A shared and common language

A shared and common language is necessary for transdisciplinary work to be successful.
People must seek out a shared word repository that is used across scientific domains.

The actual need for transdisciplinarity

Not all scientific work is transdisciplinary. There has to be a root cause shared among
disciplines to put together an interdisciplinary team and study a topic in a
transdisciplinary manner.

Problem space requirements

The scientific problem at hand dictates whether it is transdisciplinary, and that problem
must be looked at in detail to identify this issue.

Shared spaces and mechanisms

Transdisciplinary work should allow people to interact in a shared manner. Interaction
is at the core of making transdisciplinary work successful, and spaces need to be
developed that allow for this interaction.

Team science and cognition

Transdisciplinary work requires an understanding of both team science and
team cognition.

Credit

Better methods are required to acknowledge and provide credit to people (both in
academia and industry) working on transdisciplinary projects.

Metrics to measure transdisciplinary
performance

Improved metrics are needed to evaluate the performance of those who work in
transdisciplinary projects.

12

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IEEE Systems, Man and Cybernetics Magazine - October 2019

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