A Tale of Two Visions
Exploring the Dichotomy of Interest between Academia and Industry in
Visualisation
Richard Roberts
1
, Robert Laramee
1
, Paul Brookes
2
, Gary A. Smith
2
, Tony D’Cruze
2
and Matt J. Roach
1
1
Computer Science Department, Swansea University, Wales, U.K.
2
QPC Ltd, Mold, North Wales, U.K.
Keywords:
Visualisation, Industry, Collaboration, Software.
Abstract:
The pairing of a commercial organisation with an academic institution is a typical example of a symbiotic
relationship. Commercial organisations dedicate money, time, and often data into a university project with the
ultimate goal of a financial return on their prudent investments. Academic institutions welcome these relation-
ships as it supports their research in a field where obtaining funding is extremely competitive. Specifically in
the field of visualisation, the culture, visions, and goals of both academia and industry differ in unique ways.
In this position paper we explore the dichotomy of interests between the two groups, based on first hand ex-
perience and interviews, deriving recommendations for any organisation considering entering into a working
relationship with either party.
1 INTRODUCTION
Imagine two organisations. Each has an input, and
each has an output. Both require financial capital as
an input, but their outputs are not the same. The first
organisation outputs a product or service; neatly pol-
ished and saleable. The second organisation outputs
knowledge; packaged in the form of a written docu-
ment or an educated person. The nature of knowledge
is such that it isn’t ever really complete - just further
developed, whereas saleable products should be fi-
nal and complete. The juxtaposition between the two
organisations is so evident that it seems difficult to
imagine a symbiotic relationship developing between
the two.
Despite the duality between the university and in-
dustry operational processes, relationships are often
formed between the groups. To maximise the po-
tential of these relationships, each organisation must
consider how the relationship can be of mutual bene-
fit to for both parties by considering some questions;
What do I expect to receive from this relationship?
What do I expect to provide in this relationship? What
are the deliverables of my project? What are the de-
liverables of their project?
Depending on the subject field, the two groups
have varying degrees of shared interests. For example
the field of oncology is almost entirely research based
(Johns et al., 2003), where the difference between
the industrial component and academic component is
minimal, relationship challenges still remain (Stossel,
2005). However, as we stray away from charitable or-
ganisations and medical groups and move towards the
business-oriented industries we see a shift in motiva-
tion. No longer are the scientific breakthroughs mutu-
ally beneficial to both parties, but instead a dichotomy
appears whereby a business intends to utilise the part-
nership for financial reward, and the academic part-
ner desires to produce publishable research. This isn’t
necessarily incompatible, but the scope and expected
output of each party should be thoroughly discussed
before entering into the partnership.
We have worked with our industry partner since
2013 and have mutually learned a lot from one an
other. Whilst we would describe our working rela-
tionship as positive, we have definitely found that ex-
pectations of each project rarely line up perfectly.
In this paper we explore how the knowledge trans-
fer between the two parties benefits each side. We
identify where businesses can learn from data visuali-
sation practices as well as describe the value of work-
ing with industry has provided us. We examine the
nature of this relationship in the field of data visual-
isation and perform an interview study with our in-
Roberts, R., Laramee, R., Brookes, P., Smith, G., D’Cruze, T. and Roach, M.
A Tale of Two Visions - Exploring the Dichotomy of Interest between Academia and Industry in Visualisation.
DOI: 10.5220/0006635803190326
In Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - Volume 3: IVAPP, pages
319-326
ISBN: 978-989-758-289-9
Copyright © 2018 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
319
dustry parter and others to explore both sides of the
scenario. The result is a set of recommendations both
parties should consider when initiating an academic-
industry relationship.
In the next section we cover related work in this
topic, followed by our analysis of the dichotomy of in-
terest within university/industry collaboration. Then
we present some informal interview studies from both
our industry partners and small business owners who
are at varying stages of university collaboration. We
conclude with an evaluation and recommendations for
any party considering a collaboration.
2 RELATED WORK
The study of this unique relationship spans almost all
of the academic disciplines. Due to the nature of these
studies, the viewpoint is often from the perspective
of the university and not the industry partner. Each
study focuses on a slightly different facet of the rela-
tionship, ranging from motivations and benefits to the
introduction of a third party – the government.
Ankrah and AL-Tabbaa present a systematic re-
view of the literature surrounding this field (Ankrah
and Omar, 2015). Showing the top three publication
venues to be ‘Research Policy’, ‘Technovation’, and
‘R&D Management’. The survey contained 109 ar-
ticles from all areas of academic collaboration with
industry.
Appropriately, a sizeable amount of the university
and industry research focuses on the benefits of their
collaboration. De Fuentes and Dutr
`
enit examine the
long term benefits of these relationships (De Fuentes
and Dutrenit, 2012). The research addressed three pri-
mary questions, why do universities collaborate with
industry? What are the main types of knowledge
transferred? And what are the benefits of the collab-
oration? In this example the industry viewpoint is fo-
cused on, addressing the benefits to companies work-
ing with a university. Chan and Anderson explore
the benefits to academic students when collaborat-
ing together in what they describe as Action Learn-
ing’ (Chan and Anderson, 1994), the paper concludes
by stating that the union of the two groups provide
students with an excellent opportunity to experience
‘real world’ business interactions first hand. The mo-
tivation behind the relationship has also been studied
(Deste and Perkmann, 2011).
Fujisue explores the transfer of knowledge from
academia to industry within a collaborative relation-
ship (Fujisue, 1998). This transfer of knowledge is
important as it contributes to the businesses inputs
to be converted into profit (Friedman and Schwartz,
1975).
Whilst these research papers broadly explore the
nature of university-industry collaboration, this pa-
per focuses specifically on visualisation research in
academia along with the strengths and weaknesses of
such a relationship. It also examines a very specific
relationship - that of Swansea University with QPC
Ltd.
In Ben Shneiderman’s book ‘The new ABCs of
Research’ he encourages the pursuit of real solutions
to real world problems (Shneiderman, 2016). He
highlights the double value that a real world solution
brings to both academia and industry or civic organ-
isation. Shneiderman highlights that the selection of
a project with actionable problems triggers great re-
search.
A panel discussion addressing the themes of in-
dustry and academic partnerships took place at an
event called ”Uncertainty Management & Uncer-
tainty Quantification for Industry” in 2017. At the
panel a range of barriers were discussed that pre-
vent academic contributions from eventually impact-
ing real-world applications. Some of the factors in-
clude, cost, knowledge of customer demand, engi-
neering knowledge, time, computing resources, data
validation and uncertainty, results and interpretation.
Also presented was a phenomenon we call, ”The Soft-
ware Development Death Cycle” which describes the
fate of 99.9% of research prototype software at the
end of a PhD degree (Robert S Laramee, 2017).
3 A TALE OF TWO VISIONS
Consider again those two organisations. Identifying
the standardised processes of inputs and outputs in
these organisations is necessary to create the model
for collaboration. First we will look at each organi-
sation individually and then attempt to merge the two
processes and create a symbiotic model where each
organisation contributes and benefits from the rela-
tionship.
First we look at the industry organisation. Sim-
plified, businesses operate in a state of production,
whereby profit is generated from the creation of a
product or service. Most of this profit is then rein-
vested into the business to grow and expand the busi-
ness. See Figure 1.
This simplified model shows the generated prof-
its reinvested into the company. Some of the capital
will contribute towards research and development or
investment in new infrastructure, and some may be
used to pay the shareholders dividends to encourage
retention of their investors. A significant proportion
IVAPP 2018 - International Conference on Information Visualization Theory and Applications
320
Figure 1: This figure shows the simplified process of busi-
ness. Internally money is invested on many things such as
R&D or marketing, but ultimately profits should be made
on investments through the sale of products. Profits are ei-
ther saved for liquidity, re-invested in the company, or paid
to shareholders (In the case of a public limited company).
of it, however in some way contributes as input back
into the business.
The academic model looks quite different. Specif-
ically in the field of visualisation, the inputs required
are both capital to fund research and access to inter-
esting data. The generated outputs for this model cen-
tre around knowledge, either as an education student
or as a published research paper. See Figure 2.
Figure 2: This figure shows the academic process model for
data visualisation. Unlike industry, it cannot utilise its out-
puts as inputs. The larger organisation makes money from
education, however academic research typically requires
external funding to operate. The outputs of educated peo-
ple and publishable research cannot be directly reinvested
in the organisation.
The standard method of merging these models in
collaboration is for the industry partner to provide
funding and/or data to the university generate research
around a topic. In return, the university should pro-
vide something of value to the industry partner. See
Figure 3. However it is rare for industry funding alone
to be sufficient to cover all costs of collaboration. A
third party funding body is usually required to provide
a large proportion of the capital.
Figure 3: This figure demonstrates the union of both organ-
isations in a symbiotic relationship. Third party funding is
typically necessary to encourage such collaboration.
The method in Figure 3 utilises the outputs of the
industrial partner as well as in the inputs of the aca-
demic partner. Third party funding is often neces-
sary to create the collaboration as industry partners
are sometimes reluctant to invest large amounts of
money in something considered experimental or risky.
Notice the outputs of the academia model are incom-
patible with the inputs of the industry model. A big
question mark remains over what contributions can be
made to industry. How is this gap in the utility work-
flow filled?
3.1 A Case for Collaboration in
Visualisation
In this section, we address how exactly visualisa-
tion research is capable of providing unique value to
a business. The gap in the utility workflow is best
solved by addressing data challenges that the industry
partner faces.
If we look at the strengths and weaknesses of both
the software development industry and academia in
visualisation, the former is structured to create soft-
ware that is saleable. Their staff posses generalised
development skills, with the intention to create a well-
built and durable piece of software. Visualisation re-
search operates with more experimentation in mind,
often utilising quicker development lifecycles that en-
able visualisation ideas to come to fruition quickly.
Moreover the academic researcher has the knowledge
specialisation to know what visualisation methods are
available and which suit the industry partner’s data.
The value of visualisation centres around the idea
of visual data interpretation (Van Wijk, 2005). It’s not
possible for a human to read and understand a large
dataset. Even reducing the data down into statistics
A Tale of Two Visions - Exploring the Dichotomy of Interest between Academia and Industry in Visualisation
321
and reports limits the audience ability to interpret re-
sults. Visualising the data in the right way opens up
interpretation to a broader audience as well as sim-
plifies the important aspects so that analysis can ex-
plore and better understand the data. There is an in-
herent value locked up within real-world datasets, but
the knowledge required to unlock that value is rarely
held. This is where academic research can help indus-
try parters in their data challenges. Both through the
transfer of knowledge from academia to industry, but
also in the creation of visual designs tailored specifi-
cally to the datasets provided by industry. This skill is
not widely taught and so industry staff members are
generally limited in their ability to attempt visualising
complex data without the university support.
Whilst we’ve established that the academic field
of visualisation offers unique value through knowl-
edge and ability to unlock value in large datasets, it
is still unclear what deliverables are beneficial to the
industry partner. Whilst the transfer of information
to industry is useful, it may not fully compensate the
cost of funding a research position. Typically visuali-
sation research involves the creation of new software
that facilitates the analysis of data. If designed for the
use case of industry analysis, then the software could
be handed over to the industry partner as part of the
deliverable. However, research software is unlikely to
be saleable. A company would find it difficult to profit
directly from the software itself, but instead take ad-
vantage of the insights from using the software.
These new insights into industry datasets hold a
unique value. Companies often employ teams of anal-
ysis to discover features in datasets or even validate
theories they may have about the data. Visualisation
offers the ability to discover and explore very large
datasets whereby the output can be interpreted by staff
members beyond just analysts. Therefore we propose
that the most significant contribution to industry is the
outsourcing of information exploration.
3.2 Dichotomy of Interest in
Visualisation
Whilst there is a significant case for collaboration
among academia and industry, there are a number of
cases where the interest of the two organisations di-
verges. We do not consider these to be ‘deal break-
ers’, but we do recommend that they are considered
and discussed before entering into a collaboration ef-
fort.
PhD Research is Niche. If the university funding is
used to employ a PhD candidate in the research, the
goals of that student are mostly fixed around the pro-
posed topic. The researcher will spend long periods
of time working on a number of similar projects in or-
der to complete their studies. This can result in less
interest from industry partners.
Visualisation Research Has to be Novel. The
development of unique visualisation methods may
sound appealing to industry partners. However some
data challenges may best be addressed using already
existing visualisation methods or off-the-shelf tools.
Whilst there is scope for research visualising new
data with old methods, it is not the most desired
form of output from the perspective of the univer-
sity. Developing new visualisation techniques and in-
teractions can improve the output of analysis, but the
time/reward ratio for industry may be unfavourable.
Research Has Necessary Outputs. An absolute re-
quirement of academic research is the publication of
research. The writing of a publishable research paper
is a long process of uncertain duration. Rejected pa-
pers may take years to be published which can be off
putting to potential industry partners who gain very
little from being associated with a high quality pub-
lication. A serious challenge also arises if visualisa-
tions of the industry data cannot be published for data
protection reasons.
Pressure of Profits. Businesses operate with the ab-
solute requirement to make a profit. Academia does
not operate under the same conditions and so the work
requirements place less emphasis on reducing project
overheads. Less creative freedom is allowed within
business software development to streamline the cre-
ation process.
In the next section we discuss a range of informed
opinions from individuals within industry who seek
collaboration with academia and also the views of
academics seeking partnerships with industry to fur-
ther their research.
4 INTERVIEW STUDY
In order to fully evaluate the collaboration sentiments,
we performed a number of interviews with both aca-
demics and industry. During a business technology
conference (dig, 2017) we talked to small business
owners about collaboration opportunities and col-
lected their thoughts and feelings on working along-
side a university for their research. We also inter-
viewed our industry partners to evaluate their expe-
rience of collaborating with us.
Additionally, we discuss industry collaboration
with other academics who have engaged in relation-
ships of this nature so that we can explore both the
visions of both organisations.
IVAPP 2018 - International Conference on Information Visualization Theory and Applications
322
4.1 Industry
Digital Conference. Over the duration of the Digi-
tal Festival we talked with many people from differ-
ent backgrounds about the relationships between busi-
nesses and computer science academia.
We note that so much of the initial relationship be-
tween academics and industry is focused around writ-
ing grant bids. It appears that universities have more
experience in writing these bids and so they poten-
tially have more bargaining power in the negotiations
of the relationship. Third party funding is essential
for relationships with SMEs (Small-Medium Enter-
prise) as these projects are seen as unexplored and a
potential risk.
One technology business owner discussed with us
the reasons he has previously engaged in a university
collaboration - “We realised that universities have in-
vested a lot of money is R&D which has become more
advanced than what’s available in industry. They
have this deep well of knowledge that we can access,
and we’re looking to convert that into saleable prod-
ucts”.
Throughout the conference we demonstrated the
utility of data visualisation at our exhibition stand.
A business employee was interested in the concept
and spoke about how they needed their software to
be more comprehensive in its analsysis, “We want to
be able to visualise our data so that we can monetise
its output. our software is really good but it lacks that
visual component”. Showing the demand for visuali-
sation but the lack of availability for third party fund-
ing may be preventing a number of these relationships
from forming.
Whilst businesses were very keen to instigate a
collaboration, their interest was either in the knowl-
edge and insight a university can offer, or simply
cheap manual labour of software development. The
latter being incompatible with the output of academia.
The former is certainly possible, but the university
would still have academic obligations such as paper
publication. The company would need to provide an
outlet for that, e.g. supply interesting data.
Alternatively, the output of academia is a contri-
bution towards the product. In most cases in the vi-
sualisation world, this would be in the form of a vi-
sualisation design or even the visualisation research
software handed over as a deliverable. This can be
the perfect outcome for both organisations, but intel-
lectual property rights need to be discussed first. Dur-
ing our conversations at the conference, a number of
people raised IP as a potential issue with starting a
collaboration.
Industry Partner Interview. We’ve been collabo-
rating with QPC Ltd. since 2014. During this time
we have engaged in a two-way knowledge transfer,
spending time learning about the operations of the
other party and then developing visualisation software
that utilises their data. We instigated our relationship
through an Innovate UK funding opportunity and con-
tinued our relationship using the KESSII PhD funding
scheme.
We interviewed the key collaborators in QPC Ltd.
to explore their experience in partnering with us.
The central theme was the funding opportunity that
brought us together - “So any commercial business
has to have one eye on its cost, and then how do you
invest that money wisely? What grants and funding
opportunities are available that would create oppor-
tunities we wouldn’t normally have?” We asked them
about the benefits of funding. “What funding with this
type of relationship offers is the ability to finance and
create something new that we would normally have
the opportunity to do - the best example is where we
are today..
We ask what academic collaboration offers to in-
dustry - “Our focus is 100% on things that we can
build to sell. We can’t really focus on anything out-
side of that. With you guys, you have the ability to
step back and experiment to create something differ-
ent which is actually where the real growth comes
from in any business. Reinforcing our ideas about
academic creative freedom. They go on with; “So
in R&D, it’s the research part of the development we
just don’t have the time to do because of the numerous
deadlines imposed upon us..
Another benefit this collaboration offers is a fresh
perspective on insights - “It was also good to have
you guys look our data with a fresh set of eyes. We
didn’t want to guide you too much in the early stages
because we wanted to see what insights you would
make without our biases of what we already know..
They continued; “The visualisations you make always
explore different avenues to the ones we make.
We then ask specifically what we have been able
to contribute over the project duration. “When we first
set up with you guys, we found it to be very compet-
itive. We wanted to keep pace with what you were
teaching us. Knowledge transfer was huge! There
was so much we didn’t know and so we tried to just
absorb as much information as we could... It was
useful to have you guys to provide validation for our
visualisation work to show that we’ve actually done
something unique, and then we could provide valida-
tion for your visualisation work to show that it has a
real world application. .
Whilst our collaboration has been successful, we
A Tale of Two Visions - Exploring the Dichotomy of Interest between Academia and Industry in Visualisation
323
ask about the challenges they have experienced during
the relationship - “I think there’s a bit learning curve
for both parties in this. I think it took longer than
we both expected to complete that knowledge trans-
fer. I felt that by the time it was complete, the In-
novate UK project was almost over. Which is why the
KESSII funding was so great for us so we could start a
new project without the learning curve we previously
had. reiterating the value of third party funding.
When asked what advice they would give to com-
panies starting a collaborative relationship with a uni-
versity they claimed - “The values and objectives of
both entities are very different, they do conflict in a
way. And that’s something that needs to be discussed
and brought into alignment by compromise on both
sides.
One of the interviewees summarised the collabo-
rative experience by stating “It offered us as a small
company a way of complimenting our current skillset
with resources we probably wouldn’t have been able
to afford at any other time.
4.2 Academia
In this section we discuss our own views on academia
industry collaboration in visualisation, as well as per-
form interviews with staff members responsible for
developing collaborative relationships with industry.
From the perspective of academia, collaboration
efforts are usually for the purpose of furthering re-
search. In our discussion with a university staff mem-
ber whose role is to encourage the development of
these relationships, they emphasise that philanthropic
motivations from either organisation are rare. An
academic is unlikely to engage in a collaboration
project that demands complete focus on the business
product without any opportunity for publishable re-
search. Engaging in a knowledge transfer program
from academia to industry also may not benefit the
university. Conversely, a business who invests in col-
laboration where they are unable to utilise any of the
research is also not likely to benefit.
When asked why they thought that university col-
laboration still appealed to businesses, they claimed
that it came down to creative freedom to explore po-
tential solutions to problems. In business, time is
considered money. Which means that any time spent
not working on a direct solution is often considered
wasted. They are not allowed the freedom to explore
new ideas as it seen as a risk whereby money will
ultimately be lost if the research is unfruitful. This
is where academic research becomes appealing, but
also explains the reluctance to invest large amounts
of their own money into the project as it might not
produce the output they desire.
“Industry is rife with rules and regulations, they
are very limited in their creative processes. However
they can outsource their thinking time, buying a cre-
ative research outlet. states the university collabora-
tion staff. “The reason industry moves to academia
is that sometimes they want the credibility of their
knowledge. It comes with the validation of peer re-
view.
Whilst talking to some of the staff members at the
university who are collaborating with industry we no-
ticed a trend in some of the stories. A number of these
relationships attempt to force an unbalanced of work-
load on one party. We were told stories of companies
requesting more time to be invested in generic soft-
ware development projects that cannot further aca-
demic research. Where companies see the collabo-
ration as a cheap source of labour. These stories were
told as a warning to clearly define the boundaries of
the project requirements before entering into collabo-
ration.
Primarily, visualisation research offers valuable
and unique insights into data. The approach used of-
ten looks at the data from a different angle to that of
a standard data analyst due to these creative freedoms
allowed in research. These insights are a valuable de-
liverable for a collaborative project.
5 EVALUATION & CONCLUSION
After spending time talking to individuals who are ex-
ploring potential for new relationships to either fur-
ther their business or to further academic research, we
see that the dichotomy of interests is not insurmount-
able. In fact, a collaborative relationship can be ex-
tremely beneficial to both parties through knowledge
transfers, data insights, and novel research opportuni-
ties.
Below we summarise the primary arguments for
collaboration and outline a number of recommenda-
tions to potential collaborators based on our experi-
ences as well the experiences of our interviewees.
Visualisation Collaboration Evaluation. Creating
a symbiotic relationship between a business and aca-
demic visualisation research organisation can produce
great value for both parties. The academic institution
is provided with an opportunity to explore new and
interesting datasets that would typically be unavail-
able to them. Using these datasets, new visualisa-
tion methods can be devised to explore and unlock
the value held within the data and publish the results.
The collaboration opportunity provides the research
IVAPP 2018 - International Conference on Information Visualization Theory and Applications
324
organisation a funding platform to conduct their re-
search as well as a real world dataset to apply their
skills to. Ben Schneiderman explains this “Choosing
actionable problems triggers great research. Work-
ing on real world problems with real data can lead to
real solutions and enable theory validation in living
laboratories. (Shneiderman, 2016).
The business is provided with an opportunity to
develop visual data analysis tools without the cre-
ative restraint that corporate operations typically im-
pose. More risks can be taken in the research and
so the potential for unique and valuable output is in-
creased. The business will have access to the spe-
cialised knowledge that the university holds which
can be utilised in their own development processes.
Additionally the publishable research the university
creates should contain valuable insights into the busi-
nesses datasets.
Because the process is still seen as a risk, third
party funding is usually a requirement, especially for
SMEs who may not be able to fund external research
entirely by themselves. From the informal interviews
conducted with small business owners and staff mem-
bers, we established that governmental financial sup-
port is a necessity for the development of small busi-
nesses. The future of the UK is uncertain, but we sin-
cerely hope that this vital funding remains available to
small businesses and universities in the United King-
dom as it leaves the European Union.
Recommendations. Below we make a series of rec-
ommendations for entities planning to engage in aca-
demic - industry collaboration;
1. Discuss what contributions each party might bring
to the collaboration.
2. Discuss what personal requirements each party
has for the project. i.e. published papers or
saleable software.
3. Discuss what each party wishes to gain from their
collaboration partner. i.e. knowledge transfer, ac-
cess to data.
4. Firmly establish expected outputs for the collabo-
ration project as well as the deliverables from each
party, placing emphasis on the deliverable from
academia to industry.
Whilst simple, this process helps prevent either
organisation entering the collaboration with any mis-
conceptions as to the requirements of the project. A
common theme among the interviews was a propen-
sity to change requirements or modify deliverables of
the other party over the lifetime the project. This sys-
tem ensures that expectations are managed correctly.
In this paper we have attested the potential for col-
laboration between academia and industry. Although
the two organisations might not align perfectly all
the time, we believe that there is much potential for
valuable research and business development. We are
grateful for the opportunity to work alongside our in-
dustry partner QPC Ltd. and for their contributions
towards our continuing research.
These relationships are valuable because we be-
lieve it is important to implement the knowledge we
develop in the real world. Without it our visualisa-
tion research has less meaning, living only as words
on an unread document in some digital library. We
also benefit from experiencing how industry operates
in the real world, learning about their differing re-
quirements and processes - which helps us align our
creative development to maximise utility in the real
world scenarios. The future of this collaborative re-
lationship is uncertain within the UK. As EU fund-
ing dries up, both industry and academia could suffer
from having this tie cut - especially the small, devel-
oping businesses who might one day become major
contributors to the UK economy.
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