Initial principles and their implementation
Dina, Danish Informatics Network in the Agricultural Sciences, was
established in 1991 with the objective to enhance interdisciplinary
research in applications of informatics in agricultural research. This
was supposed to embrace the use of mathematical, statistical and
computer science methods.
The challenge
The background for the creation of Dina was the development in the
1980's: New demands were facing agriculture and agricultural research,
and at the same time the IT technologies were developing rapidly, thus
offering new potentials. These reasons in combination called for the
application of professionel computer science methods in agriculture.
There had been a long tradition for interaction between statistics and
agriculture under labels such as biometry and biostatistics, but a
similar tradition did not exist with computer science or with
mathematics, at least not to an appropriate extent. Mainframes and
central databases related to statistical calculations and to animal
breeding and production were already in use. But the development of
personel computers and computer networks opened up a whole range of
new possibilities that demanded new expertise on models, on algorithms
and on programming principles.
Ib Skovgaard, a leading figure of the The Danish Farmers' Association,
was instrumental within the Ministry of Agriculture in drawing
attention to these matters. A model organisation was the Biometric
Research Unit attached to the medical faculty at Copenhagen University
and headed by Prof. Niels Keiding. Another inspiration came in the
early 1980's when Prof. Dines Bjørner, DTU formulated a proposal for a
national strategy for informatics.
The following citation is from one of the original documents leading
to the formation of Dina, viz. the National research council SJVF's
preparatory paper, Nov. 2 1989; it indicates a clear understanding
that new expertise and new collaboration were needed:
"It is necessary to concentrate the informatics effort within
agricultural science ... Major tasks for the center will be the
training of researchers and making contact to the informatics
environments at the universities. In addition the center should
establish an integrated cooperation with the agricultural profession,
the advisory system and the attached industry. ... In areas such as
sensors, communication and process control we suggest that
agricultural research cooperates with the technological
environments... To reach significant results it is necessary to make a
large and well-targeted effort over several years ... To ensure a
smooth cooperation between the local centers, high-speed electronic
connections must be established in order to transfer data, including
images ..."
At that time it seemed doubtful whether computer science expertise
could be built up in the center or at KVL, cf. this citation from
Dina's first letter of intent, Oct. 16 1990:
"It could not be regarded a realistic possibility to create a solid
basis of expertise in data processing at the center. Yet it is
imperative to ensure the professionel environment through a close
contact to the university environments in data processing."
However, as shall become apparent later, it still turned out to be
possible to build up such expertise at KVL, and to attract computer
scientists to be employed at DJF, Foulum.
On April 11 1991 the final project description was submitted. During
this period, the agricultural focus was changing - from efficient
production and optimal economic outcome, to obtaining a sustainable
agriculture. Mikkelsen (1994) listed the main challenges:
- Agriculture and environment
- Overproduction concerning certain products
- Reduction of production costs
- Product diversification and product quality to meet consumer
preferences
- Land use and rural development
and he continued:
"The agricultural and related sciences are reformulating their
priorities to meet these challenges in their research
programmes. However the results tend to become increasingly complex
and hence difficult to apply. It is important to develop and use
information theory and technology in order to overcome this
difficulty. One way is to incorporate the new knowledge in efficient
decision support systems. Also the technological development in
communication chains, electronic sensors and actuators offer brand new
possibilities to agricultural production and management, possibilities
that can lead to new ways of meeting the above-mentioned
challenges. Finally, the increasing use of informatics on the farm
level, on the equipment and machinery level and on the agro-industry
level will increase the need for data communication drastically, and
there is therefor a need to improve the information infrastucture
significantly."
In the SJVF 1989 paper cited above, the challenges from IT were seen
in the following way:
"Informatics should enable us of applying the achievements of
IT to carry out tasks concerning: Measurement and data registration;
Storing of information and data; Data processing; Planning, steering
and control of processes, production and logistics as well as of
communication, dissemination and decision."
Around 1990 PC's and other computers were still expensive, and over
200.000 DKR were spent for the first server to Dina's UNIX
network. Today we buy far better PC's at 20-30.000 DKR. But equipment
was already starting to become faster and cheaper. At the same time,
old and well-known but previously unviable algorithms were implemented
and new methods developed that could take advantage of the new
computing potentials. New methods in genetics, statistics and decision
support became practicable due to fast calculation and
communication. For example, weather forecasts using radar images via
the internet was unimaginable in 1990 but is today a natural facility,
among other in Pl@nteInfo.
Challenges continue to change. Emphasis in agricultural research now
also includes ethics and animal welfare; new items such as
bioinformatics, DNA mapping, biodiversity, GMO safety, environmetrics
and genomics turn up in the media and the public agenda; and so do IT
innovations such as cellular phones, microchips and new types of
sensors. The need for informatics and IT is larger and more apparent
than ever.
Starting point and initial achievements
The starting point for Dina was in fact two pre-Dina projects - one on
image processing (M. Rudemo / SJVF) and one on databases in
agriculture (M. Flensted-Jensen /Ministry of Agriculture; see case box
"The SFD project"). Out of the latter grew a project on so-called
Expert Systems; it was financed by The Ministry of Agriculture and
attempted to use AI, Artificial Intelligence principles but since this
turned out to be rather unrealistic, focus soon changed to what is now
called DSS, Decision support systems, and for a long time DSS was the
buzz-word. In fact many Dina projects still are on the borderline
between modelling of agricultural systems and using models and other
information sources to create DSS'es.
From the start of Dina much emphasis was on PhD education; 7 PhD
scholarships were quickly given out and the students were offered
specially designed courses in computer science, based on an exchange
agreement between KVL and DTU (see later). Thus research education
with a multidisciplinary PhD training programme was established. Many
went through with the education; their PhD projects were carefully
chosen so as to be concerned with important agricultural applications
but also to deal with new and interesting informatics topics. The
tables in the Annex illustrate the success of this PhD programme.
As part of the PhD programme and in relation to the senior scientists
in Dina, several research projects were carried out. Though, in the
first period the main results were obtained through the PhD
projects. - Some of the Dina related research projects are further
elucidated as 'Cases'.
Initially, the research projects related to Dina were handled in a
strict structure of intertwined informatics and agricultural domains,
and for each project there would be a scientific committee with one
scientist from informatics and one from agriculture. This practice has
later been somewhat relaxed, but to be considered a good Dina project
it must still satisfy the double claim of being interesting from an
informatics point of view but also deal with important agricultural
issues. See the table of first-generation Dina related PhD projects.
Organisation and Networking
Dina soon had a significant effect within the participating
institutions, but also on the institutional and personal relations
between agricultural sciences and informatics disciplines at the other
Danish universities. A seemingly minor but not unimportant point was
that great care was taken in choosing a design and that the Dina logo
became registrered.
The initial participants were SP, SH, AAU and KVL, cf. Table 1 in the
Annex. Primary funding came from the Research Councils through the
PIFT-programme, and from The Ministry of Agriculture through the
projects described above. The organisation included an advisory board,
the PhD arrangement, and regular workshops / thematic days organised
for Dina's scientists but open to others. Emphasis was put on creating
an electronic communication infrastructure, based first on a UNIX
network, next also on the Internet, and soon after on web-technology
which was just emerging.
On the initiative of Dina a video-link was established between KVL and
Foulum. An early starter with this technology, Dina ran into some
beginner's trouble, but the link quickly became an indispensable tool
in the communication within the network. Later video-link facilities
were established at several other universities and institutions.
The network cooperation soon extended internationally through an
EU-concerted action EUNITA, European Network for Information
Technology in Agriculture, initiated mainly through the work of
Dina. This network led to common research projects and later also to
the establishment of EFITA and DSIJ, see below.
Collaboration grew with other universities, research institutions and
with DAAC, Danish Agricultural Advisory Center, and it became natural
to invite new members into Dina which has today 7 nodes, that is,
units at 7 different member institutions; see the following chapter
for an introduction to the nodes. All along this expansion process,
the networking principles were carefully considered. Dina is not an
institution but a network / a consortium of institutions, so it was
made clear that all Dina activities shall take place within, or in
collaboration between, existing institutions, and that all activities
must be visible in the budget.
There was some initial confusion about the concept of 'associated
projects' which made it unclear what Dina could take responsibility
for, or the honor for. In 1996-97 Dina was reorganised under a
carefully designed set of by-laws, such that today Dina has a legal
and formalised status, but still the essential original ideas have
been kept up.
Dina was evaluated favorably in the international mid-term evaluation
of the PIFT programme. Some recommendations were given, in particular
to strengthen the involvement of professional computer
scientists. These recommendations were taken seriously and the
resultant changes were successfull, see later.
Apart from its specified tasks, that is, working with research
education and specific research projects and performing network
functions, Dina also feels obliged to be an analysing, debating,
inspiring and initiating organism rooted in existing research
environments. It is Dina's ambition to have a catalyzing effect on the
development within all its member institutions.
"The fathers of Dina had providence. What we now consider to be in the
nature of things was not so in those days."
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