=Paper=
{{Paper
|id=Vol-2030/HAICTA_2017_paper8
|storemode=property
|title=Agroforestry Usage, Building Knowledge Databank for Agroforestry Training and Education
|pdfUrl=https://ceur-ws.org/Vol-2030/HAICTA_2017_paper8.pdf
|volume=Vol-2030
|authors=László Várallyai,Miklós Herdon,Charles Burriel,Szilvia Botos
|dblpUrl=https://dblp.org/rec/conf/haicta/VarallyaiHBB17
}}
==Agroforestry Usage, Building Knowledge Databank for Agroforestry Training and Education==
https://ceur-ws.org/Vol-2030/HAICTA_2017_paper8.pdf
Agroforestry usage, building Knowledge Databank for
Agroforestry training and education
László Várallyai1, Miklós Herdon2, Charles Burriel3, Szilvia Botos4
1
University of Debrecen, Business and Economics Faculty, Applied Informatics and Logistics
Institute, Hungary, e-mail: varallyai.laszlo@econ.unideb.hu
2
University of Debrecen, Business and Economics Faculty, Applied Informatics and Logistics
Institute, Hungary, e-mail: herdon.miklos@econ.unideb.hu
3
Agrosup Dijon, Institut national supérieur des sciences agronomiques, France,
e-mail: charles.burriel@educagri.fr
4
University of Debrecen, Business and Economics Faculty, Applied Informatics and Logistics
Institute, Hungary, e-mail: botos.szilvia@econ.unideb.hu
Abstract. The Agrof-MM Erasmus+ project reinforces the AgroFE project that
ended in 2015. The objective of the Agrof-MM project is to train European
agricultural stakeholders in agroforestry practices. The project will give them
the opportunity to familiarize themselves with agroforestry, and to improve
their knowledge of it, in order to work towards the development of
agroforestry in the Mediterranean and mountain regions of Europe. Thus it
widens the geographical scope and improves the level of training of the AgroF-
MM project, as well as addressing new stakeholders from 15 partners. The
paper describes the knowledge databank system prototype for Agroforestry
training and education. The knowledge databank is a component of the project
training system. It aims to gather and share a set of documents, resources that
partners can use and which will have been accessed by learners and the public
users. These resources are under different forms: Mono document objects and
Composite materials.
Keywords: Agroforestry, Knowledge Databank, Education, Training.
1 Introduction
In last decades regional growth of arable land has a significant effect in global and
European land use, thereby reducing the percentage of natural forest area. In Europe
are 29% croplands, and in Central and Eastern Europe in Hungary arable land ratio is
near to 50%, which is much higher than the European average. The global
environmental problems justify the necessary of forestation in each country.
However, this causes conflicts of interest between the agricultural and environmental
sectors. Solution of the conflict management may increase the agroforestry land use,
which means ecologically mixed land use. The European Stakeholders has accepted
that agroforestry has special ecological system.
54
The aim of the AgroF-MM (Agroforestry Education, Mediterranean and
Mountains areas) project is to play an important role in Agroforestry trainings.
Depending on the European countries, states or professional organizations and
training actors try to reintroduce Agroforestry in the course of training and
qualification in initial training and in adult education.
The aim of the Agrof-MM project is to involve farmers, future farmers, advisors
and stakeholders in Agroforestry. This agricultural system has experienced a strong
abandonment in the 20th century, to count today only a few million ha in Europe
(Nair, 2005). Following the work of scientific research, development structures and
the experiments of some professionals in recent years agroforestry has met a true
national and European recognition.
Depending on the countries, states or professional organizations and training
actors reintroduce Agroforestry in the course of training and qualification (Jamnadass
et al., 2014) in initial education (Vocational Education Training) and in adult training
(Jongmans, 1996). Based on the results of scientific research, development structures
and those of the ”farmer-researchers”, experimental courses were conducted in
different countries, including France, in the United Kingdom or in Italy, on a small
scale, as resources, trainers and available skills are scarce. It is on these four
components: the results of scientific research, professional practice formalized
training based on business situations (Gunn, 2010), innovative teaching resources,
the transfer from past AgroFE project (the AgroF-MM project is based on the
AgroFE). In the partnership countries, the need for conversion and development is
between 25,000 and 30,000 farms (Price, 1995) in the next 5 to7 years (Gregorio et
al., 2015), which means training 25,000 to 30,000 farming managers (L4 to L6 level
by country) as well as the same number of workers and ”small farmers”, on L2-L3-
L4 level by country.
1.1 Organized trainings in the project
The core of the EQF (European Qualification Framework) concerns eight reference
levels describing what a learner knows, understands and is able to do (learning
outcomes). Levels of national qualifications will be placed at one of the central
reference levels, ranging from basic (Level 1-L1) to advanced (Level 8-L8). This will
enable a much easier comparison between national qualifications.
But in order to achieve, to support these conversions, these profound changes in
modes of practical production, we need counsellors-advisors, trainers, specialists and
unfortunately the level of human resources is low. The partners have identified
training needs in the short term (Ghirardini, 2011): These needs are on the one hand
farmers and future farmers, adults and pupils (Kuhn, 1996) - students, on the other
hand, middle managers and teachers-counsellors-specialists (Mbow et al., 2014).
These requirements therefore relate to two levels of qualification L2-L3-L4 L5+/L6
and 3 types of learners (target groups) (Várallyai and Herdon, 2013):
• students (in VET - Vocational Education Training) and adults, small farmers,
future farmers and workers in farming on the one hand, mainly L2-L3 level,
sometimes L4 level,
55
• the farmers and future farmers (in larger farms) and middle management, mainly
L3-L4-L5 level, sometimes L5 level,
• the advisors-teachers-specialists, mainly level L5+L6,
In the short term, the project will address these 4 needs / three publics through an
AgroF-MM training system established by the partners, partly based on the AgroFE
Leonardo project, the development of the EU AgForward RTD (AGroFORestry that
Will Advance Rural Development, Research and Technological Development) 7th
research, the EURAF (European Agroforestry Federation) EU research association
and its working groups, and the outcomes from the French RMT and Casdar
(Fertilisation and Environnement- Frnch acronym) programme. The project would
be built on innovative teaching and training practices (Gamboa et al., 2010), France,
United Kingdom, Italy, Greece, for instance on professional situations providing
(training and certification at the workplace), access to recognized qualifications
(NQF - National Qualification Framework, EQF - European Qualification
Framework, ECVET - European credit system for vocational education and training,
ECTS - European Credit Transfer and Accumulation System), a process based on
”russian dolls” (Bustos et al., 2007; Herdon and Lengyel, 2013; Herdon and Rózsa,
2012), the certified and accredited inferior level giving access to the superior one.
1.2 Knowledge Databank overview
Supporting the agroforestry development (training on different levels (Mbow et al.,
2014; University of Missouri, 2015), extension activities, farming) in Europe one
important aim of the AgroFE (http://agrofe.eu) and the Agrof-MM
(http://agrofmm.eu) European projects is to build a knowledge databank to help the
players with agroforestry knowledge. A knowledge base or knowledge bank is a
special kind of database (Glick, 2013) for knowledge management. A knowledge
base is an information repository that provides a means for information to be
collected, organized, shared, searched and utilized. It can be either machine-readable
or intended for human use. Behind a Knowledge DataBank (KDB), there is, at least,
a back-end which is based on a special DBMS. Due to the high level of enrichment, a
KDB is more than a documentary base or a document management system.
The knowledge management (KM) is used to describe the creation of knowledge
repositories, improvement of knowledge access and sharing as well as
communication through collaboration, enhancing the knowledge environment and
managing knowledge as an asset for project partners and public. The central element
of the KM is the KDB. For building and using the KDB knowledge engineering is
needed. Organizing and storing the knowledge (represented in different content and
forms: documents, videos, photos, etc.) it is need to classify them by using
knowledge representation technologies. In the project the Dublin-Core (Weibel,
2005; Lubas et al., 2013), LOM (Learning Object metadata), Technical metadata and
the Agroforestry thesaurus are used (Castro-García and López-Morteo, 2013;
Manouselis et al., 2010).
The very important part of the development to define the AgroF-thesauri in very
detail because the word in this vocabulary links to different object (document,
lecture, presentation, videos, etc.) in the KDB. This thesauri system has been
56
developed by a working group in the project using ontology. Unfortunately the
AGROVOC Multilingual agricultural thesaurus and other system don’t contain terms
for agroforestry in details (Rajbhandari and Keizer, 2012).
2 Objectives and development methods
The main objectives are to make a synthesis of needs and expectations. The work
based on the present existing training actions and to set up a common framework.
Within this framework the target is to build an innovative training system
(contextualized, modularized trainings, use of ICT (Information and Communication
Technologies), professionals participation), to create a technical collaborative
support for the implementation of the project with communication tools (information
of partners and promotion) and providing access to the resources and training
services during and after the project (knowledge databank, interactive services). To
achieve these objectives the following main activities had to be carried out (Dosskey
et al., 2008):
• Exploitation of the tools and services;
• Building a collaborative working environment;
• Planning the architecture for development, teaching and training;
• Implementing the e-learning environment (Lengyel and Herdon, 2009);
• Designing the multimedia tools to make the system accessible for learners and
trainers.
• Based on different methods we have built a collaborative working environment
for the project partners and players who will join to this knowledge database and
information service. We used the following methods (do the following
activities):
• Using the experiences from former project and practice;
• Studying new technologies and methods;
• Developing Agroforestry courses;
• Evaluating them;
• Selection.
3 Results
3.1 Knowledge Databank System architecture (KDB)
A knowledge base or knowledge bank is a special kind of database for knowledge
management. A knowledge base is an information repository (Beddie and Halliday-
Wynes, 2010) that provides a mean for information to be collected, organized,
shared, searched and utilized. It can be either machine-readable or intended for
57
human use. Behind a Knowledge DataBank (KDB), there is, at least, a back-end
which is a DBMS.
The developed system architecture can be seen on the Fig. 1.
Fig. 1. Knowledge Base System architecture
In the context of the AgroF-MM project, the used Information and
Communication Technologies (ICTs) include four components: the collaborative
tools, the Knowledge DataBank, the tools for training and archiving and a portal that
integrates the tools.
The KDB, is to enable the sharing, access and consultation in the use of certain
resources for training. These resources are under different forms:
• Mono document object, like a photo, a text, a diagram.
• Composite materials, for example an html web page with images, “pdf” files
with pictures and diagrams, a video clip, with images and sounds, etc.
Under the project, these documents are identified, selected, proposed by partners
and included into the KDB for the evaluation of their potential use in training, by one
or more partners. A fact sheet originally written by the proposer, the institution, who
proposed it to project partners, often accompanies, completes this document.
At the end of the evaluation phase, the KDB can be extended to other contributors,
for other uses, such as exchange supports between different actors of Agroforestry.
3.2 Objectives of the KDB
There are more objectives of the KDB, which are the followings:
58
• Storing elements of knowledge, sources of technical and professional
information in relation with the domain, elements, components that could be
usefully used in education and training;
• Making professional experiences accessible to learners, students, adults in
training, experiences under the form of documents, videos, evidences, keynotes;
• Allowing the diffusion of knowledge under the form of apprenticeship modules,
together or linked to education and training platform;
• Being one of the support tools for the curricula and trainings established,
developed by the project, proposed to students, to adults, target;
• Allowing to professors, trainers, instructors to develop innovative curricula,
educations pathways, new types of pedagogical activities;
• Being, in the project, one of the support tools of the collaborative and interactive
working, especially as a mean to help the production of new education and
training and professional targeted knowledge;
• Bringing and bridging the other related KDBs (Agronomy, Agro ecology,
Environment, Water, Organic) and Agroforestry sources wherever they are
located on Earth;
• In mid-term, enlarging the domains of agroforestry which are covered by the
KDB, for instance knowledge from Mediterranean, African, Asian, experiences,
professional practices;
• In mid-term, making this knowledge accessible to other people as learners, to
other learning organizations, institutions like universities, training centres, in
respect with intellectual property;
• In long-term, for the “public part” of the KDB, making this knowledge
accessible to large public, in respect with intellectual property.
3.3 Needs in education and training - requirement of KDB
We need a place to store and structure the information and sources gathered by the
project. This place can be divided into 2 parts:
• Private part
• Public part, which means not restricted to partners but, for instance, open to
trainers and learners.
• The project needs to build the curricula and trainings, especially the technical /
professional components, which stored in a repository for the information:
• A repository to store the “objects”, the documents, the resources, the
components of the modules the project is producing and will produce;
• A place to, possibly, store some “objects”, documents, which are involved in
working tasks, in conjunction with the collaborative working system;
• A set of tools to identify the KDB components (indexation) and tools to make
this information easily accessible, search engines for instance;
• We can review some aspects of technical needs:
• Amount of data to be stored, we have to define technical constraints;
• Number of users, number of access, in short term and in midterm;
59
• Related parameters like quantity of information by user, duration of connection,
bandwidth.
The issue of private data (linked to restricted access for instance) must be
specifically treated in the second step of the project in conjunction with the access by
learners, students in relation with LMS (Learning Management System).
3.4 Selection criteria of CMS software to the KDB development
In computing, a database is gathering highly structured data, a well-defined
organization, based on different types of structures: relational, hierarchical. This is
absolutely not the case in a databank in which we store structured tables of numbers
as well as illustrated text or video or emails, external knowledge or those from the
project in their various forms. But it should be noted that the knowledge databank in
the prototype of the AgroF-MM project is based on a software, RUBEDO developed
in PHP and it is built on different components:
• a database management software (DBMS), type 'NoSQL', MongoDB;
• the user interface uses the ElasticSearch search engine.
Why we chose MongoDB as a database server. From one side the Rubedo system
is an open source software tool framework to develop websites and it contains this
type of database. From the other side MongoDB is an open-source document
database and leading NoSQL database. The benefits of using a document database
like MongoDB means that we can work with JSON-style documents across our entire
development process.
In this type of database is possible search based on text or in case of pictures
videos and other objects based on taxonomy (description text to the given object).
3.5 Development and implementation of the KDB system based on the
RUBEDO CMS
The Rubedo platform brings the advanced functions of content management together
with the power of e-commerce, all being based on Big Data (Webtales, 2017).
The Rubedo system can be accessed on three different platforms (Linux-RedHat
or Debian and Windows):
We use a yum based distribution, which name is: CentOS. The first step is
installing the MongoDB, then the Elasticsearch and Apache webserver and PHP
server side script language and finally the Rubedo system.
If the installation was correct you can add different kind of users with different
rights to the system.
If the given username and password were correct can be seen the Backoffice part,
where the appropriate pages for the users can be designed. These pages can be seen
by users on the FrontOffice part in different kind of browser programs (Fig. 2).
There can be seen more possibilities to choose. The visitors, learners, trainers, the
access is by means of the address newkdb.agrofmm.eu without further specification.
This version is open to the public. The opening welcome page is displayed in
English, with a brief introduction, (picture below – Fig. 2.). The choice of language
60
of the interface is done by clicking on the language button, pull-down menu, select
language and redisplay the page in the selected language. The general menu
Welcome, Overview, Trainings, Resources, Content types, Search tool and Wiki and
a knowledgebase DVD from the former AgroFe project results is present on every
page. The logo AgroF-MM repeats on every page with a click (on the logo) from any
page. Site map levels and a breadcrumb used to be located and to move without
necessarily go back to the Home page.
3.6 KDB menu and content introduction
The KDB has documents and links with training. Users access Digital Assets
Manager contents.
a) The choice “Trainings”' provides access to “Trainings needs” and “Trainings
objectives” of the KDB.
b) The choice Resource opens a submenu in a dedicated page. The route tree in the
resources of the KDB continues with the choice: - Gallery: the selection of
choice provides access pictures, where number of thumbnails are in the bank. By
clicking on a thumbnail, the image in full size is obtained. Video: click on the
video option causes the access to video stored in the DAM (Digital Asset
Manager) or the recorded videos and identified on public servers, such as
YouTube, etc. Some videos can be viewed online, others have to be downloaded.
Document: offers a sub-menu distinguishing between general information and
agroforestry techniques. A click on the document product logo to download the
document and its display in the user's browser if a necessary application was
installed.
c) The content types menu is a description about the usable types of content in the
Rubedo system.
d) Selection Search provides access to the integrated search engine has the
knowledge bank. In this application, the search can be performed on the entire
contents of the bank by entering a keyword may be presented in an object or an
associated content. Here can be used the object associated taxonomy for better
performance searching.
e) AgroF-MM wiki is work in progress, in line with the taxonomy “agroforestry”
of the bank.
f) A knowledgebase DVD from the former AgroFe project results in html format.
4 Taxonomy and Thesaurus
One of the most important part of the development to define the AgroF-MM-
thesaurus (Fig. 2) in very detail because the word in this vocabulary links to different
object (document, photos, presentations, videos, etc.) in the KDB. This thesaurus
system has been developed by a working group in the project using ontology.
Unfortunately the AGROVOC Multilingual agricultural thesaurus and other system
do not contain terms for agroforestry in details.
61
For designers and developers, the design and developments associated with the
management and use of the KDB covers more extensions. The ”professional domain”
extension composed of Vocabulary, Thesaurus, Taxonomy of agroforestry. The
”training” extension is dealt the question of the enrichment of documents. In relation
with KDB access, different modes and levels of enrichment have been developed and
implemented.
Fig. 2. Used thesaurus in different levels
Fig. 3. Taxonomy handling window in Rubedo system
62
The first step to identify the internal objects of KDB. In the second step we can
enter keywords (metadata) to the objects (photos, graphics, videos) to help searching
process. We use 4 taxonomies (Domain, Dublin Core, Learning Object Metadata,
Technical definition of metadata). Finally we can associate these keywords to the
appropriate objects in the KDB (Fig. 3).
The aim of the AgroFE project is to play an important role in Agro-forestry
trainings. Depending on the European countries, states or professional organizations
and training actors try to reintroduce Agro forestry in the course of training and
qualification in initial training and in adult education.
5 Conclusion
The Rubedo platform brings the advanced functions of content management, all
being based on Big Data. We use a yum based distribution, which name is:
CentOS 7. The first step to install the MongoDB, then the Elasticsearch and Apache
webserver and PHP server side script language and finally the Rubedo system. The
visitors, learners, trainers, the access is by means of the address newkdb.agrofmm.eu
without further specification. This version is open to the public. The choice of
language of the interface is done by clicking on the language button, pull-down
menu, select language and redisplay the page in the selected language.
During the development work of the KDB, an evaluation of the interface and the
organization of the access will be organized with the participation of master students,
Hungarian and French consultation conducted by students in Master AgroSup Dijon.
A first phase resulted in proposals for interface and aspects. The thesaurus and
taxonomy are very important part of KDB, it can be the base on the search strategy.
The KDB has documents links with training. Users access Digital Assets Manager
contents.
The knowledge database (knowledge data bank) is very new innovative solution
for harvesting, storing and delivering contents in agroforestry. It was used in
different training programs with good feedback. The knowledge database will serve
the Agrof-MM partners in the next years.
Acknowledgments. This publication was supported by the EU Erasmus+
Programme Key Action 2: Strategic Partnership. “ Agroforestry – Training –
Medirranean and Mountain” Ref. Number: 2015-1-FR01-KA202-015181 project.
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