=Paper=
{{Paper
|id=Vol-3672/DS-paper1
|storemode=property
|title=A Model-driven Requirements Engineering Method for Human-centered Digitalisation of
Agriculture
|pdfUrl=https://ceur-ws.org/Vol-3672/DS-paper1.pdf
|volume=Vol-3672
|authors=Chiara Mannari
|dblpUrl=https://dblp.org/rec/conf/refsq/Mannari24
}}
==A Model-driven Requirements Engineering Method for Human-centered Digitalisation of
Agriculture==
https://ceur-ws.org/Vol-3672/DS-paper1.pdf
A Model-driven Requirements Engineering Method for
Human-centered Digitalisation of Agriculture
Chiara Mannari
Department of Computer Science, University of Pisa, Italy
Institute of Information Science and Technologies "Alessandro Faedo" - ISTI, CNR, Pisa, Italy
Abstract
[Context and motivation] Digitalisation in agriculture is a socio-technical process that involves multiple stakehold-
ers with diverse backgrounds and skills, e.g., in farming or technology. Capturing process transformation requires
focusing on different dimensions, i.e., system structure, process flow, and actors’ goals. Model-driven requirements
engineering (MoDRE) techniques can offer the means to elicit and represent this multi-dimensional information.
[Question/problem] This research investigates how MoDRE techniques can support the information exchange
within interdisciplinary teams involved in the representation of process transformation in digital agriculture.
[Principal ideas/results] We propose a method for process modelling in agricultural domains consisting of (1) an
artefact based on a set of different diagrams, namely UML, i* and BPMN, (2) a procedure based on guidelines
and (3) a tool to support the co-creation of the diagrams within the context of living labs (LLs, i.e., networks
of stakeholders involved in a common socio-technical system). We plan to apply the method through action
research in the context of 20 European living labs in the agricultural domain and evaluate the method through
standard user questionnaires. [Contribution] There is little empirical evidence on using MoDRE techniques in
real-world environments. This study fills this gap by developing a method for socio-technical process modelling
in co-design contexts.
Keywords
requirements elicitation, socio-technical system, agriculture, living labs, process modelling, end-user development
1. Introduction
The adoption of digital technologies in agriculture triggers a complex process of socio-economic and
technical change called digitalisation that radically transforms the context in which human activities
are performed [1]. Agricultural digitalisation presents challenges with double-edged effects, generating
potential winners and losers [2]. To minimise the risk of undesired consequences, it is important to
early evaluate the impacts of digitalisation by performing an analysis of business processes transformed
by the introduction of digital technologies. A preliminary task for such an analysis is to create clear rep-
resentations of the process transformation considering multiple perspectives, such as social, economic,
environmental and technological.
This leads to two issues. The first is gathering multiple stakeholders with different backgrounds
and expertise to elicit the necessary information for the creation of the representations. The second is
establishing a method for representing and exchanging information that enables to reach a common
understanding across multiple domains. The solution to the first issue is carrying out activities within
Living Labs (LLs). LLs are networks of farmers, knowledge intermediaries, stakeholders, and policy-
makers that are constituted around an emerging problem and carry out interdisciplinary activities, such
as assessment, co-design and co-development of solutions in real contexts, pursuing a human-centered
approach [3]. The solution to the second issue is adopting Model-driven requirements engineering
In: D. Mendez, A. Moreira, J. Horkoff, T. Weyer, M. Daneva, M. Unterkalmsteiner, S. Bühne, J. Hehn, B. Penzenstadler, N. Condori-
Fernández, O. Dieste, R. Guizzardi, K. M. Habibullah, A. Perini, A. Susi, S. Abualhaija, C. Arora, D. Dell’Anna, A. Ferrari, S.
Ghanavati, F. Dalpiaz, J. Steghöfer, A. Rachmann, J. Gulden, A. Müller, M. Beck, D. Birkmeier, A. Herrmann, P. Mennig, K.
Schneider. Joint Proceedings of REFSQ-2024 Workshops, Doctoral Symposium, Posters & Tools Track, and Education and Training
Track. Co-located with REFSQ 2024. Winterthur, Switzerland, April 8, 2024.
$ chiara.mannari@isti.cnr.it (C. Mannari)
https://chiaramannari.github.io/ (C. Mannari)
0000-0002-5488-4150 (C. Mannari)
© 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
ceur-ws.org
Workshop ISSN 1613-0073
Proceedings
(MoDRE) techniques. MoDRE techniques, which leverage diagrammatic notations, can support the
representation of various aspects of systems requirements, e.g., functionalities, structure, goals, data,
processes, and workflows [4]. Model-driven approaches are widely used both for information exchange
between engineers and different stakeholders and as design material for software development [5].
However, MoDRE is rarely applied in co-design contexts, and specialised software to develop the
models and specific methods for the elicitation of information are typically oriented towards engineers
and analysts. Furthermore, Mavin et al. [6] highlight a lack of empirical studies on the applicability of
MoDRE to real-world environments with a relevant social component. Moreover, previous research [7]
reflects on the suitability of RE methods at the time of smart rural areas and suggests the development
of new innovative methods for agriculture.
This PhD research focuses on addressing these challenges. Using design science [8], we aim to develop
and evaluate a method based on MoDRE to represent the transformation of processes in agricultural
digitalisation to be applied in co-design contexts.
The research is carried out in the context of the four-year Horizon Europe project Maximizing the
co-benefits of agricultural digitalisation through conducive digital ecosystems (CODECS)1 that aims to
develop valuable strategies to enhance the positive impacts of digitalisation. Our research team, a group
from the Institute of Information Science and Technologies of CNR (Italy), is leading the task of process
modelling, which will be carried out as empirical research through interaction with 20 European LLs.
The approach we propose, as already accepted by the international reviewers of CODECS, is to carry
out process modelling to capture process transformation with the representation of processes before
the introduction of digital technology (as-is) and after the introduction of digital technology (to-be). We
aim to adopt MoDRE for the creation of standard and easy-to-read representations focusing on different
aspects of processes, in order to reach an overall view of the occurred transformation.
2. Related Work
A literature review was carried out primarily to identify MoDRE methods that address the representation
of process transformation in agricultural and rural domains in co-design contexts. We found that
previous literature lacks a method to solve a similar challenge despite providing strategies to model
specific aspects.
Ye et al. [9] developed a framework for enterprise integration of arable farming based on different
dimensions corresponding to different models, i.e. resource, organisation, production management, and
process. A large number of contributions, which are mostly engineers-oriented and enterprise-oriented,
originate from research in Digital Twins [10]. Recent studies focus on the adoption of Digital Twins
in the agricultural domain addressing the challenges related to virtually capturing the interactions
between living systems and their environment [11].
Alternative approaches, which prioritise users’ involvement, are mostly goal-oriented [12] and focus
on understanding the objectives and desired outcomes that stakeholders aim to achieve. These are
mostly adopted for balancing multiple, sometimes conflicting, goals. Previous research adopted the
goal-oriented i* notation [13] for requirements analysis of normative aspects in socio-technical food
traceability systems [14], while other authors [15] integrated goal and business process models for
enhanced information system analysis.
Regarding business process modelling, BPMN [16] is the prominent notation, having a large diffusion
among practitioners. BPMN models are a means for information exchange between engineers and
business analysts [17]. The language supports advanced techniques, even AI-based, for data analysis,
such as process mining [18], or change impact analysis [19]. Law et al. [20] developed a user-centered
methodology based on BPMN diagrams for requirements elicitation.
To support the modelling of contexts characterised by a relevant social component, Prilla et al. [21]
developed SeeMe, a notation supporting the modelling of uncertainties, which are considered funda-
1
https://www.horizoncodecs.eu - Last access February 7, 2024
mental features typical of social systems. Recent studies aim to enrich the language connecting the
notation with process modelling [22] and goal modelling [23].
3. Methodology
The research is being carried out as a design science project [8], making use of multiple research
strategies and methods to create reliable and useful knowledge based on empirical evidence and logical
arguments. The process of design science is articulated into five consecutive steps that will be further
explored in 4.
Design science produces results that are relevant both to the research community and to a community
of local practices. In the context of this research, the community of local practices is composed of the
20 European LLs participating in the CODECS Consortium.
We will carry out action research [24] applying and refining the method in the context of CODECS
LLs that represent multiple contexts of digitalisation. Then, the method will be finally evaluated by LLs
through interviews, focus groups and standard user questionnaires.
This PhD research received as input general problems experienced by the community of practices in
CODECS. These can be summarised in three main points: (1) stakeholders want a clear understanding
of how a certain technology impacts their business process; (2) there are information exchange issues
in LLs due to different expertise and backgrounds of the stakeholders involved; (3) stakeholders ask to
collaborate actively and be autonomous in the representation of systems and processes.
This led to the formulation of three research questions (RQs):
• RQ1: How can MoDRE techniques support communication with stakeholders involved in the rep-
resentation of a process transformation in agricultural contexts? To answer RQ1, we propose a
method based on graphical models from the MoDRE field and a procedure for data collection
based on a reporting template. In selecting the models we consider prominent notations for the
representation of social interactions and goals, system components, and processes, and we plan
to adapt the notations to maximise usefulness and understandability to stakeholders with no
expertise in the notations.
• RQ2: Can the method be applied to real agricultural contexts? To answer RQ2, we intend to assess
the method developed in RQ1 through action research [25]. We plan to apply the method to
20 European LLs from the CODECS project. LLs are characterised by different technologies,
expertise and levels of introduction of the technological solution; this will allow us to refine the
method through interaction with different contexts.
• RQ3: How to make end-users autonomous in the representation of systems and processes without
knowing formal languages? To answer RQ3, we propose the development of a web tool accessible
to LLs to support end-users in process modelling to be included in the method developed in RQ1.
The tool is conceived as a single-software web environment for requirements elicitation based on
an intuitive visual language that can be exported into standard code.
4. Research Plan
The development of this PhD research can be summarised into consecutive steps corresponding to the
steps of the design science process, according to Johannesson et al. [8].
• Step 1 — Problem explication. The research started with an analysis of the general problems
declared by stakeholders of CODECS and was consolidated with a literature review. This led to
the three RQs presented in 3.
• Step 2 — Requirements definition. In this phase, we started to address RQ1 through the sub-steps
of artefact outline and requirements elicitation. A draft of the artefact was preliminarily evaluated
with representatives of the LLs through a case study. This led to the definition of the method
composed of a set of diagrams, a procedure based on a reporting template and the tool for
end-users; this will be presented more in detail in 5. A list of requirements is currently under
refinement. In parallel, a prototype of a modelling tool for end-users addressing RQ3 is being
developed and was preliminarily evaluated through a walkthrough with experts.
• Step 3 — Artefact design and development. The outlined artefact has been further developed
following the evaluation carried out in the previous step and a second case study was conducted
in the context of a LL from CODECS, serving as a pilot study for the project. This led to an
improved version of the diagrams and to the procedure for data collection to be followed by LLs.
• Step 4 — Artefact demonstration. In this phase we address RQ2 through the application of the
method to the LLs of CODECS. Following action research, we plan to perform the data collection
in the next months and then proceed with the development of the diagrams through several
iterations with LLs. In the final phase, we plan to perform a validation of the diagrams with LLs.
• Step 5 — Artefact evaluation. We plan to perform this step once the demonstration is completed
through a validation of the entire method with LL coordinators. To ensure that the representations
produced and the procedure followed are useful and understandable, we will evaluate them
according to the Technology Acceptance Model (TAM) [26].
5. Proposed Solution and Preliminary Results
In this PhD research, we propose a method based on MoDRE to represent the process transformation
after the introduction of digital technologies in agricultural contexts. With the models, we aim to
describe all the elements of interest related to a process of transformation occurring after the introduction
of a digital technology within a socio-technical system, i.e. a system characterised by a relevant social
component. We call our method socio-technical process modelling. The transformation is emphasized by
qualitatively highlighting the differences in the process-as-is (before) and the process-to-be (after).
The method is composed of (1) a set of diagrams, (2) a procedure based on a template for data
collection within LLs, and (3) a tool to support end-users in the creation of the models. The method will
be applied and evaluated within the 20 LLs of CODECS.
The set of diagrams. To ensure completeness, the representation of a process transformation
focuses on three complementary dimensions, i.e. structure, goal and process. This can be represented
through a set of different diagrams:
• Structure: the UML class diagram provides an overview of the process structure, i.e. actors,
resources, tools, and infrastructures involved in the process-to-be and their relationships [27]. In
this representation, the new classes introduced by digital technology are in light blue. (Fig. 1a).
• Goal: the i* diagram models the goals of the process-to-be focusing on the intentional, social,
and strategic dimensions [13]. For this type of diagram, we propose to adopt a modified style
for the notation by creating an enhanced version consisting of icons for representing actors and
a different style for the symbols. This is to obtain more user-friendly representations and to
improve readability. (Fig. 1b).
• Process: the BPMN diagram [16] represents the detailed flow of the process, including actors’
tasks, procedures, and communications. Multiple diagrams are developed to represent both the
process-as-is and the process-to-be. An overlapping visualisation allows comparisons between
the overall process before and after the introduction of the digital technology (Fig. 1c).
The selection of models is based both on the literature review and the evaluation with stakeholders.
The procedure for data collection. To perform data collection, we propose a procedure based
on guidelines and a reporting template to be filled by LL coordinators. The procedure is meant to
support the elicitation of information from multiple stakeholders through workshops and focus groups.
According to this procedure, the reporting template will contain all the data necessary for the creation
of the diagrams that will be developed and syntactically validated by experts in the notations.
(a) UML class diagram
(b) i* goal diagram
(c) comparison of BPMN process diagrams
Figure 1: Models representing an irrigation process transformed by the introduction of a precision irrigation
system
The tool for end-users. In addition, a tool enabling end-users to create the models is being developed.
The tool has a double objective: to speed up the process of creation of multiple diagrams through a
single web interface and to allow users with no expertise in the notations to edit and create the diagrams.
A prototype version of the tool has been released and is presented in [28].
Case studies. The development of the method is being carried out iteratively. The process started
with the development of a draft of the artefact and a preliminary assessment through two case studies
(CS) which were collectively evaluated by a group of selected stakeholders, including both experts in
the notations and domain experts.
• CS1: is based on a smart irrigation system adopted on a pear orchard by a fruit farm2 in Tuscany. A
precision irrigation system, composed of a wireless sensor network (WSN) and a decision support
system (DSS), has promising potential in terms of economic, productive, and environmental
benefits. The diagrams are presented in 1.
• CS2: is the pilot study carried out with Pecorino Toscano, a LL from CODECS, based in Manciano,
Tuscany and focused on the activity of sheep breeding and pecorino cheese production. The
LL is built around the development and evaluation of a farm management information system
(FMIS) aimed at supporting interoperability among several on-field technologies and a mobile
application to monitor animals’ health status, food ratios and milk production.
The evaluation carried out in the CSs allowed us to refine the representations and collect requirements
for the procedure for data collection in LLs. A preliminary version of the proposed method and the two
case studies are presented in [29, 30].
2
http://www.illuminatifrutta.it last visited 7 February 2024
6. Conclusions and Future Challenges
In this PhD research, we address the challenge of modelling process transformation in the domain
of digital agriculture. We propose a method based on MoDRE that includes a set of diagrams, i.e.,
UML class diagrams, i* and BPMN, a procedure to carry out data collection and a tool for end-users.
We preliminarily evaluated the diagrams through two case studies in precision irrigation and cheese
production, and the preliminary results confirm the feasibility of the proposal. At the current state, the
TAM-based evaluation of the models has not yet been performed. However, we plan to use standard
questionnaires to evaluate the constructs of Perceived Ease of Use (PEOU), Perceived Usefulness (PU)
and Intention To Use (ITU), as done by other authors [31]. For clarity’s sake, we provide three examples
of questions we plan to ask for PEOU, PU, and ITU respectively: 1) It was easy for me to understand
what the models meant and the steps of the procedure; 2) Overall, I think that the modelling procedure
provides an effective means for evaluating the process transformation and its impact; 3) If I were to
evaluate a process transformation and its impact, I would adopt this modelling procedure.
The main challenge ahead consists of the demonstration of the artefact with the application of the
method to 20 LLs. This step will allow us to evaluate the effectiveness of the method within real
agricultural contexts which are characterised by diverse needs, skills and levels of digitalisation. This
will contribute to filling the lack of empirical evidence on the applicability of MoDRE techniques to
real-world contexts with a relevant social component, as evidenced in the previous section. At the
same time, the feedback received from LLs will allow us to fine-tune the method. Moreover, new
research challenges arise from the tool for end-users, as proposed in RQ3. A first challenge is related
to the creation of the tool which requires the development of a new user-friendly approach for the
formalisation of the diagrams based on the selected notations. A second challenge is related to the
evaluation of the tool through case studies to be performed in LLs.
Acknowledgments
This work has received funding from the European Union’s Horizon Europe research and innovation
programme under grant agreement no. 101060179.
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