Vol.4, No.5B, 41-45 (2013) Agricultural Sciences
Application of ontologies to traceability in the dairy
supply chain
L. Magliulo1, L. Genovese1, V. Peretti2, N. Murru2
1Penelope SpA, Naples, Italy; *Corresponding Author: luciano.magliulo@penelopeonline.it
2Department of Veterinary Medicine and Animal Production, University of Naples “Federico II”, Naples, Italy
Received 2013
Systems for tracking products through supply
chains range from paper-based records main-
tained by producers, processors, and suppliers
to sophisticated ICT-based solutions. In addition
to supporting product traceability, ICTs may also
support data capture, recording, storage, and
sharing of traceability attributes on processing,
genetics, inputs, disease/pest tracking and mea-
surement of environmental variables. A key suc-
cess fac tor for a trac eability s ystem is th e capa-
bility to integrate and share information along
the supply chain. ICT represents a tool to over-
come integration problems, data fusion and in-
formation dissemination. In this paper we illus-
trate the application of ontology as a tool to model
business processes and rules within an agri-
food chain. The business cas e is represented by
the Bovlac project: a scientific and technologic
platform to trace fresh cheese production.
Keywords: Information Integration; Business
Process; Ontology; Agri-food Supply Chain; Dairy
Chain, Value Chain
Food safety is a global concern. Food recalls frighten
consumers throughou t the world, leading to a w idespread
awareness about the need to adopt mandatory food trace-
ability systems.
However, mandatory provisions on traceability require
the food-processing ind ustry to record only partial details
of the full process, usually limited to adjacent suppliers
clients. This is also named the one-step-up, one-step-
down approach.
On the other hand, sophisticated consumers start de-
manding more information about the actual quality stan-
dards of the food they eat. Transparency about the ingre-
dients being used as well as proven genuineness of origin
for distinctive or traditional food and general nutrition
information for functional food are becoming increas-
ingly relevant.
The aim of this paper is to introduce the ICT system
for the traceability in the dairy and discuss the benefits of
tracing data pertaining to the quality of the food process
throughout the entire supply chain. Along with data
about product movements, this helps optimize traceabil-
ity and provides a measure of the overall performance of
the value chain.
2.1. Food Safety and Traceability
Food safety is a top priority for consumers and the
food industry. The attention paid by the media to food
safety and possible food quality problems, the globaliza-
tion of the international marketplaces, the ever increasing
risks associated with liab ility, the growing complexity of
the supply chains all represent strong drivers of trace-
ability. Eventually, safety and security represent the two
most important drivers in the food industry as dramatic
recalls have frequently been reported around the world.
According to EU law, food and feed businesses - whether
they are producers, processors or importers - must make
sure that all foodstuffs, animal feed and feed ingredients
can be traced right through the food chain, from “farm-
to-fork”. Each business must be able to identify its sup-
pliers and which businesses it supplied in a one-step-up,
one-step-down approach.
In the meantime, some visionary businesses have fa-
voured the development of voluntary traceability, which
consists of recording what-goes-where, during the trans-
formation process and along the supply chain.
Even though voluntary traceability involves more
tracking activity than in the mandatory framework, the
captured data is limited to each single move of the product
(what-goes-where). Indeed, the final purpose of both man-
datory and voluntary traceability approaches is to allow
retrieval of data in a fast and accurate manner all along
the supply chain in order to identify the desired items.
Copyright © 2013 SciRes. Openly accessible at http://www.scirp.org/journal/as/
L. Magliulo et al. / Agricultural Sciences 4 (2013) 41-45
The more complex a traceability system is, the more
data it will has to handle. Consequently, input data is
limited to that of critical events, i.e. the tracing of move-
ments that significantly affect the food product. In this
context data pertaining to quality is not perceived as
critical and therefore remains excluded from the trace-
ability systems.
Nevertheless, consumers today ask for more informa-
tion about the quality, origin and handling of the food
they purchase and eat. News of recalls and exposure to
unsafe practices have made consumers wary.
All the above withstanding, the availability of a tra-
ceability system capable of capturing valuable data dur-
ing the food processing pha ses and designed to carry this
information all along the supply chain, may well repre-
sent a remarkable opportunity for a business to differen-
tiate itself in the market.
2.2. ICT and Traceability
As argued by Hall [1], traceability systems are intro-
duced for three main reasons. First, traceability makes it
easier, faster, and cheaper to do crisis management.
Second, traceability can provide information to consum-
ers and other participants in the distribution chain, and
can increase trust in that information (credence quali-
ties). Third, companies use traceability in search of effi-
ciency gains, reasoning that better information about
how their food moves will help them streamline supply
Systems for tracking products through supply chains
range from paper-based records maintained by producers,
processors, and suppliers to sophisticated ICT-based so-
lutions. In addition to supporting product traceability,
ICTs may also support data capture, recording, storage,
and sharing of traceability attributes on processing, ge-
netics, inputs, disease/pest tracking, and measurement of
environmental variables.
A key success factor for a traceability system is the
capability to integrate and share information along the
supply chain. ICT represents a tool to overcome integra-
tion problems, data fusion and information dissemina-
The agri-food enterprises operate in a complex and
dynamic environment, so, to meet increasing demands of
consumers, government and business partners, they have
to work on innovations of products, processes and ways
of cooperation in the supply chain [2]. ICT provides sev-
eral technologies, integrated in frameworks, to solve is-
sues related to cooperation along the supply chain [3].
In [4], authors make a survey on the application of
ICT technologies to the agri-food supply chain. Several
technologies are analyzed and proposed in three different
use cases within the application domain of the food sector.
In this paper we propose the use of ontology as a tool
to model business processes and rules within an agri-
food chain. The business case is applied in the dairy in-
2.3. The Bovlac Platform
The broader vision of extending traceability to quality
data has been taken in the Bovlac project. A project de-
signed by a consortium composed of a dairy industry
(ICCA Spa), research teams in veterinary medicine and
biotechnologies at the University of Naples “Federico II”
and an ICT company (Penelope spa), and funded by Re-
gione Campania – Italy.
The initial idea was to make each process step trans-
parent, from the stable to the consumer, and provide spe-
cific information on each sing le food product as a means
of promoting the functional food principle that quality
food "is good and does good.
Within Project Bovlac, the principles described above
are fulfilled through the implementation of a computer
system capable of tracing not just the production and
packaging of the specific product “Fior di latte Napoli”(a
traditional Pasta Filata cheese of Naples), but also make
all data pertaining to the origin (stable, cow, milk, tem-
perature, etc.) accessible to consumers.
Once traced, the “identity card” of the “Fior di Latte di
Napoli” will display information on th e breeding of cows,
date of milking, milk quality, cow diet, milk production
date, milk transfer date and “Fior di Latte Napoli” pro-
duction date a n d p ackaging.
The ValueGo® ICT platform has been developed for
the traceability. The system allows consumers – simply
scanning the Qr-Code on the package with their smart-
phones –full reading of the “Fio r di Latte di Napoli” his-
tory data while purchasing .
ValueGo® is basically a system that uses a web-cen-
tric communication infrastructure between active tags
and over a wi-fi network for the acquisition and dis-
patching of data and information. Developed in an open
source environment, ValueGo® technology features two
distinctive elements: domain ontologies and active and
passive tags, i.e. RFID and NFC.
A semantic database implements the application do-
main ontology. Through the use of ontologies, the con-
cepts related to any business or product domain can be
shared in multiple application environments, and do-
main-specific knowledge can be further enriched.
The resulting software architecture builds on standard
components and a specific ValueGo® Java Framework, a
set of java classes implementing specific services; it in-
cludes classes to manage an EPCIS Repository.
Furthermore, ValueGo® operates on standard hard-
ware products, configured in a three-tier architectural
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L. Magliulo et al. / Agricultural Sciences 4 (2013) 41-45
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2.5. Ontology Application in Dairy Chains
model. The system architecture provides three levels of
interactions, catering to all active stakeholders in the
manufacturer’s ecosystem. Within ValueGo ontologies have been used to define
the operational and business models of a specific produc-
tion, the fresh cheese Pasta Filata.
ValueGo® employs identification technologies based
on radio frequency (RFID or NFC) and bar code (1D and
2D), suitable for professional use and to facilitate inter-
action with consumers.
Specifications have been analyzed w.r.t. the definition
of product characteristics (like geographical area of milk
origin and characteristics of the cheese) and processing
chain of the milk-cheese.
Data acquired during the various production phases is
transmitted in real-time to a portal that can be consulted
by anyone interested. The consumer, by using a smart-
phone equipped with an NFC reader or with an applica-
tion capable of reading a 2D-barcode, is addressed to a
web page describing the product being considered for
purchase. The system is also accessible via internet.
In particular, the concept of "Pasta Filata" can be de-
fined as a function of a series of fundamental properties,
such as the aging time, the temperature of the curd, the
consistency of the dough, the fat content and the place of
origin. In addition, the concept of "Pasta Filata" can cer-
tainly be defined as a specialization of the concept of
"Cheese" and the concept of "FiordiLatte-di-Napoli" as a
specialization of the concept of "Italian-Cheese". The
taxonomy of the previous concepts is reported here:
(Figure 1)
2.4. Ontology in Information Management
A key technology in ValueGo is the domain ontolo-
gies. The general concept of "Cheese" is related to the other
concepts of the taxonomy through the following properties:
Ontologies play an important role in information mod-
elling and management. In [5], Gruber defines an ontol-
ogy as a set of representational primitives with which to
model a domain of knowledge. The representational
primitives are typically classes (or sets), attributes (or
properties), and relationships (or relations among class
members). Ontologies are typically specified in lan-
guages that allow abstraction away from data structures
and implementation strategies. Due to their independence
from lower level data models, ontologies are used for
integrating heterogeneous databases, enabling interop-
erability among disparate systems, and specifying inter-
faces to independent, knowledge-based services.
• has-temperature-curd
• has-pasta-consistency
• has-fat-content
• has-origin-area
The first four properties are of type "ObjectProperty"
and they are given the sets of permissible values, the
remaining ones are of type "DatatypeProperty" and they
are the types of values that can take.
The concept "Fiordilatte-of-Naples" can be defined
through the following prop erties:
• Fiordilatte-of-Naples
Several researches argue about the application of ontol-
ogy in enterprise and business process modeling. In [6] a
Business Process Modelling Ontology is proposed as a part
of an approach to modeling business processes at the se-
mantic level, integrating knowledge about the or ganisational
context, workflow activities and Semantic Web Services.
as-aging-time Aging Fast
has-temperature-curd Pasta-Spun
has-pasta-consistency Spring-Pasta
has-fat-content Fat Cheese
has-origin-area Naples
Figure 1. Taxonomy of pasta filata fresh cheese.
Openly accessible at
L. Magliulo et al. / Agricultural Sciences 4 (2013) 41-45
Business processed have been modelled w.r.t. the en-
tire dairy chain in terms of specific business use cases.
These use cases describe the people involved in all stages
of the process, their roles and activities of each of them.
The use cases can be traced to the macro-phases of the
supply chain, as follows: (Figure 2)
The knowledge of the domain of interest, formalized
in business use cases of business, allows to identify, in
addition to significant figures involved, also all concepts
and properties required to model, the activities of each
stage. In particular, this modeling was performed by rep-
resenting the events related to the transitions between
activities of each stage of the production process.
2.6. Tracing the Product
Concepts modeled with ontologies have been used to trace
information made available to consumer via smartphone
or computer. Organization of traceability information re-
flect the structure of the model. As example information
about quality of milk are associated to concepts Milk-
Characteristic and Milk-Quality in the ontology. (Figure
Making the quality of products transparent for the
consumer means being able to monitor the work proce-
dures of each individual company (internal traceability),
all along the supply chain. This view is consistent with
the principle stating that: “The creation of systems of
internal traceability is a prerequisite without which there
can be no traceability”. This implies the ability to certify
the quality of production with tools capable of automati-
cally recording information about each transformation
process and the subsequent distribution.
What makes ValueGo® a suitable instrument is its
ability to adapt to different product pro cesses and various
supply chain models. Adaptation of ValueGo® to a spe-
cific production model takes place at the value chain
Figure 2. Taxonomy of processes.
Figure 3. Traceability of milk quality.
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L. Magliulo et al. / Agricultural Sciences 4 (2013) 41-45 45
level. Firstly, by tuning the software ru les, which may be
standardized for most businesses but still need some de-
gree of customisation, Secondly, working on characteris-
tics of product and processes that are more company-
Through the adaptation of the specific business proc-
esses, ValueGo® is able then to detect and record in a
database all quality-related events throughout the lifecy-
cle of each product, thus enabling the consumer to easily
trace all available product information at purchase time.
Project Bovlac is funded by Regione Campania PSR Misura 124 Ref.
n.774 of 28/12/20 10 CUP B35C10001760004
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