The Current Limitations of Blockchain Traceability:

Challenges from Industry

N. S

anchez-G

omez

1 a

, M. Mejias Risoto

1 b

, J. M. Ramos-Cueli

2 c

, T. Wojdy

nski

3 d

D. Lizcano

4 e

and J. Torres-Valderrama

1 f

University of Seville, ETS de Ingenier

ıa Inform

atica, Web Engineering and Early Testing Research Group, Seville, Spain

Soltel Group, Department of Research and Development, Leonardo da Vinci, 13, 41092 Seville, Spain

School of Banking and Management, Cracow, Poland

School of Computer Science, Madrid Open University, UDIMA, Madrid, Spain

Keywords:

Blockchain, Traceability, Model-based Software Engineering, Common Information Model.

Abstract:

Blockchain technology is a chain of cryptographically linked blocks. It was designed to be immutable, so

that the identity and traceability of the information entered would be guaranteed. After analyzing several

traceability solutions, in the context of a Spanish company project, it was found that in order for a traceability

solution to be efﬁcient and agile, an additional layer is necessary in the blockchain. Since this need originated

in the industrial sector, the subject has awakened considerable interest in the research community. This paper

explains why the extra layer is essential and why it should ideally be totally independent of the information

that is recorded on the blockchain network. Although data in a blockchain network is immutable, the paper

also outlines the need for additional veriﬁcation mechanisms capable of determining whether the raw data was

correct. Finally, it includes planned future work.

1 INTRODUCTION

Blockchain technology has evolved a lot since the in-

troduction of Bitcoin in 2008. This cryptocurrency

invented by an unknown person, or group of people,

using the name Satoshi Nakamoto (Nakamoto, 2008),

ﬁrst appeared in 2009 (Joshua, 2011), when its im-

plementation was released as open-source software.

Engineers and researchers are now realizing the ben-

eﬁts of blockchain technology and looking for ways

to integrate it into their infrastructures in numerous

sectors, from ﬁnance and supply chains to health (Al-

Saqaf and Seidler, 2017). Due to its decentralization

and reliability, blockchain technology is potentially

beneﬁcial to businesses, its enhanced security, greater

transparency, and easier traceability opening up many

new opportunities (Song et al., 2019).

https://orcid.org/0000-0001-9102-6836

https://orcid.org/0000-0002-0353-6391

https://orcid.org/0000-0003-1933-1750

https://orcid.org/0000-0003-0343-013X

https://orcid.org/0000-0001-7928-5237

https://orcid.org/0000-0002-7786-5841

Traceability is one of blockchain’s biggest advan-

tages over other solutions. Blockchain networks have

intrinsic mechanisms that facilitate both external and

internal audits (Westerkamp et al., 2020). Moreover,

blockchain networks were designed to be immutable,

so that the identity and traceability of the informa-

tion entered would be guaranteed. Although several

different techniques can be applied (Cleland-Huang

et al., 2014), blockchain offers additional functional-

ity in terms of data security, and this is very interest-

ing for certain businesses where it is a prerequisite to

have a secure, reliable record in which information

remains unchanged and traceable.

After analyzing several product/service traceabil-

ity solutions, in the context of Common Information

Model for Traceability Project (Soltel Group’s CIMT

Project is currently under development), it was found

that a ﬂexible traceability module is required: a mod-

ule totally independent of the information registered

in the blockchain network and one which, depending

on the user case, does not need to be reimplemented

and allows the tracking process to be applied to dif-

ferent components at the same time.

Sánchez-Gómez, N., Risoto, M., Ramos-Cueli, J., Wojdy

nski, T., Lizcano, D. and Torres-Valderrama, J.

The Current Limitations of Blockchain Traceability: Challenges from Industry.

DOI: 10.5220/0010213503730380

In Proceedings of the 16th International Conference on Web Information Systems and Technologies (WEBIST 2020), pages 373-380

ISBN: 978-989-758-478-7

373

The CIMT Project is part of the SERVICECHAIN

initiative, which is co-ﬁnanced with FEDER funds.

The main objective of this initiative is the industrial

research, in blockchain technology, to solve the chal-

lenges of the Spanish companies in the management

of digital identity, reliability and traceability of the

goods and services transactions against the require-

ment of digital transformation and existing regulation.

Soltel Group is part of the consortium and has the re-

sponsibility to develop the technology that allows the

traceability of the product’s life cycle, from its man-

ufacture to the acquisition by the ﬁnal consumer and

subsequent transactions, until its disposal (at the end

of its useful life). This process is mainly oriented to

Industry 4.0 and energy.

This need, ﬁrst identiﬁed in industry, has aroused

the interest of the research community. Also, al-

though data on the blockchain network remains un-

changed, industry also recognizes that additional ver-

iﬁcation mechanisms should be introduced in order to

show whether raw data is correct.

Blockchain technology can be applied in many

different healthcare contexts. It can be used, for ex-

ample, to manage Electronic Health Records (EHRs)

or in the tracking research methods used in clinical

trials to make drugs safer (Shahnaz et al., 2019). At

a high level, blockchain application can be thought of

as a two-layer EHR. One layer handles all changes: it

is a live medical record that is updated, for example,

when the patient visits the doctor. The second layer

just monitors and tracks changes, creating a note of

the ”who, when and where” associated with all the

changes that take place as the patient’s records evolve.

Blockchain networks add changes to this layer and

prevent any editing or changes, creating a secure, per-

manent record that is validated by all stake-holders

with access to the data. Although the data stay im-

mutable, the blockchain does not have a veriﬁcation

mechanism to prove whether the raw data were cor-

rect, making it necessary to have an intermediate layer

to facilitate such mechanisms.

Since blockchain has the potential for many use

cases and is applicable in numerous industries,using

Blockchain-as-a-Service (Singh and Michels, 2018)

would also allow companies to easily integrate

blockchain technology and additional functions into

their businesses without disruption to their daily pro-

cesses. Therefore, in future work it will be necessary

to address the proposed architecture.

The rest of this paper is organized as follows.

Technical background is introduced in Section 2. Sec-

tion 3 discusses the suitability of using blockchain in

the context of product or service traceability. Sec-

tion 4 analyses and proposes an additional layer for

blockchain traceability, and Section 5 provides a set

of conclusions and outlines future work.

2 TECHNICAL BACKGROUND

2.1 Blockchain and Smart Contract

Blockchain technology, based on distributed ledger

technologies (DLT), is a chain of cryptographically

linked blocks. It provides a distributed shared data

store and a computational infrastructure. As a data

structure, blockchain only allows data to be inserted.

It does not allow any existing data on the blockchain

network be updated or deleted. This is to prevent tam-

pering and revision. Blockchain technology has only

a very limited capability to support programmable

transactions and only allows small pieces of data to

be embedded in transactions for other purposes: for

example, to represent physical or digital assets.

This technology currently provides a general

purpose programmable infrastructure, and a ledger

that stores the computational results generated from

that infrastructure. Smart contracts (Alharby and

Van Moorsel, 2017) are programs deployed and run

on blockchain networks. These programs can execute

triggers, rules, and business logic (Mohanta et al.,

2018) to enable transactions. In such a decentralised

environment, blockchains can also assure traceability

of transactions, and thus achieve a high level of trans-

parency and reliability in the ledger.

2.2 Blockchain Applications

Financial entities, governments, enterprises and star-

tups are now exploring the applicability of blockchain

in their domains. Application examples include, but

are not limited to, digital currency, international pay-

ments, securities registration and ﬁnancial sector set-

tlements, registries, identity and taxation as govern-

ment services, Internet of Things (IoT) storage, com-

puting and management, and industrial supply chains

(Zheng et al., 2018). Supply chains and health-care

are considered a particularly promising area for the

application of blockchain (Wang et al., 2019) (Bell

et al., 2018).

In all these sectors, traceability is important for

one reason or another (Dessureault, 2007):

• It makes it easier to prove compliance with reg-

ulations in audits, thereby reducing exposure to

regulatory risk.

• It improves stock control in terms of reducing

wastage, managing expired stock, safety issues,

APMDWE 2020 - 5th International Special Session on Advanced Practices in Model-Driven Web Engineering

374

and increasing proﬁtability.

• It helps prevent counterfeit goods or fraudulent

products from entering the market.

• It is beneﬁcial for brands in that it helps build trust

with customers, suppliers and other stakeholders.

• It improves efﬁciency in supply chains, interna-

tional trade, chains of custody, healthcare chains,

etc.

2.3 Blockchain Oracles

Blockchain networks, or more speciﬁcally smart con-

tracts, are limited insofar that they cannot access

the external data which might be needed to control

the execution of business logic. Smart contracts are

stored on the blockchain network and can only receive

data from external services through so-called oracles

(Beniiche, 2020). These can collect information from

different sources. For example, they can monitor the

status of a product to determine whether it has arrived

and then write that status on the blockchain network.

The change in product status could then be detected

by the smart contract, which would trigger payment

following the purchase of the product.

Some blockchain-based applications have re-

cently become more complex, incorporating concepts

like smart contracts, oracles and Decentralized Au-

tonomous Organization (DAO). A DAO is a dis-

tributed application implemented to make it possible

for multiple parties, either human or machine, to in-

teract with each other (Buterin et al., 2014).

In practice, blockchain oracles are crucial to the

correct execution of a smart contract, since the inser-

tion of incorrect information may lead to actions that

are not easy to revert (e.g., certain types of money

transfer). The blockchain oracle workﬂow is typi-

cally executed between three types of participants:

data feed providers, oracle nodes/network operators,

and blockchain operators (Al-Breiki et al., 2020).

Data feed providers enable different APIs (Applica-

tion Programming Interfaces) to read and provide data

from different data sources such as sensors, stock

markets or even adhoc solutions to oracle nodes.

To illustrate this idea, Figure 1 shows an API

server made up of different REST APIs (the most

widely used web service technology).

2.4 Model-based Software Engineering

Model-Based Software Engineering (MBSE), also

known as Model-Based Engineering (MBE), Model-

Driven Engineering (MDE), Model-Driven Develop-

ment (MDD), Model-Driven Software Development

Figure 1: Blockchain network using external APIs

anchez-G

omez et al., 2020).

(MDSD) etc., is a software development paradigm fo-

cused on the application of visual modeling princi-

ples and best practices throughout the Software De-

velopment Life Cycle (SDLC) (V

olter et al., 2013).

MBSE commonly uses multi-user repository-based

modelling tools (Friedenthal et al., 2007) which pro-

vide an environment where a precise, unambiguous

view of a system’s components, including their be-

havior and interactions, can be deﬁned and managed.

The MBSE paradigm is model-based to the extent

that the visual modeling artifacts it generates are suf-

ﬁciently precise and complete to serve as a software

or systems blueprint for improving SDLC efﬁciency

and productivity. It is model-driven to the extent that

it at least partially automates - that is to say, it drives

- the SDLC via requirements that are precisely and

completely speciﬁed as part of the system model, and

which can be fully traced across the SDLC. MBSE

is therefore the formalized application of modeling to

support requirements gathering, analysis, design, ver-

iﬁcation and validation activities.

To illustrate this paradigm, Figure 2 shows the ma-

jor MBSE activities.

Models can be either abstractions or representa-

tions of reality that facilitate the understanding of its

complexity. The MBSE approach has four main ac-

tivities. The primary activity is to specify software

requirements. Uniﬁed Modelling Language (UML) is

commonly used to do this (Schumacher, 2018). Af-

ter specifying requirements, different model transfor-

mation techniques have been used to obtain the out-

put model of choice for further veriﬁcation and val-

idation. The two most common transformation ap-

proaches are Model-to-Model (M2M) transformation

and Model-to-Text (M2T) transformation (Zhu et al.,

2019). The veriﬁcation activity is carried out to eval-

uate the correctness of the model-system. If a model

fails to satisfy the veriﬁcation requirements, alter-

ations are introduced to rectify the design errors, as

shown in Figure 2. The model-system is validated

through simulation. It is common practice to gener-

ate the source code using the model transformation

technique, which is then used for simulation (Rashid

The Current Limitations of Blockchain Traceability: Challenges from Industry

375

Figure 2: The major MBSE activities (Rashid et al., 2015).

et al., 2015).

Figure 3 illustrates how the MBSE is integrated

across domains.

Figure 3: The MBSE Integration Across Domains.

In brief, MBSE is a term that predicates the use

of modelling to analyse and document key aspects of

the SDLC. This paradigm is a model-centric approach

providing a single pint of truth which is reﬂected in a

set of living artifacts (Hart, 2015).

It is important to emphasize that technological

progress requires increasingly ﬂexible, sustainable ar-

chitectures. In recent years, this has triggered greater

interest in such new model-based paradigms. These

alternatives have proved to be enormously robust,

ﬂexible and scalable compared to traditional strate-

gies. Moreover, they feature concepts like reuse

and platform independence (Rodrigues et al., 2012).

MBSE designs for platform architecture can be reused

to add more functionality and/or change the target ar-

chitecture.

2.5 Common Information Model

The Common Information Model (CIM) (Uslar et al.,

2012) is an open standard that deﬁnes how managed

elements, in an IT environment, are represented as a

common set of objects and the relationships between

them. This standard formalism was developed by the

Distributed Management Task Force (DMTF), as part

of its WBEM (Web-Based Enterprise Management)

proposal (Arora et al., 2004) (Alexander et al., 2004).

The CIM standard includes the CIM Infrastructure

Speciﬁcation that deﬁnes the architecture and con-

cepts of CIM, and CIM Schema, a conceptual schema

which deﬁnes the speciﬁc set of objects and relation-

ships between them that represent a common base for

the managed elements in an IT environment. Some

current proposals for formalizing structural diagrams

through UML are easily adaptable to CIM diagrams

(McMorran, 2007).

3 BLOCKCHAIN TRACEABILITY

INFORMATION

Product or service traceability, for example in supply

chains, is the connection of all business processes in-

volved in the commercialization, generation and dis-

tribution of goods, from raw material to ﬁnished prod-

ucts and end consumers (Xu et al., 2019). Traceability

enables consumers to track products during produc-

tion and distribution (Grover et al., 2018).

To illustrate this concept, Figure 4 shows a supply

chain traceability system for blockchain technology.

Figure 4: Supply chain traceability system for blockchain

technology.

APMDWE 2020 - 5th International Special Session on Advanced Practices in Model-Driven Web Engineering

376

Governments also use traceability systems to dis-

play relevant information (e.g. origin, location, etc.)

and issue certiﬁcates. In healthcare, traceability acts

as a point of convergence for numerous needs (Lo-

vis, 2008). In recent years, not only has traceabil-

ity or tracking become increasingly important in the

healthcare sector, but the application of blockchain

technology is also being explored to improve the in-

teroperability of patient health information between

healthcare organisations while safeguarding data pri-

vacy and security (Eryilmaz et al., 2020).

Traceability systems used in these sectors typi-

cally store information in databases controlled by the

same entity, but with such centralized storage there is

a risk that data will be interfered with. In a collab-

orative environment like blockchain, the security of

this type of system is important, especially in ﬁelds

like accountability and the processing of forensic in-

formation.

Traceability is particularly interesting for those

entities that want to adapt to new production models

currently in development or pilot phases, and also for

entities with quality certiﬁcation, where it is an essen-

tial requirement to have a reliable, secure logging sys-

tem, in which information remains unchanged. Once

data is stored in the blockchain network, it can be con-

sidered secure and immutable (Sartori, 2020).

Research conducted so far suggests that using

blockchain technology is advantageous for achieving

traceability (Aung and Chang, 2014) . Although the

same activities can be carried out using other tech-

niques, blockchain technology adds additional func-

tionality to data security (Li et al., 2020), something

that entities ﬁnd very appealing.

Data transparency is desirable because stakehold-

ers want to check the authenticity of information. And

it appears that traceability systems can beneﬁt from

the digital nature of blockchain without being affected

by blockchain’s current limitations

Basically, any workﬂow can be fully reﬂected in

blockchain technology and can operate across multi-

ple entities, similar as a collect data. Each step of the

process can be registered and, depending on the inter-

vals at which new blocks are added to the blockchain,

the block creation timestamp shows the time and date

when the information was recorded. In fact, one of the

main advantages of using blockchain traceability in-

stead of traditional solutions is that it is a mechanism

that facilitates external and internal audits (Suzuki

and Murai, 2017). Thanks to its immutable record-

ing of information, the authenticity of the data can be

irrefutably guaranteed for the different stakeholders.

In other words, anyone can easily check what each

stakeholder has registered and when. This also facil-

itates the detection of possible incidents (even auto-

matically).

It appears, therefore, that an entity no longer

needs to do anything else to guarantee the traceabil-

ity or inviolability of data in the face of possible au-

dits (it would have to do a great deal of monitor-

ing if the information were stored only in a standard

database). However, although its data remains im-

mutable in time, the blockchain does not have a veriﬁ-

cation mechanism to prove whether the raw data were

correct (Galvez et al., 2018), making it necessary to

have an intermediate layer to facilitate such veriﬁca-

tion or validation mechanisms. If a piece of data is

altered, the blockchain will not detect it. Also, as will

be detailed below, it is essential for the traceability

solution to be completely independent of the dataset

recorded in the blockchain network. This way, de-

pending on the user case, it would not be necessary to

implement it again and it would be possible to apply

the traceability process to different components at the

same time. That is to say, a product or service could

be monitored using a common dataset and the exten-

sions needed for each business case.

4 DESIGN OF THE

TRACEABILITY MODULE

As already mentioned, there are two aspects which

need to be improved in blockchain traceability. Ver-

iﬁcation mechanisms need to be adopted to check

whether the raw data is correct and the traceability

solutions need to be completely independent of the

dataset recorded in the block chain network.

From our point of view, for a blockchain traceabil-

ity solution to be efﬁcient it must take into account the

possible granularity of the information to be recorded,

the cost of operations and, above all, the agility of

the traceability monitoring. In view of these require-

ments, it is therefore necessary to have an additional

layer in the blockchain, so that the best possible bal-

ance may be obtained between them.

One of the challenges involved is that for each

application it is necessary to develop speciﬁc smart

contracts that provide not only the traceability ser-

vice, but also all other services associated with the

blockchain platform. It is also essential for the new

layer to have a ﬂexible design, offering added value

to stakeholders, and to be totally independent of the

information to be recorded in the blockchain net-

work. In other words, it must be a layer that needs

no redeployment to be able to apply the tracking pro-

cess to different components at the same time, taking

advantage of the tracking properties intrinsic to any

The Current Limitations of Blockchain Traceability: Challenges from Industry

377

blockchain network.

To address these issues, the ﬁrst objective was to

design an architecture for blockchain traceability so-

lutions with pre-established smart contracts, as shown

in Figure 5.

Figure 5: Architecture for blockchain traceability solutions.

The pillars of this puzzle are the blockchain oracle

and the external APIs. Thanks to the blockchain ora-

cle, smart contracts can be invoked in different ways,

using speciﬁc parameters or information in a data in-

terchange format such as the JSON format (REST

API).

The second objective was to design a base meta-

model which, thanks to extensions, is capable of ac-

commodating new data models without the need to

re-implement the platform.

Here, MBSE and CIM would allow independence

from the destination platform and facilitate the estab-

lishment of a base model that would make the solution

independent of the information to be processed, thus

making this service transparently and reliably acces-

sible to any client.

For the deﬁnition of the CIM model, it is therefore

necessary to deﬁne a series of types, characteristics

and basic operations which allow native types of in-

formation to be established (at the meta-model level,

interrelations, classes, values, etc. are also indicated).

In other words, this meta-model is a meta-structure

that can be used to deﬁne the information model, es-

tablishing a series of general restrictions that allow

the model to be structured and its scalability managed.

In this case, the service layer could be deﬁned at the

meta-model level, and would therefore not need to be

modiﬁed if the information model is an extension of

the meta-model (since the service layer exchanges in-

formation at the instance level, regardless of the type

of object involved).

It is important to note that the models must com-

ply with a number of requirements. On the one hand,

speciﬁc data types, properties and methods must cor-

respond to the needs of the use cases and program-

ming languages involved in the development. Once

these have been deﬁned, correspondence with those

deﬁned in the meta-model must be indicated. On the

other hand, the extensions must be derived as classes

of subclasses, preserving the predeﬁned scheme, and

must therefore always provide a detailed description

of the elements added.

CIM.jpg CIM.jpg

Figure 6: CIM meta-model diagram.

In brief, if the CIM model is used as a starting

point (as illustrated in Figure 6), its extension will

make it possible to cover one of the needs identi-

ﬁed. For example, entity class ”Address” represents

the address information of the user or organization. In

blockchain, an address is similar to an email address.

It is used to receive and send data on the blockchain

network (just as an email address is used to send and

receive messages). If ”Address” is an extension of

entity class ”Class” (this entity class is shown in ﬁg-

ure 6), ”Address” will have all the same features as

the original, plus something more than ”Class”. That

is to say, the CIM meta-model diagram can be easily

extended without modifying the original metamodel.

Since the blockchain networks can support many

use cases and are applicable in numerous industries,

many companies are beginning to use Blockchain-

as-a-Service. One example is the CIMT (Com-

mon Information Model for Traceability) Project. In

this Project, developed by Soltel Group, a hybrid

blockchain platform called ”Blockchain platform as

a Service for Traceability (BaaS-T)” is used to over-

come all the limitations (see Figure 7).

The CIMT Project uses the Ethereum network

of Alastria (an association that promotes the digi-

APMDWE 2020 - 5th International Special Session on Advanced Practices in Model-Driven Web Engineering

378

Figure 7: Blockchain platform as a Service for Traceability

(BaaS-T). Source: Soltel Group.

tal economy through the development of blockchain),

and Oraclize (Ethereum) to bring data from the out-

side world into an Ethereum smart contract. Soltel

Group Project is deﬁning tracking processes, stake-

holders, and traceability data models in order to apply

speciﬁc extensions to any business case. On the other

hand, MBSE and M2T transformations, are being ap-

plied to deﬁne three generic smart contracts (services)

that (i) will initialize any process of product or service

traceability, (ii) register possible changes, both com-

mon data and possible extensions, and (iii) perform an

advanced search to determine the evolution of a prod-

uct or service in each of its stages and to be able to

check if the raw data is correct.

5 CONCLUSIONS AND FUTURE

WORK

Blockchain technology allows all stakeholders to

check the entire history and (for example) the cur-

rent location of a product. This technology also cre-

ates transparency for all stakeholders. In fact, by irre-

versibly storing data, it creates a unique level of cred-

ibility, and allows stakeholders to strengthen their re-

lationships.

However, two aspects of blockchain traceability

need to be improved. Veriﬁcation mechanisms need

to be adopted to check whether the raw data is cor-

rect and traceability solutions must be completely in-

dependent of the dataset recorded in the blockchain

network. This paper describes a possible way to over-

come these limitations.

Firstly, it proposes an additional layer or module

of traceability that takes advantage of the characteris-

tics of blockchain oracles and APIs. Secondly, it de-

ﬁnes an extendable meta-model that can store trace-

ability information independently of the information

that is stored in the blockchain.

Planned future work includes implementing the

proposed architecture and designing the meta-model

that will facilitate the agile monitoring of product or

service traceability in blockchain networks.

ACKNOWLEDGEMENTS

First of all, we would like to thank all the experts

for their participation and for sharing their valu-

able knowledge. We would also like to thank all

the participants in our pre-tests for their collabo-

ration. This research was partially supported by

the NICO Project (PID2019-105455GB-C31) of the

Spanish Government’s Ministry of Science and In-

novation and Trop@ Project (CEI-12-TIC021) of the

Andalusian Regional Ministry of Economy, Knowl-

edge,Business and University.

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