Modelling Services for Business Knowledge Capture

Carlos Coutinho

, Ruben Costa

and Ricardo Jardim-Gonçalves

Caixa Mágica Software, Rua Soeiro Pereira Gomes, Lote 1-4 B, 1600-196, Lisboa, Portugal

CTS, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, UNINOVA, Lisboa, Portugal

Keywords: Model-Driven Development, Servitisation, Ontology Modelling, Interoperability.

Abstract: The competition inherent to globalisation has led enterprises to gather in nests of specialised business

providers with the purpose of building better applications and provide more complete solutions. This, added

to the improvements on the Information and Communications Technologies (ICT), led to a paradigm shift

from product-centrism to service-centrism and to the need to communicate and interoperate. Traditional

segments like banking, insurance and aerospace subcontract a large number of Small and Medium Enterprises

(SMEs) that are undergoing this change, and must ensure the criticality and accuracy of their business is not

affected or impacted in any way. This also is an excellent motivation for improving the capabilities for

capturing the knowledge about businesses, not only their processes and methods but also their surrounding

environment. The EU co-funded FP7 TIMBUS project comprises tools and techniques to improve business

continuity featuring an intelligent strategy for digital preservation of business assets and environments based

on risk-management. This paper proposes the modelling of service-based business information capturing

strategies to help in the proper establishment of a knowledge base that permits a seamless interoperability

between enterprises.

1 INTRODUCTION

The service globalisation perpetrated by the Internet

has led to a need for change in the traditional

businesses. Market terms and conditions dictate a

constant need to change and adapt to new

environment conditions, new paradigms and

solutions, platforms and technology solutions, trends

and fashions. Thus, being the best-of-breed no longer

means being the most efficient or having the highest

performance, it means keeping up with the look &

feel trends, being available in many platforms and

heterogeneous environments, i.e. implicates a

continuous change. Many manufacturing enterprises

currently have a very clear update and delivery

schedule plan, e.g. when deploying a new car model,

it is possible to know what the next version(s) of that

car will look like and what it shall feature.

This heterogeneity, constant change and

subsequent need for interoperability are worrying

traditional business areas like finances (banking,

insurance), aeronautics and aerospace, which usually

tend to be very conservative towards change on

account to accuracy and stability. As an example, the

aerospace industry is served by a small set of large

enterprises that implement projects and missions, and

which then subcontract several Small and Medium

Enterprises (SMEs) for supporting their development,

thus creating a network of dependencies. The need for

interoperability with the other players in these

networks is as crucial for staying in business, as the

ability to do so while maintaining the proprietary

business assets protected from the competition.

The evolution of ICT permitted faster, more

secure and robust data exchanges, promoting the

development of solutions as result of the

contributions of the several enterprises working in a

network, thus allowing the gathering of multiple

competences and expertise into higher-valued

products and solutions. Emerging paradigms like the

Internet of Things (CORDIS, 2009; Vermesan et al.,

2011) (IoT, which is reshaping the world in the form

of categorized discoverable items) and the Internet of

Services (Cardoso et al., 2008; “Internet of Services,”

2012) (IoS), together with the evolving cloud

computing’s concepts (Jeffery and Neidecker-Lutz,

2010) of Infrastructure as a Service (IaaS), Platform

as a Service (PaaS) and Software as a Service (SaaS)

are gradually transforming the existing reality into a

set of available commoditised virtual objects, services

626

Coutinho C., Costa R. and Jardim-Gonçalves R..

Modelling Services for Business Knowledge Capture.

DOI: 10.5220/0005408906260633

In Proceedings of the 3rd International Conference on Model-Driven Engineering and Software Development (MDE4SI-2015), pages 626-633

ISBN: 978-989-758-083-3

 2015 SCITEPRESS (Science and Technology Publications, Lda.)

enterprises and networks.

This increase of availability and demand of

combined solutions removed all traditional

boundaries and allowed the specialisation of

enterprises (particularly SMEs) and the building of

complex and heterogeneous provider networks. This

move from product-concentric to service-dispersed

strategies is leading to concerns about reaching and

maintaining the interoperability.

To large contractors or even final customers like

banks and space agencies, which depend on the

performance of this network of SMEs to conduct their

business, the improvement coming from the

specialisation needs to be balanced with the increase

on control of the outcomes that result of multiple

sources. The misunderstanding of a concept, a change

in a data unit, a mistaken method on a single

enterprise in the network can lead to chained mistakes

on its counterparts and consequently to errors in the

final result that are very difficult to detect and even

more difficult to trace and resolve.

It is then essential that more than describing data

and interface contracts, the interacting enterprises

publish their models, ontologies and methods so that

their partners can understand and cooperate with them

easier. Moreover, it is important that a controlling

entity (e.g., the prime contractor or the customer) is

able to control if these models and concepts are

aligned with the desired outcome.

This solution is thus essentially targeted to SMEs,

so that they are more transparent in their models and

interaction. It also helps their prime contractors to

monitor whether their requirements are properly

addressed.

The EU co-funded FP7 project TIMBUS

(TIMBUS, 2013) faces these problems and proposes

solutions that include a reasoned Digital Preservation

(DP) of business assets, where this reasoning is

performed by risk management. The main innovation

of the TIMBUS project is therefore its focus on risk

assessment based digital preservation of business

processes, thus not only bringing together but also

advancing traditional digital preservation, risk

management and business process management

disciplines. Preservation is often considered as a set

of activities carried out in isolation within a single

domain, without of taking into account the

dependencies of third-party services, information and

capabilities that will be necessary to validate digital

information in the future. Existing DP solutions focus

on more simple data objects which are static in nature.

The unique aspect of TIMBUS is that it is attempting

to advance state of the art by figuring out how more

complex digital objects can be preserved and later

restored in the same or different environments.

This approach follows the work developed in

(Jardim-Goncalves et al., 2014) to define

NEGOSEIO as an architecture that handles

interoperability negotiations. In this sense, the

contribution in this paper comprises the detail of the

first step of the NEGOSEIO methodology – The

acquisition of business knowledge to develop the

MDA and MDI models, establishing a formal model

and strategy for capturing the information about

businesses, to improve the definition of new solutions

for interoperability between enterprises, and also to

improve the reasoning behind the risk-management

analysis to select business assets for digital

preservation. These methods and framework are

being evaluated in the scope of the TIMBUS project.

Section 2 presents the background analysis on

literature over the proposed solution. Section 3

presents the proposed solutions and how they are

being applied to the determined scope. Section 4

presents the conclusions and future work.

2 LITERATURE REVIEW

The proposed methodology is based on the kernel

aspect of interoperability, proposing formal models

and strategies, supported by a framework which

includes several concepts inspired by the work of

project Manufacturing SErvice Ecosystem (MSEE), a

consortium project of the ICT Work Programme, of

the European Community's 7th Framework

Programme (FP7) (“MSEE Project,” 2012), including

Model-Driven engineering, SOA, but extending it to

Cloud-based solutions.

2.1 SSME and MDSE

The term Services Sciences, Management and

Engineering (SSME) was coined by IBM (Maglio et

al., 2006) to deal with an holistic approach stating that

businesses can be the result of a set of services – the

conjunction of people, technology, and organisations

to create value, towards becoming very adaptive and

flexible, reusable and commoditised. The SSME aims

to improve the sustainability of the development

processes, monitoring and controlling assets e.g., the

quality, productivity and innovation of services and

the exchange and widespread of services.

SSME vision states that to define a business, more

than dealing only with its tangible assets (hardware,

software, and related documentation) – hence

Technology, businesses should also be analysed

according to their processes, environment,

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procedures, quality standards, towards achieving the

business optimisation that is needed for being

competitive.

SSME also notes that an important asset of

businesses is the human factor, i.e. the capabilities of

its human resources and their interactions determine

the agility and flexibility of a business. Issues like

motivation, skills, team building and development,

leadership, personal involvement and achievements

are leading the priorities of enterprises.

All these aspects must be developed in the scope

of a business vision and strategy, which itself can be

analysed, studied and optimised by statistical

methods and Ishikawa (cause-and-effect) diagrams

and analysis towards the creation of servitised

strategies that can be reused as business development

frameworks.

The MSEE project targets to pave the way for

service development in Europe, with the creation of

virtual manufacturing factories (Factories of the

Future), which shall make use of extended

servitisation for the shift from product-centrism to

product-based services, distributed in virtual

organisations and ecosystems.

This project proposed a Model-Driven Service

Engineering (MDSE) architecture, largely inspired in

the concepts of SSME, which accounts enterprise

services to be modelled into three major aspects

(views): IT, Machine (and operation) and Human

Resources. The MDSE models are developed using

various specifications, e.g., the EN/ISO 19440

standard, the GRAI modelling language (Doumeingts

et al., 2006), the POP* language (Athena Consortium,

2011) and the Unified Service Description Language

(USDL).

2.2 Model-Driven Architectures

The term Model-Driven Architectures (MDA) was

coined by the Object Management Group (OMG),

and promotes the evolution of solutions through

successive transformations of higher-level models

into lower-level models, which eventually may result

in going down to the level of code generation (OMG,

2011). This represented a change of the undergoing

paradigm that professed that system architectures are

built by designing and maintaining its code. In this

case, the changes are performed in the models, which

are then transformed into code.

This means that interoperability may start from

the very enterprise foundations, where it is easier to

discuss business-related concepts and ideas, and then

the progressive steps of transformation into lower-

level models may also be synchronised to refine this

interoperability, so that the overhead of transforming

the concepts into code is performed by automation

tools.

The development paradigm of MDA allows the

definition of multiple levels of abstraction in the

modelling of businesses, using descriptive languages

and schemes e.g., UML, OCL, and UEML to define

the solution foundations. Applications should be

designed right from a high-level abstract

Computation Independent Model (CIM) where all

business related functionalities, objectives, methods,

context, requirements and definitions are specified

regardless of any implementation (i.e., pure design).

Then, this model shall be subject to

transformations into a more detailed Platform

Independent Model (PIM), where the business

concepts and rules are converted into activities, tasks,

ontologies, structures and algorithms, although still

independently of the underlying platform.

Finally, other vertical transformations and

conversions shall turn the PIM into a Platform

Specific Model (PSM), which provides the

foundations for the development of the application,

now targeted to a specific platform. Using the

proposed framework, changes to any model (CIM,

PIM) may trigger alterations in the other parties’

models, which then, by transformation towards new

PSMs, swiftly change the application towards

compliance with the new model.

2.3 Model-Driven Interoperability

The Model-Driven Interoperability (MDI) concept

derives from MDA: it comprises the same abstraction

layers, but in this case the target to be modelled is the

interoperation between the involved parties. The idea

behind MDI is to define models for each MDA level

that allow the exchange of information. If the MDA

can be described as a set of vertical transformations

from a conceptual high-level model to a progressively

detailed model, then MDI may be seen as a set of

horizontal transformations to allow interoperability at

each MDA level, e.g., Process, Product and

Organisational models with the System Requirements

at CIM level and transformations of these models into

interoperability models.

Projects like the Advanced Technologies for

Interoperability of Heterogeneous Enterprise

Networks and their Application (ATHENA) defined

a framework that supports interoperability throughout

the various abstraction levels and business aspects of

enterprise software engineering (Athena Consortium,

2007). (Lemrabet et al., 2010) provide simplified

views over the MDI concept and the ATHENA

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Interoperability Framework (AIF) concepts and

solutions on actions to develop each level of

interoperability:

 Interviews, workshops and BPMN choreography

diagrams for CIM levels;

 Diagrams, definition of business goals and BPMN

collaboration diagrams for PIM levels;

 Service Oriented Architectures (SOA) and BPEL

implementations at PSM levels.

(Chen et al., 2008) define a roadmap on the possible

approaches towards the development of enterprise

architectures accounting interoperability.

3 BUSINESS KNOWLEDGE

CAPTURE

The NEGOSEIO (which regards Negotiation for

Sustainable Enterprise Interoperability) Framework

builds a set of MDA and MDI models that clearly

describe the interoperating business assets, processes

and interoperability. Hence it assumes the existence

of a technology capable of capturing this knowledge

and modelling it into their ontologies. This paper

covers the issue of capturing business knowledge that

is essential to build the models for MDA and MDI, it

is essential to first develop a proper container for this

information.

Considering its characteristics and the needs that

were elicited, ontologies were the natural choice for

performing this, because more than storing data, it is

essential to also capture the relationships between the

business concepts (Cretan et al., 2012). The ontology

classes are capable to define concepts and interrelate

them, and the ontology individuals provide the

instantiation of the real artefacts of the business.

3.1 Capture Information System

A problem that comes with the ambition to provide a

solution that fits all businesses regards their

heterogeneity. This fact leads to a lot of difficulties in

the TIMBUS intent to perform an automatic capture

of the knowledge and assets about the business. This

context capture needs to be very flexible and able to

address different needs and requirements. It needs to

address open-source and proprietary environments,

new and legacy applications, and be prepared to

handle new platforms and systems, as well as

different types of security and secrecy demands. A

study analysis performed by project TIMBUS on

businesses determines that business knowledge not

only spans on different machines, using multiple

operating systems and running over multiple

platforms, as most times a lot of this information is

stored in the people’s minds and personal notes, in

archives and storage that needs to be also ingested, or

in legacy systems that need to be addressed and

instantiated, as can be seen in Figure 1.

Figure 1: Heterogeneity in capturing business knowledge.

To address and resolve these challenges, a

Context Model was designed and developed to

systematically capture relevant aspects and elements

of business processes that are essential for their

preservation and verification upon later redeployment

(Neumann et al., 2012). One first difficulty with this

matter is that a single ontology would not be able to

face the specificities of all businesses. Hence, there

was the need to develop a main context model

ontology which can be used as-is for all businesses,

called a Domain-Independent Ontology (DIO). This

ontology was authored in the Web Ontology

Language (OWL) with the support of the Enterprise

Architecture Modelling Language ArchiMate (The

Open Group, 2012) which developed a framework

specifically to address generically the modelling of

information of businesses. This is then complemented

by a set of other ontologies that are created for

modelling specific use-case scenarios, called

Domain-Specific Ontologies (DSOs) (Antunes et al.,

2014).

The resulting Context Model is, then, instantiated

into process-specific sub-models to provide a fine-

grained set of dimensions that surround a particular

use-case scenario. These relevant dimensions that

surround a business process are called context

parameters (Riedel, 2014). The specific scenarios

chosen for TIMBUS served as clear illustrations that

the Context Model is capable of supporting a vast

realm of context parameters. The context model to

capture a business’ knowledge is then the conjunction

of the DIO and the defined DSOs for that particular

business (Antunes et al., 2013).

3.2 Tools for Business Heterogeneity

Another concern that arises from the need to capture

ModellingServicesforBusinessKnowledgeCapture

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the business knowledge is the establishment of a

solution for business context acquisition tool that is

capable to be flexible enough to cope with these

definitions of the information system (i.e., it is

straightforward to develop a solution that works with

a single DIO, but handling multiple DSOs that are

developed specifically to handle the particular topics

of each business is much more complicated). As can

be seen in Figure 1 again, the challenge here is not

only coping with the DSOs, but also about developing

one solution per business, or one solution per instance

of the business, per machine or person, operating

system or platform, and so on, or alternatively, to

develop a single solution and expect the businesses to

adapt to the solution.

Another challenge that relates to this matter

regards a different aspect of the information capture

which are the changes of information with time. This

aspect, which is essential to TIMBUS, is very

relevant for any business because the interoperability

evolves with time, as business needs change, as also

the flows of information between interacting entities.

Hence there is the need to maintain a permanent

connection to the business to perceive any changes

that may conduct to updates in the models that shape

the business. However, by being permanently

connected to the business this cannot mean that the

updates of the business knowledge capturing solution

have any impact on the business itself. Therefore, any

needs to restart the whole system because of this

solution are not acceptable, as so should be avoidable

any downtime of the capturing solution. So a big

challenge is how to update the capturing solution to

cope with the business changes, or with changes in

the DSOs without breaking the business itself.

3.3 Proposed Framework

Considering all these issues, the solution architected

was to use a framework using the Open Services

Gateway Initiative – OSGi (Alliance, 2013)

philosophy. This solution provides an environment

where an application server hosts the context

acquisition framework, which consists in a main set

of tools (context acquisition) that are able to interact

with separate modules called business information

extractors. These extractors are tailored pieces of

software built as OSGi bundles that interoperate with

the framework using a defined interface. OSGi

permits these bundles to be installed, removed, started

and stopped without the need to affect any of the other

components of the system, hence coping with one of

the demands of the desired framework.

Figure 2 shows the proposed framework for the

acquisition of business information. As can be seen,

it comprises a set of static base modules and a variable

and flexible set of extractor modules. While the first

do the standard operations of information acquisition

like the aggregation of the stored information by the

multiple extractors, the latter are actually the modules

that perform the interconnection to the business

premises. These extractors can consist of generic

modules that capture standard information (e.g., the

information about the hardware installed in a target

business machine, or in a whole cluster of multiple

machines, or the software packages in a Linux

distribution, or the set of Perl modules used for a

particular application), and of specific extractors

tailored for the specific needs of a business.

Figure 2: Business Information capturing framework.

These extractors are the instruments for retrieving

the business information that is so needed for the

development of the MDA and MDI models. Having

this set of extractors built as OSGi bundles allows the

creation at the same time of a single solution for all

businesses and of a tailored solution for each business

context. It allows the evolution of the context

acquisition tool to comply with new business

requirements or with new DSOs that are defined for

storing their information. It finally allows a solution

to be fully configurable regarding how to access the

information, e.g., a solution may be built that accesses

the target machine via SSH and has full access to that

machine for retrieving information, another can be

built that comprises a local agent installed on the

target machine, that performs the extraction of

information and publishes it via web-service, or even

a solution that consists in a script to be run by a

business responsible and then submit the results in the

extraction framework. This flexibility permits the

development of solutions that are able to be accepted

by businesses that have low security demands up to

those which have the strictest ones.

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Finally, and most important of all, the definition

of this philosophy allows the analysis of multiple

disciplines for describing the business. Extractors can

be built to model the business from the point of view

of e.g., infrastructures, software, processes, legalities,

organisation, hierarchies, and interoperability. These

views can change from site to site of the business, but

can also be reused on other businesses. Moreover,

extractors may be developed that aggregate other

extractors in order to infer information from multiple

sources with a specific purpose.

Having this open architecture also allows

extractors to be built according to the proper

investment performed, i.e., an extractor that is built to

describe a particular view of a business can be

replaced by another much more thorough and that is

able to extract more detailed information if it to be

developed e.g., for a defence department or for an

aerospace segment. Building more complex and

complete extractors may then mean more investment

in their development, hence the development of this

business context acquisition framework allowed the

fostering of another market, which is one of the

development of extractors, in a business model

similar to the one used in mobile apps.

As can also be seen in Figure 2, the results of the

extractions, coming from multiple disciplines, with

multiple sources and degrees of accuracy and time,

are then compiled and stored in the context model. All

the ontologies in the context model are then merged,

thus allowing interesting conclusions to be achieved

by reasoning and inferring the properties of the

individuals after the consolidation of the various

ontologies.

The extractors and reasoners are subsequently

applied to the Context Model (or to an instance of it)

for extracting, monitoring, and reasoning for digital

preservation purposes. The technical dependencies on

software and services can be captured and described

via CUDF (Common Upgradeability Description

Format) defined in the MANCOOSI project

(Mancoosi Consortium, 2013) for systems which are

based on packages. Such an approach enables

TIMBUS to capture the complete setup and

dependencies of a specific configuration for long-

term preservation, which can be re-created, re-

executed, and redeployed at a later time on modern

hardware and with a different business scenario.

3.4 Use-case Validation

This research work was being implemented in the

scope of the TIMBUS project. This project is now

finishing, having validated its results in a set of well-

defined real use-cases.

One of these use-cases regards the analysis for

business continuity and risk management towards

digital preservation of the network of dams in

Portugal, performed by the National Civil

Engineering Laboratory (LNEC, 2013). The

applicability of this paper in this particular use-case

was then validated using a set of indicators and

validation rules, which include the amount of

different terminologies and processes that need to be

harmonised throughout the different dams or the

different sensor suppliers, the amount, effort and cost

of the rework happening due to semantic

misalignment before and after the application of the

framework, the amount of time spent on harmonising

these semantic issues with and without formal

negotiation, the advantages in amount of time and

cost of having a rich historic record of previous

negotiations and negotiation steps and resulting

outcomes. While unfortunately most results of

TIMBUS have restrictions to their publishing

regarding the proprietary rights of each business of

the use-cases that were used for the project’s

assessment, nevertheless several evidences were

published documenting the business capturing

process success: (TIMBUS, 2014b) shows the whole

process of capturing information for the sample use-

case of preserving an open-source workflow process

business, and (TIMBUS, 2014a, 2014c, 2014d)

present public assessments and validation of the

results of the TIMBUS tools and processes, which

include the Business Capturing presented in this

document.

4 CONCLUSIONS AND FUTURE

WORK

Business complexity is rapidly increasing due to

globalisation and, well, evolution. In this fast-pace,

there are options and business decisions that need to

be taken rapidly as well. The lack of maturity of

numerous enterprises leads them to early and poorly

designed solutions for enterprise interoperability,

leading to some obvious mistakes that can be

corrected immediately, and others that are not so

obvious or detectable. When these are finally

detected, some may require a reinstate of some of the

business premises and environment. While the

TIMBUS project is aiming to support the

development of this by performing risk management

and selective digital preservation of assets, it is also

ModellingServicesforBusinessKnowledgeCapture

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based on the traditional risk management empirical

analysis. This paper proposed an information model

and a framework to support a mature, decision-

support analysis of the business continuity, based on

the modelling of the various entities and aspects

related to enterprise interoperability, supported by a

servitised set of supporting activities which are

defined to perform the interoperability and to support

it. The proposed framework was then validated in the

scope of the project TIMBUS’s use-cases. As future

work, the authors foresee improving the current

framework to provide it elements to perform a better

decision support with respect to which disciplines to

handle, their accuracy, better ways to automate the

merging of the ontologies. One possible solution to

achieve this is via the use of the negotiation

framework NEGOSEIO, thus closing its own loop.

ACKNOWLEDGEMENTS

The authors wish to acknowledge the support of the

European Commission through the funding under the

Framework Programme for research and

technological development and demonstration

activities, through projects TIMBUS (FP7 / 269940)

and FITMAN (FP7 / 604674).

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