A New Approach to Semantically Derive Enterprise Information
Architecture from Business Process Architecture
Mahmood Ahmad and Mohammed Odeh
Software Engineering Research Group, Faculty of Environment and Technology, University of the West of England,
Coldharbour Lane, Bristol, BS16 1QY, U.K.
Keywords: Enterprise Information Architecture, Semantic Information Architecture, Semantic Information Integration,
Semantically Derived Information Architecture, Enterprise Information Management.
Abstract: The design of enterprise information architecture (EIA) is a critical success factor of the information
management capability of an enterprise. The EIA design not only supports business process re-engineering
activity but can also facilitate radical design of new business processes. This paper demonstrates that EIA
can be derived semantically from the business process architecture, hence overcoming the classical
problems of time-consuming interviews for business information analysts by using semantically enriched
BPA to derive information entities and processes with the help of domain and process ontologies. The
cancer care and registration process of a health organisation has been used as a case-study for demonstration
purposes. This approach is currently being transformed into a generic Framework for semantic enterprise
information architecture design with an aim to bridge the gap between business architectures and enterprise
information architectures.
1 INTRODUCTION
Classically, the EIA design activity consisted of
building a map of a firm's information resources and
business functions based on time-consuming
managerial interviews. The subsequent time
requirements led to an increasing lack of interest
from the strategic management in this vital design
effort. However, a consistent emphasis on the
vitality of IA (Information Architecture) design in
relation to a firm's business processes and
information resources has remained the case
(Martin, 1989; Teng and Kettinger, 1995) in the
business information management research
community.
Recent research has identified that the
information management capability of an enterprise
has a significant contribution towards development
of its capabilities in customer management, process
management and performance management (Mithas
et al., 2011; Sauer and Willcocks, 2003). The
Information Management (IM) Capability may be
defined as the ability to provide data and
information within the desired accuracy and time
scale for a given enterprise business process. This
implies that the design of information architecture
(IA) is of pivotal importance for developing the IM
capability. The enhancement implied by this ability
develops customer management (CM) capability that
generates opportunities to develop customer
relationships both as consumers and innovation
partners. The IM capability can also contribute
towards developing and redesigning business
processes for carrying out the activities of an
enterprise, reflecting on the Process Management
(PM) capability of the enterprise, (Mithas et al.,
2011).
The design of enterprise information architecture
may, however, remain irresponsive to requirements
of gathering business analytics data as well as to
changes in business strategy unless it incorporates a
comprehensive analysis of business information into
the EIA design. Business information resources
(business entities and processes) of an enterprise can
have pivotal role in information (data) quality,
security and corporate strategy as the requirements
from these enterprise areas translate into how well
and what information resources are managed in the
enterprise, and to what extent they correspond to the
business process architecture of the enterprise.
This paper puts forward an approach that bridges
this gap between business architecture and enterprise
363
Ahmad M. and Odeh M..
A New Approach to Semantically Derive Enterprise Information Architecture from Business Process Architecture.
DOI: 10.5220/0004561803630369
In Proceedings of the 15th International Conference on Enterprise Information Systems (ICEIS-2013), pages 363-369
ISBN: 978-989-8565-61-7
Copyright
c
2013 SCITEPRESS (Science and Technology Publications, Lda.)
information architecture using semantic
technologies. Semantic information about the
business process architecture can be used to derive
information architecture of the enterprise which is
not only responsive to business information needs
but that can also provide leverage to the design of
new business processes. Section 2 discusses the
classical and contemporary attempts to BPA-
oriented EIA. Section 3 discusses the proposed
approach that semantically derives EIA entities and
processes of the enterprise from BPA ontological
artefacts. Section 4 demonstrates the current work
through a case-study in cancer-care domain while
identifying some adjustments for the parent
framework that conceptualises the BPA
methodology. Section 5 discusses issues in this
approach that we currently face with some possible
remedies, and Section 6 concludes this paper.
2 RELATED WORK
Non-Semantic approaches to IA design include
enterprise data model approach by (Brancheau et al.,
1989), long-range information architecture and
ends/means analysis approaches (Wetherbe and
Davis 1983), critical success factors approach
(Rockart 1979), Information Engineering (IE) based
approaches (Martin, 1989) such as IBM's Business
System Planning (BSP) and strategic data modeling
(SDM). Among these approaches, the enterprise data
model approach and the IE-based approaches were
business process-centric; however, the IE-based
approaches lacked appeal due to the absence of
technological advances of today (Kettinger et al.
1996; Teng and Kettinger, 1995). More recently, the
EIA is seen as a part of the overall enterprise
architecture (EA) of an enterprise and is also
mentioned as data architecture. Examples of these
approaches include Zachman's Information Systems
Architecture (ISA) (Zachman, 1987; Sowa and
Zachman, 1992), the Architecture Development
Model (ADM) by TOGAF (TOGAF, 2009) and the
CEiSAR model (CEiSAR, 2008).
Semantic approaches for Enterprise Architecture
(EA) include the TOronto Virtual Enterprise
(TOVE), (Fox et al., 1995), however, no semantic
approach to generate a data (or information)
architecture of an enterprise is process-centric.
Genre and Ontologies Based Information
Architecture Framework (GOBIAF) by (Kilpelinen,
2007) is based on information need interviews and
not based on the knowledge of business entities and
processes. The Field-Actions approach by (Pascot et
al., 2011) uses field actions for incorporating
business process information and uses HL7 ontology
but it lacks derivation of information architecture of
an enterprise.
3 THE PROPOSED APPROACH
3.1 EIA Semantic Derivation
The approach presented in this paper derives the
EIA elements from the fundamental elements of
business process architecture of an enterprise
modelled using the Riva BPA methodology (Ould
2005). The Riva methodology concentrates on the
business of the enterprise and collects essential
business entities (EBEs) without which the
enterprise will cease to perform its function. It may
also collect additional information which is related
to a particular way by which an enterprise may have
decided to run its business (called designed business
entities or DBEs). It extracts from these business
entities a set of units of work (UoWs), each of which
leads to a business process at the operational (case
processes – CPs), managerial (case management
processes – CMPs) and strategic (case strategy
processes – CSPs) levels respectively. It must be
noted here that the CMP and CSP processes are not
carried out by business managers or enterprise
strategists, rather their names indicate the very
nature of the tasks they carry out for a particular
EBE of UoW. The CMP and CSP, however, can be
used by business managers and / or CIOs to induce
changes in BPA for the corresponding entities
corresponding to any new decisions made at the
enterprise level. This needs to be carried out using
enterprise information systems which rely on the
EIA, hence highlighting the need for the EIA
elements to be directly derivable from the BPA.
3.2 The BPAOnt Ontology
The elements of Riva BPA methodology by (Ould,
2005) were conceptualised into the BPAOnt
ontology (Yousef et al., 2009) in their
BPAOntoSOA Framework. This ontological
representation of BPA can be named as semantically
enriched BPA. The BPAOnt ontology was
developed in OWL (W3C-OWL, 2004) and contains
BPA concepts like EBE (essential business entity),
UOW (units of work), Riva_Relations (within
UOWs), CP (case process) and CMP (case
management process), and relationships among
these concepts which makes a good starting point for
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the design of the EIA. The starting point for the
BPAOntoSOA Framework are crude BP models of
an enterprise modelled using Role-Activity
Diagrams (RADs) or more recent BP modelling
languages like BPMN (Yousef et al., 2009). The
business information that causes the development of
BPA of an enterprise should rather originate from
some other sources, in our view, such as business
documents etc. However, the BPAOnt ontological
concepts developed through the BPAOntoSOA
Framework are considered enough for our approach
to start deriving the EIA elements.
As the effort of developing the semantically
enriched BPA is a one-off activity for an enterprise
corresponding to the developed business process
architecture, and needs only minor adjustment
corresponding to business change, an Enterprise
Information Architecture that holds direct additional
knowledge of business processes helps improving
the automation of the EIA design process. Thus, it
reduces the time requirements for interviews and
questionnaires in the sense that the knowledge of
business entities and processes is already captured
through a semantically enriched BPA. However, this
time-saving is more relaizable once the process of
semantically enriched BPA development is
automated by either accessing machine-readable
business process models and workflows or by using
natural language processing techniques to analyse
business documents and extract business process
architectural elements.
3.3 EIA Derivation
The enterprise IA contains design elements that are
derivable from the BPA and are one step closer to
the systems level because EIA elements represent
explicit concepts that can be programmed in an
object-oriented environment to develop a business
information system that can not only capture events
in the enterprise, but can also respond to those
events. The EIAOnt ontology has been designed in
OWL (W3C-OWL, 2004) using the approach by
(Noy and McGuiness 2001) and based on IA
concepts by (Gilchrist and Mahon, 2004) and
(Evernden and Evernden, 2003; Brancheau et al.,
1989), and forms a major component of the
BPAOntoEIA Framework. Fundamental EIA
elements are EIA entities and EIA processes which
are conceptualised as InformationEntity and
EIAProcess concepts respectively in the EIAOnt
Ontology. The InformationEntity concept is
based on the Bung-Wand-Weber’s ontological
model of information that provides ontological basis
for both concrete (physical) and conceptual (non-
physical) entities (Wand and Weber, 1990).
Although this type of entity classification provides a
sound ontological basis for specification and
semantic representation of EIA entities, yet this
classification may not be essential for designing and
implementing enterprise information system based
on these entities. This framework consists of a three-
step approach for EIA derivation:
Figure 1: The proposed approach for Deriving EIA from Enterprise BPA.
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1) The first step of this approach derives initial set
of EIA entities and processes from the EBE and
process instances of the BPAOnt ontology by
instantiating the BPAOntoSOA Framework for a
particular enterprise. The semantic derivation of
the EIA entities includes which EBEs qualify to
become EIA entities and classifies each of them
into concrete and conceptual entities. The
semantic derivation also includes derivation of
EIA processes from process concepts of BPA,
and also captures the associated relationships
among process instances, which are taxonomic
(whole-part) and / or non-taxonomic.
2) The second step of this derivation uses the
instances of the EIA information entity and
process concepts of the EIAOnt ontology to
search for related concepts in external domain
ontologies. This also includes identifying the
taxonomic and non-taxonomic relationships
among new and existing case-study entities and
processes. The search for related entities and
processes may also result in formation of new
external domain ontologies or updating enriching
external ontologies through a structured process
of searching and cataloguing EIA information
entities and processes.
3) Finally, more complex EIA elements such as
EIA traceability matrices, EIA diagrams (such as
Figure 2: RAD Model of the CCR Patient General
Reception sub-process.
Information flow diagrams and / or Entity-
Relationship diagrams) and EIA information
views are to be derived. As the name suggests,
the EIA traceability matrices provide traceability
information for information entities (IEs)
corresponding to EBEs in BPA, IEs vs EIA
Processes, and the like to ensure that all EIA
elements are traceable to generate complete
information flow diagrams for an EIA process.
4 THE CANCER CARE
CASE-STUDY
We demonstrate our new approach by applying it to
one sub-process of the Cancer Care and Registration
(CCR) process of King Abdullah Cancer Centre in
Jordan. The CCR case-study was used by (Yousef et
al., 2009) in her research for identifying services
corresponding to the BPA elements. The CCR case-
study includes the sub-processes of the Patient
General Reception, Hospital Registration, Cancer
Detection, Cancer Treatment and Patient Follow-up.
Of these, we use Patient General Reception sub-
process that models the process of a patient’s
general reception at the Cancer Care Centre. Figure
2 shows the RAD (Ould, 2005) model of Patient
General Process.
4.1 CCR BPA Elements
The EBEs and UoWs generated by the instantiated
by BPAOntoSOA Framework are listed in Table 1.
The output of CCR BPA is described as BPAOnt-
CCR in Figure 1. The units of work are listed in
bold. Corresponding to every UoW listed, the Riva
BPA methodology generates an instance of CP
concept and one instance of CMP concept. Before
identifying EIA elements, we propose to complete
the BPAOntoSOA framework by adding an instance
of the CSP concept for every unit of work.
4.2 The CCR EIA Elements
The BPA elements generated by BPA (Table 1)
form the basis for the EIA entities and processes in
BPAOntoEIA Framework. The semantic derivation
process for EIA entities includes SWRL rules that
identify which EBEs qualify to become EIA entities.
The EBEs, which are semantically derived as EIA
entities, are classified as concrete or conceptual
entities. This basic classification is useful because it
can facilitate the decision-making processes within
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Table 1: BPA elements for the Patient General Reception
sub-process in the CCR case-study.
EBEs or UoWs
Patient General Reception
Receptionist (General)
Patient
Medical Records
Appointment
Patient File
Emergency Unit
Cancer detection unit
Database
Patient details
Case Processes (CPs)
Handle Patient general reception
Handle a patient medical record
Case Management Processes (CMPs)
Manage the flow of Patient general reception
Manage the flow of patient medical record
business information system, e.g. supply chain and
delivery of a printed book or an electronic book
(ebook) version and decide upon cost of delivery
accordingly. In the CCR context, EMERGENCY
UNIT is a physical entity and has a location,
whereas DATABASE is a conceptual entity.
The EIA derivation function generates the
CRUD (Create, Read, Update and Delete) processes
for every EIA entity. The CRUD processes are sub-
concepts of EIAProcess concept in EIAOnt
Ontology. The CPs and CMPs also form an initial
set of EIA (non-CRUD) processes. Once
relationships between these concepts are established
and traceability among these elements is determined,
the EIA design function then moves on to search in
external domain and process ontologies, using
automated ontology search processes to look for
related entities and processes. This is possible only
when domain specific knowledge for a particular
business exists, e.g. cancer care domain knowledge
for CCR case-study. If there is no domain specific
knowledge, the EIA design process can then develop
new domain knowledge as its by-product. The
search may result in significant increase in the
number of EIA entities and processes. The
traceability for these newly found EIA elements
should establish many-to-many relationships
between EIA entities and the initial set of EIA
entities which were originally EBEs in BPA. Many-
to-many relationships also exist between EIA
processes and the EIA entities they access, use and /
or modify. Table 2 lists the set of EIA entities and
processes in the case-study sub-process after
searching for related entity and process concepts in
the NCI Thesaurus (Ceusters et al., 2005) and the
Medical Ontology by Advance Genome Clinical
Trials (ACGT) project (Cocos et al., 2008). We have
noted that entities in these ontologies are not
classified into concrete and conceptual entities and
we therefore recommend constructing a new
ontology using this classification for EIA entities.
The complete EIA for CCR is referred to an
EIAOnt-CCR in Figure 1.
Table 2: Count of EIA elements derived from BPA for
Patient General Reception sub-process in CCR case-study
after look-up in ACGT Medical Ontology for entities.
EIA Element Count
EIA Entities
Entities derived from BPA
Entities searched from
domain ontologies
Concrete entities
Conceptual entities
EIA Processes
EIA Processes
CRUD Processes
IE Management (IEMP)
Processes
IE Strategy Process (IESP)
EIA Traceabilit
y
Matrices
10
8
2
5
5
41
3
32
3
3
4
In this table, the IEMP processes are the
processes for CMPs in the BPA that manage CPs,
and the IESP processes correspond to CSPs.
5 DISCUSSION
The derivation process of these EIA elements has
highlighted a number of important issues which can
be significant for a complete and correct design of
an EIA. Firstly, we note that this approach
significantly depends upon the correctness and
completeness of the Riva BPA elements identified
by instantiating (Yousef et al., 2009)’s
BPAontoSOA framework. The starting point of the
BPAOntoSOA framework is, however, the business
process models of the case-study enterprise that
were originally developed through on-site interviews
in a previous research (Aburub, 2006). We suggest
that the input for BPA development needs to be
business documents and business use cases and not
necessarily BP models. This, however, should not
affect the correctness and validity of EIA as the
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needed BPA elements are instances of the BPAOnt
concepts, and hence it will generate an EIA
corresponding to these BPA elements.
Secondly, although this approach causes EIA
design to be heavily dependent upon the business
process architecture, yet this becomes a strength and
not a weakness of the approach because our
proposed EIA is more business process-aware and it
is more responsive to business process change if it
includes a change management mechanism that
tracks any changes in BPA and makes corresponding
adjustments to EIA architectural elements. The
changes in BPA translate into changes in Riva BPA
business entities, processes or relations between its
units of work. The change management mechanism
of the EIA should capture these changes and initiate
EIA ‘change processes’ to assess the impact of these
changes and implement them. Thus, future
information requirements, that are not yet expressed
in process models will need to emerge from a review
of BPA models (driven by strategic management),
followed by change in EIA. This limitation or
dependence should be seen as an opportunity to
review business process architecture. Future
information requirements that do not need change in
process models may be met through change
management processes acting independently of
BPA.
Thirdly, the EIA derivation process needs to
identify whole-part relationships among the EIA
entities derived from BPA and also for the entities
searched from external domain ontologies. This
includes identifying which EIA entities are merely
multiple instances of another entity and whether this
parent entity needs to be included as an EIA entity
or not. We may call this refactoring of EIA entities.
For instance, there are 10 RECEPTIONIST EBE
instances in the BPA. This leads the information
architect to define one RECEPTIONIST instance
with a variable place of deployment. Furthermore,
the RECEPTIONIST entity may be a sub-entity of a
PERSON entity of which PATIENT is another sub-
entity. The whole-part relationship may be added to
the information about EIA entities using OWL
properties and SWRL rules (SWRL, 2004).
Fourthly, in order to ensure the correctness of
EIA derivation approach, human input from
information architect (IA) may be essential at certain
stages of EIA derivation. For example, the IA’s
input may be required when refactoring of EIA
entities and processes is carried out. This may be
carried out through special-purpose dialogue boxes,
which may render the above derivation process
semi-automated rather than being fully automated,
hence further work for further evolution of the
current work.
Finally, limitations of such an approach to derive
EIA from BPA emerge from those of BPA
methodology. This approach is critically dependent
upon the Riva methodology as the underlying BPA
methodology. This is because the Riva BPA
methodology is systematic and focuses on business
entities and process in a way that brainstorms all
entities and units of work that lead to processes, thus
identifying the business components along its
natural fault-lines and hence providing a
comprehensive (initial) set of EIA entities and
processes.
6 CONCLUSIONS
We have presented a new generic approach for
semantically deriving the Enterprise Information
Architecture of an enterprise from its Business
Process Architecture. We have also demonstrated
results of this derivation using a real and validated
case study based on Cancer Care and Registration in
Jordan, namely the CCR case-study. Moreover, we
have identified some shortcomings in the current
BPAOntoSOA framework algorithm with respect to
the extraction of EBEs from business processes and
hence the reflection on the inclusion of case strategy
process (CSP) in the BPAOnt ontology for a given
BPA case. Currently, this approach is limited to the
derivation of the fundamental EIA elements such as
EIA entities and processes, and the traceability
matrices that ensure forward / backward traceability
from/to these elements. This approach is to be
extended to generate more advanced EIA elements
such as information views and information flow
diagrams while exploiting the dynamic relations
within the BPA’s units of work and the traceability
of EIA entities and EIA processes that access these
entities. Further research includes the generalisation
of this approach to a validated Semantic Framework,
with maximum automaticity, for deriving the design
of an enterprise information architecture from the
given business process architecture of that
enterprise.
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