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{{Paper
|id=Vol-1637/paper_6
|storemode=property
|title=Highlighting the Gaps in Enterprise Systems Models by Interoperating CGs and FCA
|pdfUrl=https://ceur-ws.org/Vol-1637/paper_6.pdf
|volume=Vol-1637
|authors=Simon Polovina,Hans-Jürgen Scheruhn,Stefan Weidner,Mark von Rosing
|dblpUrl=https://dblp.org/rec/conf/iccs/PolovinaSWR16
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==Highlighting the Gaps in Enterprise Systems Models by Interoperating CGs and FCA==
https://ceur-ws.org/Vol-1637/paper_6.pdf
Highlighting the Gaps in Enterprise Systems
Models by Interoperating CGs and FCA
Simon Polovina1 , Hans-Jürgen Scheruhn2 ,
Stefan Weidner3 , and Mark von Rosing4
1
Conceptual Structures Research Group, Sheffield Hallam University, UK
2
Business Informatics, Hochschule Harz, Wernigerode, Germany
3
SAP UCC & School of Computer Science, University Magdeburg, Germany
4
LEADing Practice ApS | Global Univerisity Alliance, Denmark
s.polovina@shu.ac.uk, hscheruhn@hs-harz.de,
weidner@ucc.uni-magdeburg.de, mvr@leadingpractice.com
Abstract. Enterprises arise from creative human endeavours, articu-
lated through business concepts encoded in enterprise information sys-
tems through a modular Enterprise Information Model (EIM). The EIM
thus brings the productivity of computers to bear. Essentially, the EIM
represents conceptual structures, which align the computer’s structured
way of working with the human’s conceptual way of thinking. Using
an industrial-strength SAP exemplar known as ‘Global Bike Inc.’, and
expressing its EIM’s meta-objects as meta-object → relation → meta-
object, Conceptual Graphs (CGs) simplified the EIM’s modules, which
consist of four business layers and two information systems layers. The
logical simplification of these modules is extended into four levels of detail
that culminate in performance indicators being assigned to each of the
six layers. From the CGs, Formal Concept Analysis (FCA)’s CGtoFCA
algorithm was used to generate the meta-objectarelation → meta-object
binaries that identified the pathways layer-wise and level-wise between
the meta-objects. Through the interoperability of CGs and FCA, gaps in
the conceptual structure of the EIM as highlighted by its performance in-
dicator or measure, implying that the layer is not as modular as intended.
Keywords: Enterprise Information Model (EIM), Business Layers (Value,
Competency, Service, Process), Information Systems Layers (Applica-
tion, Data), Levels (Enterprise, Department, Workplace, Performance
Indicator / Measure), GBI (Global Bike Inc.), ARIS (Architecture of In-
tegrated Information Systems), SAP Solution Manager, Enterprise Re-
source Planning (ERP) Systems, Meta-Objects, Conceptual Graphs, For-
mal Concept Analysis
1 Introduction
Enterprise information systems are nowadays mainstream to business activ-
ity [16]. Enterprises arise from creative human endeavours, articulated through
high-level business concepts that in turn are embodied by the lower-level data
46
structures that computerised enterprise system applications rely on to bring their
productivity to bear [10]. An exemplar of enterprise systems to date is SAP SE
(www.sap.com). SAP is the world’s market-leader for enterprise systems soft-
ware and services. SAP (which in English stands for Systems, Applications and
Products) have built their reputation on understanding business systems. Given
its impact, this vendor thus forms the background of our work as we now present.
SAP’s systems tend to be purchased and used by larger scale enterprises,
with consequently large-scale data sets. Consequently, learning SAP for new-
comers is a major task without having a reference implementation of this scale
to understand its capabilities and potential [5]. To address this issue, Global Bike
Inc. (GBI) has been developed5 that is used world-wide by SAP’s University Al-
liances program for learning, research and industrial practice (uac.sap.com) [3].
As well as learning material and supporting documentation, GBI includes a En-
terprise Information Model (EIM) that demonstrates GBI’s alignment of busi-
ness, information systems and the underlying technology [13]. The model uses
the well-known and industry-standard ARIS software that provides a range
of modelling constructs in a comprehensive software tool from Software AG
(www.softwareag.com). Furthermore the EIM is connected to a running SAP
enterprise system implementation through an SAP-specific product known as
SAP Solution Manager [12]. The GBI business and information system concepts
are depicted as meta-objects and are interconnected with other meta-objects
through semantic relations, as we will explain later on in the paper. Pertinent to
understand meanwhile is that human creativity through business concepts are
articulated into a form that is encoded into a application or data structure that
the computer can process.
An opportunity therefore arises to explore the effectiveness of this contem-
porary approach using Conceptual Structures (CS), given its stated purpose of
harmonising the creativity of humans with the productivity of computers [2]. We
might expect that CS will discover hidden meaning or gaps as previous work has
shown using a technique that maps Conceptual Graphs to Formal Concept Anal-
ysis [7]. It is this approach, but this time with an industrial-strength example
(i.e. GBI) that we now investigate and present the findings.
2 Conceptual Structures
Table 1 is derived from previous work that describes the EIM [11]. In that work,
the particular industry of GBI (bike manufacture) is used to demonstrate a gen-
eral EIM that can be applied to all industries. This EIM shows the meta-objects
of the business layer (Value, Competency, Service and Process) and the infor-
mation system layer (Application and Data). These horizontal layers are further
described by vertical levels ranging from 1 to 4, where 1 are the most high-level
meta-object and 4 the most specific meta-objects. Level 1 refers to the whole
5
The SAP UA GBI environment consists of a set containing three parts: 1) SAP
solutions (landscape), 2) GBI model company, and 3) curriculum material (including
slides, exercises, case studies)
47
Table 1. Information Meta Objects Mapping
Business Layer Information System Layer (ERP, HANA)
Layer:
Value Competency Service Process Application Data
Level
1 Vision, Business Business Business Application Enterprise
Mission Function Service Process Module Data Cluster
Strategy, Organizational Organizational
Goal unit unit
2 Vision, Business Business Process Application Department
Mission Function Service Step Function Data Cluster
Strategy, Organizational Organizational
Goal unit unit
3 Vision, Business Business Process Application Workplace
Mission Function Service Activity Task Data Entity
Strategy, Transaction
Goal Code,
System
organizational
Unit
Dimension
Objective Business Event Business
Object Object
Data Entity Data Entity
Event
Business Data Data
Media / Object Object
Accounts (Media)
Business Services Process Application
Roles Roles Role Roles
Business Service Process Application
Roles Rules Rules Rules
4 Performance Business Service Process IT Fact Table
Indicator Compliance Level Performance Governance Customizing
Agreement Indicator Data Table
(SLA) (PPI)
Master Data
Table / View
Transaction
Data Table
Revenue/ System Key
CostFlow Measurements Foreign Key
Describing Attributes
48
enterprise, level 2 a department or organisational unit (e.g. sales) within the
enterprise, level 3 the actual workplace (e.g location) in the organisational unit,
and level 4 is the performance indicator and other measures used to evaluate the
alignment and effectiveness of its above 3 layers. Level 1 is thus the most con-
ceptual and level 4 the most structural. As concepts and structures are thereby
aligned as meta-objects in the matrix given by this table, it offers an initial
conceptual structure of the EIM.
3 Conceptual Graphs and Formal Concept Lattices
From this starting point, Conceptual Graphs (CGs) enabled us to focus on the
meta-objects and their relations, through CGs’ simple concept → relation →
concept nature [6, 14]. Furthermore we could make use of CGs [Type-Label:
Referent] components in each CGs concept. To identify gaps and missing mean-
ing (semantics) and in line with previous work, FCA (Formal Concept Analysis)
was then applied through the CGtoFCA algorithm [1, 7, 8]. The outcome is then
presented as a Formal Concept Lattice (FCL). A CG was produced for each
layer [6, 14]. Each layer has a meaning its own right given their distinctive head-
ings (i.e. Value, Competency, Service, Process, Application, Data). Our intention
was thereby to capture each layer as a modular ‘semantic unit’ in its own right.
The result for the Value Layer in the EIM is accordingly shown in Fig. 1.
Fig. 1. Value, CGs
The Value CG depicts the each meta-object name (i.e. Vision, Mission, Strat-
egy, Goal) as a CG type label. To instantiate it an a particular meta-object, a
unique identifier appears in the referent field. For example, v1V denotes that
a meta-object that is Vision (v), Level 1 (1), and V (Value layer). Likewise,
g3V for example describes Goal, Level 3, Value and so on. The [Enterprise:
@enterprise] concept follows an alternative pattern where (@enterprise) is
49
a CGs measure referent. The pointer to Enterprise follows that of the previous
work [1, 7, 8]. The overall significance of this concept that all the activities that
make up an enterprise ultimately point to the enterprise6 , even though Enter-
prise is absent in the table. The relations (e.g. ((assigned to)) also do not
appear in the table; they are however in the EIM. Space does not permit the
detailed description of the relations but are explicated elsewhere [11]. Essentially
((assigned to) refers to a horizontal relation usually in the same layer while
(consists of) is a vertical relation between the levels in the layers. (There is
no associated layer or level for Enterprise as it reflects the ultimate culmination
of all the layers and levels). The relation measured-by has its usual meaning.
The FCL for the Value layer will be discussed shortly.
The CG and the FCL for the next layer i.e. Competency is not shown due to
space restrictions. Fig. 2 shows the following Service layer CG, which nonethe-
less highlights similar findings to that of Competency. It exhibits the same
[Type-Label: Referent] and (relation) pattern as illustrated by Fig. 1 and
its explanation above. So, for example bs1S in [Business Service: bs1S] de-
scribes bs for Business Service, 1 is Level 1, and S is Service. In this layer there
is an (occurrence copy) relation too. Essentially, this relation describes two
meta-objects that are synonymous, except they appear in different layers. For
example, [Business Service: bs1S] → (occurrence copy) → [Business
Process: bp1P]. They are therefore not co-referent, and might be described
as ‘pseudo-synonym’ meta-objects. The FCL generated by CGtoFCA for the
Service layer is shown by figure 3.
Fig. 3 is the result of the CGtoFCA algorithm transforming the meta-object→
relation → meta-object triples in the CG of Fig. 2 to meta-objectarelation→
meta-object binaries7 . Like in the previous work, it thus identified the pathways
layer-wise and level-wise between the concepts (meta-objects) and (semantic)
relations [1,7,8]. Using index numbers to illustrate that the relations are distinct
from each other (e.g. assigned toN where N ≥ 1 ≤ 3), the CGtoFCA FCL
Fig. 3 evidences that [Enterprise: @enterprise] is not bottommost. That
is because of the meta-objectarelation attributes that are outside the intent
of the level 4 key performance indicator (KPI) meta-object [Service Level
Agreement (SLA): sla4s], which evaluates the Service layer.
An inspection of Fig. 2 shows that there are the three (occurrence copy)
relations that do not point directly or indirectly through the other concepts to
[Enterprise: @enterprise] in that figure. As they are not co-referent they
cannot simply be removed. To do so would break the link with the associated
meta-objects in the Process layer. Nor should vertical relations be (arbitrarily)
added; such relations would anyway be outside of the semantic scope of this
6
We could have stated [Enterprise: GBI] but given our earlier remark about the
generality of the EIM we chose @enterprise.
7
The CGtoFCA algorithm is implemented in software (http://cgfca.sourceforge.net/)
and uses the CGIF file format output from CharGer
(http://charger.sourceforge.net/), in which the CGs were drawn. Concept Ex-
plorer (http://conexp.sourceforge.net/) was used to generate the FCL.
50
Fig. 2. Service, CGs
Fig. 3. Service, FCA
51
layer, which is Service not Process. Rather, these (occurrence copy) desti-
nation meta-objects in Process represent a messaging structure between these
layers. As it stands, the layer is not a self-contained semantic unit. Although not
shown the same happens for the Competency layer meta-objects. In passing it is
worth remarking in ARIS that these occurrences are the same object, so in that
sense the problem does goes away. But they are ‘pseudo-synonyms’, evidenced
by them not being co-referent semantically. Put simply, Process needs Service to
be a semantic unit, and vice versa. The same issue applies to Competency and
its same dependencies with Service.
Fig. 4. Value, FCA
52
The CGs and FCL for the remaining layers (i.e. Process, Application, Data)
are not shown once more due to brevity of space. Application and Data are
however illustrated elsewhere [9], in which Data in the EIM emerges to be a
semantic unit i.e. [Enterprise: @enterprise] is the object in the bottommost
concept. This also happens with the Value FCL that is now presented in Fig. 4.
This is evidenced by Fig. 1 in which the arrows in the Value CG show a flow
from one starting point (v1V) to one ending point (@enterprise). Value and
Data can thus be recognised as meta-objects in their own right. Such a meta-
object would be a meta-object of all the meta-objects inside their respective
layers. An analogy emerges with the object-oriented principle of high cohesion
(where expressibility is encapsulated within the layer) and low coupling (where
the dependencies between the layers are decreased as much as possible), thereby
reducing the maintenance and modification costs of the enterprise system, the
models and the human energy to maintain them [4, 15, 17].
4 Conclusions
GBI, ARIS and SAP Solution Manager provide a comprehensive and detailed
EIM (Enterprise Information Model), in the pursuit of conceptual structures.
CGs (Conceptual Graphs) and FCA (Formal Concept Analysis) highlighted the
gaps in the existing EIM. These discoveries were achieved by a focus on the lay-
ers (from Value to Data) and their levels, ranging from 1 to 4 denoting their level
of detail going from the most conceptual to the most structural. Through the
interoperability of CGs and FCA, gaps in the conceptual structure of the EIM
were highlighted in certain layers (i.e. Competency, Service, Process and Appli-
cation) and its performance indicator or other measure (i.e. level 4), implying
that these layers (unlike Value and Data) may not be as modular as intended.
Enterprise systems could thereby benefit from layers made up of semantic units
with better-defined interfaces (borrowing ideas from object-orientation) rather
than as present. Taking this approach, enterprise systems can increase their ef-
fectiveness in contributing to the enterprise’s human-driven purpose.
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