Enterprise Ontologies: Open Issues and the State of Research
A Systematic Literature Review
Artur Leinweber, Max Freiberg, Patrick Spenke and Birger Lantow
Chair of Business Information Systems, University of Rostock, Albert-Einstein-Str. 22, 18057 Rostock, Germany
Keywords: Enterprise Ontology, Systematic Literature Review, Systematic Selection.
Abstract: The aim of this work focused on the content of the subject ”Enterprise Ontology”. We present our ongoing
work on analysing literature about enterprise ontology models. The provision of this analysis is on the one
hand a summary of some previously published papers according to the topic and at the same time a precise
differentiation can be documented between each work. Our contributions are twofold: first, we show how to
find appropriate literature according to specific criteria and second, we answer special research questions
which belong to ”Enterprise Ontology”. Moreover, the results of the different authors presented in this paper
are innovative visions about creating and implementing tools or ontological models.
1 INTRODUCTION
The concept of an Enterprise Ontology (EO) has
received some attention in the last years. Many
papers have been published that show EOs as a tool
for enterprise development. Benefits generated with
the help of EO, can be direct savings (Gailly and
Poels, 2009; Wautelet et al.,1998;Sunkle et al.,
2013) or an increase of business process efficiency
(Guangwen and Hu, 2009; Moura et al., 2010) for
example.
This paper tries to find answers to questions
regarding past and ongoing research on EO. Where
appropriate it shows statistics of different aspects of
scientific activities in the area. The result is a
categorization of streams in EO research. Our
systematic analysis does not go into every detail of
the papers, nor does it discuss the opinion of all
authors. The main aim of this paper is to give a
summary which generally describes research
activities in the area of EO.
The remainder of this paper is organized as
follows. The next section generally introduces the
concept of Enterprise Ontologies. Section 3 briefly
discusses the process of a systematic literature
review and its specific implementation for our
investigation. This includes the formulation of the
research questions. The findings of the performed
literature review are described in section 4. The last
section 5 outlines the most important conclusions.
2 ENTERPRISE ONTOLOGY
An ontology is an explicit specification of a
conceptualization (Gruber, 1995). The ontology
includes definitions of concepts and an indication of
how concepts are inter-related which collectively
impose a structure on the domain and constrain the
possible interpretations of terms (Uschold, 1995) .
The ontology is used to improve communication
between either humans or computers. In the
concrete, the ontology is used to assist in
communication between human agents, to achieve
interoperability among computer systems, or to
improve the process and/or quality of engineering
software systems (Jasper and Uschold, 1999). The
combination of the computer systems of an
enterprise, their connections to each other and the
related exchange of information can be seen as the
Enterprise Architecture (EA) (Stelzer 2010;
Hanschke 2009; Meyer and Birsöz, 2009; Rosauer et
al., 2004; Feldschmid, 2009) . Therefore, if the
Enterprise Architecture is defined in an ontology,
communication problems in EA related tasks can be
reduced. Ontologies provide a tool for
communication and for formalization.
Concretely, stakeholders of an enterprise can
share exact and common interpretations of the
Enterprise Architecture and its components.
Furthermore, systems interoperability can be
improved. This fosters internal system integration
280
Leinweber A., Freiberg M., Spenke P. and Lantow B..
Enterprise Ontologies: Open Issues and the State of Research - A Systematic Literature Review.
DOI: 10.5220/0005081102800287
In Proceedings of the International Conference on Knowledge Engineering and Ontology Development (KEOD-2014), pages 280-287
ISBN: 978-989-758-049-9
Copyright
c
2014 SCITEPRESS (Science and Technology Publications, Lda.)
and external cooperation (Kang et al., 2010). In
general, an EO is a formal and explicit specification
of a shared conceptualization among a community of
people of an enterprise (or a part of it). It includes
static, kinematic, and dynamic aspects, for example
reflecting the Enterprise Architecture.
In particular, an ontology satisfies the next five
quality requirements (C
4
E) (Dietz, 2006):
Coherence - the different aspects of the
models form a logical and truly integrated
entirety
Comprehensiveness - all relevant issues are
covered, so the entirety is complete
Consistency - the models are free from
contradictions and irregularities
Conciseness - the entirety is compact and
succinct, no superfluous matters are contained
in the models
Essence - shows only the essence of the
enterprise, its core structure
Enterprise ontologies can be used in many different
sectors and various organizational roles, for
example:
Managers are enabled to understand the
essence of their enterprise.
Software developers can use a formal
specification of organizational aspects .
Employees are aware of the role they fulfil in
the organization of the enterprise.
Auditors - Enterprise Ontologies can provide
full transparency to the operations of an
enterprise.
3 STUDY DESIGN AND
OVERVIEW
The following section describes the process of
developing a systematic literature review. Prior to
the review process, a topic of interest must be
defined. Furthermore, research questions regarding
this topic of interest need to be formulated. They
represent the basis of the study and serve as a
guidance during the data extraction. Regarding the
topic of EO, the following questions drew our
attention:
RQ1: How much research activity on the field of
EO has there been since 2007?
RQ2: What research topics are being investigated?
RQ3: What research approaches are being used?
RQ4: What applications are seen for EOs?
RQ5: Which topics regarding EO need further
research according to the authors?
The review process is divided into four different
parts (see Figure 1). The first activity is to identify
conference series, journals and catalogues that are
likely to represent state of the art of research on the
topic of interest. Here a base set of papers for review
is extracted by keyword search. The second step is
the exclusion/inclusion of papers based on title and
abstract. Then, the remaining papers have to be
classified and data has to be extracted with regard to
the research questions. The fourth and last step is to
analyse the extracted data. This review process is
based on the guidelines for systematic literature
reviews by Kitchenham and Charters (Ivarsson and
Gorschek, 2009) .The next paragraphs describe the
performance of these steps in detail.
Figure 1: Review Process (Ivarsson and Gorschek, 2009).
3.1 Identification of Papers
The first step was the identification of EO related
papers in a selection of appropriate literature
sources. Sources were the journals on ”Computers in
Industry” (CII), Information Systems (IS), Expert
Systems with Applications (ESA) and the digital
libraries of Springer, of the Association for
Computing Machinery (ACM), of the Computer
Society (CSDL), and of the Institute of Electrical
and Electronics Engineers (IEEE).
In order ensure a comprehensive and unbiased
identification, certain keywords have been
determined to apply them in the search process.
These keywords were elaborated by test searches
or by altering the form of the words, e.g. plural.
Figure 2 presents the search terms used. Papers have
only been selected if one of the keywords appeared
in the title or abstract. A full text search would have
resulted in too many irrelevant papers. (Ivarsson and
Gorschek, 2009; Kitchenham, 2004).
3.2 Paper Selection
In this step, the abstract is examined to reduce the
remaining research papers to the ones which are
relevant for answering the research questions. A
main criterion for the selection was that the paper
has to deal with the topic EO by investigating
methods, tools, theories, examples, deployment,
evaluation etc. Additionally, only research papers
have been included because our focus lies on
EnterpriseOntologies:OpenIssuesandtheStateofResearch-ASystematicLiteratureReview
281
Figure 2: Paper Selection - Overview.
research streams.
Regarding the abstract in- or exclusion of papers
was based on the following rule:
Include: One of the activities like investigating
methods, tools, theories, examples, deployment,
evaluation etc. is named as a main contribution
of the paper.
Exclude: Otherwise
3.3 Data Extraction
This process was based on full text studying.
Relevant data was mapped directly to the research
questions and stored in a table. For each selected
paper, this table contained a reference to the original
paper and paper meta-data like the author and the
author’s affiliation. Later a classification of the
paper content with regard to the research questions
was added. (Ivarsson and Gorschek, 2009).
3.4 Data Analysis
The data analysis summarizes the results of the data
extraction and provides answers to the research
questions. The analysis can be descriptive or
quantitative. Quantitative and descriptive
information should be arranged in tables or figures
with respect to the research questions. These tables
or figures should highlight the differences and
similarities of the papers. Regarding the
classification of paper content there is an iteration
between data extraction and data analysis. For
example, the classification scheme of research
approaches (RQ 3) is based on the approaches found
by performing the paper analysis. (Ivarsson and
Gorschek, 2009; Kitchenham, 2004).
3.5 Threats to Validity
There are two main threats to validity. First, there is
the selection bias. The sample taken for literature
review may not represent the current state of
research. Nevertheless, figure 2 shows a broad base
of identified papers regarding the topic. Thus, our
selection is considered to be representative. The
second threat lies in the process of data extraction.
For example, the classification of the papers is based
on subjective decisions to some extent. The research
questions help to reach a certain level objectivity.
Additionally, the data extraction process has been
done by three persons on order to reduce the
individual influence of a single subject.
Figure 3: Research activity on the field of EO.
KEOD2014-InternationalConferenceonKnowledgeEngineeringandOntologyDevelopment
282
4 RESULTS AND ANALYSIS
In the previous sections the purpose and the process
of the systematic literature review have been
described. This section describes the results of data
analysis. The research questions that have been
formulated at the beginning are used to structure the
results.
RQ1: How much activity on the field of
”Enterprise Ontology” has there been since 2007?
In general, there has been some activity in the
research area of EOs in the period from 2007 to
today. Figure 3 shows the activity in a graph.
The blue line describes the absolute number of
papers that have been found in the corresponding
year. There are two major turning points. The peak
of activity was in the year 2009 and the bottom in
2011. After 2011 the activity increases but the
number of papers has not yet been as high as in
2009. The orange line displays the trend over the
complete period of time. Apparently, the trend of the
research in the field of EOs decreases slightly.
Nevertheless, since there was a turning point in 2011
it seems that EO research will get more attention in
the next years.
RQ2: What research topics are being
investigated?
There is no dominant research topic that is covered
by the majority of the selected papers. But the
classification by research topics lead to a ranking.
The following overview shows the quantities of
papers that are summed up to a topic (see figure 4):
• 11 papers are related to the topic of Creating
Enterprise Ontologies; an example of this class is
the paper ”Enterprise Ontology - Diagnostic
Approach”. It deals with the construction of an
enterprise ontology with the purpose of diagnosing
economic situations.(Andreasik, 2008)
• 9 papers are related to the use of Enterprise
Ontologies as Supportive Tools for information
systems; an example for this class is the paper ”TCM
(Traditional Chinese Medicine) Telemedicine with
Enterprise Ontology Support a Form of Consensus-
Certified Collective Human Intelligence” which is
about constructing telemedicine systems with EO
support. (Wilfred et al., 2009)
• 5 papers are related to the Mapping and
Modelling of Enterprise Ontologies. The difference
between this topic and Creating Enterprise
Ontologies lies in the focus on altering existing
ontologies in contrast to ontology creation; an
example for this class is the paper ”Towards
Ontology-Driven Information Systems: Redesign
and Formalization of the REA Ontology” which is
about the transformation of EOs (Gailly and Poels,
2007)
• 4 papers are about Tools and Examples of
Enterprise Ontologies; an example for this class is
the paper ”A Core Ontology for Business Process
Analysis” which deals with an example of an
ontology that enhances business process analysis.
(Pedrinaci et al., 2008)
• 3 papers are related to Enterprise Ontology
based Frameworks; an example for this class is the
paper ”Organization-Ontology Based Framework for
Implementing the Business Understanding Phase of
Data Mining Projects” which presents theoretical
work on an ontological framework. (Sharma and
Osei-Bryson, 2008)
The topics of the remaining 8 papers cannot be
assigned to classes defining a general topic. They are
summarized in the class Other. The following chart
provides a graphical overview of the allocation.
Figure 4: Research topics.
RQ3: What research approaches are being used?
The most common research methods used to
evaluate the subject EOs are Theoretical Work
(54%) followed by Prototyping (27%)(see also
figure 5). An interesting point is that our research
shows a significant count of Experiments and Case
Studies. The reason might be that this research
methods focus on verification and evaluation of
already existing prototypes and techniques in the
area of EOs. The large number of papers containing
just Theoretical Work may have its reason in the
lower amount of resources needed. Additionally
there might be too much attention to theoretical
work in the community. ”As recent developments in
the sciences demonstrate, this often goes hand in
hand with a misrepresentation of the role of
theoretical work”. (Atmanspacher, 2010)
On the other hand, the topic EO is still in the
early stages of research. Therefore, it might be that
many issues must be clarified in advance before the
approaches can be applied in practice. This could
explain the high number of papers having
Theoretical Work as research approach. However,
EnterpriseOntologies:OpenIssuesandtheStateofResearch-ASystematicLiteratureReview
283
our study also shows a remarkable number of papers
on a Prototype which does not fit to the previous
assumption. There are many approaches, methods,
and applications (see RQ 4) for Enterprise
Ontologies that have already been validated in
practice.
RQ4: What applications are seen for
”Enterprise Ontology”?
Based on the literature review, there are different
purposes of EOs that can be categorized into the
following classes:
Creating Artefacts
A variety of approaches have been found concerning
the use of EOs for the creation of new methods and
applications solving enterprise problems. Based on
an EO it is possible to create a Corporate Memory
(Probst and
Jussupova-Mariethoz, 2007), Value- and
Design-Chains (Chae et al., 2009) , Information
Systems (Schartz et al., 2010) , Reports (Schartz et
al., 2010) , a Diagnosis of an economic situation
(Andreasik, 2008) of a company.
Figure 5: Research Approaches.
Interoperability and Translating/Mapping
Approaches to realize interoperability in several
application areas have been discovered. With
”Ontology Mapping” (Harding and Kumar, 2013) it
is possible to convert existing ontologies into a state
where all ontologies can be connected with each
other. In addition, there are mapping methods in
order to translate an EO into a full functional
information system (Hysmans et al., 2010) . Another
approach is semantic interoperability (Chae et al.,
2009). Here, the focus lies on the integration of
enterprise values with consideration of the meanings
underlying these values. Finally there are also
possibilities to make heterogeneous information
massifs of business applications interoperable
(Leppänen, 2007; Gailly and Poels, 2007).
Integration and Collaboration
In addition to the integration of information
systems and the collaboration of enterprises (Lee et
al., 2010; Chae et al., 2009) , there are also
applications to align business ontologies for
integrating heterogeneous business processes (Jung,
2009). Furthermore, there are possibilities for
planning and integrating businesses (Zordan and
Umar, 2009) with EOs and also approaches to
integrate entire businesses (Gailly and Poels, 2007;
Leppänen, 2007).
Support and Handling Knowledge
Enterprise Ontologies offer the opportunity to
support business processes (Starzecka et al., 2008;
Lee et al., 2010) , improving quality in education
(Isbandi, 2013) and dealing with competency models
(Sanchez-Alonso et al., 2012). Furthermore,
managers and other leading actors can use EOs for
better decision making (Isbandi, 2013) . In addition,
EOs can be used to control the quality for enterprise
models and can assist at data mining (Liu et al.,
2007) . Moreover, EOs can form a base for
knowledge-management (Woo et al., 2009) , support
collecting knowledge (Chen, 2008; Starzecka et al.,
2008) and knowledge sharing with different
participants (Wang et al., 2008) .
Summarized, EOs offer many possible
applications as shown above. Though, the strength
of EOs is the support of enterprises at realizing
interoperability, integration and collaboration.
Another important and usefully application is
managing information and knowledge of enterprises.
RQ5: Which topics on the field of ”Enterprise
Ontology” need further research according to the
authors?
In order to summarize potential future research
streams regarding EOs, a classification scheme
based on the outlook sections of the selected papers
has been constructed. Based on our results we were
able to determine the structure as follows.
Validation of Proposed Approaches
Most of the authors say that their approaches have to
be validated (Starzecka, 2008; Harding and Kumar,
2013; Lee et al., 2010; Huysmans et al., 2010; Latifi
et al., 2011; Isbandi, 2013; Sharma and Osei-Bryson,
2008; Moura et al., 2010; Pedrinaci et al., 2008;
Gailly and Poels, 2007; Gailly and Poels, 2007a;
Gailly and Poels, 2009; Wautelet et al., 2009; Jung,
2009; Jiang et al., 2010). This can be proven for
example by surveys, practical implementations in
companies or maybe expert surveys. It needs to
mentioned that most paper’s basic idea is to create
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an ontology or to use ontologies to support
(enterprise) systems (see RQ2). The result of that
fact is that the authors need feedback from other
instances, because most of their ideas are theoretical
works or prototypes (see RQ3).
New classification of Business Values in Real life
A topic for further research activities is the
classification of business values. The classification
of these values includes the relationships between
business strategies, business processes and
enterprise resources explicitly (Woo et al., 2009; Lee
et al., 2010; Latifi et al., 2011; Isbandi, 2013;
Sharma and Osei-Bryson, 2008; Starzecka et al.,
2008; Gailly and Poels, 2007; Wautelet et al., 2009;
Schütz et al., 2013; Zordan and Umar, 2009;
Andreasik, 2008). With the support or integration of
EO in the field of these business interconnections
researches could access the next level of the
business environment. Members of enterprises could
help to interpret the new information, because the
semantics need to be clarified.
Collaborate with EO through Semantic
synchronization
Some authors think that a specific ontology can
increase interoperability between systems
(Leppänen, 2007). With the help of semantic
operations the user or a system can interact in a
more understandable way with another system. The
next step will be combining two or more ontologies
(Schwart et al., 2010; Pooley and Chen, 2009;
Gaaloul et al., 2012; Soussi and Aufaure, 2012;
Poels and Decreus, 2008) in order to allow
collaboration in a bigger scale regarding the content.
Get more Efficiencies and Improvements with the
help of EO
Some problems occur in the understanding of
controlling approaches. Some authors created
different tools or models, which could handle this
problem. For example a metrics computation engine
(Lee et al., 2010;Pedrinaci et al., 2008; Probst and
Jussupova-Mariethoz, 2007) which detects process
deviations or a knowledge base construction (Li and
Huang, 2008) , which could give useful controlling
information. These ontology applications can realize
for example efficiency improvements (Moura et al.,
2010; Yao et al., 2009; Xie, 2009; Chen, 2008;
Sanchez-Alonso et al. 2012) or can help in problem
analysis (Wilfred et al., 2009; Santos et al., 2013;
Wang et al., 2008; Sunkle et al., 2013). The goal is
to maximize interoperability of controlling systems,
the profit or the accuracy of information and to
minimize complexity in systems and in system
interaction.
The extension of EO
There are different ontologies which represent
economic values. For example REA (McCarthy and
Geerts, 2002), the e3-value ontology (Gordijn,
2002), and the e-Business Model Ontology (e-BMO)
(Osterwalder, 2004). Based on these some authors
intent to provide extensions (Gailly and Poels, 2009;
Gailly et al., 2013; Sunkle et al., 2013). Mostly these
papers provide ontology prototypes. Thus, here is a
potential ti investigate the practical utility of these
prototypes and to discuss further improvements.
5 CONCLUSIONS
The presented systematic literature review analysed
the field of Enterprise Ontology research. Out of 135
initially found articles, 40, reaching from 2007 to
2013, have been finally included in the review.
Regarding the publication activity, the period of
2007-2013 shows that the previously falling trend
may turn into a positive direction in the near future.
The evaluation of the papers has shown that
most of the content relates to the creation of
ontologies or the use of particular ontologies.
Detailed core concepts are the creation of a new
application software or methods to deal with a
special problem. The realization of interoperability
or the integration of different information massifs is
another core concept. It is also important to mention
that ontologies contribute to handling knowledge of
an enterprise and to the translation or mapping of
information.
A further important fact is that Enterprise
ontologies can be used for collaboration between
companies and are used to support various business
processes.
Finally, Enterprise Ontologies provide an
interesting research topic which has the potential for
further research activities and practical integration
into enterprises. The results may be used for
example as quality indicators, which may be
included into industrial and standardized models and
methods.
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