Results from a Survey among Small and Medium-sized Enterprises
Ohgren and Kurt Sandkuhl
School of Engineering at J
oping University, P.O. Box 1026, 55111 J
oping, Sweden
SME, Ontology Construction, Ontology Engineering, Survey, Product Complexity, Project Complexity.
During the last years, an increasing number of successful cases of using ontologies in industrial application
scenarios have been reported, the majority of these cases stem from large enterprises. The intention of this
paper is to contribute to an understanding of potentials and limits of ontology-based solutions in small and
medium-sized enterprises (SME). The focus is on identifying application areas for ontologies, which motivate
the development of specialised ontology construction methods. The paper is based on results from a survey
performed among 113 SME in Sweden, most of them from manufacturing industries. The results of the survey
indicate a need from SME in three application areas: (1) management of product configuration and variability,
(2) information search and retrieval, and (3) management of project documents.
During the last years, an increasing number of suc-
cessful cases of using ontologies in industrial appli-
cation scenarios have been reported, see for exam-
ple (Lau and Sure, 2002) and (Sandkuhl and Billig,
2007). However, the majority of these cases stem
from large enterprises, or IT-intensive middle-sized or
small enterprises (SME). Most SME outside the IT-
sector probably never have heard about ontologies.
Do these SME really need ontologies? Are there
shortcomings and a need for improvement in appli-
cation areas where the use of ontologies can create
substantial benefits? Existing studies about IT use in
SME, like (Lybaert, 1998), do not cover ontologies
or knowledge representation techniques sufficiently.
Studies focusing on usage of innovative ICT technol-
ogy, like (Koellinger, 2006), target a wider audience
than SME.
Considering the characteristics of successful cases
in larger enterprises, similar cases should also exist
in SME, but drawing conclusions from experiences
of larger enterprises with regards to SME is not rec-
ommendable, as SME have their own characteristics
(Levy et al., 2002): SME often belong to the group of
”late adopters” of new technology, i.e. they prefer ma-
ture technologies, which are easy to deploy, use and
maintain. SME show a clear preference for to a large
extent standardised solutions. Innovation projects in
SME typically have to create business value within a
short time frame.
The intention of this paper is to contribute to an
understanding of potentials and limits of ontology-
based solutions in SME with a focus on ontology ap-
plication areas. The paper is based on results from
a survey performed among SME in Sweden. The re-
mainder of the paper is structured as follows: in sec-
tion 2 we discuss background work together with the
aim of the conducted survey. The survey setup is de-
scribed in section 3. In section 4 the results of the
survey are described. A discussion of the survey re-
sults regarding aim etc. is found in section 5. Finally,
in section 6 conclusions are drawn.
This chapter briefly illuminates three aspects, which
form an important background for the remaining part
of the paper.
In section 2.1: For what purpose and in what areas
could SME possibly use ontologies?
In section 2.2: How to judge whether there is an
application potential in the identified areas?
In section 2.3: To which research activities in on-
tology engineering is the survey supposed to con-
Öhgren A. and Sandkuhl K. (2008).
DO SME NEED ONTOLOGIES? - Results from a Survey among Small and Medium-sized Enterprises.
In Proceedings of the Tenth International Conference on Enterprise Information Systems - ISAS, pages 104-111
DOI: 10.5220/0001704201040111
2.1 Application Areas for Ontologies
The literature in the area of ontology engineering
identifies a variety of different applications in many
different areas. In (Obitko, 2001) the authors describe
some: ontologies can be used for expressing domain-
general terms in a top-level ontology, for knowledge
sharing and reuse, for communication in multi-agent
systems, natural language understanding, and to ease
document search to mention some of them.
Uschold and Gr
uninger specify three different cat-
egories where ontologies can be used, see (Uschold
and Gruninger, 1996). The first is communication:
ontologies can be used to increase and facilitate com-
munication among people. The second usage area de-
fined is inter-operability. Ontologies can serve as an
integrating environment for different software tools.
The third usage area is systems engineering, in which
ontologies can play an important part in the design
and development of software systems. They can help
to identify requirements of a system and to explicitly
define relationships among components of a system.
They can also be used to support reuse of modules
among different software systems.
In (McGuinness, 2002) several application areas
for ontologies are mentioned. Ontologies can be used
for navigation, browsing, and search support. Consis-
tency checking can also be handled with ontologies
to some extent. Ontologies can provide configuration
support and support validation and verification testing
of data.
Within OntoWeb four different usage areas for
ontologies are defined, as seen in (Ontoweb, 2004):
enterprise portals and knowledge management, e-
commerce, information retrieval, and portals and web
communities. In this context, information retrieval
means to use ontologies for understanding the con-
cepts being searched and avoid the mistake of missed
positives (failure to retrieve relevant answers) and
false positives (retrieval of irrelevant answers).
When analysing the above sources, four applica-
tion areas of ontologies in enterprises are named sev-
eral times. These four application areas will be used
as starting points for identifying ontology application
fields of relevance for SME:
navigation, browse, and search support for infor-
mation retrieval in enterprises or for managing
capturing and representing knowledge for the pur-
pose of knowledge sharing,
configuration and validation support of products
like software systems,
supporting inter-operability between different IT-
systems, e.g. in a collaboration between customer
and supplier.
2.2 How to Judge Ontology Application
The previous section identified application areas for
ontologies, which potentially are of interest for SME.
One task of the planned survey will be to confirm
that these fields really can be found in the SME sam-
ple under consideration, i.e. that a sufficient part
of the SME have product configuration challenges,
need support in document or information retrieval, or
work in collaboration projects with suppliers requir-
ing inter-operability.
The mere existence of an application field alone,
however, does not indicate that the use of ontologies
is appropriate in this field. Small projects or sim-
ple product configurations, to just take two examples,
might well be manageable in an efficient way without
any IT support at all. How to judge when it makes
sense to consider the use of ontologies? In this pa-
per we will follow the opinion of various scholars in
the field that the complexity of an application case is
an essential parameter to take into account when de-
ciding about the use of ontologies. The more com-
plex the application scenario, the more likely the use-
fulness of ontologies. In the context of this paper,
project complexity and product complexity are of par-
ticular interest. Approaches for determining or even
measuring project complexity and product complex-
ity could directly contribute to identifying the share of
SME with either complex project situations or com-
plex products.
A review regarding the concept of project com-
plexity performed by Baccarini (see (Baccarini,
1996)) proposes to define complexity as ”consisting
of many varied interrelated parts”, to distinguish be-
tween organisational and technological complexity,
and to operationalise this in terms of ”differentiation
and interdependence”. Differentiation refers to the
number of varied elements, e.g. tasks or components;
interdependence characterises the interrelatedness be-
tween these elements. Regarding organisational com-
plexity, Baccarini identified among other indicators
the number of organisational units involved and the
division of labour. For technological complexity, the
diversity of inputs and output and the number of spe-
cialities (e.g. subcontractors) are considered.
In the area of product complexity, work of Hob-
day, see (Hobday, 1998), regarding distinctive fea-
tures of complex products and systems identifies di-
mensions defining the nature of a product and its com-
DO SME NEED ONTOLOGIES? - Results from a Survey among Small and Medium-sized Enterprises
plexity. The not exhaustive list of 15 critical prod-
uct dimensions provided by Hobday includes quantity
of sub-systems and components, degree of customisa-
tion of products and intensity of supplier involvement.
These dimensions will be used in combination with
Baccarini’s project complexity indicators when eval-
uating the survey results in section 5.
2.3 Previous Work on Ontology
Construction Methods
The work presented in this paper is part of a research
program focusing on industrial applications of enter-
prise ontologies, with particular focus on SME. The
overall intention is to lower the threshold for adap-
tation of ontology-based applications in industry by
reducing time and costs for ontology development.
Previous work focused on analysing existing ontology
development methods with respect to their suitability
for SME, see (
Ohgren and Sandkuhl, 2005), and on
proposing and applying a newly developed method in
this context, see (Blomqvist et al., 2006). Although
the initial experiences with the new method were pos-
itive, the conclusion was that a further specialisation
would be recommendable.
In order to prepare this specialisation, the de-
mands of SME and the relevance of ontologies for
different application fields had to be investigated. The
survey presented in this paper was performed in or-
der to contribute to this objective. Thus, the sur-
vey focused on the applications, requirements and
shortcomings perceived by the users in the enterprises
rather than on the IT-solution aspects, i.e. details of
IT-infrastructure or IT in use.
Based on the background work described in 2.1, the
following five conjectures were defined regarding the
application areas for ontologies in SME.
1. There is a need for supporting information search-
ing and thus reducing the time needed to find the
right information.
2. There is a need for supporting management of
configurations or variations of products. This
could be differences and similarities, dependen-
cies between variants of a product, or dependen-
cies between products, which could be used for
example to improve reuse of parts of products
and/or reuse of design processes.
3. There is a need for structuring documents and
supporting document management, for example
in order to support project work.
4. There exists a need for supporting collaboration
and inter-operability in networks of companies,
and/or supply chains.
5. There is a need for capturing enterprise knowl-
edge, like development rules, process knowledge,
or design principles in order to avoid dependen-
cies from certain individuals.
3.1 Interviews
Prior to the survey interviews were held in order to
investigate how to proceed within the previously dis-
cussed application areas. In total eleven people from
seven companies were interviewed to see their view
on potential problems and ideas regarding the conjec-
tures and to identify suitable fields and questions for
a questionnaire survey. The companies’ sizes ranged
from three employees up to 2300. The companies also
differed in type and industrial sectors.
The interviews resulted in the decision to go on
with a questionnaire to further investigate the first
three conjectures listed above, namely information
searching, configurations/variants of products and
document management.
According to the interviewees most information
within the field of supply chain or networks of en-
terprises is based on personal experience, which was
deemed very hard or even not possible to document.
The conclusion here was not to continue with the two
last conjectures, i.e. with both supply-chains and net-
work of enterprises, and documenting expert knowl-
3.2 Survey Layout
The questionnaire finally consisted of 35 questions
on six pages. The questionnaire was divided into
six parts in varying size, where the first four ques-
tions concerned the company: number of employees,
yearly turnover, industrial sector, and the respondent’s
role within the company.
The next part was related to conjecture 1, included
ten questions, and dealt with document and informa-
tion management. This part included questions about
how much time the respondent used daily to find and
save information connected to his or her work, where
to find this information, etc.
The third part, which was connected to conjec-
ture 3, concerned only companies working in projects
and included six questions about the number of em-
ployees in each project, how long time the projects
ran, and some information about the documents in the
ICEIS 2008 - International Conference on Enterprise Information Systems
The following eleven questions were related to
conjecture 2 and targeted only producing companies.
These questions addressed how many products the
company had, how many components each product
consists of, how many suppliers that contribute to
each product, and in how many variants each product
is made.
Finally there were questions regarding non-
documented personal knowledge and regarding tax-
onomies and nomenclatures. The answers to these
questions will not be discussed in section 5 as they
are not related to the conjectures.
3.3 Sample
In order to reach out to an appropriate number of
companies, the schools host company database was
used. These companies already have a connection to
the school and were therefore deemed more interested
in responding to such a questionnaire than companies
without an established connection to the education
and research performed at the school. The database
also includes contact persons at each company, to
whom the questionnaire was directly addressed to.
The questionnaire was sent to 436 companies in
the end of 2005. 24 of the sent questionnaires came
back unopened due to wrong addresses or unknown
addresses, which means that the number of possible
respondents was reduced to 412. 164 answers were
received, all of them were considered useful and were
used in the analysis, giving a response rate of 39,8%
(164/412), which is considered to be quite high.
Among the 164 returned questionnaires, 51 were
returned by large companies, i.e. companies with
more than 250 employees or more than 400 Mio SEK
yearly turnover (approx. 43 Mio EUR). The size of
the sample taken into account for this paper is 113
small and medium-sized enterprises with approx. half
of them with less than 50 employees.
This section presents the results of the survey. The
section is structured into three parts, which corre-
spond to the conjectures introduced in section 3:
retrieving information and documents (4.1), prod-
uct complexity (4.2) and document management in
projects (4.3).
4.1 Retrieving Information and
In the survey, a clear majority of the sample perceive
that they receive ”far too much” (41%) or ”too much
information (28%). 27% think the amount of infor-
mation is adequate, only 4% think they do not receive
enough information.
Regarding the time needed daily to find the right
information for the work at hand, the distribution is
as shown in figure 1. Even though half of the sam-
ple needs less than half an hour daily to find the right
information, it can be noted that a substantial part of
the working hours is consumed by searching for in-
formation. 33% of the sample consume up to an hour
daily, 11% need more than one hour, 5% even more
than two hours.
> 12060-12030-6010-30< 10
Figure 1: Time needed daily to find the right information
for the work at hand (in minutes).
The participants were also asked how difficult it
is to find the information needed for the work task at
hand. Within the sample, nobody answered that it is
”very difficult” to find the required information. ”Rel-
atively easy” and ”medium difficult” both received
approx. 40%; ”very easy” and ”difficult” both ap-
prox. 9%. Not surprisingly, the respondents with a
higher daily time effort for finding information also
had a tendency to perceive it as more difficult to find
the right information.
Concerning the sources for finding required infor-
mation, joint file servers in the companies and the In-
ternet are the most often used sources, followed by the
own PC: 70% answered that the file server is ”often”
or ”very often” the source for information, 64% the
Internet and 49% the own PC. Intranet and document
management systems (DMS) are less frequently used
(36% and 26%, respectively), which to some extent
will be based on the fact that 29% of the sample do
not have an Intranet and 31% do not have a DMS.
The established DMS and Intranet solutions in en-
terprises are used quite intensively: 40% of all re-
spondents use these systems several times a day, 29%
nearly every day. 17% use these IT-systems a few
times during the week and 14% use them only a few
DO SME NEED ONTOLOGIES? - Results from a Survey among Small and Medium-sized Enterprises
times in a month or even more seldom.
Regarding the question how to find the requested
information in the above mentioned sources, most re-
spondents rely on their memory from earlier cases
(67%), use keyword search (60%) or the existing di-
rectory structure (59%). Furthermore, a substantial
part of the respondents ask their colleagues for the
needed information (29%).
Considering the potential for improving informa-
tion management in SME, not only the introduction
of Intranet or DMS in companies without those sys-
tem types is a possibility, but also the improvement of
these systems as such. Among the respondents who
have an Intranet or DMS 50% of the respondents note
that it is not possible to subscribe new or changed
information, 17% stated that they got too many hits
when searching for information, 19% claimed they
got irrelevant hits, and others wish for an improved
structure of the information, either with relation to the
work process (19%), or with regards to the product
structure used in the company (33%).
4.2 Product Complexity
Another part of the survey was addressing the issue
of product complexity. In industry domains devel-
oping or manufacturing physical products, the num-
ber of components in the product, potential versions
and variants of the product and number of suppliers
contribute to product complexity. The product related
part was answered by 61 of 113 SME. The following
part of the results is based on these 61 responses.
The number of products found in the sample was
quite high: 62% of all respondents stated that they
have more than 50 products. 5% and 13% have be-
tween 11 and 25 or between 26 and 50 products, re-
spectively. 15% of all respondents have between 4
and 10 products, 5% even less than 4 products.
Most of the products have a small number of vari-
ants. 47% of the respondents answered that there are
on average less than 6 variants, 23% between 6 and
12. 4% stated that there are between 13 and 25 vari-
ants, 9% between 26 and 50, and 17% more than 50
The average number of components in these prod-
ucts is either quite high or quite low. 35% of the re-
spondents state that a product on average has more
than 50 components. 42% have less than 10 compo-
nents per product (23% less than 4 components; 19%
between 4 and 10). 21% state the average number is
between 11 and 25. At 2% of the respondents it is
between 26 and 50.
In the large majority of the enterprises, a descrip-
tion is available which components are parts of what
product: 88% answered that some kind of product
structure exists, 8% answered there is no such struc-
ture, the remaining did not know. The existence of
such a description or product structure would ease the
development of an ontology in the field of variability
The average number of suppliers contributing to
a product is less than 3 at 16% of the respondents,
between 3 and 5 at 27%, between 6 and 9 at 16%,
between 10 and 15 at 15% and more than 15 at 26%
of the participating SME.
Reuse of components in new products or new vari-
ants of an existing product could be improved consid-
erably, according to the opinion of a majority of the
respondents. 26% state that currently there is no reuse
of components at all, 15% answer that there is nearly
no reuse. 26% answer that reuse happens sometimes,
20% state that reuse happens often, 13% very often.
On the question whether it would be possible to reuse
more, 16% respond ”definitively possible”, 48% ”yes,
probably” and 36% think it is not possible.
4.3 Document Management in Projects
The survey also included a number of questions on
projects performed in the enterprises. Main inten-
tion was to investigate the complexity of projects per-
formed and the documentation involved. The project
related questions were answered by 71 out of in total
113 SME participating in the survey. The following
part of the results is based on these 71 answers.
In order to get information about project complex-
ity, the survey included questions about the number
of project members, run time, number and volume of
project documents, structure and content of project-
related documents. Based on the respondents’ an-
swers, the projects in SME are rather small in terms of
project members. 39% state a project has only up to
3 members, 51% have between 4 and 8 members and
only 10% have more than 8 members. The large ma-
jority of the projects has a run time of more than one
month but less than one year: 39% state that the aver-
age project run time is between 1 and 4 months, 32%
have an average run time between 4 and 12 months.
Enterprises with average project length of less than
one month (20%) and more than one year length (9%)
are in the minority.
The number of documents produced in a project
varies considerably within the sample: 37% of the re-
spondents state that there are on average less than 10
documents, 35% between 11 and 25 documents, 13%
between 26 and 60, and 15% more than 60 documents
in a project.
Most of the documents are quite small in terms of
ICEIS 2008 - International Conference on Enterprise Information Systems
number of pages. 51% state that the documents on
average have less than 4 pages and 37% between 4
and 10 pages. Only 10% of the respondents have an
average document size of between 11 and 25 pages,
3% between 26 and 50 pages.
Regarding the document structure, standardisation
seems to be common practise. In more than 85%, the
document structure is identical in different projects
(38%) or nearly identical (47%). 11% state that the
structure sometimes is similar. A not at all similar
structure in different projects can be found only at 4%
of the respondents.
The first conjecture addressed the need for support-
ing search and information retrieval in SME. Experi-
ences from using ontologies for structuring informa-
tion or within search engines show clearly that they
can contribute to improving precision. Examples for
investigation in this field can be found in (Ciravegna
and Petrelli, 2006) and (Redon et al., 2007). However,
the main question to discuss from an SME perspective
is which approach creates the best benefit/effort ratio,
i.e. substantial benefits at a reasonable price.
As a considerable part of SME neither have In-
tranets or DMS, and as even the established sys-
tems have improvement potential, these improve-
ments should be made first before starting on ontol-
ogy development.
Thus, our conclusion regarding use of ontologies
for supporting information management in SME is:
the SME participating in our survey perceive di-
verse information management problems, like dif-
ficulties to find the right information, shortcom-
ings in the established IT-systems or information
overload. This presents an application field for
the use of conventional technologies should be
given preference to ontologies when improving
information management in SME.
The second conjecture addressed the need for sup-
porting management of product configuration and
variation. The fact that 61 of 113 SME responded
to the questions regarding product variability in the
survey gives a first indication that many SME actu-
ally provide physical products consisting of various
parts. In section 2.2 the concept of product com-
plexity was briefly discussed including indicators for
product complexity. For the purpose of evaluating the
product complexity in the sample, we included four
Low Medium High Very
No of Products No of Components
No of Suppliers No of Variants
Figure 2: Distribution of very low to very high for the four
product-related criteria.
criteria, which are connected to four questions in the
number of products,
average number of components per product,
average number of suppliers per product,
number of variants.
These four criteria match directly to the indica-
tors proposed by Baccarini and Hobday (see 2.2). For
each of these four criteria, the survey questions of-
fered five different choices. Mapping these choices on
a scale from ”low” to ”very high”, i.e. the choice with
the lowest number of products, components, variants
and suppliers is mapped to ”low” and the choice with
the highest number is mapped to ”very high”, helps to
visualise the distribution of the answers regarding the
four criteria. Figure 2 shows this distribution.
Furthermore, it is important to know whether there
is a correlation between the four criteria, for exam-
ple whether companies with a high number of prod-
ucts also have a high number of variants and many
suppliers. When investigating this aspect, we found
31 cases with at least two criteria receiving at least
”high”. Of these 31 cases were 21 with two times
”very high” and 16 with three times at least ”high”.
Figure 3 visualises these 16 cases.
In terms of complexity, we consider at least the 16
cases shown in figure 3 as complex enough to seri-
ously investigate the use of ontologies. The 16 cases
show both, a very high degree of differentiation and
interdependencies between the criteria. Even for the
other 15 cases, who at least receives two times ”high”
or ”very high”, we see development potentials for on-
tologies, as all of them at least have one criteria on
”medium” level, which contributes to substantial dif-
ferentiation and interdependencies.
Based on the above discussion, we conclude that
there is a need for supporting variability management.
Approximately a quarter of all SME in the sample
DO SME NEED ONTOLOGIES? - Results from a Survey among Small and Medium-sized Enterprises
No. products
No. components
No. suppliers
No. variants
Medium Low
Figure 3: Cases from the survey with highest product com-
Low Medium High Very
No of Employees Time Range
No of Documents No of Pages in Each Document
Figure 4: Distribution of very low to very high for the four
project document management-related criteria.
and more than half of those SME answering the prod-
uct related questions have a substantial complexity in
their product portfolio.
Conjecture 3 focused on the need for supporting
document management in project work. 71 of 113
SME responded to the questions regarding project
work, which indicates that many SME actually use
project organisation based on documents. Evaluating
the complexity of document management in projects
again included four criteria, which are connected to
questions in the survey:
average number of employees in a project,
average number of documents per project,
average duration of projects,
average number of pages per documents.
The first two criteria directly relate to Baccarini’s
work (see 2.2); the other two were derived in order to
represent document complexity. The survey questions
offered five different choices for each of these four
criteria, which were mapped on a scale from ”low” to
”very high”. Figure 4 visualises the distribution of the
answers regarding the four criteria.
No. employees
Time range
No. documents
Pages in each
Medium Low
Figure 5: Cases from the survey with highest project docu-
ment management complexity.
Considering the correlation between the four cri-
teria, we found 13 cases with at least two criteria re-
ceiving at least ”high”. Of these 13 cases were 5 with
two times ”very high”. Figure 5 visualises these 13
In terms of complexity, we consider at least the 13
cases shown in figure 5 as complex enough to seri-
ously investigate the use of ontologies. These cases
show both, a very high degree of differentiation and
interdependencies between the criteria. Comparing
these figures with the situation in product complex-
ity (conjecture 2), the significance of a need for sup-
porting project document management is not as high.
However, 18% of the SME working in project organ-
isation and 11% of all SME in the sample show a
high complexity, which from our perspectives is suf-
ficient motivation to aim at supporting project docu-
ment management.
The main purpose of this paper is to contribute to re-
search on ontology development methods by investi-
gating, which application areas for ontologies in SME
could motivate the development of specialised ontol-
ogy construction methods. The performed survey was
guided by five conjectures intended to help in identi-
fying such areas, which can be used to summarise the
There is a need for supporting information search-
ing: the survey results clearly confirmed this con-
jecture. However, existing tools like DMS could
be used to support these needs.
There is a need for supporting management of
configurations or variations of products: again,
the survey results clearly supported this conjec-
ICEIS 2008 - International Conference on Enterprise Information Systems
There is a need for structuring documents and
support of document management: the survey re-
sults supported this conjecture, but not to the same
extent as in the first two conjectures.
There exists a need for supporting collaboration
and interoperability in networks of companies:
this conjecture was not included in the survey,
as the interviews performed prior to the study
indicated significant problems in capturing suffi-
ciently detailed information with ontologies.
There is a need for capturing enterprise knowl-
edge: again, this conjecture was not further in-
vestigated after the interviews, as big concerns
were expressed that capturing personal knowl-
edge would be feasible.
Thus, the conclusion from the survey is that SME
need ontologies mainly in the area of product con-
figuration and variability modelling. This application
area will be given highest priority when developing a
purpose-oriented ontology construction method. The
application area with the second highest priority is
document management for supporting project work.
This area can be seen as a sub-area of information
search and retrieval with specific focus on project sup-
Regarding the last two conjectures, we received
a number of indications in the interviews and even
within the survey, that application potential of ontolo-
gies could exist for capturing knowledge in SME and
for supporting supply chains. However, this is not per-
ceived as a priority area by the SME and will thus
have the lowest priority in future work.
The main limitations of the survey are:
the survey only included SME from a geographi-
cally limited area, which is the south of Sweden,
the majority of SME participating in the survey
were manufacturing companies,
the size of the sample was not large enough for
achieving results of statistical significance.
These limitations should be taken into account
when investigating whether the results are transfer-
able to other areas or applicable in other research con-
Baccarini, D. (1996). The concept of project complexity - a
review. International Journal of Project Management,
Blomqvist, E.,
Ohgren, A., and Sandkuhl, K. (2006). On-
tology Construction in an Enterprise Context: Com-
paring and Evaluating Two Approaches. In Proc. of
the 8th International Conference on Enterprise Infor-
mation Systems.
Ciravegna, F. and Petrelli, D. (2006). Annotating document
content: a knowledge management perspective. Inter-
national Journal of Indexing, 24(5).
Hobday, M. (1998). Product Complexity, Innovation and
Industrial Organisation. Research Policy, 26:689–710.
Koellinger, P. (2006). Impact of ICT on Corporate Perfor-
mance, Productivity and Employment Dynamics. The
European E-business Market Watch. Special Report
No. 01/2006.
Lau, T. and Sure, Y. (2002). Introducing Ontology-based
Skills Management at a Language Insurance Com-
pany. In Modellierung in der Praxis - Modellierung
fr die Praxis, volume 12 of LNI.
Levy, M., Powell, P., and Yetton, P. (2002). The Dynam-
ics odf SME Information Systems. In Small Business
Economics, Vol. 19, No. 4.
Lybaert, N. (1998). The Information Use in a SME: Its
Importance and Some Elements of Influence. Small
Business Economics, 10(2).
McGuinness, D. L. (2002). Ontologies Come of Age. In
Spinning the Semantic Web: Bringing the World Wide
Web to Its Full Potential. MIT Press.
Obitko, M. (2001). Ontologies - Description and Applica-
tions. Technical report, Gerstner Laboratory for Intel-
ligent Decision Making and Control, Czech Technical
University in Prague.
Ohgren, A. and Sandkuhl, K. (2005). Towards a Methodol-
ogy for Ontology Development in Small and Medium-
Sized Enterprises. In IADIS Conference on Applied
Computing, Algarve, Portugal.
Ontoweb (2004). Ontology-based information ex-
change for knowledge management and elec-
tronic commerce. Downloaded from http:// 2004-
Redon, R., Larsson, A., Leblond, R., and Longueville, B.
(2007). Vivace context based search platform. In
CONTEXT07, volume 4635 of LNCS (LNAI), pages
397–410. Springer, Heidelberg.
Sandkuhl, K. and Billig, A. (2007). Ontology-based Arte-
fact Management in Automotive Electronics. Interna-
tional Journal for Computer Integrated Manufactur-
ing (IJCIM), 20(7):627–638.
Uschold, M. and Gruninger, M. (1996). Ontologies: Prin-
ciples, Methods, and Applications. Knowledge Engi-
neering Review, 11(2), 93–155.
DO SME NEED ONTOLOGIES? - Results from a Survey among Small and Medium-sized Enterprises