=Paper=
{{Paper
|id=None
|storemode=property
|title=Towards Pattern-Based Knowledge about Ontological Resource Reuse
|pdfUrl=https://ceur-ws.org/Vol-568/paper2.pdf
|volume=Vol-568
}}
==Towards Pattern-Based Knowledge about Ontological Resource Reuse==
https://ceur-ws.org/Vol-568/paper2.pdf
Towards Pattern-based Knowledge
about Ontological Resource Reuse
Cristina Sarasua1
Vicomtech - Visual Interaction Communication Technologies, Paseo Mikeletegi 57, Parque
Tecnológico Miramon, 20009 San Sebastián, Spain
csarasua@vicomtech.org
Abstract. Ontology reuse is still an unsolved matter on the Semantic Web. Even
though ontology specification languages provide a means for knowledge reuse
and ontology management technology has evolved, ontology reuse is seldom en-
countered in applications. The more resources there are available, the more pos-
sibilities there are for ontology reuse, and paradoxically the more difficult it is to
perform ontology reuse. This thesis proposes the notion of Ontological Resource
Reuse Patterns (ORRPs), which state pattern-based knowledge about ontological
resources to encourage ontological knowledge comprehension and to enhance
ontology selection. ORRPs provide useful knowledge to improve ontology reuse
to some extent.
Key words: ontology reuse, ontoloy patterns, ontology metadata, selection
1 Problem Statement
During the last few years, the amount of available ontological resources has increased
considerably and the effort undertaken by the community to build the so-called next
generation Semantic Web tools and applications has led to relevant improvements in
ontology engineering [1]. However, knowledge reuse, which is one of the key features
of Semantic Web technologies, seems to be under exploited. Even though ontology
alignment, ontology merging and ontology integration have already been studied in
depth [2], there are still many open research challenges related to the three core phases
of ontology reuse: discovery, selection and integration [3].
The lack of success in reuse can be due to several reasons such as the poor quality of
existing ontologies, their complexity or their low modularity. Moreover, understand-
ing and using third party ontologies can be time-consuming, especially for non-experts,
and if no additional information or assistive tools are provided, developers end devel-
oping new ontologies that model similar knowledge, reinventing the wheel. Ontology
documentation can enable a better understanding of ontological resources by means
of human- and machine- readable descriptions, helping both in ontology selection and
evaluation (which are related to each other as concluded by Sabou [4]). Recently devel-
oped systems are able to store and present annotations mainly about specification and
authorship. This approach denotes an important step forward because the information
2 Cristina Sarasua
provided can be useful to filter suitable ontologies at first glance, but it does not sug-
gest how ontologies can be (re)used. The provision of rich metadata describing not only
technical details about the implementation, but also about the usage of the ontology can
further improve ontology reuse.
2 State of the Art
This section is a brief introduction to the state of the art about ontology metadata and
the latest ontology reuse technology. Besides traditional schema directories and plain
repositories published several years ago, sophisticated technology is being constructed
to manage large ontology repositories using collaborative authoring or even P2P en-
vironments. Bioportal [5] and Cupboard [6] are two remarkable systems for ontology
repositories. The OOR (Open Ontology Repository) initiative [7] is a joint effort to de-
velop an interoperability infrastructure to allow the execution of the whole metadata
lifecycle. These systems have as their core element an ontology metadata standard,
OMV (Ontology Metadata Vocabulary), proposed by Hartmann et. al [8], which spec-
ifies information about a useful set of ontology features regarding representation, au-
thorship and ontology engineering issues. Simperl [9] presented the OntoMeta tool and
PROMI, an automatic OMV-based metadata generator and a merging and integration
platform respectively. The OMEGA algorithm [10] is a three step algorithm to har-
vest, extract and reuse OMV metadata from ontologies. The Linking Open Data (LOD)
dataset cloud is composed of a great increasing amount of connected data sources de-
scribing miscellaneous domains in RDF. voiD (Vocabulary of Interlinked Datasets) [11]
describes datasets on the Web of Data using RDFS, and it can be employed together
with other vocabularies such as DC (Dublin Core). An extraordinary work related to
reuse has been achieved in NeOn toolkit and NeOn methodology [12], and although
pattern definition in ontology engineering is a relatively premature discipline, design
patterns have been introduced by means of the Extreme Design (XD) plugin. Accord-
ing to Gangemi’s et al.[13] definition, Ontology Design Patterns (OPs) are solutions to
solve an ontology design problem that appeared several times. Content Patterns (CPs),
already published at the ODP portal with other types of patterns, provide a modelling
solution (to be imported into the new ontology) that satisfies the user requirements.
These technologies show that there has been a great progress in the field. However,
systems could provide more information about the way in which particular ontological
resources can be related to reuse.
3 Proposed Approach
The PhD thesis proposal investigates how descriptive ontological information supplied
by current systems can be improved, so as to provide users with best practices on how to
proceed when reusing ontological resources. Ontological Resource Reuse Patterns (OR-
RPs), which are feasible solutions to solve the reuse of a particular ontological resource,
will be generated, presented and used in order to encourage ontological knowledge
comprehension and to enhance ontology selection on the Semantic Web. These patterns
elucidate an exemplary solution based on ontology reuse methodologies, knowledge
Towards Pattern-based Knowledge about Ontological Resource Reuse 3
extracted from ontology classification and application scenarios, and the specific on-
tological resource to be described. Specific ontological resources are analysed on the
basis of different criteria, in order to obtain mainly three types of information: informa-
tion about the manner in which it should be reused (according to its original purpose),
information about the way it is being currently reused and information about its possi-
ble usage. ORRPs do not provide modelling solutions to user conceptual requirements
(as CPs do), they describe the manner in which specific existing ontological resources
can be reused.
Fig. 1. The Ontological Resource Reuse Patterns Framewok
Figure 1 illustrates the concept of ORRPs. This thesis will consider ORRPs for both
structure and data. Therefore, ontology repositories become as relevant as the datasets
included in the LOD cloud. It is worth emphasising that ORRPs refer to ontological
resources because they focus both on terminology and annotations. Nevertheless, the
set of ontological resources will be limited to those that apply Semantic Web technolo-
gies. The pattern-based knowledge will offer rich descriptions, to complement existing
ones, such as OMV- and voiD-based annotations on the triple space. Once the informa-
tion sources are identified, the first step towards a reuse pattern will be to extract the
information required for the construction of the reuse pattern (Extraction Layer). As
a second step, this information will be processed in order to generate the actual reuse
pattern (Processing Layer). The third step of the process consists in making the reuse
pattern available on the Semantic Web (Publication Layer). Valuable knowledge for
reuse will be produced considering that it could be retrieved both by human users and
software applications. Consequently, ORRPs will need to be specified in a human- and
a machine- readable manner. Semi-automatic techniques will be used to obtain relevant
information. For example, an ontologist would browse an online repository accessing
ORRP knowledge associated with multiple ontologies in order to comprehend their pur-
pose, similarities and differences. The ontologist would understand why CIDOC CRM
can help with the integration of cultural information, as well as the manner in which it
could coexist with other ontologies. ORRPs could also be useful for providing a better
alignment of LOD datasets for certain purposes.
Expected contributions of the PhD thesis will include a model that formally defines a
reuse pattern for ontological resources, tools to generate and present reuse patterns and
a simple methodology related to reuse patterns.
4 Cristina Sarasua
4 Methodology
This thesis will focus on basically three research questions: How can pattern-based
knowledge be defined for describing the reuse of particular ontologies? How can this
knowledge contribute to the evaluation of particular ontologies in terms of reusability?
How can ontology selection processes use this knowledge? The proposed methodol-
ogy is based on the iteration of six standard steps. Firstly, an analysis of the state of
the art should be performed studying existing technologies and ontological resources in
terms of ontology reuse, documentation and pattern definition techniques. The second
step involves the definition of representative scenarios for ORRPs. Thirdly, the speci-
fication of the requirements is needed in order to identify key features that should be
supported. The fourth and fifth steps entail the design, formalisation and implementa-
tion of the ORRP model, the extraction, generation and publication modules, and the
interaction of the framework with existing related systems. Finally, the evaluation step
will be executed to guarantee the correctness of the system and to perform qualitative
and quantitative user research (in order to determine whether ORRPs are a valuable
source of knowlegde for improving efficiency, quality or quantity of ontology reuse).
Validation scenarios will target primarly existing multimedia ontologies, as well as on-
tologies related to Cultural Heritage and Tourism domains.
5 Results
Currently the objective of the thesis has been identified and the analysis of the state of
the art has begun. A set of scenarios have been defined, involving different use cases
where both human users and software applications can benefit from ORRPs. Since such
scenarios represent the basis for the specification of an initial list of requirements, they
must take into account on the one hand, multiple types of ontological resources that
reuse patterns describe (e.g. LOD datasets), and on the other hand, the advantages over
the state of the art. Although a list of requirements has been outlined, it should be fur-
ther extended. Furthermore, this preliminary approach has been discussed with a small
group of experts, although it would be desirable to receive the feedback from more
experts in ontology reuse of the Semantic Web community. Moreover, the fact that
modular ontologies facilitate ontology reuse and that defining modular ontologies and
integrating them subsequently is considered to be a good strategy [14], is also being
considered. Therefore, ORRPs should consider both ontologies as a whole and ontolo-
gies as a composition of modules.
6 Conclusions and Future Work
Ontology reuse is crucial to reach the Semantic Web. Despite the fact that current tech-
nology enables ontology reuse, this feature has not been clearly exploited. Hence, new
techniques should be discovered to encourage reuse. This paper briefly presents the
motivation and the proposed approach of the thesis, whose main goal is to explore how
pattern-based knowledge about ontological resources can improve ontology compre-
hension and ontology selection on the Semantic Web. ORRPs are envisioned to be a
Towards Pattern-based Knowledge about Ontological Resource Reuse 5
rich source of knowledge for ontology reuse, that together with other initiatives can
achieve some progress in the field.
Future work will focus on the clarification and refinement of these initial requirements
obtained. Thus, a systematic case study analysis will be carried out in order to find out
some patterns within the current usage of outstanding ontological resources. Addition-
ally, surveys among ontology experts and non-experts will be performed in order to
obtain valuable information about current problems and research challenges.
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