=Paper=
{{Paper
|id=Vol-1766/om2016_poster9
|storemode=property
|title=Exploiting ontology matching to support reuse in PURO-started ontology development
|pdfUrl=https://ceur-ws.org/Vol-1766/om2016_poster9.pdf
|volume=Vol-1766
|authors=Marek Dudáš,Ondřej Zamazal,Vojtěch Svátek
|dblpUrl=https://dblp.org/rec/conf/semweb/DudasZS16
}}
==Exploiting ontology matching to support reuse in PURO-started ontology development==
https://ceur-ws.org/Vol-1766/om2016_poster9.pdf
Exploiting Ontology Matching to Support Reuse
in PURO-started Ontology Development
Marek Dudáš, Ondřej Zamazal, and Vojtěch Svátek
Department of Information and Knowledge Engineering,
University of Economics, W. Churchill Sq.4, 130 67 Prague 3, Czech Republic,
{marek.dudas|ondrej.zamazal|svatek}@vse.cz
1 Introduction
We have recently proposed an innovative method of ontological engineering [1]:
easing OWL ontology development by first creating a model in a less constrained
language called PURO, allowing the engineer to focus on defining what is to be
described by the ontology in an example real-world situation. The model is then
automatically transformed to OWL, while allowing the user to choose the OWL
encoding style.1 The result is then finalized in a common tool like Protégé. We
present an experimental implementation demonstrating how the above-described
proposal can be enhanced by exploiting ontology matching, allowing to reuse
entities from existing ontologies (as best practice in ontology design) or searching
for a combination of existing ontologies that could cover the desired domain. We
used ontology matching to search for relevant entities in existing ontologies for
the given PURO model, visualize them and enable their easy reuse in our PURO-
started ontology development approach. The approach is similar to vocabulary
reuse tools like LOVER [4], however, the coupling with PURO is novel.
2 Design and Implementation
To find out whether there are OWL entities in existing ontologies that could cover
some part of the PURO model, we simply take the OWL fragment generated
from the model, match it to as many ontologies as possible, and present the
results in a user-friendly way. To increase the chance of finding a match, the
matching is run for four different encoding style OWL variants generated from
the PURO model. We match the OWL fragment to Linked Open Vocabularies
(LOV).2 The matching is implemented as a RESTful service and executed in
two steps. First, to speed up the process, we select candidate ontologies from
LOV using vocabulary term search available from the LOV API, considering all
terms from the OWL fragment. Second, the ontology candidates are matched to
the OWL fragment using the state-of-the-art ontology matching tool LogMap
[3]. We use a cached LOV snapshot to gain speed and reliability.
1
E.g., whether a relationship will be represented by a property or class membership.
2
http://lov.okfn.org/
The PURO-to-OWL transformation is made via a series of SPARQL update
queries. To allow that, the PURO model is first serialized into RDF. The queries
use RDF annotations to keep track of which PURO entities have been trans-
formed to which OWL entities. This allows translating the OWL-to-OWL corre-
spondences produced by the matching service to PURO-to-OWL mappings and
visualize the latter in the original PURO model. Namely, entities (represented by
nodes in the PURO model node-link visualization) with available mappings to
OWL are highlighted by lines encircling them and labeled with the ontology IRI
where the entity has been found. This way the user can see which parts of the
PURO model are potentially covered by which existing ontologies. The visual-
ization can therefore be useful on its own, simply suggesting relevant ontologies
that can cover a given situation modeled in PURO.3
A list of the mappings found for a PURO entity is displayed when the PURO
entity node is selected. By selecting an OWL entity from the list, the mapping
is stored in the RDF PURO serialization and visualized in the PURO model as
a separate node of different color. When the PURO-to-OWL transformation is
run, the mapped entities are used by the SPARQL queries for transformation of
corresponding PURO entities, instead of creating new OWL entities.
3 Results so Far and Future Work
The proof-of-concept implementation, available online as part of the web-based
tool OBOWLMorph,4 suggests that the basic idea is valid. We have yet to eval-
uate whether matching to several OWL encoding style variants brings any im-
provement compared to using just a default one. Compared to manual visualiza-
tion of local ontology coverage [2], automated visualization is less complete and
imprecise, but could serve to bootstrap the manual approach.
The research is supported by UEP IGA F4/28/2016. Ondřej Zamazal is sup-
ported by CSF 14-14076P.
References
1. Dudáš, M., Hanzal, T., Svátek, V., Zamazal, O.: OBOWLMorph: Starting ontology
development from PURO background models. In: International Experiences and
Directions Workshop on OWL. pp. 14–20. Springer (2015)
2. Dudáš, M., Hanzal, T., Svátek, V.: What can the ontology describe? visualizing
local coverage in PURO modeler. In: VISUAL@EKAW (2014)
3. Jiménez-Ruiz, E., Grau, B.C.: Logmap: Logic-based and scalable ontology matching.
In: International Semantic Web Conference. pp. 273–288. Springer (2011)
4. Schaible, J., Gottron, T., Scheglmann, S., Scherp, A.: LOVER: support for modeling
data using linked open vocabularies. In: Proceedings of the Joint EDBT/ICDT 2013
Workshops. pp. 89–92. ACM (2013)
3
We presented such a use case earlier [2], but only as an aid for the user allowing to
highlight parts of the PURO model by hand. Now the same is done automatically.
4
http://goo.gl/IjTwlX, please use login and password “om2016”.