=Paper=
{{Paper
|id=Vol-1908/paper17
|storemode=property
|title=Aligning Top-level and Domain Ontologies
|pdfUrl=https://ceur-ws.org/Vol-1908/paper17.pdf
|volume=Vol-1908
|authors=Daniela Schmidt,Cassia Trojahn,Renata Vieira
|dblpUrl=https://dblp.org/rec/conf/ontobras/SchmidtTV17
}}
==Aligning Top-level and Domain Ontologies==
https://ceur-ws.org/Vol-1908/paper17.pdf
Aligning Top-level and Domain Ontologies -
Expected date for defense: March/2019
Daniela Schmidt∗ , Cassia Trojahn† , Renata Vieira∗
1∗ Pontifical Catholic University of Rio Grande do Sul (Brazil)
daniela.schmidt@acad.pucrs.br, renata.vieira@pucrs.br
† Institut de Recherche en Informatique de Toulouse (France)
cassia.trojahn@irit.fr
Abstract. Many efforts in the ontology matching field have been particularly
dedicated to domain ontologies, however the problem of matching domain and
top-level ontologies has been addressed to a lesser extent, particularly due to
their different levels of abstraction. This work aims at filling the gap in this area.
We intend to propose an approach to align top-level and domain ontologies. The
use of general lexical databases as an intermediary layer is a direction.
1. Introduction
Ontologies have been applied in many areas motivated mainly by the need to create, to
share and to reuse knowledge. The rich semantics and formalization of top-level ontolo-
gies are important requirements for ontology design [Mika et al. 2004], they act as well
as semantic bridges supporting very broad semantic interoperability between ontologies
[Mascardi et al. 2007, Mascardi et al. 2010]. In that sense, they play a key role in on-
tology matching, which is the process of finding correspondences between entities from
different ontologies.
The advantage of top-level ontologies is to gather lots of available knowledge
and create super structures for information that provide interoperability for many appli-
cations. However, most efforts in ontology matching have been particularly dedicated to
domain ontologies and the problem of matching domain and top-level ontologies has been
addressed to a lesser extent. This problem poses different challenges in this field, particu-
larlly due to the different levels of abstraction of these ontologies. This is a complex task,
that requires knowledge about the semantic context of concepts, which goes beyond the
frontiers of what is encoded in the ontology.
In particular the differences in the abstraction levels of domain and foundational
ontologies will require a change of focus from finding equivalence relation to the identi-
fication of subsumption relations. In fact, when having different levels of abstraction it
might be the case that the matching process should focus in finding subsumption rather
than equivalence correspondences, since the top-level ontology has concepts at a higher
level. This is largely neglected by most matching systems. Approaches dealing with this
task are mostly based on manual matching [Brodaric and Probst 2008, Mika et al. 2004].
In order to evaluate the quality and correctness of the generated alignments in
the process of top-level and domain ontology matching, reference alignments (also called
gold standard) are required. Reference alignments could be developed manually by ex-
perts or in a semi-automatic way, where the resultant alignment from matching systems
is used against the manual analysis.
Considering the discussion above, this thesis aims to contribute to the problem of
matching domain and top-level ontologies. We are proposing an approach to automati-
cally align domain and top-level ontologies. This paper summarizes the thesis proposal
which will be estimated to be developed till march/2019.
The remaining of this paper is organized as follows. Section 2 introduces the
theoretical background on top-level ontology and ontology alignment. Then, we discuss
on available state-of-the-art matching systems and the lexical database WordNet. Section
3 presents the related work. Section 4 describes our initial experiments. Section 5 presents
our thesis proposal including research hypothesis, and research goals. Section 6 concludes
this paper.
2. Background
2.1. Top-level ontologies
A top-level ontology is a high-level and domain independent ontology. The concepts ex-
pressed are intended to be basic and universal to ensure generality and expressivity for
a wide range of domains. It is often characterized as representing common sense con-
cepts and concerns concepts which are meta, generic, abstract and philosophical. Some
examples of well known top-level ontologies are BFO [Grenon et al. 2004], DOLCE
[Gangemi et al. 2002], GFO [Herre et al. 2007], SUMO [Niles and Pease 2001] and UFO
[Guizzardi 2005]. A review of them is presented in [Mascardi et al. 2007].
2.2. Ontology matching
The process of finding correspondences between ontology entities is known as ontol-
ogy matching. It takes as input two ontologies os (source) and ot (target) and an (pos-
sibly empty) alignment A to be completed, and determines as output an alignment A0 ,
i.e., a set of correspondences. Here, we borrow the definition of correspondence from
[Euzenat and Shvaiko 2007]:
Definition 1 (Correspondence) A correspondence can be defined as , such
that: es and et are entities (e.g., concepts, properties, instances) of os and ot , respectively;
r is a relation holding between two entities es and et , (for instance, equivalence, subsump-
tion, disjointness, overlapping); and n is a confidence measure number in the [0;1] range.
The confidence assigns a degree of trust on the correspondence from the matcher.
2.3. WordNet
WordNet [Miller 1995] is a general-purpose large lexical database of English. Nouns,
verbs, adjectives and adverbs are grouped into sets of cognitive synonyms (synsets), each
expressing a distinct concept. Synsets are interlinked by means of conceptual-semantic
and lexical relations. A synset denotes a concept or a sense of a group of terms. Word-
Net also provides textual descriptions of the concepts (gloss) containing definitions and
examples. For instance, for the concept “Poster”, one of the associated WordNet synsets
(SID-06793426-N) groups the synonyms “poster, posting, placard, notice, bill, card”, to-
gether with a gloss “a sign posted in a public place as an advertisement; a poster advertised
the coming attractions”.
3. Related Work
In the literature it is possible to identify different uses of top-level ontologies. In the
ontology matching field, top-level ontologies could be seen as a resource to obtain or
improve the alignment between domain ontologies. In this way, [Padilha et al. 2012] pro-
pose an approach to explore alignment patterns based on the Unified Foundational On-
tology (UFO). In [Mascardi et al. 2010], a set of algorithms is developed to exploit top-
level ontologies as semantic bridges to solve heterogeneity problems of domain ontology
alignments. One algorithm that helps the developer to choose a more suitable top-level
ontology for use together with domain ontologies is presented in [Khan and Keet 2012].
The top-level ontologies which are able to be recommended are DOLCE, BFO, GFO, and
SUMO. The same authors present a repository called ROMULUS with the aim of improv-
ing semantic interoperability of top-level ontologies [Khan and Keet 2013]. In ROMU-
LUS, there are alignments among three top-level ontologies (DOLCE, BFO and GFO)
with each other manually and using automatic matching tools [Khan and Keet 2013]
We are particularly interested in aligning top-level and domain ontologies. There-
fore, we investigated the existing alignments regarding top-level ontologies and exter-
nal resources such as WordNet, once, background knowledge from external resources
such as WordNet has been largely exploited in matching domain ontologies, as a way
for improving similarity measures [Lin and Sandkuhl 2008]. In this way, Gangemi et al.
[Gangemi et al. 2002] present an effort to align WordNet nouns with DOLCE top-level
ontology. More recently Silva et al. [Silva et al. 2016] present an extension of the pre-
vious alignment between DOLCE and WordNet nouns [Gangemi et al. 2002] to include
verbs. In the same way, it is possible to see alignments between WordNet and other
top-level ontologies as BFO [Seppälä 2015], Cyc [Reed and Lenat 2002], and SUMO
[Niles and Pease 2003].
During the investigation, we observe the importance of using top-level ontologies
to aggregate semantics and reduce heterogeneity problems between ontologies. More-
over, we can observe that lexical databases such as WordNet are used in the ontology
alignment task as an external resource to identify domain concepts correspondence. How-
ever, we identify less efforts to automatize the process of alignment. In fact, we do not
identify an application developed specifically to align domain and top-level ontologies.
The available matching systems were developed to align ontologies in a same domain
and there is no evaluation of them in the task of align domain and top-level ontologies.
Therefore, we are proposing a matching approach and a reference alignment for its eval-
uation. We start our investigation evaluating the output of available matching systems
[Schmidt et al. 2016a]. We also investigate the use of WordNet as a validator for the
alignments [Schmidt et al. 2016b]. These studies are described in the next section.
4. Initial Experiments
In order to define our proposal, we develop two initial experiments towards the problems
we will address in our thesis. First, we made an analysis of some available matching sys-
tems participating in previous OAEI campaigns. We use these matchers to align domain
and top-level ontologies. Even though they were not developed specifically for that pur-
pose, they are the currently available tools. Also they present many different approaches
for the alignment problem and their output might help us to investigate the problem. This
study has been published in the International Workshop on Ontology Matching (OM-
2016) [Schmidt et al. 2016a] and discusses the challenges observed in the task of align
domain and top-level ontologies.
In a second analysis, we used WordNet to automatically validate the generated
alignments from the first study. This study was concerned with the automatic validation
of candidate alignments between top-level and domain ontologies, exploiting WordNet
background knowledge and the notion of context. We apply our approach for validat-
ing alignments generated by the matching tools and discuss the results against the man-
ual validation presented in [Schmidt et al. 2016a]. This study has been published in the
Brazilian Ontology Research Seminar (ONTOBRAS-2016) [Schmidt et al. 2016b] and
discusses the obtained results and benefits to adopt external resources to validate gener-
ated correspondences.
5. Research hypothesis, Goals and Methodology
Considering the depicted discussed challenges of aligning top-level and domain ontolo-
gies, we define a research hypothesis which will be a guide of our research work as follow:
The lexical database WordNet could be a way to improve and obtain gains in relation to
the state-of-the-art matching systems in the task of align general domain and top-level on-
tologies, once, there are previous alignments between top-level ontologies and WordNet.
Also, WordNet is a source of knowledge regarding subsumption relation between terms,
which is essential for this kind of alignment.
We aim at proposing an approach for automatic ontology alignment between top-
level and domain ontologies. To explore this field, we developed some preliminary studies
which made it possible to delimit the scope of our work. In the experiments, we adopted
the conference domain which is one of the participant domains of OAEI evaluation cam-
paigns. For this domain, there is no reference alignments involving top-level ontologies.
Reference alignments are important sources to compare and evaluate automatic matching
approaches. Hence, we intend to build a reference alignment between ontologies of the
conference domain and top-level ontologies.
Considering our preliminary studies, we intend to adopt the previous alignments
between the lexical database WordNet and some well known top-level ontologies such
as DOLCE and SUMO as an intermediary step to align domain ontologies with some
of the top-level ontologies. The option of the WordNet regarding the other databases
is because there are previous alignments of this base with several top-level ontologies.
Moreover, WordNet presents common sense terms so it can help us in the identification
of correspondences between domain and top-level concepts, where the domain if of a
more general kind such as the conferences domain.
Our approach consists in, given a domain ontology as input, identifying the most
appropriate WordNet synset for each domain concept. The synset identification is based
on the concept context. A context is constructed from all information available about an
ontology entity, including entity naming (ID), annotation properties (usually labels and
comments) and information on the neighbors (super and sub-concepts). Next, the selected
synset has to be found in the alignment between WordNet and top-level ontology. Since
the synset is previously mapped to the top-level ontology, we will track the top-level
concept to map them with the domain concept.
Hence, our process could be divided in four main steps: (i) extraction of the ontol-
ogy concepts; (ii) processing of the context related to each concept; (iii) use of the context
to retrieve the appropriate synset in WordNet; and (iv) the track of the top-level concept
based on the alignment of the WordNet synset to top-level ontology concept.
We intend to evaluate our approach through a prototype which can be compared
with other available matching tools. We are aware that they are not developed specifically
to align domain and top-level ontologies, however that is currently the only comparison
possible. In addition, we intend to develop a reference alignment which will allow us to
evaluate our approach in terms of precision recall and F-measure. Hence, in the end of
our work, we intend to contribute with (i) the creation of a reference alignment for do-
main and top-level ontologies; The chosen domain is conferences adopted in our previous
experiments regarding DOLCE and SUMO top ontologies which we intend to adopt in
our work. (ii) an approach to align top-level and domain ontologies automatically; and
(iii) a prototype implementing our alignment approach and its evaluation.
6. Final Remarks
In this paper, we present a summary of our thesis proposal. We described the theoretical
background adopted as a basis to our work and current related work. We developed some
initial analysis which were useful to identify the current situation of available tools in the
task of align top-level and domain ontologies. In the same way, we investigated the use of
external resources as a way to validate the resulting alignments. Hence, we consider that
the lexical database WordNet could be a useful external resource in the task of aligning
top-level and domain ontologies, specially because there are alignments between some of
the most common top-level ontologies and WordNet.
We are aware of some limitations regarding the use of WordNet, since it usually
lacks very specialized terms and it does not contain compound terms. Also, regarding
the previous alignment involving WordNet and top-level ontologies we are limited to the
version of WordNet used in the alignment and in some top-level ontologies, the alignment
could be not complete and cover only nouns, or other specific group of terms. Besides
these limitations, considered the lack of options for dealing with this problem and, on the
other hand, alignments already given for WorNet and top ontologies, we believe that such
proposal may improve the current status in this research area.
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