=Paper=
{{Paper
|id=Vol-1766/oaei16_paper9
|storemode=property
|title=LogMap family participation in the OAEI 2016
|pdfUrl=https://ceur-ws.org/Vol-1766/oaei16_paper9.pdf
|volume=Vol-1766
|authors=Ernesto Jiménez-Ruiz,Bernardo Cuenca Grau,Valerie Cross
|dblpUrl=https://dblp.org/rec/conf/semweb/Jimenez-RuizGC16
}}
==LogMap family participation in the OAEI 2016==
https://ceur-ws.org/Vol-1766/oaei16_paper9.pdf
LogMap family participation in the OAEI 2016
E. Jiménez-Ruiz1 , B. Cuenca Grau2 , and V. Cross3
1
Department of Informatics, University of Oslo, Oslo, Norway
2
Department of Computer Science, University of Oxford, Oxford, UK
3
Computer Science and Software Engineering, Miami University, Oxford, OH, United States
Abstract. We present the participation of LogMap and its variants in the OAEI
2016 campaign. The LogMap project started in January 2011 with the objective
of developing a scalable and logic-based ontology matching system. This is our
seventh participation in the OAEI and the experience has so far been very positive.
LogMap is one of the few systems that participates in all OAEI tracks.
1 Presentation of the system
Ontology matching systems typically rely on lexical and structural heuristics and the
integration of the input ontologies and the mappings may lead to many undesired log-
ical consequences. In [12] three principles were proposed to minimize the number of
potentially unintended consequences, namely: (i) consistency principle, the mappings
should not lead to unsatisfiable classes in the integrated ontology; (ii) locality principle,
the mappings should link entities that have similar neighbourhoods; (iii) conservativ-
ity principle, the mappings should not introduce alterations in the classification of the
input ontologies. Violations to these principles may hinder the usefulness of ontology
mappings. The practical effect of these violations, however, is clearly evident when
ontology alignments are involved in complex tasks such as query answering [20].
LogMap [11, 13] is a highly scalable ontology matching system that implements the
consistency and locality principles. LogMap also supports (real-time) user interaction
during the matching process, which is essential for use cases requiring very accurate
mappings. LogMap is one of the few ontology matching system that (i) can efficiently
match semantically rich ontologies containing tens (and even hundreds) of thousands
of classes, (ii) incorporates sophisticated reasoning and repair techniques to minimise
the number of logical inconsistencies, and (iii) provides support for user intervention
during the matching process.
LogMap relies on the following elements, which are keys to its favourable scalabil-
ity behaviour (see [11, 13] for details).
Lexical indexation. An inverted index is used to store the lexical information contained
in the input ontologies. This index is the key to efficiently computing an initial set of
mappings of manageable size. Similar indexes have been successfully used in informa-
tion retrieval and search engine technologies [2].
Logic-based module extraction. The practical feasibility of unsatisfiability detection
and repair critically depends on the size of the input ontologies. To reduce the size of
the problem, we exploit ontology modularisation techniques. Ontology modules with
well-understood semantic properties can be efficiently computed and are typically much
smaller than the input ontology (e.g. [5]).
Propositional Horn reasoning. The relevant modules in the input ontologies together
with (a subset of) the candidate mappings are encoded in LogMap using a Horn propo-
sitional representation. Furthermore, LogMap implements the classic Dowling-Gallier
algorithm for propositional Horn satisfiability [6]. Such encoding, although incomplete,
allows LogMap to detect unsatisfiable classes soundly and efficiently.
Axiom tracking. LogMap extends Dowling-Gallier’s algorithm to track all mappings
that may be involved in the unsatisfiability of a class. This extension is key to imple-
menting a highly scalable repair algorithm.
Local repair. LogMap performs a greedy local repair; that is, it repairs unsatisfiabilities
on-the-fly and only looks for the first available repair plan.
Semantic indexation. The Horn propositional representation of the ontology modules
and the mappings is efficiently indexed using an interval labelling schema [1] — an
optimised data structure for storing directed acyclic graphs (DAGs) that significantly
reduces the cost of answering taxonomic queries [4, 21]. In particular, this semantic
index allows us to answer many entailment queries as an index lookup operation over
the input ontologies and the mappings computed thus far, and hence without the need
for reasoning. The semantic index complements the use of the propositional encoding
to detect and repair unsatisfiable classes.
1.1 LogMap variants in the 2016 campaign
In the 2016 campaign we have participated with two additional variants:
LogMapLt is a “lightweight” variant of LogMap, which essentially only applies (effi-
cient) string matching techniques.
LogMapBio includes an extension to use BioPortal [8, 9] as a (dynamic) provider of
mediating ontologies instead of relying on a few preselected ontologies [3].
This year we did not participate with LogMapC4 since in OAEI 2016 there are not
alignment tasks suitable for a correct evaluation of LogMapC.5 The repair algorithm in
LogMapC is more aggressive than in LogMap, which harms its results if the alignment
task does not take into account the conservativity principle.
1.2 Adaptations made for the 2016 evaluation
LogMap’s algorithm described in [11, 13, 14] has been adapted with the following new
functionalities:
i Extended multilingual support. We have extended our multilingual module with
additional translations.
4
LogMapC is a variant of LogMap which, in addition to the consistency and locality principles,
also implements the conservativity principle (see details in [22–24]).
5
The interested reader please refer to [24, 17] for examples of alignment tasks suitable for
LogMapC.
ii Extended instance matching support. We have partially adapted LogMap’s in-
stance matching module to cope with the new OAEI 2016 tasks.
iii BioPortal module. We have adapted LogMapBio with respect to the changes in the
BioPortal API. Note that LogMapBio only participates in the biomedical tracks. In
the other tracks the results are expected to be the same as LogMap.
1.3 Link to the system and parameters file
LogMap is open-source and released under GNU Lesser General Public License 3.0.6
LogMap components and source code are available from the LogMap’s GitHub page:
https://github.com/ernestojimenezruiz/logmap-matcher/.
LogMap distributions can be easily customized through a configuration file contain-
ing the matching parameters.
LogMap, including support for interactive ontology matching, can also be used
directly through an AJAX-based Web interface: http://krrwebtools.cs.ox.
ac.uk/. This interface has been very well received by the community since it was
deployed in 2012. More than 2,500 requests coming from a broad range of users have
been processed so far.
1.4 Modular support for mapping repair
Only a very few systems participating in the OAEI competition implement repair tech-
niques. As a result, existing matching systems (even those that typically achieve very
high precision scores) compute mappings that lead in many cases to a large number of
unsatisfiable classes.
We believe that these systems could significantly improve their output if they were
to implement repair techniques similar to those available in LogMap. Therefore, with
the goal of providing a useful service to the community, we have made LogMap’s ontol-
ogy repair module (LogMap-Repair) available as a self-contained software component
that can be seamlessly integrated in most existing ontology matching systems [16, 7].
2 General comments and conclusions
Please refer to http://oaei.ontologymatching.org/2016/results/ for
the results of the LogMap family in the OAEI 2016 campaign.
2.1 Comments on the results
LogMap has been one of the top systems in the OAEI 2016 and one of the few system
that participates in all tracks. Furthermore, it has also been one of the few systems
implementing repair techniques and providing (almost) coherent mappings in all tracks.
LogMap’s main weakness is that the computation of candidate mappings is based
on the similarities between the vocabularies of the input ontologies; hence, in the cases
where the ontologies are lexically disparate or do not provide enough lexical informa-
tion LogMap is at a disadvantage.
6
http://www.gnu.org/licenses/
2.2 Discussions on the way to improve the proposed system
LogMap is now a stable and mature system that has been made available to the commu-
nity and has been extensively tested. There are, however, many exciting possibilities for
future work. For example we aim at improving the current multilingual features and the
current use of external resources like BioPortal. Furthremore, we are applying LogMap
in practice in the domain of oil and gas industry within the FP7 Optique7 [19, 15, 10,
18]. This practical application presents a very challenging problem.
Acknowledgements
This work was supported by the Centre for Scalable Data Access (SIRIUS), the EPSRC
projects ED3, Score! and DBOnto, and by the EU FP7 project Optique (grant agreement
318338).
We would also like to thank Ian Horrocks, Alessandro Solimando, Anton Morant,
Yujiao Zhou, Weiguo Xia, Xi Chen, Yuan Gong and Shuo Zhang, who have contributed
to the LogMap project in the past.
References
1. Agrawal, R., Borgida, A., Jagadish, H.V.: Efficient management of transitive relationships
in large data and knowledge bases. In: ACM SIGMOD Conf. on Management of Data. pp.
253–262 (1989)
2. Baeza-Yates, R.A., Ribeiro-Neto, B.A.: Modern Information Retrieval. ACM Press /
Addison-Wesley (1999)
3. Chen, X., Xia, W., Jiménez-Ruiz, E., Cross, V.: Extending an ontology alignment system
with bioportal: a preliminary analysis. In: Poster at Int’l Sem. Web Conf. (ISWC) (2014)
4. Christophides, V., Plexousakis, D., Scholl, M., Tourtounis, S.: On labeling schemes for the
Semantic Web. In: Int’l World Wide Web (WWW) Conf. pp. 544–555 (2003)
5. Cuenca Grau, B., Horrocks, I., Kazakov, Y., Sattler, U.: Modular reuse of ontologies: Theory
and practice. J. Artif. Intell. Res. 31, 273–318 (2008)
6. Dowling, W.F., Gallier, J.H.: Linear-time algorithms for testing the satisfiability of proposi-
tional Horn formulae. J. Log. Prog. 1(3), 267–284 (1984)
7. Faria, D., Jiménez-Ruiz, E., Pesquita, C., Santos, E., Couto, F.M.: Towards annotating po-
tential incoherences in bioportal mappings. In: 13th Int’l Sem. Web Conf. (ISWC) (2014)
8. Fridman Noy, N., Shah, N.H., Whetzel, P.L., Dai, B., et al.: BioPortal: ontologies and inte-
grated data resources at the click of a mouse. Nucleic Acids Research 37, 170–173 (2009)
9. Ghazvinian, A., Noy, N.F., Jonquet, C., Shah, N.H., Musen, M.A.: What four million map-
pings can tell you about two hundred ontologies. In: Int’l Sem. Web Conf. (ISWC) (2009)
10. Giese, M., Soylu, A., Vega-Gorgojo, G., Waaler, A., Haase, P., Jimenez-Ruiz, E., Lanti, D.,
Rezk, M., Xiao, G., Ozcep, O., Rosati, R.: Optique — Zooming In on Big Data Access.
Computer 48(3), 60–67 (2015)
11. Jiménez-Ruiz, E., Cuenca Grau, B.: LogMap: Logic-based and Scalable Ontology Matching.
In: Int’l Sem. Web Conf. (ISWC). pp. 273–288 (2011)
12. Jiménez-Ruiz, E., Cuenca Grau, B., Horrocks, I., Berlanga, R.: Logic-based assessment of
the compatibility of UMLS ontology sources. J. Biomed. Sem. 2 (2011)
7
http://www.optique-project.eu/
13. Jiménez-Ruiz, E., Cuenca Grau, B., Zhou, Y., Horrocks, I.: Large-scale interactive ontology
matching: Algorithms and implementation. In: Europ. Conf. on Artif. Intell. (ECAI) (2012)
14. Jiménez-Ruiz, E., Grau, B.C., Solimando, A., Cross, V.V.: Logmap family results for OAEI
2015. In: Proceedings of the 10th International Workshop on Ontology Matching collocated
with the 14th International Semantic Web Conference (ISWC 2015), Bethlehem, PA, USA,
October 12, 2015. pp. 171–175 (2015), http://ceur-ws.org/Vol-1545/oaei15_
paper10.pdf
15. Jiménez-Ruiz, E., Kharlamov, E., Zheleznyakov, D., Horrocks, I., Pinkel, C., Skjæveland,
M.G., Thorstensen, E., Mora, J.: BootOX: Practical Mapping of RDBs to OWL 2. In: Interna-
tional Semantic Web Conference (ISWC) (2015), http://www.cs.ox.ac.uk/isg/
tools/BootOX/
16. Jiménez-Ruiz, E., Meilicke, C., Cuenca Grau, B., Horrocks, I.: Evaluating mapping repair
systems with large biomedical ontologies. In: 26th Description Logics Workshop (2013)
17. Jimenez-Ruiz, E., Payne, T.R., Solimando, A., Tamma, V.: Limiting logical violations in on-
tology alignment through negotiation. In: Proceedings of the 15th International Conference
on Principles of Knowledge Representation and Reasoning (KR). AAAI Press (April 2016)
18. Kharlamov, E., Hovland, D., Jiménez-Ruiz, E., Lanti, D., Lie, H., Pinkel, C., Rezk, M.,
Skjæveland, M.G., Thorstensen, E., Xiao, G., Zheleznyakov, D., Horrocks, I.: Ontology
Based Access to Exploration Data at Statoil. In: International Semantic Web Conference
(ISWC). pp. 93–112 (2015)
19. Kharlamov, E., Jiménez-Ruiz, E., Zheleznyakov, D., et al.: Optique: Towards OBDA Systems
for Industry. In: Eur. Sem. Web Conf. (ESWC) Satellite Events. pp. 125–140 (2013)
20. Meilicke, C.: Alignment Incoherence in Ontology Matching. Ph.D. thesis, University of
Mannheim (2011)
21. Nebot, V., Berlanga, R.: Efficient retrieval of ontology fragments using an interval labeling
scheme. Inf. Sci. 179(24), 4151–4173 (2009)
22. Solimando, A., Jiménez-Ruiz, E., Guerrini, G.: Detecting and correcting conservativity prin-
ciple violations in ontology-to-ontology mappings. In: Int’l Sem. Web Conf. (ISWC) (2014)
23. Solimando, A., Jiménez-Ruiz, E., Guerrini, G.: A multi-strategy approach for detecting and
correcting conservativity principle violations in ontology alignments. In: Proc. of the 11th
International Workshop on OWL: Experiences and Directions (OWLED). pp. 13–24 (2014)
24. Solimando, A., Jimenez-Ruiz, E., Guerrini, G.: Minimizing conservativity violations in on-
tology alignments: Algorithms and evaluation. Knowledge and Information Systems (2016),
https://github.com/asolimando/logmap-conservativity/