=Paper=
{{Paper
|id=Vol-1515/poster10
|storemode=property
|title=Visualization and editing of biomedical ontology alignments in AgreementMakerLight
|pdfUrl=https://ceur-ws.org/Vol-1515/poster10.pdf
|volume=Vol-1515
|dblpUrl=https://dblp.org/rec/conf/icbo/MartinsFP15
}}
==Visualization and editing of biomedical ontology alignments in AgreementMakerLight==
https://ceur-ws.org/Vol-1515/poster10.pdf
Visualization and editing of biomedical ontology alignments in
AgreementMakerLight
Catarina Martins 1 , Daniel Faria 2 , Catia Pesquita 1
1
LaSIGE, Departamento de Informática, Faculdade de Ciências, Universidade de Lisboa
2
Instituto Gulbenkian de Ciência
ABSTRACT mappings; a Mapping Viewer dedicated to the graph representation
Biomedical ontologies pose interesting challenges to the visualiza- of each mapping and its neighbors (Figure 1) and the Alignment
tion of ontology alignments due to their size and complexity. Reviewer that lists all the mappings involved in the alignment with
AgreementMakerLight (AML) is a lightweight ontology alignment information about each one (Figure 2).
system that is particularly suited to the alignment of biomedical onto-
logies.
Here, we present the updates and evolution of the AML graphical
user interface, with a focus on alignment visualization and alignment
editing.
1 INTRODUCTION
Several biomedical ontologies have overlapping or related domains,
and matching them would greatly increase their interoperability.
Ontology matching techniques produce an alignment between two
ontologies by establishing correspondences between their elements.
Each correspondence is called a mapping and an alignment corre-
sponds to the set of all mappings.
Biomedical ontologies pose challenges in ontology alignment and
alignment visualization due to their usually large size, and com-
plexity which can lead to several computational and visualization
issues.
AgreementMakerLight(AML) is a lightweight ontology matching
system that is particularly well-suited to matching biomedical onto-
logies, since it can handle large ontologies with complex termino-
logy (Faria et al., 2013a). AML has achieved top performances in Fig. 1. Visualization of a mapping between two different ontologies in the
the biomedical ontologies tasks in OAEI 2013 (Faria et al., 2013b) Mapping Viewer tab.
and 2014 (Faria et al., 2014), an international competition for onto-
logy alignment systems. It includes several matching techniques
supported by a graphical user interfacePesquita et al. (2014).
Other ontology matching systems provide user interfaces and visu- 3 COMPUTING OR LOADING AN ALIGNMENT
alization and editing features (e.g.: COMA 3.0 (Massmann et al., The user can load the ontologies in either OWL or RDFs, then he
2011), AgreementMaker (Cruz et al., 2009), RepOSE (Ivanova and has the option to load a precomputed alignment or to match the
Lambrix, 2012)). However, they struggle to handle large ontologies ontologies he desires to analyze. In GUI-mode, AML provides two
with multiple inheritance (which is a common case in the biomedi- matchers: an automatic matcher and a custom matcher where the
cal domain). user can decide which techniques will be involved in the alignment.
We present the latest advancements in the graphical user interface The user also has the possibility to repair an alignment (Santos et al.,
for AML, focusing on the novel user alignment editing capabilities 2013) or to evaluate an alignment against a reference standard . All
and element inspection views. Editing is accompanied by a mapping of these features grant the user the opportunity to save the produced
graph-based visualization that supports users in decision making. alignment in RDF or in a tab-separated text file.
AML is open-source and freely available (as runnable Jar and
Eclipse Project) at https://github.com/AgreementMakerLight/AML- 4 EDITING AN ALIGNMENT
Project. For more information, please check: http://aml.fc.ul.pt. The new update allows the user to alter an existing alignment (either
loaded or computed by AML) in the Alignment Reviewer tab. To
remove an existing mapping, the user can select it from the list of
2 AGREEMENTMAKERLIGHT GUI mappings (Figure 2). To add a new mapping, the user can select the
The graphical user interface of AML comprises three main areas: appropriate option and then use a label based search for the classes
the Resource Panel where information about the ontologies and the or properties to map (Figure 3). Both types of changes are recorded
alignment is displayed, like the number of classes, properties and when the alignment is saved.
Copyright c 2015 for this paper by its authors. Copying permitted for private and academic purposes 1
Martins et al
disjoint axioms. The inspection view for properties includes label,
domain, range and property type.
5 VISUALIZING A MAPPING
The alignment can be navigated using three different strategies:
• the next/previous mapping option;
• select a mapping from the list of mappings in the Alignment
Reviewer tab or in the appropriate sub-menu;
• searching a certain mapping containing a certain term of
interest, which is supported by an auto-complete function.
Once a mapping is selected, it can be visualized in the Mapping
Viewer tab which includes a graph-based representation of the map-
ping and its neighborhood. The neighborhood of a mapping includes
the classes that are at a predefined distance from the mapped classes,
and any mappings between them (see Figure 1).
6 CONCLUSION
User involvement in ontology matching is greatly influenced by
Fig. 2. List of mappings between two different ontologies in the Alignment
the availability of suitable user interfaces and adequate visuali-
Reviewer tab.
zation approaches. The recent updates to AgreementMakerLight’s
user interface have made it possible for users to edit a loaded
or computed alignment, while being supported by element inspe-
ction capabilities and graph-based visualization of mappings in their
context. In future work, we plan to include the visualization of
conflicting mappings caused by logical incoherence (Martins et al.,
2015). This will allow user to tailor an alignment to their specific
purposes since ensuring absolute coherence can decrease the use-
fulness of an alignment in some cases, due to the loss of meaningful
mappings through the repair process (Pesquita et al., 2013).
Fig. 3. Add Mapping window in AML.
ACKNOWLEDGEMENTS
This work was partially supported by FCT through funding of
LaSIGE Research Unit, ref.UID/CEC/00408/2013.
REFERENCES
Cruz, I. F., Antonelli, F. P., and Stroe, C. (2009). Agreementmaker: efficient matching
for large real-world schemas and ontologies. Proceedings of the VLDB Endowment,
2(2), 1586–1589.
Faria, D., Pesquita, C., Santos, E., Palmonari, M., Cruz, I. F., and Couto, F. M. (2013a).
The agreementmakerlight ontology matching system. In On the Move to Meaningful
Internet Systems: OTM 2013 Conferences, pages 527–541. Springer.
Faria, D., Pesquita, C., Santos, E., Cruz, I. F., and Couto, F. M. (2013b). Agreemen-
tmakerlight results for oaei 2013. page 101.
Faria, D., Martins, C., Nanavaty, A., Taheri, A., Pesquita, C., Santos, E., Cruz, I. F.,
and Couto, F. M. (2014). Agreementmakerlight results for oaei 2014.
Ivanova, V. and Lambrix, P. (2012). A system for debugging taxonomies and their align-
ments. In Proceedings of the 1st International Workshop on Debugging Ontologies
and Ontology Mappings, volume 79, pages 37–42.
Martins, C., Jimenez-Ruiz, E., Santos, E. P., and Pesquita, C. (2015). Towards
visualizing the mapping incoherences in bioportal.
Massmann, S., Raunich, S., Aumüller, D., Arnold, P., and Rahm, E. (2011). Evolution
Fig. 4. Class inspection views. of the coma match system. volume 49.
Pesquita, C., Faria, D., Santos, E., and Couto, F. M. (2013). To repair or not to repair:
reconciling correctness and coherence in ontology reference alignments. page 13.
These tasks can be supported by the inspection of each mapping Pesquita, C., Faria, D., Santos, E., Neefs, J.-M., and Couto, F. M. (2014). Towards
which is accessible from the Alignment Reviewer tab (see Figure visualizing the alignment of large biomedical ontologies. In Data Integration in the
Life Sciences, pages 104–111. Springer.
4). The inspection view for classes provides lexical information, Santos, E., Faria, D., Pesquita, C., and Couto, F. (2013). Ontology alignment
which includes local name and synonyms, and structural informa- repair through modularization and confidence-based heuristics. arXiv preprint
tion, which includes direct superclasses, high-level ancestors and arXiv:1307.5322.
2 Copyright c 2015 for this paper by its authors. Copying permitted for private and academic purposes