As the main way for knowledge representation for the purpose of machine understanding, ontologies are widely used in di erent application domains. This requires more and more domain speci c information to be inserted into ontologies, making them harder to be easily understood by a human and there is a growing need to develop ontology visualization tools. However, most of existing tools focus on either a speci c user requirement or ontology-speci c features. To this end, in this demo, we introduce a new generic and user-friendly ontology visualization tool, called BioOntoVis, for visualizing and editing ontologies. We present the general architecture of the tool focusing on the web-based user interface and di erent ontology visualization schemes. Through the demonstration of BioOntoVis, we introduce the tool's capabilities and highlight its e ectiveness and usability.
Ontologies are the basic components of the Semantic Web, where underlying
data are well structured for the purpose of full machine understanding. An
ontology consists of a set of concepts (classes), a set of attributes (data type
properties), relationships (object properties), and constraints to abstractly
represent a speci c domain. An important aspect is how to facilitate the process
of design, management, and exploration of complex structures. This results in a
growing need for ontology visualization tools that simplify the user involvement
in di erent ontology-related management processes [
Furthermore, and as a main way of knowledge representation, ontologies have
been becoming more and more widely used in di erent application domains.
Therefore, there exist a large number of ontologies, some of them containing
hundreds of thousands of concepts or more. For example, BioPortal 3 contains 737
ontologies with 9,604,539 classes (with an average 13,157 classes per ontology).
The arising number of developed ontologies as well as the number of concepts
each ontology has make ontology visualization a di cult task. Even though, a
3 http://bioportal.bioontology.org/ (access on October 25, 2018)
number of ontology visualization approaches have been developed [
To this end, in this paper, we introduce a new ontology visualization tool,
called BioOntoVis 4, which is based on a combination of visualization techniques
to re ect the mentioned challenges. The proposed tool follows three main steps,
including: (i) reading and parsing the input ontology, (ii) a set of processing
aspects to make the ontology suitable for visualization, and (iii) nally, the
suitable visual representation is selected to visualize the ontology. The proposed
BioOntoVis tool supports node-link and tree, zoomable, and 3D information
landscape [
To deal with visualizing ontologies meeting di erent application domains as well as variant user requirements, we present a new ontology visualization tool, BioOntoVis, introducing a high-level architecture for a generic pipeline for ontology visualization. The pipeline has three main steps: parsing, processing, and visual representation.
Parsing. An ontology O can be represented as a set of entities, such that an entity is either a concept (class), a relation, or an instance (individual). The set of concepts and the set of relations are disjoint, where there is a concept hierarchy between the set of concepts, and there is also a relation hierarchy among relations. Before visualizing an ontology, a parsing step is needed to extract the ontology entities and transform them into a JSON format to be graphically represented. We select working with the OWL API 5 to deal with ontologies with di erent formats. The appropriate parser is automatically selected at runtime when an ontology is loaded.
Processing. This step focuses on the cognitive features included in the visualization tool aiming to strengthen the user's support. It includes both basic and advanced functionalities. The basic functionalities include: i) colors: we de ne a color scheme for a better distinction between several ontology entities. For example in the sheye view, we choose a dark-blue scheme for super-classes, light-blue for sub-classes, orange for the properties and a pink scheme for individuals. This color scheme is clearly very helpful in identifying the ontology elements variations, ii) shapes: BioOntoVis provides various views with various node shapes. This option gives several choices to the user to visualize ontologies. In the network view as an example, we used a rectangle shape, however in the sheye view we used a circle shape, iii) zooming: we use two di erent zooming types: 4 This work was originally motivated by the need to visualize ontologies from the bio domain, hence the name. 5 http://owlcs.github.io/owlapi/ geometric and semantics. The geometric zoom allows the user to explore certain ontology entities in detail when she zooms-in analyzing the global structure of the ontology once she zooms-out. The semantics zoom o ers the possibility to see details of a speci c entity by zooming, and iv) details; an ontology contains a large amount of information and description (metadata), including entity name, label, types, and relations' types, ect. To this end, BioOntoVis supports illustrating these information. It contains a circular attractive menu, shows general details about the ontology, such as the metadata, the ontology format and the number of concepts, properties and individuals.
(a) Tree view
(b) Fisheye view
Advanced functionalities the proposed tool supports include: i) search:
nding an ontology entity by visually scanning the ontology graph is a very di cult
process, especially in the context of big ontologies. Therefore, the current
implementation of the tool contains a search window to quickly nd particular entities
or other elements by their names/labels. In the tree interface, once a user tapes
in the window, a list containing the set of relevant entities appears to facilitate
the search process. We then visualize the searched entity with a di erent color.
ii) editing operators: ontologies posses a very complex structure and editing
its entities is a hard task. This is due to the fact that each edit process has
to check the correctness and consistency of the modi ed ontology. Therefore,
most of existing ontology visualization tools lack the advanced functionalities
that are important for the user to interact more with the displayed ontology. For
example, ontology modularization partitions an ontology into a set of partitions
(modules) [
Visual representation. To cover a wide range of ontologies, BioOntoVis provides three views of visual representations, which are: tree, network, and sheye view. As shown in Fig. 1a, the tree view representation is a hierarchical node-link view, in which the ontology is represented as a set of interconnected nodes in di erent levels. In this view, the user can extend or compress the tree, by displaying or hiding children nodes allowing the user to control the depth of the tree. In the network view, the nodes have rectangle shapes and are connected to each other through edges. In this view, colors have their meanings to facilitate distinguishing between ontology entities. Moreover, a detailed box appears once a node is selected to give detailed information about the entity, and its relationships. In large ontology visualization, links between concepts would be drawn crossing and overlapping each others, which cause a very messy and potentially unusable view of the ontology graph. Therefore, we implemented the sheye view in the tool to deal with this problem. This view demonstrates the selected node surrounded by the ones that are related to it, hiding all the others, as shown in Fig. 1b. 3
In this demonstration, we will start by presenting the di erent features of BioOntoVis such as various capabilities of the tool to visualize di erent ontologies using di erent views, such as tree, network, or sheye based on the characteristics of the ontology, as shown in Figs. 1a and 1b. The demonstration will consist of two main parts. First, we would like the user to appreciate the importance of the visualization phase. Second, we present di erent operations that can be employed on the displayed ontology. To this end, the BioOntoVis tool is provided with a nice web interface6, where the user can upload her ontology and then select which visualization view to show the ontology. Through this web interface, the user can get some metadata about the ontology, such as format, the number of concepts, the number of properties, etc. Later, the user can adjust the view to t her needs. 4
A part of this research was supported by DAAD funding through the BioDialog project. A. Algergawy' work is partly funded by DFG in the scope of CRC 1067 AquaDiva.