Florian Haag

Visualizing ontologies with VOWL

The Visual Notation for OWL Ontologies (VOWL) is a well-specified visual language for the user-oriented representation of ontologies. It defines graphical depictions for most elements of the Web Ontology Language (OWL) that are combined to a force-directed graph layout visualizing the ontology. In contrast to related work, VOWL aims for an intuitive and comprehensive representation that is also understandable to users less familiar with ontologies. This article presents VOWL in detail and describes its implementation in two different tools: ProtegeVOWL and WebVOWL. The first is a plugin for the ontology editor Protege, the second a standalone web application. Both tools demonstrate the applicability of VOWL by means of various ontologies. In addition, the results of three user studies that evaluate the comprehensibility and usability of VOWL are summarized. They are complemented by findings from an interview with experienced ontology users and from testing the visual scope and completeness of VOWL with a benchmark ontology. The evaluations helped to improve VOWL and confirm that it produces comparatively intuitive and comprehensible ontology visualizations.

VOWL 2: User-Oriented Visualization of Ontologies

Ontologies become increasingly important as a means to structure and organize information. This requires methods and tools that enable not only ontology experts but also other user groups to work with ontologies and related data. We have developed VOWL, a comprehensive and well-specified visual language for the user-oriented representation of ontologies, and conducted a comparative study on an initial version of VOWL. Based upon results from that study, as well as an extensive review of other ontology visualizations, we have reworked many parts of VOWL. In this paper, we present the new version VOWL 2 and describe how the initial definitions were used to systematically redefine the visual notation. Besides the novelties of the visual language, which is based on a well-defined set of graphical primitives and an abstract color scheme, we briefly describe two implementations of VOWL 2. To gather some insight into the user experience with the new version of VOWL, we have conducted a qualitative user study. We report on the study and its results, which confirmed that not only the general ideas of VOWL but also most of our enhancements for VOWL 2 can be well understood by casual ontology users.

Visual SPARQL querying based on extended filter/flow graphs

SPARQL is currently the major query language for the Semantic Web. However, writing SPARQL queries is not an easy task and requires some understanding of technologies like RDF. In order to enable users without this knowledge to query linked data, visual interfaces are required that hide the SPARQL syntax and provide graphical support for query building. Based on the concept of extended filter/flow graphs, we present a novel approach for visual querying that addresses the unique specifics of SPARQL and RDF. In particular, it enables the creation of SELECT and ASK queries, though it can also be used for other query forms. In contrast to related work, the users do not need to provide any structured text input but can create the queries entirely with graphical elements. Our approach supports most features of SPARQL and hence also the construction of complex query expressions. It has been implemented in a visual querying framework and tested on different RDF datasets, including DBpedia that is used as an example in this paper. Since the filter/flow concept is empirically well-founded, we expect our approach to be very usable, which is additionally supported by the results of a qualitative user study we conducted.

QueryVOWL: Visual Composition of SPARQL Queries

In order to make SPARQL queries more accessible to users, we have developed the visual query language QueryVOWL. It defines SPARQL mappings for graphical elements of the ontology visualization VOWL. In this demo, we present a web-based prototype that supports the creation, modification, and evaluation of QueryVOWL graphs. Based on the selected SPARQL endpoint, it provides suggestions for extending the query, and retrieves IRIs and literals according to the selections in the QueryVOWL graph. In contrast to related work, SPARQL queries can be created entirely with visual elements.

Towards a unified visual notation for OWL ontologies: insights from a comparative user study

Browsing ontologies and making sense of their concepts and relationships are important activities in knowledge engineering. They are supported by a large number of tools that often provide visual representations of the ontologies for better illustration. However, different notations are used to represent the ontologies which can be confusing when switching tools. Furthermore, many representations provide only basic overviews of the ontologies that are not sufficient to get a deeper understanding of the concepts and relationships. A unified visual notation for OWL ontologies would be most helpful to overcome these limitations. Having this goal in mind, we compare two different notations for OWL ontologies in this paper: the UML profile of the Ontology Definition Metamodel (ODM) and the Visual Notation for OWL Ontologies (VOWL). We report on a comparative user study of these notations and discuss benefits and limitations raised by the study participants. Based on these findings, we draw some general conclusions regarding the development of a unified visual notation for OWL ontologies.

QueryVOWL: A Visual Query Notation for Linked Data

In order to enable users without any knowledge of RDF and SPARQL to query Linked Data, visual approaches can be helpful by providing graphical support for query building. We present QueryVOWL, a visual query language that is based upon the ontology visualization VOWL and defines mappings to SPARQL. We aim for a language that is intuitive and easy to use, while remaining flexible and preserving most of the expressiveness of SPARQL. In contrast to related work, the queries can be created entirely with visual elements, taking into account RDFS and OWL concepts often used to structure Linked Data. This paper is a revised version of a workshop paper where we first introduced QueryVOWL. We present the query notation, some example queries, and two prototypical implementations of QueryVOWL. Also, we report on a qualitative user study that indicates lay users are able to construct and interpret QueryVOWL graphs.

Simplifying filter/flow graphs by subgraph substitution

Although the filter/flow model is a useful concept for query visualization, the resulting graphs can be quite complex. We aim to reduce this complexity by substituting recurring subgraphs with more compact structures. Based on related work on extensions to the filter/flow concept, we have identified four recurring subgraphs that can be significantly simplified by substitutions. We describe these substitutions and discuss the preconditions that must be satisfied for their application. An example of news filtering illustrates how the substitutions can be used to simplify the overall structure of filter/flow graphs and increase their readability.

SparqlFilterFlow: SPARQL Query Composition for Everyone

SparqlFilterFlow provides a visual interface for the composition of SPARQL queries, in particular SELECT and ASK queries. It is based on the intuitive and empirically well-founded filter/flow model that has been extended to address the unique specifics of SPARQL and RDF. In contrast to related work, no structured text input is required but the queries can be created entirely with graphical elements. This allows even users without expertise in Semantic Web technologies to create complex SPARQL queries with only little training. SparqlFilterFlow is implemented in C#, supports a large number of SPARQL constructs and can be applied to any SPARQL endpoint.

OntoViBe 2: Advancing the Ontology Visualization Benchmark

A variety of ontology visualizations have been presented in the last couple of years. The features of these visualizations often need to be tested during their development or for evaluation purposes. However, in particular for the testing of special concepts and concept combinations, it can be difficult to find suitable ontologies. We have developed OntoViBe, an ontology covering a wide variety of OWL language constructs for the purpose of testing ontology visualizations. This paper presents OntoViBe 2, which extends the first version by annotations, individuals, anonymous classes, and a module for testing different combinations of cardinality constraints, among others. We describe the design principles underlying OntoViBe 2 and present the supported features in a coverage matrix. Finally, we load OntoViBe 2 with ontology visualization tools and point to some noteworthy aspects of the respective visualizations that become apparent and demonstrate how OntoViBe can be used for testing ontology visualizations.

VESPa: A Pattern-based Visual Query Language for Event Sequences

Movement data can often be enriched with additional information that enables analysts to ask new questions, for instance about POIs visited and meetings that imply interactions between persons. Information on spatiotemporal events such as visits or meetings can be especially valuable for digital forensics, marketing analysis, and urban planning. Most existing query languages for movement data, however, do not take that additional information into account. We address this gap by proposing VESPa, a pattern-based graphical query language to express, check, and refine hypotheses about spatio-temporal event sequences. Using VESPa, the analyst can sketch abstract assumptions and use the pattern to query the data for matches. The applicability of our approach is demonstrated in two case studies with different datasets. We also report on a small user study in which several construction and comprehension tasks were successfully solved in an interactive implementation