G-OWL: A Complete Visual Syntax for OWL 2 Modeling and Communication

Tracking #: 2550-3764

Gilbert Paquette
Michel Héon

Responsible editor: 
Aldo Gangemi

Submission type: 
Full Paper
Semantic web ontologies are usually modeled using standard text-based syntaxes such as OWL/XML, Functional, Manchester or Turtle. Over recent years, there has been an increasing need for representing ontologies visually to help ontological engineers or modelers represent elicited knowledge from domain expert, big data, model data structures or simply present data schemas and metadata to general users. We believe a visual representation is an essential way for understanding knowledge and to help elaborate formal ontologies for their communication and their use by humans. In this paper, we present the Graphical Ontology Web Language (G-OWL), a visual syntax for the graphical modeling and visualization of OWL 2 or RDFS ontologies. In line with previous research in cognitive science, G-OWL uses syntactic and semantic principles that simplify both its use and its interpretation. Indeed, the use of typology and polymorphism makes it possible to minimize the number of visual signs in a grammar, thus reducing the cognitive load on users, while preserving the formal character of the ontology. This G-OWL visual syntax is integrated in a software tool called OntoCASE4G-OWL to support the elaboration of ontologies and their translation to standard text-based syntaxes such as Turtle. This paper aims to present the definition of the G-OWL visual syntax and to demonstrate its highly readable character through an objective assessment of criteria such as: semiotic clarity, semantic transparency and graphic complexity. The G-OWL visual syntax will also be compared with other visual syntaxes and will be evaluated in order to measure its highly human-readability in reading activities, modeling or new knowledge deduction by novice, intermediate and expert in ontology modeling.
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Solicited Reviews:
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Review #1
By Peter Haase submitted on 05/Jan/2021
Major Revision
Review Comment:

The article presents G-OWL, which at its core provides a visual notation for the modelling and visualisation of OWL ontologies.
The visual notation applies syntactic and semantic principles grounded in cognitive science in order to minimise the number of visual signs and thus to reduce the cognitive load on users.
The visual notation will be implemented in a software tool, currently under development. An evaluation is performed in a comparison with other visual syntaxes.

Overall, the article is very well written and organised.
Sections 1 and 2 provides a very good overview of the motivation, history and foundations of the work, in particular the grounding in the MOF-based metamodelling approach.
Section 3 gives a comprehensive description of the GOWL visual notation itself. The notation is well thought through and the design choices are clearly explained.
Section 4 seems to be missing in the numbering.
Section 5 explains the visual modelling theory that guided the definition of G-OWL.
Section 6 provides a profound comparative analysis of the G-OWL notation with alternative visual syntaxes in Topbraid Composer.
Section 7 discusses related work and experimental findings.
Section 8 provides a conclusion.

However, there are a number of deficiencies that in my view require a major revision of the article. I will discuss them along these three lines:
- the metamodelling approach
- the maturity of the tool
- the evaluation against / comparison with state of the art

=== The metamodelling approach ===
The work is based on and explained in terms of 1) constructs of the ontology language (“ontological theory”), 2) constructs of the metamodel, and 3) constructs of the visual notation. (Cf. e.g. Fig. 21)
The need for (and usefulness of) the distinction between 1) and 2) is not clear to me, especially considering that the OWL 2 ontology language already provides its own meta model! as part of the standard. Specifically, the OWL 2 language is defined in terms of a MOF metamodel in the structural specification document (https://www.w3.org/TR/owl2-syntax/) Further background is described in:

Bernardo Cuenca Grau, Ian Horrocks, Boris Motik, Bijan Parsia, Peter F. Patel-Schneider, Ulrike Sattler:
 OWL 2: The next step for OWL. J. Web Semant. 6(4): 309-322 (2008)

Similarly, the Object Management Group (OMG) has specified an Ontology Definition Metamodel (ODM) for OWL 2 along with a UML Profile. (cf. https://www.omg.org/spec/ODM/1.1/PDF). While the ODM is referenced, the current reference is [20] is outdated by 6 years, also the a discussion of that standardized metamodel relative to the own metamodel (and why a new one needed to be created) is missing.

There are also predecessors of that work that lead into the definition of OWL 2 and the ODM of the OMG. Specifically, this work defined a metamodel for OWL including a visual notation via a UML profile:

Saartje Brockmans, Peter Haase, Pascal Hitzler, Rudi Studer:
 A Metamodel and UML Profile for Rule-Extended OWL DL Ontologies. ESWC 2006: 303-316

With a metamodel that directly specifies the ontology language, the rather complex mapping between 1), 2) and 3) as shown in figure 21 collapses to a simple correspondence between the constructs of the ontology language (as defined in the meta model) and the visual notation, as shown e.g. here:
Semantic clarity and completeness can thus be achieved much more directly, without a detour via “construct overload” followed by a “symbol redundancy” (in many cases).

That said, I believe the presented principles of Section 5 are an excellent instrument to guide and assess the definition of a visual notation.

=== Maturity of the tool ===
While the visual notation has been completely defined, the corresponding tool OntoCASE4G-OWL s still under development. No version of that software is currently accessible for review.
In fact, the only screenshot of the tool (pg. 13) looks more like a mockup than a screenshot from an actual system.
However, the usefulness and usability can only be evaluated within an actually implemented system.
The visual notation makes heavy use of nesting, containers and other advanced concepts, where it is not clear what the user interaction for creating and manipulating these constructs would look like. It’s one thing to create a mockup of a model, but an entirely different thing for an ontology developer to create such model with an actual tool.

=== Evaluation against the state-of-the-art ===
The state-of-the-art is not fully considered in the evaluation.
This starts with the abstract stating that ontologies are usually modelled using text-based syntaxes. While such expert users certainly exist, to the best of my knowledge, most ontology development is done using tools such as Protege, i.e. through UIs that do not require text-based authoring of ontologies.

While the comparison with TBC is very extensive, other visual notations and tools are covered insufficiently in Section 7.1.
The discussion mentions (in a footnote) another study of the authors under submission to the same journal. That submission indeed provides more detail, however, it is not yet published (accepted) and without that additional reference, the work is not really self-contained. The tools and their syntaxes are only briefly mentioned with high level summary statements and some small examples, but neither a detailed overview nor a comprehensive comparative study.

That leaves a very strange situation: Effectively, we have a detailed comparison of the G-OWL notation, which is not yet implemented, with a notation in a tool (TBC Standard Edition), which, according to the referenced website [18], is not further developed and supported anymore. In contrast, other tools that are used today for visual ontology modelling / visualisation, are not included in the detailed comparison and evaluation.

The laboratory findings in Section 7.2 are also rather shallow, the compiled results only provide very limited insights about the experiment and its results.
Section 7.3 effectively just states that the modelling/authoring software has not yet been evaluated, because the software is not finished yet.

Minor comments
pg. 1: Intrroduction-> Introduction
pg. 5: “At this level, there a two-representation possible.” -> “At this level, there a two representations possible.”
pg. 5: broken reference (“Erreur”)
Fig 8: Ressource -> Resource
pg. 9: “set of couples” -> “set of tuples”
pg 17: “The two TBC visualization syntax” -> “The two TBC visualization syntaxes”
check for consistent capitalisation, e.g. “owl:dataProperty” -> “owl:DataProperty”

Review #2
Anonymous submitted on 21/Jan/2021
Review Comment:

In this paper the authors propose G-OWL, which is a visual syntax for OWL ontologies. The authors address and interesting and relevant problem as. The effective visual modelling of ontologies is a longstanding challenge; indeed, it is an acknowledged problem relevant to all modelling endeavours where humans use models to communicate. The paper is written well and the description of G-OWL is thorough. The G-OWL visual syntax is furthermore integrated into the OntoCASE4G-OWL software. G-OWL was evaluated using Moody’s Physics of Notations Theory (PoNT) [1] as well as a laboratory experiment with 17 participants using the cognitive walkthrough method, and the results indicate that G-OWL is slightly preferred by participants.

Clarity and quality of writing

The clarity and quality of writing is adequate, however, there is a lack of relevant resources, which will be elaborated upon in the next sections. Furthermore, several claims are made for which no evidence is presented or citations provided, and revision of the paper is necessary.

Relevance and Originality

Ontology visualization is indeed a topic that is relevant to SWJ. The research is not totally original as the visualization of ontologies has always been a research topic since the specification of the original RDF and OWL standards by the W3C.

Technical Quality and Significance of Results

To publish research within a scientific journal such as SWJ, it should necessarily adhere to the necessary standards. In the first place any research should be positioned within the relevant body of scientific knowledge. In thus aspect the paper is lacking as there exist a large body of research on ontology visualization and visualization of conceptual models, (for instance [2–4]). The authors do not include any of these resources and existing research, and do not position their work within this domain. It is thus not possible to understand how G-OWL compares with similar approaches or whether it indeed resolves some of the identified challenges. Most of the work referred to in section 1.4. seem to be own previous research and not related work.

One of the well-known challenges is for instance that ontologies are generally large with many composite, often complex constructs, especially when one of the OWL 2 languages, such as OWL-DL, is adopted. Most visualization tools and visual representations acknowledge this challenge, and it is not clear whether G-OWL acknowledges this challenge at all. Furthermore, OWL 2 consists of a family of languages, not just OWL-DL, and most of these are based on RDF and RDFS, which specifies a meta-datamodel. The syntax and semantics of this family of languages differ, and none of this is acknowledged by the G-OWL research.

A further challenge with all modelling visualization is the communication. Indeed, the references by Moodly extensively used indicate specifically that communication is the primary concern of the visualization of models such as ontologies (although ontologies in essentially more than just a model, but a formalization of the knowledge within a domain). Human communication is not trivial, and is closely associated with effective visualization. To what level ambiguity is tolerated (or as referred to by the authors ‘polysemy’) depends on the purpose of models and hence the visualization. High level conceptual models where ambiguity can be tolerated need not be specified as formally as models where ambiguity cannot be tolerated, e.g. UML models that specify system requirements. The ambiguity of UML models and the huge cost it has due to incorrect and ineffective system implementations is a well-documented challenge. The Semantic Web stack acknowledges these differences, that is why the RDF linked web is not specified as formally as OWL-DL where several reasoners can be used to check for consistency. Just developing G-OWL as a graphical representation / syntax without acknowledging this context, including the purpose of the visualization and the associated necessary human communication constraints, does not make sense. With regards to ontologies, would it not make much more sense to start with the semantics of the language and ensure that the developed visualizations represent the semantics accurately and assist users with modelling correctly?

I would therefore strongly disagree with the claim that “The underlying hypothesis are that the use of polymorphism, typology, and polysemy, as well as the introduction of containers for central ontology- building operations, make it possible to reduce the number of symbols of the language while preserving the formal character and completeness of the language. “ This seem to be a complete over simplification of a vast body of research on the purpose and impact of visual modelling.

Whether visualizations are effective and fulfils its purpose, is also very subjective and would very much depend on individual users and their background. I personally would probably find the graphical syntax of G-OWL inadequate because of previous exposure to ontology visualization and the need to model OWL-DL constructs and semantics precisely because it has such an impact if it is not correct. A thorough developed evaluation experiment with several users would therefore add a lot of benefit.

The positioning of G-OWL within the MDA framework in Fig 1. and the subsequent discussion is confusing. From the discussion it seems that the figure depicts the development of the G-OWL constructs within the Eclipse Modeling Framework that is based on ER and UML, and not really G-OWL, because that would pose the question why ER is used on level M3 and not RDF? ER and UML have very different semantics than OWL, of which the open-world assumption is just one small example. Because of these differences in semantics the translation of OWL-based ontologies to UML or even ER and vice versa have been topics of extensive research.

The evaluation of G-OWL using the principles of PoNT is interesting, however, the evaluation seems to be quite subjective without convincing evidence. Given the casual adoption of OWL 2 and OWL-DL without reference to the semantics it is difficult to agree that there is for instance, evidence of G-OWL adhering to the principle of “Semiotic Clarity and Completeness” which means “a notation must have a one-to-one correspondence between each symbol and its referent concept.” I strongly disagree that there is sufficient evidence in the evaluation using PoNT to support the claims made in the conclusion about G-OWL.

More detail on whether the laboratory experiment facilitates communication, specifically with regards to the semantics of OWL, would be useful.

There is not convincing evidence for claims such as “In this paper, we presented the Graphical Web Ontology Language (G-OWL), a visual syntax that favors human readability and software modeling support for building semantic web ontologies.“

Given the current status of the paper and the requirements to position the research adequately I would recommend a reject of this version of the paper for SWJ. Repositioning the work by taking the fundamental principles of modelling, visualization of models, as well the Semantic Web, RDF, OWL and ontology visualization into account would require a rewrite and not just a revision. If the work is about visualization and visualization software without the semantics of OWL, then the SWJ is not the correct platform for publication.

Minor Revisions:
• Fix grammar: “We now presents the process…”
• Please add citations to the documents referred to in Table 1.

1. Moody, D., van Hillegersberg, J.: Evaluating the Visual Syntax of UML: An Analysis of the Cognitive Effectiveness of the UML Family of Diagrams. In: International Conference on Software Language Engineering. p. 18. Springer, Berlin, Heidelberg (2008).
2. Katifori, A., Halatsis, C.: Ontology Visualization Methods—A Survey. ACM Computing Surveys. 39, 43 (2007).
3. Lanzenberger, M., Sampson, J., Rester, M.: Visualization in Ontology Tools. In: 2009 International Conference on Complex, Intelligent and Software Intensive Systems. pp. 705–711. IEEE, Fukuoka, Japan (2009). https://doi.org/10.1109/CISIS.2009.178.
4. Dudá, M., Lohmann, S., Svátek, C.: Ontology visualization methods and tools: a survey of the state of the art. The Knowledge Engineering Review. 33, 1–39 (2018). https://doi.org/doi:10.1017/S0269888918000073.

Review #3
Anonymous submitted on 01/Feb/2021
Review Comment:

This paper represents a visual syntax, G-OWL, for representing ontologies. As the name suggests, G-OWL is closely aligned with OWL. The authors cover a lot of material in this paper: (a) presentation of the G-OWL syntax, (b) an evaluation compared to other notations using Moody’s physics of notations, and (c) a relatively small user study to evaluate G-OWL against other notations. The authors claim, for the most part, that these two evaluations establish that G-OWL is more human-readable that competing notations.

Overall, I have mixed feelings about this paper. On the positive side, it is great to see such a diverse coverage of material in the paper. It is very evident that a lot of work has gone in to the design of G-OWL, with particular consideration given to human aspects, reflecting the inaccessible nature of textual languages to non-computing end users. The multi-faceted approach to evaluation is also to be commended, here exhibited by exploiting Moody’s work and the user study. On the negative side, however, I find significant shortcomings in the research, or at least how it is presented, as I will explain in the coming paragraphs. These shortcomings, in my view, arise precisely due to the diverse nature of the paper’s content: so much has been included that none of it is covered to the depth I would expect to see in a scientific paper. This paper could be split into (at least) three journal papers, each covering one of (a), (b) and (c) above.

From this perspective, then, making a recommendation to the editor on a decision for this paper is not easy. I can see many merits in the work and the shortcomings would suggest a recommendation of major revisions. In turn, these revisions would make for a very long paper indeed, and perhaps far too much for one publication. Given this line of reasoning, I feel I can only recommend ‘reject’, which feels rather harsh given the potential for the paper to be transformed into a high quality piece of research. However, this recommendation would more readily give the authors the option of considering whether to sub-divide their research into a set of individually stronger papers, each with a more directed contribution.

So, focusing on the shortcomings, I will consider each of (a), (b) and (c) in turn. My most significant reservations lie with (a) and (b).

Regarding (a), this contribution is largely covered in the paper by sections 2 and 3 and my concern relates to two specific claims made by the authors in the introduction: that G-OWL has a _completely visual_ syntax, and its symbols have semantic correspondents in W3C recommended semantic web syntax. Here, I also include one quote, taken from page 18: “The G-OWL Model is a totally visual language …. It achieves a complete visual symbolization of OWL”.

Regarding the claim that G-OWL is completely visual, which is made in many places in the paper, I find this highly disputable. Aside from the rather philosophical question of what it means to be ‘visual’ or ‘completely visual’, how can G-OWL be considered ‘completely visual’ when it exploits textual annotations for _fundamental_ parts of its syntax? For instance, the standard textual notations for the union and intersection of classes are exploited within ‘containers’ to assert that the container represents the union, resp. intersection, of the contained classes. Other standard textual notations are used in a similar way. In addition, links are annotated with opaque textual abbreviations. These abbreviated annotations are paramount to understanding the semantic content provided by the link and the linked graphical components. Surely this points towards G-OWL being a hybrid notation, using the authors’ own definition of hybrid? Indeed, the authors make a very similar point about other languages to which they compare G-OWL: “In TBCGraph, … all the kinds of properties are covered by putting OWL 2 textual expression directly on the links, making the representation dual, only partially visual…” As a further quote (my highlighting) “Although G-OWL contains *some semantic aspects denoted by textual elements* on the figures representing its entities or relations, *there are no semantic aspects that are represented textually*.” I am left with the impression that these kinds of inconsistent arguments arise in various places in the paper, including places where a criticism applied to another notation could equally be applied to G-OWL, but it is not.

Further, given the goal that G-OWL sets out to improve ontology readability, including by non-computer scientists, why were standard textual symbols exploited? Why were (readable) naming conventions for arrow labels avoided and, instead, replaced by single letters that must be internalised and have their semantics recalled when needed? Why use textual annotations in the corners of the containers used for property types? It is particularly confusing, to me at least, why a dash is used as part of some labels: S for symmetric, -S for asymmetric, R for reflexive, -R for irreflexive. The dash appears more like a negation of the first property, which would clearly have the potential for misunderstanding (obv. asymmetric is not the property of being not symmetric etc). Overall, the design choices made for G-OWL need more careful explanation and justification, and claims about being ‘entirely visual’ either more clearly made or entirely removed.

Now, regarding the quote from page 18, nowhere in the paper is it actually _proved_ that G-OWL is a complete visualization of OWL. One approach to proving this result would be to establish that basic vocabulary of G-OWL and OWL align and, in addition, that the grammatical rules used to construct statements in each notation also align. Of course, this approach may not be appropriate. But, the point is that the authors have made an unsubstantiated claim about the expressivity of G-OWL. The paper should actually prove that this property holds, not just merely assert it. The extent to which this is a major addition to the paper will depend on the ease with which the result can be established.

I have some positive comments on the design, however. The use of containers to form groups of related concepts is a nice feature of the language. Visual ontology languages rarely use spatial relations between their graphical objects to convey semantics and are largely based on topological relations (being based on node-link diagrams). G-OWL is not unique, though, in its blending of topological and spatial relations in its grammar. One example is concept diagrams, which go much further than G-OWL in their use of spatial relations. Indeed, they avoid many of the textual annotations that G-OWL exploits, although not all of them. In this regard, it would have been interesting for the authors to discuss why they have not further reduced the textual annotations used by G-OWL. Based on how concept diagrams have been designed, specifically for modelling ontologies, there may be many ways to further reduce the textual elements of G-OWL via the use of more spatial syntax. It would be nice to see if this was possible.

Relatedly, the design could also be further explored and justified by appealing to the work of Shimojima, amongst others, on so-called free rides which has been more recently extended to the notion of an observational advantage. This idea is related to work by Peirce, who the authors already cite. Piece writes on the direct observation of truths from an object that arise from the object’s construction. Does the G-OWL notation give rise to many observable facts, beyond those that are intended to be encoded? This is a notable point, since the ability of diagrams, and visual notations generally, to convey information explicitly that would usually require deduction is widely seen as one of their important strengths: effective visualizations should, ideally, support observability. See Shimojima’s book [e], for more on this aspect of visual notation design and effectiveness.

I will now turn my attention to (b): the evaluation compared to other notations using Moody’s physics of notations. In one sense, this evaluation is very carefully structured, as it proceeds by considering nine principles in turn that are suggestive of an effective visual language. However, the execution of this analysis, which forms sections 5.3 and 6 of the paper is, in my view, lacking sufficient depth and objectivity to be scientifically robust. The evaluation needs to be deeply expanded, so that each of the nine principles is given its due attention. At present, the presentation is suggesting that the authors have cherry picked parts of notations to argue about whether a principle is met or not and, invariably, the ‘best’ notation is G-OWL. Now, it may well be the case that Moody’s framework can indeed be used to make such a deduction. However, to be convincing, the evaluation should consider the notations in their entirety, not just carefully selected examples to illustrate the possibility that a principle is either met or not. In my view, the current write-up has a biased feel: the impression is that the authors selected properties of the notations that are geared towards supporting the superiority of G-OWL. They can readily overcome this (likely false) impression by giving a much more in-depth, carefully structured analysis of each notation with respect to the principles. Indeed, I would encourage them to carefully articulate a method by which the notations were explored in the context of seeing whether they meet, or to what extent they meet the nine principles.

In addition to a more methodological approach to this evaluation, the authors should exercise more caution in what they can deduce from it. Whilst an entirely valid approach to evaluation, it is not possible to necessarily deduce that a notation that better meets the principles is guaranteed to be more effective. All that can be said is that, for example, notation A better meets the principles than notation B, which _suggests_ that notation A may be more effective for some tasks. However, a true judgement of whether a notation is more effective for certain tasks can never be fully established and the best evidence to support such a hypothesis is an empirical evaluation designed to test competing notations for specific tasks. A simple example of such a study can be seen in [a] below. In light of this, even accounting for the user study in the paper, I do not believe the authors can justify these two claims given in the introduction: “its semantic is easily interpretable by humans from the
visual representation;” and “compared to semantic web ontology language its syntax contains a limited number of visual symbols to be easily manageable for modeling and communication to human readers and designers”. Other claims on accessibility, readability or any kind of claims about the relative effectiveness of G-OWL compared to other notations should be examined by the authors and either justified or rephrased as conjecture or opinion.

Relatedly, but not a major concern regarding (b), I was surprised that Warren et al.’s research papers on the accessibility of description logics and, specifically, the Manchester OWL syntax were not referenced, not least because they highlight accessibility issues with traditional textual ontology languages. Notable omissions include [b,c,d], although I would encourage the authors to explore other publications by these authors as they may help to motivate or justify some claims made in the paper.

My last major concern is with regard to (c): the small user study to evaluate G-OWL against other notations. Here, I can be brief: any study should be reported on in sufficient detail to allow it to be reproduced by other scientists. The details given in this paper fall far short of this requirement. I appreciate that this was a small-scale study but, nonetheless, the authors are making some deductions about the relative effectiveness of the evaluated notations. The study design is missing, with only brief details provided. No indication is given about how the participants were recruited nor confirmation that they were independent from the authors. Did they know that the authors developed G-OWL? If they did, this is a threat to the validity of the study. In fact, the threats to validity are not discussed at all. The analysis of the collected responses is also weak, with deductions, even though tentative, based on comparing absolute average scores with no attempt to check for significant differences.

Moving on from (a), (b) and (c), it would also be useful if the authors clarified the intended use of G-OWL. At times, it felt like the goal was to (i) visualise OWL ontologies and at other times to (ii) visualise the domains being described by ontologies. These are clearly not the same goal. Specifically, the authors suggest that one goal was to help those less able to read computing-like languages to understand ontologies – is this in the sense of (i) or (ii)? There could be some tension between _effectively visualizing an owl ontology_ and _effectively visualizing the domain being modelled by the OWL ontology_. These different perspectives could be more clearly explored in the paper, particularly in the context of the design of G-OWL. Do these two different design goals lead to trade-offs in the design of G-OWL for example?

I could make many other comments, some significant and others more minor, on the content of the paper. However, my main concerns raised above are sufficient to justify the recommendation made. In any revised version of this paper, I encourage the authors to carefully check all of the claims they make and ensure that they are fully justified. Any claims based on opinion are mere conjecture and should be phrased as such.

I very much hope to see a resubmission of this paper, as I believe there is the kernel of some high quality research here but it needs a lot more space dedicated to its dissemination to reveal its depth and robustness.

[a] Alharbi et al. Visual logics help people: An evaluation of diagrammatic, textual and symbolic notations.
[b] Warren et al. Improving comprehension of Knowledge Representation languages: a case study with Description Logics.
[c] Warren, Ontology Users’ Survey report, available at http://kmi.open.ac.uk/people/member/paul-warren.
[d] Warren et al. The usability of Description Logics: Understanding the cognitive difficulties presented by Description Logics.
[e] Shimojima, Semantic Properties of Diagrams and their Cognitive Potentials.