Owl Monkey: Auto-Adaptive Application Builder for the Semantic Web of Things

Tracking #: 2185-3398

Louis Bherer
Luc Vouligny
Arnaud Zinflou
Christian Desrosiers

Responsible editor: 
Guest Editors SemWeb of Things for Industry 4.0 - 2019

Submission type: 
Full Paper
Owl Monkey (OM) is an OWL auto-adaptive web application builder developed at Hydro-Québec. OM users are able to explore and build views on an OWL ontology and share those views without any prior knowledge of the technologies involved. Users can then do analytics over those views, use them to modify database content or export them. OM is highly generic and suitable for use with most OWL ontologies. Applications built with OM auto-adapt to modifications of the ontology and require no subsequent reprogramming. The overall effect is lower costs for application development and maintenance. Because of the genericity and auto-adaptability of this tool, this approach is a prime candidate for development of Industry 4.0 applications drawing on the Semantic Web of Things.
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Solicited Reviews:
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Review #1
By Prem Jayaraman submitted on 03/Jun/2019
Review Comment:

The paper presents Owl Monkey, an visual ontology tool that allows composition of sharing of views by users with little or no knowledge of the technology. The topic is very interesting and is an important area given the amount of data that Industry 4.0 will generate and the veracity and limited semantic annotation of such data. However, the paper has several weakness that need to be addressed before it can be considered for publication.

• The paper is generally very poorly written. It is verbose and very hard to follow/understand
• The contribution and the novelty of the paper is not clear.
• Is OM a contribution of this paper of a use-case at Hydro-Quebec developed using OM is the contribution? This is not clear.
• The related work fails to motivate and highlight the gaps in the literature
• The relation to Industry 4.0 and the proposed work is not clear
• Most importantly, the paper lacks any evaluation and/or a methodology to evaluate such a solution
• Given usability is a key outcomes of the solution, a solid user study with participants from Hydro-Quebec could potentially be a good validation strategy

Review #2
By Armin Haller submitted on 17/Jun/2019
Review Comment:

The article describes Owl Monkey (OM), an application that supports naive ontology users to build views on an ontology. The application has been built for an industrial use cases in Hydro Quebec. The application is also positioned to be particularly useful in the context of an IoT application. Although the proposed application addresses an important problem, namely the support of domain experts who are naive ontology engineers, in creating queries on an ontology model, the paper in its current form is lacking in detail, scientific rigour and lacks an evaluation. In the following I detail on these issues:

- Lack of formal definitions: The paper lacks completely any formal definitions of terms and operations that are performed by the application on the TBox and ABox model. The authors mention that through "lazy class loading" (unclear what that means), the same set of generic queries can be used for ad hoc addition of a class to the solution set. What is the solution set and how can classes be added? From this statement it appears as if the tool allows for the creation of classes, instances and queries, but again, it is unclear what the user actually generates? To give some examples on how definitions are missing, the tool apparently distinguishes "subject classes" and "non-subject classes", but it is unclear what that means, formally. Then the authors mention that the "forms are built dynamically based on the visible columns of the grid and the column order" and "the nature of the required fields is determined by the ranges of the properties represented by these columns." What are the visible columns and how are they generated? It continues with a lack of definitions for "term patterns", "semantic grid", "view class", "column groups" etc. Consequently, it is totally unclear if the tool actually allows to build queries, classes and properties or even to create individuals, i.e. there is no clear distinction between the TBox and ABox in the query building, and what variables are created in these queries. The latter is also a consequence of not defining in the paper, what the user actually creates through the GUI. The authors claim that the proposed application is a Visual Query System (VQS), but what is created by the tool, SPARQL queries or maybe even SPARQL templates (SHACL or SheX)? Restrictions on properties seem to also only take domain range restrictions into account, but not single range existential restrictions (guarded class restrictions). Another example of a lack of detail is the statement that "it was necessary to develop contrivances to avoid redoing the inference whenever data was modified. This has allowed the use of forward chaining for all use cases encountered to date."

- Lack of positioning of the application in regards to state-of-the-art. Considerable space in the Literature Review is given to the introduction of standard concepts such as SPARQL, RDF, OWL, triple stores etc., but state of the art in the three areas the authors identified as methods directly related to the proposed application, visual query systems, form representations and facet representations is not discussed. A large body of work is available in the areas of form-based ontology editing (e.g. https://scholar.google.com.au/scholar?hl=en&as_sdt=0%2C5&q=form-based+rd...) and visual query systems (e.g. https://scholar.google.com.au/scholar?hl=en&as_sdt=0%2C5&q=visual+query+...). Only later in the paper, some tools that the authors consider related work are mentioned, [21, 22, 24, 25], but not critically discussed.

- Lack of Evaluation or Use Case Evidence: The paper has been submitted as a Full Paper and therefore the lack of an evaluation is by itself an exclusion criteria for publication. The paper does mention that the tool was built for Hydro-Québec, but it fails to report on results of its usage. It appears as if the tool has not been fully rolled out yet, and no evidence can be provided at this stage, that the tool indeed eases the burden of building ontology models. This evidence of how the application would benefit naive users in comparison to the state of the art ontology editors such as WebProtege is crucial for a publication of this type. A submission as an Application Report, that has less strict requirements on an evaluation, would allow the authors to detail on the impact of the described application in a use case, rather than a comprehensive evaluation.

In light of the aforementioned issues, and the fact that the journal operates under a strict two-strike-rule, I recommend a reject and encourage the authors to resubmit the work as an application report once they can report on some evidence from the use case on how the application has helped engineers in Hydro-Québec to build ontology views.

Review #3
Anonymous submitted on 05/Aug/2019
Major Revision
Review Comment:

Summary: The paper describes OWL Monkey (OM), which is an auto-adaptive web application builder based on OWL ontologies. The primary contribution of the work is that OM allows users with little to no knowledge of semantic web technologies browse and explore ontologies as well as share ontology views with other users thereby improving the prototyping process in application development. OM enables this through visualisation interface, which allows graphical or form-based navigation and browsing of ontologies. The work is timely and much-needed given the increasing application and use of ontologies for understanding and analysing complex and heterogeneous data. Although ontologies have been proven valuable to analyse such data, their adoption and use are heavily dependent on the expertise of the users. Therefore, the work presented in this paper is clearly important and relavant to the Semantic Web Journal.

Originality: While the problem of ontology visualisation is not new and visualisation is the core feature of OM, the originality and novelty of the work is reflected in the auto-adaptive feature of OM. In the literature review section, the authors have presented related research and commercial work. They have identified where OM fits in the big picture and where its contributions lie. However, the reader is left to anlayse how OM differs from or adds on to the existing work already done. Therefore, I would suggest the authors to clearly outline how and where OM adds to the existing work or fills a research gap. Also, the section on commercial solutions needs to be expanded with the inclusion of Ontotext (https://www.ontotext.com/), which also provides a comprehensive set of tools for building semantic web applications and using semantic web technologies. Furthermore, Ontotext's GraphDB also provides a graphical interface for visual query building.

Significance of the results: The paper comprehensively describes OM but the results are distributed through the paper. This requires the reader to come up with a mental picture on how the presented outcomes (such as genericity, usability of OM etc.) demonstrate the contributions of the paper as outlined in Section 1 (Introduction). The paper contains no evaluation of the time taken to build complex queries as well as building queries that require significant inferencing. While the use case of Hydro-Quebec is discussed in section 4, no actual results on the time taken to build those applications have been presented. This, therefore, challenges the authors' claim of the usability of OM in evolutive prototyping as well as minimiing the effort required during rollout and maintenance. A strong point of the paper is that the authors have mentioned the current limitations of OM along with potential solutions or an indication of the direction of future research to address those limitations.

Quality of writing: The paper is well-written with a good flow and is easy to follow. The text in figure 1 is quite small and difficult to read onscreen even after zooming. A better quality figure or one with higher magnification would be better. The relationships text is not visible in its entirety in figure 2.

In conclusion, the work is definitely relevant and would be interesting to the readers. However, a section on the results is essential to better understand and confirm the contributions that are claimed by the authors.