Ontology and semantic net based technology applied to smart corrosion protection modelling & simulation

Tracking #: 3057-4271

Peter Klein
Heinz Adolf Preisig
Martin Thomas Horsch
Natalia Alexandra Konchakova

Responsible editor: 
Guest Editors SW for Industrial Engineering 2022

Submission type: 
Full Paper
Ontology-based integrated materials modelling for an active protective coating system design is presented and applied to a practical example. For this purpose, an ontological methodology implemented using the Process Modelling suite (ProMo) is developed to be used with an open simulation platform (OSP), \ie, a workflow management and orchestration framework that can be integrated into digital infrastructures. The target infrastructures, which are under development in various Horizon 2020 projects include modelling marketplaces, open innovation platforms, and open translation environments, among others. Semantic interoperability for the communication between the involved digital infrastructures relies on ontologies that are aligned with Elementary Multiperspective Material Ontology (EMMO) at the top level; in particular, the Ontology for Simulation, Modelling, and Optimization (OSMO) is employed as an ontologization of the Modelling Data metadata schema (MODA) in combination with the Physicalistic Interpretation of Modelling and Simulation Interoperability Infrastructure (PIMS-II) mid-level ontology. The challenge of addressing semantic heterogeneity is addressed by working toward crosswalks between domain-specific and mid-level ontologies for industrially relevant problems, where knowledge graph transformation is evaluated as a candidate solution for a future implementation strategy. The involved semantic artefacts are platform-agnostic, and their EMMO compliance allows for a specification of executable modelling and simulation workflows on multiple EMMO-compliant OSPs. We demonstrate the presented approach on an industrially relevant example for developing active corrosion protection of metallic surfaces.
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Major Revision

Solicited Reviews:
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Review #1
By Toshihiro Ashino submitted on 13/Apr/2022
Minor Revision
Review Comment:

The paper presents a physical model for smart coatings for corrosion protection. using MODA and EMMO, two different upper ontologies for modeling materials, they makes different descriptions. Authors also describes the correspondence, they call "crosswalk", between these two different descriptions. These attempts may be useful for sharing and interoperability of workflows for materials development on digital research platforms.

However, it only illustrates the concept with figures and does not include samples described in OWL, RDF, etc., and it describes semi-automatic conversion of relationships between ontologies, but lacks description of their implementations. Providing supplemental files on these is preferable.

In terms of readability, there is no explanation of the symbols related to LDT (logical data transfer) described in Fig. 7, such as the notation r_{run}. [20] shows a description of such as "writes finally (w_{fin})", but not all of this kind of notation is explained.

Is accoring in p.6, line 44 a typo in "according"?

Review #2
Anonymous submitted on 09/May/2022
Major Revision
Review Comment:

(0) General Comments

Interesting work, but needs clarity. Lots of background and information is thrown at the reader and it isn't logically connected. The contributions seem to be uncorrelated and it isn't too clear what benefit they provide since there is a lack of a single purpose to the paper. The submission reads like a review paper, but I don't think that was the intent of the work.

(1) Originality

Not quite clear what the contribution of the authors is. At first, it seems that they intend to model a physical system. Here, it is unclear whether they are developing a new semantic network or just demonstrating how to use existing ones. Then, it seems the authors are suggesting new frameworks: one for integrating MODA and ProMO and one for performing KGTS. Here, it becomes rather unclear whether these frameworks were applied to the case study of coatings because the wording suggests that everything developed was only a potential or possible ontology or semantic net.

More specifically, the authors go in great detail about both the coating process and the simulation process. However, it is unclear how the suggested ontology and semantic nets are connected or applied to either. The authors demonstrate how OSMO can be used to represent the simulations, but is that their contribution? How does their work provide additional benefits? And if the authors do not intend to model the physics of the coating in an ontology, why go into great detail discussing the physics of the coating process?

Overall, I think the paper would benefit from the authors clearly listing how each of their contributions are related and clearly stating one unifying benefit of their work.

(2) Significance of the results

It seems models 1-4 described on pages 4&5 are physics based models not ontological models. Make it explicit.

Explicitly state the connection between the physical process and the modeling. Ex. Page 9, line 2, logical resources are what in the physical process or simulation?

Not quite clear what tasks were actually undertaken. For example, in section 2.3 the coating model is presented as a possible physical topology. What are the other options and what is the benefit of this proposed possible topology? Also, in section 4, the authors say that an SDO might reannotate the KGTS. Figure 11 also states that the figure only represents a potential application. Are these sections only describing the development of frameworks? How were these frameworks applied to the case studies? If there are multiple possible modeling approaches how were the presented models chosen?

(3) Quality of the writing

Figure 1 - not quite sure what the octahedrons represent. Are the coatings layered materials of one unit cell thickness? Where is the substrate? Is one set of octahedrons the coating and the other the material? Not sure where the crack is in this figure.

Figure 8 - need more background on cognitive process / Peircean semiotics modeling. Unclear what the symbols used in the figure represent. R, d_m, s'_m, etc.

(A) Data is organized with README


(B) Data is complete and enables replication

Cannot determine.

(C) Appropriate repository for long-term discoverability

(D) Provided artifacts are complete

Cannot determine.

Review #3
Anonymous submitted on 15/Jun/2022
Review Comment:

The manuscript submitted by Klein et al. describes the application of semantic technologies to support the translation of industrially-relevant problems into modelling workflows in the context of corrosion protection of metallic surfaces. The work is original, well presented, and of great relevance in the field of semantic technologies for modelling and simulation integrated workflows. The authors may wish to consider some changes to improve the impact of their work:
1. The description of the use case (sec. 2.1) contains several technical terms and concepts, which can be hard to understand for readers that are unfamiliar with corrosion protection. A simple explanation of main concepts and processes could help.
2. Similarly, sec. 2.5 refers to several concepts that can be hard to understand for readers that are less familiar with mereotopology and Peircean semiotics.
3. Some figures should probably be reviewed. For example, Fig. 4 looks like a collage of screenshots, as some words are highlighted by the spell checker. Several symbols/lettering introduced in some of the figures (for example, Fig. 7) are not explained. The caption of some figures can be made some clear, for example Fig. 7.
4. In section 2.3, a comparison with other methodologies that can be used to represent workflows could be added.