=Paper=
{{Paper
|id=Vol-2969/paper47-FoisShowCase
|storemode=property
|title=OSMO: Ontology for Simulation, Modelling, and Optimization
|pdfUrl=https://ceur-ws.org/Vol-2969/paper47-FoisShowCase.pdf
|volume=Vol-2969
|authors=Martin Thomas Horsch,Daniele Toti,Silvia Chiacchiera,Michael Seaton,Gerhard Goldbeck,Ilian Todorov
|dblpUrl=https://dblp.org/rec/conf/jowo/HorschTCSGT21
}}
==OSMO: Ontology for Simulation, Modelling, and Optimization==
https://ceur-ws.org/Vol-2969/paper47-FoisShowCase.pdf
OSMO: Ontology for Simulation, Modelling, and
Optimization
Martin T. Horsch1,2,3 , Daniele Toti4 , Silvia Chiacchiera2 , Michael A. Seaton2 ,
Gerhard Goldbeck5 and Iilian T. Todorov2
1
High Performance Computing Center Stuttgart, Nobelstr. 19, 70569 Stuttgart, Germany
2
UK Research and Innovation, STFC Daresbury Laboratory, Keckwick Ln, Daresbury WA4 4AD, UK
3
University of Central Lancashire, School of Psychology and Computer Science, Preston PR1 2HE, UK
4
Catholic University of the Sacred Heart, via della Garzetta 48, 25133, Brescia, Italy
5
Goldbeck Consulting Ltd., St. John’s Innovation Centre, Cowley Rd, Cambridge CB4 0WS, UK
Abstract
This work describes the ontology OSMO, i.e., an ontologization and extension of MODA, a workflow
metadata standard that constitutes a mandatory requirement within a number of European calls and
projects in the context of materials modelling. OSMO was developed within the Horizon 2020 project
VIMMP (Virtual Materials Marketplace) and is part of a larger effort in ontology engineering driven by
the European Materials Modelling Council, with the Elementary Multiperspective Material Ontology
(EMMO) as its core. As such, OSMO provides connections and alignments with other related domain
ontologies in computational engineering, including the EMMO itself. This work summarizes the domain,
purpose, and design choices underlying OSMO, commenting on the implementation of OSMO and its
applications.
Keywords
applied ontology, simulation workflows, research data provenance, process data technology, MODA
(Model Data), OSMO, Elementary Multiperspective Material Ontology (EMMO)
1. Introduction
The Ontology for Simulation, Modelling, and Optimization (OSMO) is a metadata standard for
modelling and simulation workflows in computational engineering [1]. Comparable semantic
artefacts from related lines of development include EngMeta [2, 3], MODA [4] (see below),
and PIMS-II [5, 6]; research data provenance in general, not tailored to materials modelling,
is addressed by widespread ontologies such as PROV-O [7] and the BPMN 2.0 ontology [8].
OSMO is part of the system of marketplace-level domain ontologies developed by the Virtual
Materials Marketplace (VIMMP) project for use in the logical layer of the digital marketplace
platform [3, 9], supporting interoperability between internal components and with external
FOIS 2021 Ontology Showcase, held at FOIS 2021 - 12th International Conference on Formal Ontology in Information
Systems, September 13-17, 2021, Bolzano, Italy
" martin.horsch@stfc.ac.uk (M. T. Horsch); daniele.toti@unicatt.it (D. Toti)
0000-0002-9464-6739 (M. T. Horsch); 0000-0002-9668-6961 (D. Toti); 0000-0003-0422-7870 (S. Chiacchiera);
0000-0002-4708-573X (M. A. Seaton); 0000-0002-4181-2852 (G. Goldbeck); 0000-0001-7275-1784 (I. T. Todorov)
© 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
Workshop
Proceedings
http://ceur-ws.org
ISSN 1613-0073
CEUR Workshop Proceedings (CEUR-WS.org)
digital platforms. The platform interoperability aspects rely on the line of work toward domain-
ontology development advanced by the European Materials Modelling Council (EMMC ASBL),
and accordingly, the Elementary Multiperspective Material Ontology (EMMO) is employed as
a foundational ontology to facilitate crosswalks [3, 10, 11, 12]. OSMO comprises a complete
ontologization of MODA (“Model Data”), a pre-existing metadata standard based on tables with
plain-text content intended for human-to-human communication, cf. CEN workshop agreement
17284:2018 [4]. MODA is a template for the standardized description of materials models; it is
endorsed by EMMC ASBL along with the EMMO, and the uptake of MODA has been mandatory
in a series of calls from Horizon 2020 and continues to be an explicit requirement in the
Horizon Europe work programme [13, pp. 173, 177]. Accordingly, a substantial corpus of MODA
workflow descriptions has been compiled from Horizon projects; a representative selection of
such workflows is included in an Annex of the Review of Materials Modelling (RoMM) [14] with
OSMO as the ontology version of MODA, these human-readable metadata become machine-
processable and can be integrated into ontology-based semantic technology frameworks.
2. Ontology Design
The original purpose of RoMM [14] and MODA [4] was to guide users toward a complete
high-level documentation of materials models, starting from use cases and including all relevant
computational details. In this regard, it was meant to provide all necessary aspects for describing,
reproducing, curating, and interfacing with other models, guiding modellers step-by-step
throughout their modelling workflows. However, the semantic expressivity of the graph notation
from MODA is rather limited, making workflow descriptions too ambiguous for common
applications (e.g., technical-level reproducibility). The connections between steps, or sections,
of a workflow lack clearly characterized semantics altogether; connections are uniformly shown
as blue arrows in the MODA graph notation, by which different ways of coupling, linking,
user interaction, and data transfer cannot be distinguised. Moreover, it does not immediately
facilitate an integration of resources distributed over the semantic web: Descriptors in MODA
are essentially plain-text labels; they do not canonically contain any resolvable or non-resolvable
identifiers for RDF semantic-web resources or FAIR digital objects. To integrate MODA metadata
into knowledge bases that rely on ontology-driven semantic technology, it was necessary
to develop an ontology version of MODA; specifically, this requirement from the VIMMP
project (and, similarly, the MarketPlace project with which VIMMP aims at complete platform
interoperability1 ) motivated the development of OSMO. Therefore, the main motivations behind
the design of OSMO were, on the one hand, to make MODA-based annotations machine-
processable and, on the other hand, to address the limitations of MODA mentioned above. These
objectives were attained by constructing a domain ontology and providing an alignment and
interconnection with other related ontologies, including the EMMO, creating crosswalks to a
variety of domain ontologies from other projects [11, 12]. Accordingly, OSMO integrates the
representation of application cases (including MODA use cases), solvers, models, and processors
from MODA; these are enriched with additional semantic information given by the structuring
1
Virtual Materials Marketplace (VIMMP): H2020 grant agreement no. 760907, https://vimmp.eu/; MarketPlace:
H2020 grant agreement no. 760173, https://the-marketplace-project.eu/.
Figure 1: Fragment of the taxonomy for the workflow resource branch of OSMO; arrows indicate
subsumption, i.e., rdfs:subClassOf.
of these elements into a class hierarchy, as well as by including elements for logical data transfer
and explicit dependencies among the workflow sections [1], cf. Fig. 1.
3. Datasets and Applications
As a metadata standard for modelling and simulation workflows, application scenarios for
OSMO fall into two categories: First, it can be used to specify workflows or parts of a workflow
in advance at multiple stages, e.g., to support project planning (Horizon proposals often contain
MODA workflows) and simulation deployment by open simulation platforms (OSPs) [1, 6];
specifically, the description can restrict itself to the application case (e.g., a translation case [15,
16] or a MODA use case [4]), by which a problem description can be submitted to a materials
modelling marketplace where it can be addressed by “translators,” i.e., experts in academia-
to-business knowledge transfer [9, 15, 16]. Second, simulation results can be annotated with
OSMO metadata to characterize their provenance, which is crucial to making research data
FAIR by facilitating their reproducibility and providing epistemic grounding to substantiate the
extent to which the results can be trusted [5, 17]; this aspect of using MODA and OSMO is most
relevant to research data infrastructures where discipline-specific data with a heterogeneous
provenance (e.g., grounded in data-driven, model-driven and experimental scientific practices)
need to be integrated while keeping track of their epistemic status [18, 19].
Accordingly, OSMO is mainly used to provide metadata on plans or requirements, on the one
hand (for workflows to be carried out in the future, or alternatively for purposes or reporting,
in hindsight), and metadata meant to support workflow orchestraction or to document the
provenance of simulation results at a more technical level, on the other hand. In the first case,
the annotation is naturally comparably abstract, since it aims at supporting project management
or matchmaking during translation where it is necessary to communicate information in a more
aggregated way. It is here that the MODA templates work best; RoMM [14, pp. 79–374] includes
a series of examples from 36 projects. The ontologization provided by OSMO, including the
additional features mentioned above, supports technical-level documentation, facilitating the
exchange of workflow metadata with components such as OSPs [1, 20]. To develop platform
interoperability for the molecular model database (MolMod DB) of the Boltzmann-Zuse Society
for Computational Molecular Engineering (BZS), cf. Stephan et al. [21], OSMO was used to
specify rigid intermolecular pair potentials for low-molecular fluids [22]. Industrially relevant
application cases from VIMMP include multi-phase flow simulation with OpenFOAM [23, 24]
and molecular dynamics simulation of wetting and adhesion [25].
4. External Ontologies and Crosswalks
The VIMMP system of ontologies is connected to about 20 external semantic artefacts [3, 9].
These links are not specific to OSMO itself which is mainly connected to the other VIMMP
marketplace-level domain ontologies directly; the relation between OSMO and the Materials
Modelling Translation Ontology (MMTO), which is particularly close, is discussed in previous
work [15]. The projects associated with EMMC ASBL, including VIMMP, jointly mainly rely on
the EMMO [10] for semantic interoperability between platforms and to align their respective
domain ontologies [11, 12]. However, MODA and the EMMO are not very closely related
in their foundational approach and require a major effort to obtain a viable alignment; the
main challenge in situating OSMO in relation to other semantic artefacts therefore consisted
in facilitating crosswalks from MODA to the EMMO. Two crosswalk strategies have been
developed for this purpose. It depends on the circumstances and requirements what connection
is more suitable for a concrete task; however, they can also be applied jointly, complementing
each other.
First, mediated by the PIMS-II mid-level ontology for cognitive processes [5, 6], sections
are mapped to steps of a cognitive action and described using sign-object-interpretant triads,
following the approach to semiotics introduced by Peirce, a formalism that is also employed by
the EMMO [10, 26]. This alignment scheme, discussed in detail elsewhere [6], preserves the
structure of a MODA/OSMO workflow; fine-grained information content may be lost, since
PIMS-II is comparably close to the EMMO itself and operates at a substantially higher degree
of abstraction than MODA/OSMO. The second crosswalk employs multiple elements for in-
termediate transformation steps, including VIPRS (VIMMP primitives), the mid-level ontology
module of the VIMMP semantic interoperability architecture [3], the European Virtual Mar-
ketplace Ontology (EVMPO), which reflects agreements between the VIMMP and MarketPlace
project consortia at an early stage of development, and the EMMO-VIMMP Integration (EVI)
module. Therein, OSMO concepts are mapped to EMMO concepts by means of EVMPO and
EVI, whereas OSMO relations are mapped to mereosemiotic chain relations [3, 5], transforming
the structure of the knowledge graph; for an example, cf. previous work [22]. This connection
makes less use of foundational elements of the EMMO; however, it retains greater taxonomical
detail, and the detailed content of the MODA tables is better preserved if this route is fol-
lowed. As a major mechanism of the second crosswalk, OSMO concepts including logical term,
section, section aspect, and workflow resource are mapped to the EMMO concept Symbolic,
and where one entity can be shown to act as a representamen for another, it is mapped to a
Sign, and hasSign from the EMMO is employed for the representation relation; in this way,
a simulation overview (the OSMO rendering of the MODA cover sheet) is understood to act
as a representamen for a simulation. All relations from OSMO are subsumed under EMMO
relations (or chains of EMMO relations), and all concepts from OSMO are subsumed under
EMMO concepts.
5. Technical Details and Availability
OSMO is specified using the RDF, RDFS and OWL formalisms,2 and it has been deployed
and tested on a Stardog3 triplestore. Supporting tools for development and testing have been
developed in Java version 1.8+. The OWL axiomatization of the ontology in TTL format is
available at http://www.molmod.info/semantics/osmo.ttl.
Acknowledgments
This work was funded from the European Union’s Horizon 2020 research and innovation
programme through grant agreement no. 760907, Virtual Materials Marketplace; it was facilitated
by activities of the Innovation Centre for Process Data Technology (Inprodat e.V.). The co-author
M.T.H. also acknowledges funding from DFG project no. 441926934, NFDI4Cat, within the NFDI
programme of the German Joint Science Conference (GWK).
References
[1] M. T. Horsch, et al., J. Chem. Eng. Data 65 (2020) 1313–1329. doi:10.1021/ acs.jced.9b00739.
[2] B. Schembera, D. Iglezakis, Int. J. Metadata Semant. Ontol. 14 (2020) 26–38. doi:
10.1504/IJMSO.2020.107792.
[3] M. T. Horsch, S. Chiacchiera, W. L. Cavalcanti, B. Schembera, Data Technology in Materials
Modelling, Springer, 2021.
[4] CEN-CENELEC Management Centre, workshop agreement 17284:2018, CEN, 2018.
[5] M. T. Horsch, in: Proc. JOWO 2021 (FOUST 2021), to appear, CEUR-WS, 2021. Preprint
doi:10.5281/zenodo.4849611.
[6] P. Klein, H. A. Preisig, M. T. Horsch, N. Konchakova, in: Proc. JOWO 2021 (FOMI 2021), to
appear, CEUR-WS, 2021.
[7] L. Moreau, P. Groth, J. Cheney, T. Lebo, S. Moles, J. Web Semant. 35 (2015) 235–257.
doi:10.1016/j.websem.2015.04.001.
[8] M. Rospocher, C. Ghidini, L. Serafini, in: P. Garbacz, O. Kutz (Eds.), Proc. FOIS 2014, IOS,
2014, pp. 133–146.
2
Resource Description Framework (RDF): http://www.w3.org/RDF/; RDF Schema (RDFS): http://www.w3.org/
TR/rdf-schema/; Web Ontology Language (OWL): https://www.w3.org/OWL/.
3
Stardog Enterprise Knowledge Graph: https://www.stardog.com/platform/.
[9] M. T. Horsch, et al., Künstl. Intell. 34 (2020) 423–428. doi:10.1007/s13218-020-00648-9.
[10] EMMC ASBL, Elementary multiperspective material ontology (emmo), 2021. URL: https:
//github.com/emmo-repo/EMMO.
[11] J. Francisco Morgado, E. Ghedini, G. Goldbeck, A. Hashibon, G. J. Schmitz, J. Friis, A. de
Baas, in: Proc. SeDiT 2020, CEUR-WS, 2020.
[12] D. Höche, N. Konchakova, M. Zheludkevich, T. Hagelien, J. Friis, in: Proc. WCCM-
ECCOMAS 2020, Scipedia, 2021. doi:10.23967/wccm-eccomas.2020.263.
[13] European Commission, Horizon Europe work programme. 7. Digital, industry, and space,
decision C(2021)4200, EC, 2021.
[14] A. F. de Baas (Ed.), What Makes a Material Function? Let Me Compute the Ways, EU
Publications Office, Luxembourg, 2017.
[15] M. T. Horsch, S. Chiacchiera, M. A. Seaton, I. T. Todorov, B. Schembera, P. Klein, N. A.
Konchakova, in: Proc. DAMDID 2020, Springer, 2021. doi:10.1007/978-3-030-81200-3 4.
[16] M. Pezzotta, J. Friis, G. J. Schmitz, N. Konchakova, D. Höche, D. Hristova-Bogaerds, P. Asi-
nari, L. Bergamasco, G. Goldbeck, Report on translation case studies describing the gained
experience, Technical report, EMMC, 2021. doi:10.5281/zenodo.4457849.
[17] M. Williams, Philos. Phenomenol. Res. 60 (2000) 607–612. Doi:10.2307/2653818.
[18] S. Herres-Pawlis, O. Koepler, C. Steinbeck, Angew. Chem. Int. Ed. 58 (2019) 10766–10768.
doi:10.1002/anie.201907260.
[19] C. Wulf, et al., ChemCatChem 13 (2021) 3223–3236. doi:10.1002/cctc.202001974.
[20] S. P. Huber, et al., Sci. Data 7 (2020) 300. doi:10.1038/s41597-020-00638-4.
[21] S. Stephan, M. T. Horsch, J. Vrabec, H. Hasse, Mol. Sim. 45 (2019) 806–814. doi:
10.1080/08927022.2019.1601191.
[22] M. T. Horsch, et al., in: Proc. ISWC 2020 Demos and Industry Tracks, CEUR-WS, 2020, pp.
134–137.
[23] A. Marcato, G. Boccardo, D. Marchisio, Chem. Eng. J. 417 (2021) 128936. doi:10.
1016/j.cej.2021.128936.
[24] G. Tronci, A. Buffo, M. Vanni, D. Marchisio, Comp. Fluids 227 (2021) 105026. doi:
10.1016/j.compfluid.2021.105026.
[25] M. Chiricotto, G. Giunta, H. A. Karimi-Varzaneh, P. Carbone, Soft Mater. 18 (2020) 140–149.
doi:10.1080/1539445X.2019.1701497.
[26] M. T. Horsch, S. Chiacchiera, B. Schembera, M. A. Seaton, I. T. Todorov, in: Proc. WCCM-
ECCOMAS 2020, Scipedia, 2021. doi:10.23967/wccm-eccomas.2020.297.