3.3 Modelling, Simulation and Computational Resources
43
tions between “virtual graphs” and “concrete graphs”), etc., a conventional MODA
description can be obtained. Similarly, the usual human-readable MODA forms can
be obtained by reducing all OSMO aspects to an elementary numerical or textual
description.
3.4 Engineering Applications and Validation
The Materials Modelling Translation Ontology (MMTO) deals with the process of
“translating” a problem from engineering practice to modelling and simulation—
and from the simulation outcome back to an actionable decision [28]. The role of the
materials modelling translator is specified in detail by the EMMC Translators’ Guide
(ETG), cf. Hristova et al. [19]; accordingly, a translator needs to be able to bridge
the “language gap” between industrial end users and academic model providers
and software owners. The work of a translator aims at delivering not just modelling results, but a solution for an industrial engineering problem, understood more
holistically. In business administration and management, such problems are usually
addressed in terms of Key Performance Indicators (KPIs), where a KPI is understood
to be a descriptor (indicator) underlying process and product opimization, ultimately
characterizing some feature or property that can serve as a selling argument. The
underlying orientation towards marketing reflects a point of view corresponding to
organizational roles that are comparably distant from research and development.
In scenarios that arise in such a context, it necessarily appears to be most crucial to
address concerns that are immediately relevant to Business-to-Administration (B2A),
Business-to-Business (B2B) and Business-to-Customer (B2C) relations [30].
In the MMTO,
10 which predominantly targets communities of users in engineering
practice (rather than industrial business administration), the concept
mmto:key_performance_indicator is reserved for scalar quantities that are relevant
for characterizing, modelling or optimizing processes and products by CME/ICME
methods. On this basis, two major distinctions are to be made from the point of view
of a materials modelling translator [28]:
1. Some KPIs are closely related to human sentience (aesthetics, haptics, taste,
etc.). Studies aiming at gaining information on these quantities typically rely on
market research and other empirical methods that involve human subjects; such
indicators are referred to as subjective KPIs (mmto:subjective_kpi). Obversely, an
objective KPI (mmto:objective_kpi) can be determined by a standardized process,
e.g. a measurement, experiment or simulation, the result of which (assuming that
it is conducted correctly) does not depend on the person that carries it out.
2. An objective KPI is technological (mmto:technological_kpi) if it is observed or
measured within a technical or experimental process, referring directly to proper10 MMTO: https://purl.vimmp.eu/semantics/mmto/mmto.ttl (non-resolvable
IRI), mirrored at http://www.molmod.info/semantics/mmto.ttl (resolvable URL).
43
tions between “virtual graphs” and “concrete graphs”), etc., a conventional MODA
description can be obtained. Similarly, the usual human-readable MODA forms can
be obtained by reducing all OSMO aspects to an elementary numerical or textual
description.
3.4 Engineering Applications and Validation
The Materials Modelling Translation Ontology (MMTO) deals with the process of
“translating” a problem from engineering practice to modelling and simulation—
and from the simulation outcome back to an actionable decision [28]. The role of the
materials modelling translator is specified in detail by the EMMC Translators’ Guide
(ETG), cf. Hristova et al. [19]; accordingly, a translator needs to be able to bridge
the “language gap” between industrial end users and academic model providers
and software owners. The work of a translator aims at delivering not just modelling results, but a solution for an industrial engineering problem, understood more
holistically. In business administration and management, such problems are usually
addressed in terms of Key Performance Indicators (KPIs), where a KPI is understood
to be a descriptor (indicator) underlying process and product opimization, ultimately
characterizing some feature or property that can serve as a selling argument. The
underlying orientation towards marketing reflects a point of view corresponding to
organizational roles that are comparably distant from research and development.
In scenarios that arise in such a context, it necessarily appears to be most crucial to
address concerns that are immediately relevant to Business-to-Administration (B2A),
Business-to-Business (B2B) and Business-to-Customer (B2C) relations [30].
In the MMTO,
10 which predominantly targets communities of users in engineering
practice (rather than industrial business administration), the concept
mmto:key_performance_indicator is reserved for scalar quantities that are relevant
for characterizing, modelling or optimizing processes and products by CME/ICME
methods. On this basis, two major distinctions are to be made from the point of view
of a materials modelling translator [28]:
1. Some KPIs are closely related to human sentience (aesthetics, haptics, taste,
etc.). Studies aiming at gaining information on these quantities typically rely on
market research and other empirical methods that involve human subjects; such
indicators are referred to as subjective KPIs (mmto:subjective_kpi). Obversely, an
objective KPI (mmto:objective_kpi) can be determined by a standardized process,
e.g. a measurement, experiment or simulation, the result of which (assuming that
it is conducted correctly) does not depend on the person that carries it out.
2. An objective KPI is technological (mmto:technological_kpi) if it is observed or
measured within a technical or experimental process, referring directly to proper10 MMTO: https://purl.vimmp.eu/semantics/mmto/mmto.ttl (non-resolvable
IRI), mirrored at http://www.molmod.info/semantics/mmto.ttl (resolvable URL).