2.1 Engineering Metadata
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keys, according to [5]. Its task is to describe the research objects or parts of it and its
relation to other objects. They are still interpretations; however, they are constructed
in a transparent and comprehensible way and derived from a common understanding
of the research object, and lead to a fixed negotiation. The approach described in this
chapter could also be called an ontology-based metadata, since the metadata model
is engineered from an object model. As depicted in Fig. 1.1, hierarchical models
such as EngMeta range below an ontology; however, their task is also to balance
the depth of domain knowledge representation and the depth of digitization. The
question in what terms a metadata model is different from an ontology has already
been discussed in Sect. 1.2.
2.1.1.2 Object Model
The object model is the starting point for engineering a metadata model and marks
the first phase in the creation process [5]. In this phase, an object model, respectively,
an ontology description is carved out in a non-formal or natural language (and maybe
containing graphical elements) describing and explicating all the relevant objects,
terms, relations and rules. Every person potentially involved has to contribute to this
process, since the metadata model will act as a semantic convention for a common
understanding of the research data described.
The first part of engineering an object model is a clear and fixed understanding
of what the object of research is, and what data it is representing. This can only be
conducted by the analysis of the research process with all the stakeholders included.
In this step, following information must be gathered:
• Entities All relevant entities (or objects) of the research process must be identified.
This includes finding classes of entities, grouping entities or merging them. In
materials modelling, one entity which is relevant is, for example, the component
which represents a chemical species.
• Attributes For each entity defined in the previous step, attributes describing the
entity must be found. To stick with the example, the component is characterized
by attributes like a name, the smiles or IUPAC code and a unit.
• Relations In this part, the relations between the entities must be cleared, e.g. how
they are linked to each other to deliver a holistic description. The arguments must
be reasonable, but are strongly specific to the research. For example, one could
argue that the component is related to the simulated target system. Usually in
metadata modelling, is-part-of relations are sufficient to model the vast majority
of cases. However, relations are not limited to these hierarchical types and may
give a semantically more advanced description which will eventually lead towards
ontologies.
15
keys, according to [5]. Its task is to describe the research objects or parts of it and its
relation to other objects. They are still interpretations; however, they are constructed
in a transparent and comprehensible way and derived from a common understanding
of the research object, and lead to a fixed negotiation. The approach described in this
chapter could also be called an ontology-based metadata, since the metadata model
is engineered from an object model. As depicted in Fig. 1.1, hierarchical models
such as EngMeta range below an ontology; however, their task is also to balance
the depth of domain knowledge representation and the depth of digitization. The
question in what terms a metadata model is different from an ontology has already
been discussed in Sect. 1.2.
2.1.1.2 Object Model
The object model is the starting point for engineering a metadata model and marks
the first phase in the creation process [5]. In this phase, an object model, respectively,
an ontology description is carved out in a non-formal or natural language (and maybe
containing graphical elements) describing and explicating all the relevant objects,
terms, relations and rules. Every person potentially involved has to contribute to this
process, since the metadata model will act as a semantic convention for a common
understanding of the research data described.
The first part of engineering an object model is a clear and fixed understanding
of what the object of research is, and what data it is representing. This can only be
conducted by the analysis of the research process with all the stakeholders included.
In this step, following information must be gathered:
• Entities All relevant entities (or objects) of the research process must be identified.
This includes finding classes of entities, grouping entities or merging them. In
materials modelling, one entity which is relevant is, for example, the component
which represents a chemical species.
• Attributes For each entity defined in the previous step, attributes describing the
entity must be found. To stick with the example, the component is characterized
by attributes like a name, the smiles or IUPAC code and a unit.
• Relations In this part, the relations between the entities must be cleared, e.g. how
they are linked to each other to deliver a holistic description. The arguments must
be reasonable, but are strongly specific to the research. For example, one could
argue that the component is related to the simulated target system. Usually in
metadata modelling, is-part-of relations are sufficient to model the vast majority
of cases. However, relations are not limited to these hierarchical types and may
give a semantically more advanced description which will eventually lead towards
ontologies.