Systems, Models, Simulation (SMS)-Ontology

Making models, the ability to simulate them, and the simulation results part of the Semantic Web requires an ontology that links the real (or envisioned) world in terms of systems, context, initial state, …​ to their abstract representations as model instances, input data, initial conditions et cetera and also captures knowledge about the involved concepts. The SMS-ontology developed in this repository does just that.

Moreover, the SMS-/FMI-ontology captures interrelations of the concepts and roles of the FMI-ontology and the SMS-ontology.

Installation

There is no need to install anything if you just want to use the ontologies.

If you want to run the tests and/or contribute, see below.

Usage

Use the SMS-ontology to “talk” about systems, models and simulations in RDF independent of the modelling formalism used.

If you’re using FMI, please have a look at the FMI-ontology and fmi2rdf-parser. A reasoner can infer triples in the SMS-namespace from triples in the FMI-namespace via the SMS-/FMI-ontology if desired.

Competency Questions

Competency questions are used to assess whether or not the developed ontology can fulfil its purpose. They are realized as unit tests, written in Python using the pytest framework. Since the competency questions involve instance retrieval, an ABox is needed; it is populated in tests/data/individuals.ttl.

Since also the inferences are required for answering some queries, the competency questions are evaluated against a file that also contains all inferences made by Protégé. It is manually exported as tests/data/individuals_with_reasoning.ttl because Protégé unfortunately has no CLI for this.

Find all competency questions currently supported using the aforementioned individuals in tests/questions.yaml.j2.

Known Issues

To be resolved as soon as possible

• ❏ Revise/complete the SMS-/FMI-ontology

• ❏ Provide additional example(s)

• ❏ …​

To be resolved soonish

• ❏ Create release (tag, GitHub)

• ❏ Explore ontology-driven modelling on the base of the FMI- and SMS-ontologies

• ❏ Capture interrelations with SSN/SOSA?

• ❏ …​

To be resolved eventually

• ❏ Improve score in FOOPS! scanner

• ❏ …​

Contributing

Feedback is very welcome! Please open an issue for questions, remarks and bug reports; or open a pull request if you want to improve something.

The code in this repository uses Semantic Versioning (semver) and follows the semver specification.

Development

Clone the repository locally. Then, install the dependencies using pipenv install and pipenv install --dev. Activate the resulting virtual environment with pipenv shell. For details, see the dependency specification in Pipfile and the documentation of pipenv.

The Python code is formatted automatically using black and isort.

Naming Conventions for Ontology Development

• CamelCase is used to form names consisting of several words; whitespaces are not allowed

• Classes/concepts start with a capital letter; the singular form of the concept name is used

• Role names start with a lowercase letter

• Role names that indicate a has or is a-relationship are prefixed using has and is, respectively

• rdfs:comment-annotations are full sentences that end with a period and have a language annotation

License

The ontologies and test code/data are licensed under the MIT License. This is specified in the format suggested by the REUSE SOFTWARE-initiative. In short: SPDX IDs are included in every textual file and the license text can be found in ./LICENSES/.