EMMO results from a multidisciplinary effort to develop a standard representational framework that is consistent with scientific principles and methodologies. It is based on physics, analytical philosophy and information and communication technologies. EMMO provides a framework for knowledge capture and interoperability in applied science and engineering, especially materials science and manufacturing. It is released under a Creative Commons CC BY 4.0 license.
- EMMO Wiki - documentation
- Publication list - EMMO-related publication list maintained by EMMC
- EMMO reference index - all classes and properties
- Usage tips - how to work with EMMO using Protégé
- EMMO name and logo - some notes about the name
This repository contains the EMMO top- and middle level ontologies, constituting the core of EMMO. The EMMO top-level ontology consists of the foundation level, which introduces the fundamental theory of mereocausality and the perspective level, which supports a pluralistic representation of the world.
The EMMO middle-level ontology consists of the reference level, which includes the full standard model of physics and the representation of data and information, and the discipline level, providing a common foundation for different disciplines including metrology, materials and manufacturing. Each level is implemented in a set of interdependent modules as illustrated in the figure below.
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The different levels and versions of EMMO can be imported according to the following table:
| Level | Ontology IRI | Description |
|---|---|---|
| TLO | https://w3id.org/emmo/tlo | EMMO top level ontology. Include mereocausality and perspectives. |
| MLO | https://w3id.org/emmo/mlo | EMMO middle level ontology (excluding the full standard model and specialised units). |
| foundation | https://w3id.org/emmo/foundation | The fundamental mereocausal theory and basic annotations. |
| perspectives | https://w3id.org/emmo/perspectives | The EMMO perspectives level. |
| reference | https://w3id.org/emmo/reference | The EMMO reference level. |
| disciplines | https://w3id.org/emmo/disciplines | The EMMO disciplines level. |
| domain | Domain level ontologies maintained in separate repositories. See below | |
| application | Application level ontologies maintained in separate repositories. See below |
EMMO has a modular structure, where each of the foundation, perspectives, reference and disciplines levels contain several modules, as shown in the more detailed figure of the EMMO structure.
A table with all modules can be found here.
EMMO provides in several versions.
| Ontology | Ontology IRI | Description |
|---|---|---|
| EMMO | https://w3id.org/emmo/emmo | EMMO middle level ontology. Equivalent to MLO in the above table. |
| EMAX | https://w3id.org/emmo/emax | EMMO maximal, middle level ontology including the full standard model and specialised units. |
| HUME | https://w3id.org/emmo/hume/hume | EMMO for humans: Like EMMO but with human-readable IRIs. Intended for examples. |
| ELITE | https://w3id.org/emmo/elite/elite | EMMO LITE: Subset of HUME intended for rapid testing of graph databases. |
| EMMO inferred | https://w3id.org/emmo/inferred | Inferred version of EMMO (based on EMAX). |
| HUME inferred | https://w3id.org/emmo/hume/inferred | Inferred version of HUME (based on EMAX). |
Note
Importing any of the above ontologies requires a client that understands owl:imports.
It will also be slow due to recursive import of modules.
If you only need entities, it will much faster to import any of the namespaces listed below.
In EMMO, all entities (i.e. classes, properties and individuals) lives in the same namespace. The namespace depends on the EMMO version according to this table:
| EMMO Version | Prefix | Namespace | Description |
|---|---|---|---|
| EMMO maximal | emmo | https://w3id.org/emmo# | Namespace with all entities (classes, properties and individuals) from EMAX. |
| HUME | hume | https://w3id.org/emmo/hume# | Like EMMO maximal, but with the numerical IRIs converted to human readable IRIs. |
| ELITE | elite | https://w3id.org/emmo/elite# | A subset of HUME, extended with convenient shortcuts. |
EMMO 1.0.0 Reference Level is compliant with OWL2 DL and supports HermiT and FaCT++ reasoners. The axioms have been optimised to reduce reasoning time, facilitating usage and development. Developers of EMMO based ontologies are encouraged to use a reasoner to ensure consistency with the overall framework. However, all relevant inferred axioms have been already included in the ontology, so that the EMMO 1.0.0 can also be used as-is with reasoning based on less expressive rules than OWL2 DL, or without reasoning at all, according to users' needs.
Based on the EMMO core, a set of domain-level ontologies have been developed by the community. They either import one of the versions of EMMO listed on https://emmo-repo.github.io/ or selected modules from EMMO core. The following table lists the public EMMO-based domain ontologies that we are aware of. Please create an issue if you have a public domain ontology that you think should be listed here.
EMMO application ontologies are engineered for a specific use or application by reusing and extending concepts from one or more domain ontologies. Even though the delineation between "domain" and "application" ontologies is somewhat arbitrary, a main difference is that the application ontologies are generally not developed for reuse by other domain or application ontologies, while such reuse is the main focus of domain ontologies.
A description of the EMMO Governance, organisation of related repositories, conventions and how to contribute can be found here.
You can contact EMMO Authors via emmo@emmc.eu
This work has been supported by several European projects, including:
- EMMC-CSA (2016-2019); funding from the European Union’s Horizon 2020 Research and Innovation Programme, under Grant Agreement n. 723867.
- SimDOME (2019-2023); funding from the European Union’s Horizon 2020 Research and Innovation Programme, under Grant Agreement n. 814492.
- MarketPlace (2018-2022); funding from the European Union’s Horizon 2020 Research and Innovation Programme, under Grant Agreement n. 760173.
- VIMMP (2018-2021); funding from the European Union’s Horizon 2020 Research and Innovation Programme, under Grant Agreement n. 760907.
- OntoTrans (2020-2024); funding from the European Union’s Horizon 2020 Research and Innovation Programme, under Grant Agreement n. 862136.
- ReaxPro (2019-2023); funding from the European Union’s Horizon 2020 Research and Innovation Programme, under Grant Agreement n. 814416.
- OntoCommons (2020-2023); funding from the European Union’s Horizon 2020 Research and Innovation Programme, under Grant Agreement n. 958371.
- OYSTER (2017-2021); funding from the European Union’s Horizon 2020 Research and Innovation Programme, under Grant Agreement n. 760827.
- NanoMECommons (2021-2025); funding from the European Union’s Horizon 2020 Research and Innovation Programme, under Grant Agreement n. 952869.
- OpenModel (2021-2025); funding from the European Union’s Horizon 2020 Research and Innovation Programme, under Grant Agreement n. 953167.
- SFI PhysMet (2020-2028); funding from the Research Council of Norway, project no. 309584.
- BIG-MAP (2020-2024); funding from the European Union’s Horizon 2020 Research and Innovation Programme, under Grant Agreement n. 957189.
- MatCHMaker (2023-2027); funding from the European Union's Horizon Europe Research and Innovation Programme, under Grant Agreement n. 101091687.
- PINK (2024-2027); funding from the European Union's Horizon Europe Research and Innovation Programme, under Grant Agreement n. 101137809.
- BatCAT (2024-2027); funding from the European Union's Horizon Europe Research and Innovation Programme, under Grant Agreement n. 101137725 and the UK Research and Innovation (UKRI) under the UK government’s Horizon Europe funding guarantee under Grant Agreement n. 10091190.
This work was conducted using the Protégé resource, which is supported by grant GM10331601 from the National Institute of General Medical Sciences of the United States National Institutes of Health.