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License: CC BY 4.0 CI tests

The European Materials & Modelling Ontology (EMMO)

About

EMMO is a multidisciplinary effort to develop a standard representational framework (the ontology) for applied sciences. It is based on physics, analytical philosophy and information and communication technologies. It has been instigated by materials science and provides the connection between the physical world, the experimental world (materials characterisation) and the simulation world (materials modelling). It is released under a Creative Commons CC BY 4.0 license.

EMMO in a Nutshell

The EMMO ontology is structured in shells, expressed by specific ontology fragments, that extends from fundamental concepts to the application domains, following the dependency flow.

Top Level

The EMMO top level is the group of fundamental axioms that constitute the philosophical foundation of the EMMO. Adopting a physicalistic/nominalistic perspective, the EMMO defines real world objects as 4D objects that are always extended in space and time (i.e. real world objects cannot be spaceless nor timeless). For this reason abstract objects, i.e. objects that does not extend in space and time, are forbidden in the EMMO.

EMMO is strongly based on the analytical philosophy dicipline semiotic. The role of abstract objects are in EMMO fulfilled by semiotic objects, i.e. real world objects (e.g. symbol or sign) that stand for other real world objects that are to be interpreted by an agent. These symbols appear in actions (semiotic processes) meant to communicate meaning by establishing relationships between symbols (signs).

Another important building block of from analytical philosophy is atomistic mereology applied to 4D objects. The EMMO calls it 'quantum mereology', since the there is a epistemological limit to how fine we can resolve space and time due to the uncertanity principles.

The mereotopology module introduces the fundamental mereotopological concepts and their relations with the real world objects that they represent. The EMMO uses mereotopology as the ground for all the subsequent ontology modules. The concept of topological connection is used to define the first distinction between ontology entities namely the Item and Collection classes. Items are causally self-connected objects, while collections are causally disconnected. Quantum mereology is represented by the Quantum class. This module introduces also the fundamental mereotopological relations used to distinguish between space and time dimensions.

The physical module, defines the Physical objects and the concept of Void that plays a fundamental role in the description of multiscale objects and quantum systems. It also define the Elementary class, that restricts mereological atomism in space.

Figure 1. The EMMO top level.

In EMMO, the only univocally defined real world object is the Item individual called Universe that stands for the universe. Every other real world object is a composition of elementaries up to the most comprehensive object; the Universe. Intermediate objects are not univocally defined, but their definition is provided according to some specific philosophical perspectives. This is an expression of reductionism (i.e. objects are made of sub-objects) and epistemological pluralism (i.e. objects are always defined according to the perspective of an interpreter, or a class of interpreters).

The Perspective class collects the different ways to represent the objects that populate the conceptual region between the elementary and universe levels.

Middle Level

The middle level ontologies act as roots for extending the EMMO towards specific application domains.

Figure 2. The EMMO perspectives.

The Reductionistic perspective class uses the fundamental non-transitive parthood relation, called direct parthood, to provide a powerful granularity description of multiscale real world objects. The EMMO can in principle represents the Universe with direct parthood relations as a direct rooted tree up to its elementary constituents.

The Holistic perspective class introduces the concept of real world objects that unfold in time in a way that has a meaning for the EMMO user, through the definition of the classes Process and Participant.

The Perceptual perspective class introduces the concept of real world objects that can be perceived by the user as a recognisable pattern in space or time. Under this class the EMMO categorises e.g. formal languages, pictures, geometry, mathematics and sounds. Phenomenic objects can be used in a semiotic process as signs.

The Physicalistic perspective class introduces the concept of real world objects that have a meaning for the under applied physics perspective.

The semiotics module introduces the concepts of semiotics and the Semiosis process that has a Sign, an Object and an Interpreter as participants. This forms the basis in EMMO to represent e.g. models, formal languages, theories, information and properties.

Figure 3. The semiotic level.

EMMO relations

All EMMO relations are subrelations of the relations found in the two roots: mereotopological and semiotical. The relation hierarchy extends more vertically (i.e. more subrelations) than horizontally (i.e. less sibling relations), facilitating the categorisation and inferencing of individuals.

Imposing all relations to fall under mereotopology or semiotics is how the EMMO force the developers to respect its perspectives. Two entities are related only by contact or parthood (mereotopology) or by standing one for another (semiosis): no other types of relation are possible within the EMMO.

Repository Description

You can find the EMMO ontology at http://emmo.info/emmo. The basic structure of the EMMO is collected by the top ontology.

The overall middle level ontologies are collected by the emmo ontology.

The OWL2-DL sources are available in RDF/XML format.

A description of the EMMO Governance, organisation of related repositories, conventions and how to contribute can be found here.

How To Use It

In order to be able to view and navigate the EMMO ontology we recommend to download the Protégé editor from https://protege.stanford.edu/products.php#desktop-protege.

See these instructions for how to set up Protégé for working with EMMO-based ontologies.

The fastest way to access the EMMO is to open the ontology via Protégé via the menu under File -> Open from URL... and copy the URL http://emmo.info/emmo: Protégé will automatically download all the necessary dependencies.

The EMMO hierarchy will be visible only after reasoning inference: use ctrl-R to start the reasoner and under the Entities tab, select the Classes subtab and Inferred in the scroll button.

It is recommended to use FaCT++ as reasoner. You can select it through the menu Reasoner. An instruction for how to install the FaCT++ plugin on Protege 5.5.0 on Windows can be found in the doc subdirectory.

To access EMMO from Python, we recommend EMMO-python.

Pre-inferred ontology and documentation

Browsable documentation and pre-inferred versions of EMMO are available on GitHub Pages.


Contacts:

Emanuele Ghedini University of Bologna (IT) email: [email protected]

Gerhard Goldbeck Goldbeck Consulting Ltd (UK) email: [email protected]

Acknowledgement

This work has been supported by several European projects, including:

  • EMMC-CSA (2016-2019), that has received funding from the European Union’s Horizon 2020 Research and Innovation Programme, under Grant Agreement n. 723867.
  • SimDOME (2019-2023), that receives funding from the European Union’s Horizon 2020 Research and Innovation Programme, under Grant Agreement n. 814492.
  • MarketPlace (2018-2022) that receives funding from the European Union’s Horizon 2020 Research and Innovation Programme, under Grant Agreement n. 760173.
  • VIMMP (2018-2021) that receives funding from the European Union’s Horizon 2020 Research and Innovation Programme, under Grant Agreement n. 760907.
  • OntoTrans (2020-2024) that receives funding from the European Union’s Horizon 2020 Research and Innovation Programme, under Grant Agreement n. 862136.
  • ReaxPro (2019-2023) that receives funding from the European Union’s Horizon 2020 Research and Innovation Programme, under Grant Agreement n. 814416.

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.

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