https://orcid.org/0000-0002-6776-1213 https://orcid.org/0000-0001-7564-7990 ASMO is an ontology that aims to define the concepts needed to describe commonly used atomic scale simulation methods, i.e. density functional theory, molecular dynamics, Monte Carlo methods, etc. ASMO uses the Provenance Ontology (PROV-O) to describe the simulation process. Atomistic Simulation Methods Ontology (ASMO) 0.0.1 definition The official definition, explaining the meaning of a class or property. Shall be Aristotelian, formalized and normalized. Can be augmented with colloquial definitions. 2012-04-05: Barry Smith The official OBI definition, explaining the meaning of a class or property: 'Shall be Aristotelian, formalized and normalized. Can be augmented with colloquial definitions' is terrible. Can you fix to something like: A statement of necessary and sufficient conditions explaining the meaning of an expression referring to a class or property. Alan Ruttenberg Your proposed definition is a reasonable candidate, except that it is very common that necessary and sufficient conditions are not given. Mostly they are necessary, occasionally they are necessary and sufficient or just sufficient. Often they use terms that are not themselves defined and so they effectively can't be evaluated by those criteria. On the specifics of the proposed definition: We don't have definitions of 'meaning' or 'expression' or 'property'. For 'reference' in the intended sense I think we use the term 'denotation'. For 'expression', I think we you mean symbol, or identifier. For 'meaning' it differs for class and property. For class we want documentation that let's the intended reader determine whether an entity is instance of the class, or not. For property we want documentation that let's the intended reader determine, given a pair of potential relata, whether the assertion that the relation holds is true. The 'intended reader' part suggests that we also specify who, we expect, would be able to understand the definition, and also generalizes over human and computer reader to include textual and logical definition. Personally, I am more comfortable weakening definition to documentation, with instructions as to what is desirable. We also have the outstanding issue of how to aim different definitions to different audiences. A clinical audience reading chebi wants a different sort of definition documentation/definition from a chemistry trained audience, and similarly there is a need for a definition that is adequate for an ontologist to work with. PERSON:Daniel Schober GROUP:OBI:<http://purl.obolibrary.org/obo/obi> definition definition source Formal citation, e.g. identifier in external database to indicate / attribute source(s) for the definition. Free text indicate / attribute source(s) for the definition. EXAMPLE: Author Name, URI, MeSH Term C04, PUBMED ID, Wiki uri on 31.01.2007 PERSON:Daniel Schober Discussion on obo-discuss mailing-list, see http://bit.ly/hgm99w GROUP:OBI:<http://purl.obolibrary.org/obo/obi> definition source A normal distribution probability density function has a formula of: f(x) = 1/(√(2 π) σ) e^-((x - μ)^2/(2 σ^2)) An annotation property that represents a mathematical formula. Asiyah Yu Lin, Jie Zheng, Yongqun He mathematical formula Examples of a Contributor include a person, an organization, or a service. Typically, the name of a Contributor should be used to indicate the entity. Contributor An entity responsible for making contributions to the resource. Examples of a Creator include a person, an organization, or a service. Typically, the name of a Creator should be used to indicate the entity. Creator An entity primarily responsible for making the resource. Description may include but is not limited to: an abstract, a table of contents, a graphical representation, or a free-text account of the resource. Description An account of the resource. Title A name given to the resource. In current practice, this term is used primarily with literal values; however, there are important uses with non-literal values as well. As of December 2007, the DCMI Usage Board is leaving this range unspecified pending an investigation of options. The range of skos:altLabel is the class of RDF plain literals. skos:prefLabel, skos:altLabel and skos:hiddenLabel are pairwise disjoint properties. alternative label An alternative lexical label for a resource. Acronyms, abbreviations, spelling variants, and irregular plural/singular forms may be included among the alternative labels for a concept. Mis-spelled terms are normally included as hidden labels (see skos:hiddenLabel). definition A statement or formal explanation of the meaning of a concept. example An example of the use of a concept. A general note, for any purpose. A resource has no more than one value of skos:prefLabel per language tag, and no more than one value of skos:prefLabel without language tag. The range of skos:prefLabel is the class of RDF plain literals. skos:prefLabel, skos:altLabel and skos:hiddenLabel are pairwise disjoint properties. preferred label The preferred lexical label for a resource, in a given language. The relation between an activity and the type of computation method employed. has computational method The relation between an Energy Calculation activity and the input parameters used. has input parameter The relation between an activity and the interatomic potential used. has interatomic potential The relation between an Energy Calculation activity and the relaxation degrees of freedom set as constraints in the calculation. has relaxation DOF The relation between an activity and the statistical ensemble set in the simulation. has statistical ensemble The relation between the input parameter set and the unit of the quantity. (e.g. eV for energy cutoff) has unit The relation between a calculated property and the activity through which it was obtained. was calculated by An object property to express the accountability of an agent towards another agent. The subordinate agent acted on behalf of the responsible agent in an actual activity. actedOnBehalfOf starting-point agents-responsibility hadDelegate generated expanded entities-activities prov:generated is one of few inverse property defined, to allow Activity-oriented assertions in addition to Entity-oriented assertions. wasGeneratedBy influenced expanded agents-responsibility wasInfluencedBy A prov:Entity that was used by this prov:Activity. For example, :baking prov:used :spoon, :egg, :oven . used starting-point entities-activities wasUsedBy An prov:Agent that had some (unspecified) responsibility for the occurrence of this prov:Activity. wasAssociatedWith starting-point agents-responsibility wasAssociateFor Attribution is the ascribing of an entity to an agent. wasAttributedTo starting-point agents-responsibility Attribution is the ascribing of an entity to an agent. contributed Attribution is a particular case of trace (see http://www.w3.org/TR/prov-dm/#concept-trace), in the sense that it links an entity to the agent that ascribed it. IF wasAttributedTo(e2,ag1,aAttr) holds, THEN wasInfluencedBy(e2,ag1) also holds. The more specific subproperties of prov:wasDerivedFrom (i.e., prov:wasQuotedFrom, prov:wasRevisionOf, prov:hadPrimarySource) should be used when applicable. wasDerivedFrom starting-point derivations A derivation is a transformation of an entity into another, an update of an entity resulting in a new one, or the construction of a new entity based on a pre-existing entity. hadDerivation Derivation is a particular case of trace (see http://www.w3.org/TR/prov-dm/#term-trace), since it links an entity to another entity that contributed to its existence. wasGeneratedBy starting-point entities-activities generated Because prov:wasInfluencedBy is a broad relation, its more specific subproperties (e.g. prov:wasInformedBy, prov:actedOnBehalfOf, prov:wasEndedBy, etc.) should be used when applicable. This property has multiple RDFS domains to suit multiple OWL Profiles. See <a href="#owl-profile">PROV-O OWL Profile</a>. wasInfluencedBy qualified agents-responsibility The sub-properties of prov:wasInfluencedBy can be elaborated in more detail using the Qualification Pattern. For example, the binary relation :baking prov:used :spoon can be qualified by asserting :baking prov:qualifiedUsage [ a prov:Usage; prov:entity :spoon; prov:atLocation :kitchen ] . Subproperties of prov:wasInfluencedBy may also be asserted directly without being qualified. prov:wasInfluencedBy should not be used without also using one of its subproperties. influenced influencer: an identifier (o1) for an ancestor entity, activity, or agent that the former depends on; http://www.w3.org/TR/2013/REC-prov-dm-20130430/#term-influence influencee: an identifier (o2) for an entity, activity, or agent; http://www.w3.org/TR/2013/REC-prov-dm-20130430/#term-influence An activity a2 is dependent on or informed by another activity a1, by way of some unspecified entity that is generated by a1 and used by a2. wasInformedBy starting-point entities-activities informed hasXCFunctional represents the relationship between a density functional theory method and the exchange-correlation energy functionals it takes. has XC functional A data property linking an input parameter with the value set. has value has reference A data property linking an entity with a reference (e.g. bibliographic) to another resource. The time at which an activity ended. See also prov:startedAtTime. endedAtTime starting-point entities-activities It is the intent that the property chain holds: (prov:qualifiedEnd o prov:atTime) rdfs:subPropertyOf prov:endedAtTime. The time at which an activity started. See also prov:endedAtTime. startedAtTime starting-point entities-activities It is the intent that the property chain holds: (prov:qualifiedStart o prov:atTime) rdfs:subPropertyOf prov:startedAtTime. Ab Initio Molecular Dynamics is a computational method where finite-temperature dynamical trajectories are generated by using forces obtained directly from electronic structure calculations performed ‘‘on the fly’’ as the simulation proceeds. Ab Initio Molecular Dynamics AIMD Ab initio MD Computational method is a method used to numerically solve mathematical models and study the behaviour of physical systems. Computational Method Density functional theory is a computational method used to study the electronic structure and ground state of atoms, molecules, and, solids. This technique determines the properties of a many-electron system thorugh functionals of the spatially dependent electron density. Density Functional Theory DFT Embedded Atom Model is an many-body interatomic potential which contains two contributions to the potential energy: the embedding term, which describes the energy required to embed an atom into an electron cloud, and the pair-wise interaction. https://doi.org/10.1103/PhysRevLett.50.1285 E(r) = \sum_i F_i (\rho_i(r_i)) + 1/2 \sum_{i,j} \varphi(r_{i,j}) Embedded Atom Model EAM Energy calculation is an activity where the energy of the system is computed within the given optimization constraints. This activity does not specify the way the energy is calculated, it can be used to refer to a rigid calculation or also to energy minimization or optimization. See RelaxationDOF class for specifics about the constraints. Energy Calculation Energy Difference Calculation Input Parameter are the parameters provided as input to the software tool performing the numerical calculations. Input Parameter Interatomic potentials, in the context of computer simulations, are mathematical functions to calculate the potential energy of a system of atoms with given positions in space. https://en.wikipedia.org/wiki/Interatomic_potential Interatomic Potential Kinetic Monte Carlo Method is a variation of the Monte Carlo method, intended to simulate the time evolution of a process with known transition rates among states. Kinetic Monte Carlo Method kMC Lennard-Jones Potential is a general two-body interatomic potential, which separates the interaction between atoms into a repulsive part, r^(–n), and attractive part, r^(–m), with (n > m). https://doi.org/10.1021/acs.jctc.4c00135 E(r) = 4\epsilon[(\sigma/r)^{12}-(\sigma/r)^{6}] Lennard-Jones Potential 12-6 potential LJ potential Machine Learning Potential is an interatomic potential which maps the 3N-dimensional configurational space of the system onto its potential energy surface, represented by a discrete set of DFT energies included in the training dataset. https://doi.org/10.1016/j.actamat.2021.116980 Some of the most commonly used MLIP are: Atomic Cluster Expansion (ACE), Moment Tensor Potential (MTP) and Neural Network Potential (NNP) Machine Learning Potential MLIP MLP Modified Embedded Atom Model is an interatomic potential which extends EAM to include angular forces. https://doi.org/10.1103/PhysRevB.46.2727 Modified Embedded Atom Model MEAM Molecular dynamics is a computational method for simulation of complex systems, modelled at the atomic level. The equations of motion are solved numerically to follow the time evolution of the system, allowing the derivation of kinetic and thermodynamic properties of interest by means of ‘computer experiments’. https://doi.org/10.1038/npg.els.0003048 Molecular Dynamics MD Molecular force field is a type of interatomic potential that contains the functional forms used to describe the intra- and inter-molecular potential energy of a collection of atoms, and the corresponding parameters that will determine the energy of a given configuration. ISBN-13: 9780192524706 Force Field Molecular Force Field Molecular statics is a computational method that uses a constrained optimization technique to minimize the energy of the system at the atomic level. It is usually employed within a Molecular Dynamics framework. Molecular Statics MS Monte Carlo Method is a computational method that models the probability of different outcomes. The system is evolved to a new state which is chosen from a randomly generated ensemble of possible future states. Then, using some criteria, this new state is accepted or rejected with a certain probability. Monte Carlo Method MC Monte Carlo Simulation Relaxation Degrees of Freedom are the degrees of freedom allowed for the relaxation of the simulation cell in an atomistic simulation. The instances of this class indicate the type of relaxation allowed, i.e. relaxation of the atomic positions, cell volume and cell shape. Relaxation Degrees of Freedom RelaxationDOF Statistical Ensemble is a collection of points in phase space. TheŒ points are distributed according to a probability density, which is determined by the chosen fixed macroscopic parameters (NPT, NVT, etc.). Each point represents a typical system at any particular instant of time. ISBN-13: 9780192524706 Statistical Ensemble Stillinger-Weber Potential is an interatomic potential comprising both two- and three-atom contributions to describe interactions in solid and liquid forms of Si (and other diamond structures). https://doi.org/10.1103/PhysRevB.31.5262 Stillinger-Weber Potential Calculated Property A calculated property is a property of a material resulting from a calculation or simulation. A unit of measure, or unit, is a particular quantity value that has been chosen as a scale for measuring other quantities the same kind (more generally of equivalent dimension). For example, the meter is a quantity of length that has been rigorously defined and standardized by the BIPM (International Board of Weights and Measures). Any measurement of the length can be expressed as a number multiplied by the unit meter. More formally, the value of a physical quantity Q with respect to a unit (U) is expressed as the scalar multiple of a real number (n) and U, as \(Q = nU\). Unit Activity starting-point entities-activities http://www.w3.org/TR/2013/REC-prov-constraints-20130430/#prov-dm-constraints-fig An activity is something that occurs over a period of time and acts upon or with entities; it may include consuming, processing, transforming, modifying, relocating, using, or generating entities. http://www.w3.org/TR/2013/REC-prov-dm-20130430/#term-Activity http://www.w3.org/TR/2013/REC-prov-n-20130430/#expression-Activity Agent starting-point agents-responsibility An agent is something that bears some form of responsibility for an activity taking place, for the existence of an entity, or for another agent's activity. http://www.w3.org/TR/2013/REC-prov-dm-20130430/#term-agent http://www.w3.org/TR/2013/REC-prov-n-20130430/#expression-Agent Entity starting-point entities-activities http://www.w3.org/TR/2013/REC-prov-constraints-20130430/#prov-dm-constraints-fig An entity is a physical, digital, conceptual, or other kind of thing with some fixed aspects; entities may be real or imaginary. http://www.w3.org/TR/2013/REC-prov-dm-20130430/#term-entity http://www.w3.org/TR/2013/REC-prov-n-20130430/#expression-Entity Organization expanded agents-responsibility An organization is a social or legal institution such as a company, society, etc. http://www.w3.org/TR/2013/REC-prov-dm-20130430/#term-agent http://www.w3.org/TR/2013/REC-prov-n-20130430/#expression-types Person expanded agents-responsibility Person agents are people. http://www.w3.org/TR/2013/REC-prov-dm-20130430/#term-agent http://www.w3.org/TR/2013/REC-prov-n-20130430/#expression-types SoftwareAgent expanded agents-responsibility A software agent is running software. http://www.w3.org/TR/2013/REC-prov-dm-20130430/#term-agent http://www.w3.org/TR/2013/REC-prov-n-20130430/#expression-types A DFT method is a computational quantum mechanical modelling method used to investigate the electronic structure based on optimization of the energy over electronic densities. Density Functional Theory Method An ExchangeCorrelationEnergyFunctional is a functional to compute the exchange correlation energy. Exchange Correlation Energy Functional A GeneralizedGradientApproximation is a classification of exchange correlation energy functionals that only use the local value of the electronic density and its gradient. Generalized Gradient Approximation A hybrid functional is a classification of exchange correlation energy functionals that combine exact exchange from HartreeFock theory with another exchange correlation energy approximation. Hybrid Functional A hybrid generalized gradient approximation is a classification of exchange correlation energy functionals that combine exact exchange from Hartree–Fock theory with generalized gradient approximation. Hybrid Generalized Gradient Approximation A hybrid meta generalized gradient approximation is a classification of exchange correlation energy functionals that combine exact exchange from Hartree–Fock theory with meta generalized gradient approximation. Hybrid Meta Generalized Gradient Approximation A LDA is a classification of exchange correlation energy functionals that only use the local value of the electronic density. Local Density Approximation A MetaGeneralizedGradientApproximation is a classification of exchange correlation energy functionals that only use the local value of the electronic density and its gradient and the Kohn–Sham orbital kinetic energy density. Meta Generalized Gradient Approximation Atomic positions are allowed to change in the calculation. Atomic Position Relaxation In the canonical ensemble the temperature, volume, and the number of particles of every species are kept constant. ISBN-13: 978-0323902922 Canonical Ensemble NVT ensemble Cell shape is allowed to change in the calculation. Cell Shape Relaxation Cell volume is allowed to change in the calculation. Cell Volume Relaxation In the grand canonical ensemble the temperature, volume, and the chemical potential are kept constant. ISBN-13: 978-0323902922 Grand Canonical Ensemble µVT ensemble In the isoenthalpic-isobaric ensemble the enthalpy, pressure, and the number of particles of every species are kept constant. ISBN-13: 978-0323902922 Isoenthalpic–Isobaric Ensemble NPH ensemble In the isothermal-isobaric ensemble the temperature, pressure, and the number of particles of every species are kept constant. ISBN-13: 978-0323902922 Isothermal–Isobaric Ensemble NPT ensemble In the microcanonical ensemble the energy, volume, and the number of particles of every species are kept constant. ISBN-13: 978-0323902922 Microcanonical Ensemble NVE ensemble