Preferred Name

Event
Synonyms
Definitions

Any physical, social, or mental process, event, or state. More theoretically, events can be classified in different ways, possibly based on 'aspect' (e.g. stative, continuous, accomplishement, achievement, etc.), on 'agentivity' (e.g. intentional, natural, etc.), or on 'typical participants' (e.g. human, physical, abstract, food, etc.). Here no special direction is taken, and the following explains why: events are related to observable situations, and they can have different views at a same time. If a position has to be suggested here anyway, the participant-based classification of events seems the most stable and appropriate for many modelling problems. (1) Alternative aspectual views Consider a same event 'rock erosion in the Sinni valley': it can be conceptualized as an accomplishment (what has brought a certain state to occur), as an achievement (the state resulting from a previous accomplishment), as a punctual event (if we collapse the time interval of the erosion into a time point), or as a transition (something that has changed from a state to a different one). In the erosion case, we could therefore have good motivations to shift from one aspect to another: a) causation focus, b) effectual focus, c) historical condensation, d) transition (causality). The different views refer to the same event, but are still different: how to live with this seeming paradox? A typical solution e.g. in linguistics (cf. Levin's aspectual classes) and in DOLCE Full (cf. WonderWeb D18 axiomatization) is to classify events based on aspectual differences. But this solution would create different identities for a same event, where the difference is only based on the modeller's attitude. An alternative solution is suggested here, and exploits the notion of (observable) Situation; a Situation is a view, consistent with a Description, which can be observed of a set of entities. It can also be seen as a 'relational context' created by an observer on the basis of a 'frame'. Therefore, a Situation allows to create a context where each particular view can have a proper identity, while the Event preserves its own identity. For example, ErosionAsAccomplishment is a Situation where rock erosion is observed as a process leading to a certain achievement: the conditions (roles, parameters) that suggest such view are stated in a Description, which acts as a 'theory of accomplishments'. Similarly, ErosionAsTransition is a Situation where rock erosion is observed as an event that has changed a state to another: the conditions for such interpretation are stated in a different Description, which acts as a 'theory of state transitions'. Consider that in no case the actual event is changed or enriched in parts by the aspectual view. (2) Alternative intentionality views Similarly to aspectual views, several intentionality views can be provided for a same Event. For example, one can investigate if an avalanche has been caused by immediate natural forces, or if there is any hint of an intentional effort to activate those natural forces. Also in this case, the Event as such has not different identities, while the causal analysis generates situations with different identities, according to what Description is taken for interpreting the Event. On the other hand, if the possible actions of an Agent causing the starting of an avalanche are taken as parts of the Event, then this makes its identity change, because we are adding a part to it. Therefore, if intentionality is a criterion to classify events or not, this depends on if an ontology designer wants to consider causality as a relevant dimension for events' identity. (3) Alternative participant views A slightly different case is when we consider the basic participants to an Event. In this case, the identity of the Event is affected by the participating objects, because it depends on them. For example, if snow, mountain slopes, wind, waves, etc. are considered as an avalanche basic participants, or if we also want to add water, human agents, etc., that makes the identity of an avalanche change. Anyway, this approach to event classification is based on the designer's choices, and more accurately mirrors lexical or commonsense classifications (see. e.g. WordNet 'supersenses' for verb synsets). Ultimately, this discussion has no end, because realists will keep defending the idea that events in reality are not changed by the way we describe them, while constructivists will keep defending the idea that, whatever 'true reality' is about, it can't be modelled without the theoretical burden of how we observe and describe it. Both positions are in principle valid, but, if taken too radically, they focus on issues that are only partly relevant to the aim of computational ontologies, which assist domain experts in representing a certain portion of reality according to their own assumptions and requirements. For this reason, in this ontology version of DOLCE, both events and situations are allowed, together with descriptions (the reason for the inclusion of the D&S framewrok in DOLCE), in order to encode the modelling needs, independently from the position (if any) chosen by the model designer.

ID

http://www.ontologydesignpatterns.org/ont/dul/DUL.owl#Event

comment

Any physical, social, or mental process, event, or state. More theoretically, events can be classified in different ways, possibly based on 'aspect' (e.g. stative, continuous, accomplishement, achievement, etc.), on 'agentivity' (e.g. intentional, natural, etc.), or on 'typical participants' (e.g. human, physical, abstract, food, etc.). Here no special direction is taken, and the following explains why: events are related to observable situations, and they can have different views at a same time. If a position has to be suggested here anyway, the participant-based classification of events seems the most stable and appropriate for many modelling problems. (1) Alternative aspectual views Consider a same event 'rock erosion in the Sinni valley': it can be conceptualized as an accomplishment (what has brought a certain state to occur), as an achievement (the state resulting from a previous accomplishment), as a punctual event (if we collapse the time interval of the erosion into a time point), or as a transition (something that has changed from a state to a different one). In the erosion case, we could therefore have good motivations to shift from one aspect to another: a) causation focus, b) effectual focus, c) historical condensation, d) transition (causality). The different views refer to the same event, but are still different: how to live with this seeming paradox? A typical solution e.g. in linguistics (cf. Levin's aspectual classes) and in DOLCE Full (cf. WonderWeb D18 axiomatization) is to classify events based on aspectual differences. But this solution would create different identities for a same event, where the difference is only based on the modeller's attitude. An alternative solution is suggested here, and exploits the notion of (observable) Situation; a Situation is a view, consistent with a Description, which can be observed of a set of entities. It can also be seen as a 'relational context' created by an observer on the basis of a 'frame'. Therefore, a Situation allows to create a context where each particular view can have a proper identity, while the Event preserves its own identity. For example, ErosionAsAccomplishment is a Situation where rock erosion is observed as a process leading to a certain achievement: the conditions (roles, parameters) that suggest such view are stated in a Description, which acts as a 'theory of accomplishments'. Similarly, ErosionAsTransition is a Situation where rock erosion is observed as an event that has changed a state to another: the conditions for such interpretation are stated in a different Description, which acts as a 'theory of state transitions'. Consider that in no case the actual event is changed or enriched in parts by the aspectual view. (2) Alternative intentionality views Similarly to aspectual views, several intentionality views can be provided for a same Event. For example, one can investigate if an avalanche has been caused by immediate natural forces, or if there is any hint of an intentional effort to activate those natural forces. Also in this case, the Event as such has not different identities, while the causal analysis generates situations with different identities, according to what Description is taken for interpreting the Event. On the other hand, if the possible actions of an Agent causing the starting of an avalanche are taken as parts of the Event, then this makes its identity change, because we are adding a part to it. Therefore, if intentionality is a criterion to classify events or not, this depends on if an ontology designer wants to consider causality as a relevant dimension for events' identity. (3) Alternative participant views A slightly different case is when we consider the basic participants to an Event. In this case, the identity of the Event is affected by the participating objects, because it depends on them. For example, if snow, mountain slopes, wind, waves, etc. are considered as an avalanche basic participants, or if we also want to add water, human agents, etc., that makes the identity of an avalanche change. Anyway, this approach to event classification is based on the designer's choices, and more accurately mirrors lexical or commonsense classifications (see. e.g. WordNet 'supersenses' for verb synsets). Ultimately, this discussion has no end, because realists will keep defending the idea that events in reality are not changed by the way we describe them, while constructivists will keep defending the idea that, whatever 'true reality' is about, it can't be modelled without the theoretical burden of how we observe and describe it. Both positions are in principle valid, but, if taken too radically, they focus on issues that are only partly relevant to the aim of computational ontologies, which assist domain experts in representing a certain portion of reality according to their own assumptions and requirements. For this reason, in this ontology version of DOLCE, both events and situations are allowed, together with descriptions (the reason for the inclusion of the D&S framewrok in DOLCE), in order to encode the modelling needs, independently from the position (if any) chosen by the model designer.

definition

Any physical, social, or mental process, event, or state. More theoretically, events can be classified in different ways, possibly based on 'aspect' (e.g. stative, continuous, accomplishement, achievement, etc.), on 'agentivity' (e.g. intentional, natural, etc.), or on 'typical participants' (e.g. human, physical, abstract, food, etc.). Here no special direction is taken, and the following explains why: events are related to observable situations, and they can have different views at a same time. If a position has to be suggested here anyway, the participant-based classification of events seems the most stable and appropriate for many modelling problems. (1) Alternative aspectual views Consider a same event 'rock erosion in the Sinni valley': it can be conceptualized as an accomplishment (what has brought a certain state to occur), as an achievement (the state resulting from a previous accomplishment), as a punctual event (if we collapse the time interval of the erosion into a time point), or as a transition (something that has changed from a state to a different one). In the erosion case, we could therefore have good motivations to shift from one aspect to another: a) causation focus, b) effectual focus, c) historical condensation, d) transition (causality). The different views refer to the same event, but are still different: how to live with this seeming paradox? A typical solution e.g. in linguistics (cf. Levin's aspectual classes) and in DOLCE Full (cf. WonderWeb D18 axiomatization) is to classify events based on aspectual differences. But this solution would create different identities for a same event, where the difference is only based on the modeller's attitude. An alternative solution is suggested here, and exploits the notion of (observable) Situation; a Situation is a view, consistent with a Description, which can be observed of a set of entities. It can also be seen as a 'relational context' created by an observer on the basis of a 'frame'. Therefore, a Situation allows to create a context where each particular view can have a proper identity, while the Event preserves its own identity. For example, ErosionAsAccomplishment is a Situation where rock erosion is observed as a process leading to a certain achievement: the conditions (roles, parameters) that suggest such view are stated in a Description, which acts as a 'theory of accomplishments'. Similarly, ErosionAsTransition is a Situation where rock erosion is observed as an event that has changed a state to another: the conditions for such interpretation are stated in a different Description, which acts as a 'theory of state transitions'. Consider that in no case the actual event is changed or enriched in parts by the aspectual view. (2) Alternative intentionality views Similarly to aspectual views, several intentionality views can be provided for a same Event. For example, one can investigate if an avalanche has been caused by immediate natural forces, or if there is any hint of an intentional effort to activate those natural forces. Also in this case, the Event as such has not different identities, while the causal analysis generates situations with different identities, according to what Description is taken for interpreting the Event. On the other hand, if the possible actions of an Agent causing the starting of an avalanche are taken as parts of the Event, then this makes its identity change, because we are adding a part to it. Therefore, if intentionality is a criterion to classify events or not, this depends on if an ontology designer wants to consider causality as a relevant dimension for events' identity. (3) Alternative participant views A slightly different case is when we consider the basic participants to an Event. In this case, the identity of the Event is affected by the participating objects, because it depends on them. For example, if snow, mountain slopes, wind, waves, etc. are considered as an avalanche basic participants, or if we also want to add water, human agents, etc., that makes the identity of an avalanche change. Anyway, this approach to event classification is based on the designer's choices, and more accurately mirrors lexical or commonsense classifications (see. e.g. WordNet 'supersenses' for verb synsets). Ultimately, this discussion has no end, because realists will keep defending the idea that events in reality are not changed by the way we describe them, while constructivists will keep defending the idea that, whatever 'true reality' is about, it can't be modelled without the theoretical burden of how we observe and describe it. Both positions are in principle valid, but, if taken too radically, they focus on issues that are only partly relevant to the aim of computational ontologies, which assist domain experts in representing a certain portion of reality according to their own assumptions and requirements. For this reason, in this ontology version of DOLCE, both events and situations are allowed, together with descriptions (the reason for the inclusion of the D&S framewrok in DOLCE), in order to encode the modelling needs, independently from the position (if any) chosen by the model designer.

isDefinedBy

http://www.ontologydesignpatterns.org/ont/dul/DUL.owl

label

Event

note

Any physical, social, or mental process, event, or state. More theoretically, events can be classified in different ways, possibly based on 'aspect' (e.g. stative, continuous, accomplishement, achievement, etc.), on 'agentivity' (e.g. intentional, natural, etc.), or on 'typical participants' (e.g. human, physical, abstract, food, etc.). Here no special direction is taken, and the following explains why: events are related to observable situations, and they can have different views at a same time. If a position has to be suggested here anyway, the participant-based classification of events seems the most stable and appropriate for many modelling problems. (1) Alternative aspectual views Consider a same event 'rock erosion in the Sinni valley': it can be conceptualized as an accomplishment (what has brought a certain state to occur), as an achievement (the state resulting from a previous accomplishment), as a punctual event (if we collapse the time interval of the erosion into a time point), or as a transition (something that has changed from a state to a different one). In the erosion case, we could therefore have good motivations to shift from one aspect to another: a) causation focus, b) effectual focus, c) historical condensation, d) transition (causality). The different views refer to the same event, but are still different: how to live with this seeming paradox? A typical solution e.g. in linguistics (cf. Levin's aspectual classes) and in DOLCE Full (cf. WonderWeb D18 axiomatization) is to classify events based on aspectual differences. But this solution would create different identities for a same event, where the difference is only based on the modeller's attitude. An alternative solution is suggested here, and exploits the notion of (observable) Situation; a Situation is a view, consistent with a Description, which can be observed of a set of entities. It can also be seen as a 'relational context' created by an observer on the basis of a 'frame'. Therefore, a Situation allows to create a context where each particular view can have a proper identity, while the Event preserves its own identity. For example, ErosionAsAccomplishment is a Situation where rock erosion is observed as a process leading to a certain achievement: the conditions (roles, parameters) that suggest such view are stated in a Description, which acts as a 'theory of accomplishments'. Similarly, ErosionAsTransition is a Situation where rock erosion is observed as an event that has changed a state to another: the conditions for such interpretation are stated in a different Description, which acts as a 'theory of state transitions'. Consider that in no case the actual event is changed or enriched in parts by the aspectual view. (2) Alternative intentionality views Similarly to aspectual views, several intentionality views can be provided for a same Event. For example, one can investigate if an avalanche has been caused by immediate natural forces, or if there is any hint of an intentional effort to activate those natural forces. Also in this case, the Event as such has not different identities, while the causal analysis generates situations with different identities, according to what Description is taken for interpreting the Event. On the other hand, if the possible actions of an Agent causing the starting of an avalanche are taken as parts of the Event, then this makes its identity change, because we are adding a part to it. Therefore, if intentionality is a criterion to classify events or not, this depends on if an ontology designer wants to consider causality as a relevant dimension for events' identity. (3) Alternative participant views A slightly different case is when we consider the basic participants to an Event. In this case, the identity of the Event is affected by the participating objects, because it depends on them. For example, if snow, mountain slopes, wind, waves, etc. are considered as an avalanche basic participants, or if we also want to add water, human agents, etc., that makes the identity of an avalanche change. Anyway, this approach to event classification is based on the designer's choices, and more accurately mirrors lexical or commonsense classifications (see. e.g. WordNet 'supersenses' for verb synsets). Ultimately, this discussion has no end, because realists will keep defending the idea that events in reality are not changed by the way we describe them, while constructivists will keep defending the idea that, whatever 'true reality' is about, it can't be modelled without the theoretical burden of how we observe and describe it. Both positions are in principle valid, but, if taken too radically, they focus on issues that are only partly relevant to the aim of computational ontologies, which assist domain experts in representing a certain portion of reality according to their own assumptions and requirements. For this reason, in this ontology version of DOLCE, both events and situations are allowed, together with descriptions (the reason for the inclusion of the D&S framewrok in DOLCE), in order to encode the modelling needs, independently from the position (if any) chosen by the model designer.

preferred label

Event

prefixIRI

dul:Event

Event

DUL:Event

prefLabel

Event

disjointWith

http://www.ontologydesignpatterns.org/ont/dul/DUL.owl#Quality

http://www.ontologydesignpatterns.org/ont/dul/DUL.owl#Object

subClassOf

http://www.ontologydesignpatterns.org/ont/dul/DUL.owl#Entity

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Delete Mapping To Ontology Source
https://spec.industrialontologies.org/ontology/core/Core/Event BTO-BFO LOOM
http://www.cidoc-crm.org/cidoc-crm/E5_Event CIDOC-CRM LOOM
http://rs.tdwg.org/dwc/terms/Event PPO LOOM
http://rs.tdwg.org/dwc/terms/Event FOVT LOOM
http://rs.tdwg.org/dwc/terms/Event BCO LOOM
http://purl.bioontology.org/ontology/LNC/LP34961-0 LOINC LOOM
http://purl.bioontology.org/ontology/PMR.owl#Event PMR LOOM
http://purl.bioontology.org/ontology/CMDO/CM0533 CMDO LOOM
http://www.semanticweb.org/DIASUS/OntoSIM#Ocorrencia ONTOSIM LOOM
http://purl.bioontology.org/ontology/LNC/MTHU019184 LOINC LOOM
http://www.ebi.ac.uk/efo/EFO_0009629 OCD LOOM
http://www.ebi.ac.uk/efo/EFO_0009629 CCONT LOOM
http://www.ebi.ac.uk/efo/EFO_0009629 EFO LOOM
http://www.ebi.ac.uk/efo/EFO_0009629 EFO LOOM
http://www.ebi.ac.uk/efo/EFO_0009629 GSSO LOOM
http://rds.posccaesar.org/2008/02/OWL/ISO-15926-2_2003#Event RDL LOOM
http://rds.posccaesar.org/2008/02/OWL/ISO-15926-2_2003#Event INVERSEROLES LOOM
http://rds.posccaesar.org/2008/02/OWL/ISO-15926-2_2003#Event ISO-ANNOTATIONS LOOM
http://rds.posccaesar.org/2008/02/OWL/ISO-15926-2_2003#Event ENTITY LOOM
http://rds.posccaesar.org/2008/02/OWL/ISO-15926-2_2003#Event ISO-15926-2_2003 LOOM
https://w3id.org/brainteaser/ontology/schema/Event BT-ONTOLOGY LOOM
https://w3id.org/biolink/vocab/Event BIOLINK LOOM
http://purl.org/NET/c4dm/event.owl#Event VIVO-ISF LOOM
http://purl.org/NET/c4dm/event.owl#Event HENECON LOOM
http://purl.org/NET/c4dm/event.owl#Event VIVO LOOM
http://purl.org/NET/c4dm/event.owl#Event GEOSPECIES LOOM
http://purl.org/NET/c4dm/event.owl#Event G-PROV LOOM
http://purl.org/NET/c4dm/event.owl#Event MATERIALSMINE LOOM
http://ontology.ip.rm.cnr.it/ontologies/DOLCE-Lite#Event CONTSONTO LOOM
https://schema.org/Event MOSAIC LOOM
http://purl.obolibrary.org/obo/NCIT_C25499 INBIO LOOM
http://purl.obolibrary.org/obo/NCIT_C25499 PREMEDONTO LOOM
http://purl.obolibrary.org/obo/NCIT_C25499 EPIO LOOM
http://purl.obolibrary.org/obo/NCIT_C25499 GENEPIO LOOM
http://psink.de/scio/Event SCIO LOOM
http://www.semanticweb.org/cbmi/ontologies/2018/10/aceso#C25499 ACESO LOOM
http://id.loc.gov/ontologies/bibframe/Event PMO LOOM
http://www.semanticweb.org/rajas.gokhale/ontologies/2022/4/untitled-ontology-9#event UMMS LOOM
https://w3id.org/gdmt/Event GDMT LOOM
http://purl.bioontology.org/ontology/STY/T051 MEDLINEPLUS LOOM
http://purl.bioontology.org/ontology/STY/T051 RO LOOM
http://purl.bioontology.org/ontology/STY/T051 ICD9CM LOOM
http://purl.bioontology.org/ontology/STY/T051 RCD LOOM
http://purl.bioontology.org/ontology/STY/T051 MESH LOOM
http://purl.bioontology.org/ontology/STY/T051 SNMI LOOM
http://purl.bioontology.org/ontology/STY/T051 CPT LOOM
http://purl.bioontology.org/ontology/STY/T051 MEDDRA LOOM
http://purl.bioontology.org/ontology/STY/T051 WHO-ART LOOM
http://purl.bioontology.org/ontology/STY/T051 ICD10CM LOOM
http://purl.bioontology.org/ontology/STY/T051 MDDB LOOM
http://purl.bioontology.org/ontology/STY/T051 ICD10 LOOM
http://purl.bioontology.org/ontology/STY/T051 STY LOOM
http://purl.bioontology.org/ontology/STY/T051 ATC LOOM
http://purl.bioontology.org/ontology/STY/T051 PDQ LOOM
http://purl.bioontology.org/ontology/STY/T051 NDDF LOOM
http://purl.bioontology.org/ontology/STY/T051 RXNORM LOOM
http://purl.bioontology.org/ontology/STY/T051 MSTDE LOOM
http://purl.bioontology.org/ontology/STY/T051 HL7 LOOM
http://purl.bioontology.org/ontology/STY/T051 NDFRT LOOM
http://purl.bioontology.org/ontology/STY/T051 MSTDE-FRE LOOM
http://purl.bioontology.org/ontology/STY/T051 CRISP LOOM
http://purl.bioontology.org/ontology/STY/T051 AI-RHEUM LOOM
http://purl.bioontology.org/ontology/STY/T051 ICD10PCS LOOM
http://purl.bioontology.org/ontology/STY/T051 SNOMEDCT LOOM
http://purl.bioontology.org/ontology/STY/T051 COSTART LOOM
http://purl.bioontology.org/ontology/STY/T051 NCBITAXON LOOM
http://purl.bioontology.org/ontology/STY/T051 HCPCS LOOM
http://purl.bioontology.org/ontology/STY/T051 VANDF LOOM
http://purl.bioontology.org/ontology/STY/T051 LOINC LOOM
http://purl.bioontology.org/ontology/STY/T051 OMIM LOOM
http://purl.bioontology.org/ontology/STY/T051 ROO LOOM
http://purl.bioontology.org/ontology/STY/T051 ICPC2P LOOM
http://PharmAccess/MomCare/#EVENT MOMCARE LOOM
http://informatics.mayo.edu/TEO.owl#TEO_0000025 TEO LOOM
http://purl.org/ontology/bibo/Event GBOL LOOM
http://purl.org/ontology/bibo/Event G-PROV LOOM
http://purl.org/ontology/bibo/Event MATERIALSMINE LOOM
http://schema.org/Event BIBLIOTEK-O LOOM
http://schema.org/Event APRO LOOM
http://schema.org/Event SCHEMA LOOM
http://schema.org/Event FAST-EVENT LOOM
http://vocab.fairdatacollective.org/gdmt/Event FDC-GDMT LOOM
http://vocab.fairdatacollective.org/gdmt/Event GDMT LOOM
http://doe-generated-ontology.com/OntoAD#Event ONTOAD LOOM
http://www.semanticweb.org/fall#event FALLS LOOM
http://presence-ontology.org/ontology/Event PREO LOOM
http://www.limics.fr/ontologies/menelastop#event TOP-MENELAS LOOM
http://purl.obolibrary.org/obo/EKBE_0000048 LHN LOOM
http://www.w3.org/2006/time-entry#Event ICPS LOOM
http://purl.org/datacite/v4.4/Event DATACITE-VOCAB LOOM
http://ncicb.nci.nih.gov/xml/owl/EVS/Thesaurus.owl#C25499 NCIT LOOM
http://sbmi.uth.tmc.edu/ontology/ochv#C0441471 OCHV LOOM
http://purl.obolibrary.org/obo/SDDO_3000044 SLSO LOOM
http://purl.bioontology.org/ontology/LNC/LP36131-8 LOINC LOOM
http://purl.bioontology.org/ontology/LNC/LP281747-8 LOINC LOOM
http://purl.org/hed/releases/2024-06-10/hed/HED_0012001 HED LOOM
http://purl.bioontology.org/ontology/LNC/LP97906-9 LOINC LOOM
http://purl.allotrope.org/ontologies/process#AFP_0003737 AFO LOOM
http://purl.obolibrary.org/obo/CCTO_000072 CCTOO LOOM
http://webprotege.stanford.edu/RDMZI7c9dfBOLXjLz9RghVT UHC-METADATA LOOM
http://www.onto-med.de/ontologies/gfo.owl#Event GFO LOOM
http://purl.bioontology.org/ontology/SNOMEDCT/272379006 ACESO LOOM
http://purl.bioontology.org/ontology/SNOMEDCT/272379006 ELECTRICA LOOM
http://purl.bioontology.org/ontology/SNOMEDCT/272379006 SNOMEDCT LOOM
http://purl.org/net/OCRe/OCRe.owl#OCRE400004 OCRE LOOM
http://www.limics.fr/ontologies/ontoparonnoy#Evenement ONTOPARON LOOM
http://www.limics.fr/ontologies/ontoparonnoy#Evenement ONTOPARON_SOCIAL LOOM
http://purl.obolibrary.org/obo/TRAK_0000093 TRAK LOOM
http://purl.org/biotop/biotop.owl#Event BT LOOM
https://w3id.org/reproduceme#Event REPRODUCE-ME LOOM
https://www.infrarisk-fp7.eu/vocabs/#Event INFRARISK LOOM
http://vocabs.lter-europe.net/EnvThes/10056 ENVTHES LOOM
http://www.projecthalo.com/aura#Event AURA LOOM
https://neic.no/neic-ahm2023-onto#event NEIC-ONTO LOOM
http://sweetontology.net/phen/Event SWEET LOOM
http://purl.obolibrary.org/obo/IEV_0000000 PTS LOOM
https://w3id.org/linkml-common/Event COMET LOOM
http://purl.bioontology.org/ontology/LNC/LP94957-5 LOINC LOOM
http://www.limics.fr/ontologies/menelastop/event ONTOPSYCHIA LOOM
http://purl.bioontology.org/ontology/LNC/MTHU017695 LOINC LOOM
http://www.purl.org/decide#Event DECIDE LOOM
http://neurolog.unice.fr/ontoneurolog/v3.0/dolce-particular.owl#event ONL-MSA LOOM
http://neurolog.unice.fr/ontoneurolog/v3.0/dolce-particular.owl#event OntoVIP LOOM
http://neurolog.unice.fr/ontoneurolog/v3.0/dolce-particular.owl#event ONL-MR-DA LOOM
http://neurolog.unice.fr/ontoneurolog/v3.0/dolce-particular.owl#event ONL-DP LOOM
http://www.semanticweb.org/ontologies/2010/10/BPO.owl#event BHO LOOM
http://purl.org/dc/dcmitype/Event SCHEMA LOOM
http://purl.org/dc/dcmitype/Event DCMITYPE LOOM