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Emi Semantic Model

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Emi Semantic Model

Working on the EMI semantic model at Emi Semantic Model

Checking if the mermaid format used by Tarcisio can be used to draft the model directly in dendron notes

graph TD d[":Mass-Spectrometer-A"]-->|rdf:type|sosa:Platform d-->|sosa:hosts|d2["Sampler-A"] d2-->|rdf:type|sosa:Sampler d2-->|sosa:madeSampling|oo["Sampling-S1"] oo-->|rdf:type|a["sosa:Sampling"] oo-->|"sosa:hasFeatureOfInterest -> prov:used"|s["Raw-Material-S1"] oo-->|sosa:hasResult|es1["Extracted-Sample-S1"] es1-->|rdf:type|emi:ExtractSample s-->|rdf:type|sSample["sosa:Sample, emi:RawMaterial"] s-->|sosa:isSampleOf|t["a Taxon"] t-->|rdf:type|w["<a href=http://www.wikidata.org/entity/Q16521>wikidata:Q16521</a>"] s-->|"emi:isClassifiedWith (optional)"|w2["Specimen Type Vocabulary"] oo-->|sosa:usedProcedure|proc["Sampling-procedure-S1"] proc-->|rdf:type|sosa:Procedure

Description of the SSN

https://www.w3.org/TR/vocab-ssn/#intro

https://github.com/w3c/sdw-sosa-ssn

The Semantic Sensor Network (SSN) ontology is an ontology for describing sensors and their observations, the involved procedures, the studied features of interest, the samples used to do so, and the observed properties, as well as actuators. SSN follows a horizontal and vertical modularization architecture by including a lightweight but self-contained core ontology called SOSA (Sensor, Observation, Sample, and Actuator) for its elementary classes and properties. With their different scope and different degrees of axiomatization, SSN and SOSA are able to support a wide range of applications and use cases, including satellite imagery, large-scale scientific monitoring, industrial and household infrastructures, social sensing, citizen science, observation-driven ontology engineering, and the Web of Things. Both ontologies are described below, and examples of their usage are given.

What is SOSA compared to SSN

SOSA provides a lightweight core for SSN and aims at broadening the target audience and application areas that can make use of Semantic Web ontologies. At the same time, SOSA acts as minimal interoperability fall-back level, i.e., it defines those common classes and properties for which data can be safely exchanged across all uses of SSN, its modules, and SOSA.

Modularization

This section appears convoluted for me (PMA).

A CHatGPT digest indicates

In simple terms, this section talks about breaking down a complex set of rules and definitions (called an ontology) into smaller, more manageable parts to make it easier to use. Imagine it as dividing a big book into chapters, each with its own topic. There are two main ways to do this:

Vertical Segmentation: This is like dividing the book into chapters where each chapter builds on the previous one. For example, Chapter 2 builds on what you learned in Chapter 1. However, Chapter 1 doesn't need anything from Chapter 2. It's like a one-way street.

Horizontal Segmentation: This is like having chapters that depend on each other. Chapter 3 might need some information from Chapter 2 to make sense, and Chapter 2 might need something from Chapter 1. It's like a network of connections between chapters.

The goal of all this is to make it easier for different groups of people to use the rules and definitions (ontology) in a way that suits their needs. So, for example, one group might want to use a simplified version of the rules (like a summary of a book), while another group might want to use a more detailed version (like reading every page of the book). This helps different people work with the same set of rules but in ways that make sense to them.

In any case it is clear the the SOSA is at the core of the SSN and has been build to be reused for other use cases than the ones initially envisioned. This makes it valuable in our case.

Origins of SSN and SOSA

In the Origins of SSN and SOSA we can read that

The initial SSN has been criticized for its partially inconsistent handling of virtual sensors (including software and simulations) and related classes and properties. The new SSN and SOSA address this issue by allowing all major classes to be virtual, and to better support humans and other animals as agents.

This is great as it should allow us to model as sensors :

  • humans (e.g. a Collector)
  • machines (e.g a Mass Spectrometer)
  • softwares (e.g. a Computational MS soft such as Sirius)

Core terms and properties for SOSA

Overview of Classes and Properties This section is non-normative.

  • Classes: sosa:ActuatableProperty , sosa:Actuation , sosa:Actuator , sosa:FeatureOfInterest , sosa:ObservableProperty , sosa:Observation , sosa:Platform , sosa:Procedure , sosa:Result , sosa:Sample , sosa:Sampler , sosa:Sampling , sosa:Sensor [Show all SOSA and SSN terms]

  • Object Properties: sosa:actsOnProperty , sosa:madeByActuator , sosa:hasFeatureOfInterest , sosa:hasResult , sosa:hasSample , sosa:hosts , sosa:isActedOnBy , sosa:isFeatureOfInterestOf , sosa:isHostedBy , sosa:isObservedBy , sosa:isResultOf , sosa:isSampleOf , sosa:madeActuation , sosa:madeBySampler , sosa:madeBySensor , sosa:madeObservation , sosa:madeSampling , sosa:observedProperty , sosa:observes , sosa:phenomenonTime , sosa:usedProcedure [Show all SOSA and SSN terms]

  • Datatype Properties: sosa:hasSimpleResult , sosa:resultTime

Observation perspective

Actuation perspective

Sampling perspective

Trying Mermaid class diagramm (https://mermaid.js.org/syntax/classDiagram.html) as these representation start to look crowded

classDiagram Collector --> Field_Sampling : sosa_madeSampling class Collector{ rdf:type a sosa:Sampler } class Field_Sampling{ rdf:type a sosa:Sample }

Schema of an EMI Observation procedure

graph TD Smartphone -->|rdf:type|sosa:Sensor Smartphone -->|sosa:madeObservation|Field_Observation["Field_Observation"] Smartphone -->|sosa:observes|Pictures["Pictures"] Field_Observation -->|rdf:type|sosa:Observation["sosa:Observation"] Field_Observation -->|sosa:observedProperty|Pictures["Pictures"] Pictures --> |rdf:type|sosa:Observable_property["sosa:Observable_property"] Field_Observation -->|sosa:usedProcedure|Observation_Procedure["Observation_Procedure"] Field_Observation -->|sosa:resultTime|xsd:dateTime Field_Observation -->|"sosa:hasFeatureOfInterest"|Living_System["Living_System"] Field_Observation -->|sosa:hasResult|iNaturalist_Observation["iNaturalist_Observation"] Living_System -->|skos:narrower|t_a["ex:Taxon_a"] Living_System -->|skos:narrower|t_b["ex:Taxon_b"] t_a -->|rdf:type|w["<a href=http://www.wikidata.org/entity/Q16521>wikidata:Q16521</a>"] t_b -->|rdf:type|w["<a href=http://www.wikidata.org/entity/Q16521>wikidata:Q16521</a>"] t_a -->|"emi:isClassifiedWith (optional)"|w2["Specimen Type Vocabulary"] t_b -->|"emi:isClassifiedWith (optional)"|w2["Specimen Type Vocabulary"]

Schema of an EMI Collection procedure

graph TD Collector -->|rdf:type|sosa:Sampler Collector -->|sosa:madeSampling|Field_Sampling["Field_Sampling"] Field_Sampling -->|rdf:type|sosa:Sampling["sosa:Sampling"] Field_Sampling -->|sosa:usedProcedure|Sampling_Procedure["Sampling_Procedure"] Field_Sampling -->|sosa:resultTime|xsd:dateTime Field_Sampling -->|"sosa:hasFeatureOfInterest"|Living_System["Living_System"] Field_Sampling -->|sosa:hasResult|Field_Sample["Field_Sample"] Living_System -->|skos:narrower|t_a["ex:Taxon_a"] Living_System -->|skos:narrower|t_b["ex:Taxon_b"] t_a -->|rdf:type|w["<a href=http://www.wikidata.org/entity/Q16521>wikidata:Q16521</a>"] t_b -->|rdf:type|w["<a href=http://www.wikidata.org/entity/Q16521>wikidata:Q16521</a>"] t_a -->|"emi:isClassifiedWith (optional)"|w2["Specimen Type Vocabulary"] t_b -->|"emi:isClassifiedWith (optional)"|w2["Specimen Type Vocabulary"]

Schema of an EMI Extraction procedure

graph TD Extractor -->|rdf:type|sosa:Actuator Extractor -->|sosa:madeActuation|Lab_Extraction["Lab_Extraction"] Lab_Extraction -->|rdf:type|sosa:Actuation["sosa:Actuation"] Lab_Extraction -->|sosa:usedProcedure|Lab_Extraction_Procedure["Lab_Extraction_Procedure"] Lab_Extraction -->|sosa:resultTime|xsd:dateTime Lab_Extraction -->|"sosa:hasFeatureOfInterest"|Field_Sample["Field_Sample"] Lab_Extraction -->|sosa:hasResult|Lab_Extract["Lab_Extract"]

Schema of an EMI Mass Spectrometry analysis procedure

graph TD Mass_Spectrometer -->|rdf:type|MS_Actuator["sosa:Actuator"] Mass_Spectrometer -->|rdf:type|MS_Sampler["sosa:Sampler"] Mass_Spectrometer -->|sosa:madeActuation|Mass_Spectrometry_Analysis["Mass_Spectrometry_Analysis"] Mass_Spectrometer -->|sosa:madeSampling|Mass_Spectrometry_Analysis["Mass_Spectrometry_Analysis"] Mass_Spectrometry_Analysis -->|rdf:type|MS_Actuation["sosa:Actuation"] Mass_Spectrometry_Analysis -->|sosa:usedProcedure|Mass_Spectrometry_Analysis_Procedure["Mass_Spectrometry_Analysis_Procedure"] Mass_Spectrometry_Analysis -->|sosa:resultTime|ms_time["xsd:dateTime"] Mass_Spectrometry_Analysis -->|"sosa:hasFeatureOfInterest"|Lab_Extract["Lab_Extract"] Mass_Spectrometry_Analysis -->|sosa:hasResult|Mass_Spectrometry_Results["Mass_Spectrometry_Results"]

Schema of an EMI overall procedure

graph TD subgraph field subgraph collection Collector -->|rdf:type|sosa:Sampler Collector -->|sosa:madeSampling|Field_Sampling["Field_Sampling"] Field_Sampling -->|rdf:type|sosa:Sampling["sosa:Sampling"] Field_Sampling -->|sosa:usedProcedure|Sampling_Procedure["Sampling_Procedure"] Field_Sampling -->|sosa:resultTime|fs_time["xsd:dateTime"] end subgraph observation Smartphone -->|rdf:type|sosa:Sensor Smartphone -->|sosa:madeObservation|Field_Observation["Field_Observation"] Smartphone -->|sosa:observes|Pictures["Pictures"] Field_Observation -->|rdf:type|sosa:Observation["sosa:Observation"] Field_Observation -->|sosa:observedProperty|Pictures["Pictures"] Pictures --> |rdf:type|sosa:Observable_property["sosa:Observable_property"] Field_Observation -->|sosa:usedProcedure|Observation_Procedure["Observation_Procedure"] Field_Observation -->|sosa:resultTime|fo_time["xsd:dateTime"] Field_Observation -->|sosa:hasResult|iNaturalist_Observation["iNaturalist_Observation"] Field_Observation -->|"sosa:hasFeatureOfInterest"|Living_System["Living_System"] Field_Sampling -->|"sosa:hasFeatureOfInterest"|Living_System["Living_System"] Living_System -->|skos:narrower|t_a["ex:Taxon_a"] Living_System -->|skos:narrower|t_b["ex:Taxon_b"] end Lab_Extraction -->|"sosa:hasFeatureOfInterest"|Field_Sample["Field_Sample"] t_a -->|rdf:type|w["<a href=http://www.wikidata.org/entity/Q16521>wikidata:Q16521</a>"] t_b -->|rdf:type|w["<a href=http://www.wikidata.org/entity/Q16521>wikidata:Q16521</a>"] t_a -->|"emi:isClassifiedWith (optional)"|w2["Specimen Type Vocabulary"] t_b -->|"emi:isClassifiedWith (optional)"|w2["Specimen Type Vocabulary"] Field_Sampling -->|sosa:hasResult|Field_Sample["Field_Sample"] subgraph lab direction TB subgraph mass_spectrometry Mass_Spectrometer -->|rdf:type|MS_Actuator["sosa:Actuator"] Mass_Spectrometer -->|rdf:type|MS_Sampler["sosa:Sampler"] Mass_Spectrometer -->|sosa:madeActuation|Mass_Spectrometry_Analysis["Mass_Spectrometry_Analysis"] Mass_Spectrometer -->|sosa:madeSampling|Mass_Spectrometry_Analysis["Mass_Spectrometry_Analysis"] Mass_Spectrometry_Analysis -->|rdf:type|MS_Actuation["sosa:Actuation"] Mass_Spectrometry_Analysis -->|sosa:usedProcedure|Mass_Spectrometry_Analysis_Procedure["Mass_Spectrometry_Analysis_Procedure"] Mass_Spectrometry_Analysis -->|sosa:resultTime|ms_time["xsd:dateTime"] Mass_Spectrometry_Analysis -->|sosa:hasResult|Mass_Spectrometry_Results["Mass_Spectrometry_Results"] end subgraph extraction Extractor -->|rdf:type|sosa:Actuator Extractor -->|sosa:madeActuation|Lab_Extraction["Lab_Extraction"] Lab_Extraction -->|rdf:type|sosa:Actuation["sosa:Actuation"] Lab_Extraction -->|sosa:usedProcedure|Lab_Extraction_Procedure["Lab_Extraction_Procedure"] Lab_Extraction -->|sosa:resultTime|xsd:dateTime Lab_Extraction -->|sosa:resultTime|le_time["xsd:dateTime"] end Lab_Extraction -->|sosa:hasResult|Lab_Extract["Lab_Extract"] Mass_Spectrometry_Analysis -->|"sosa:hasFeatureOfInterest"|Lab_Extract["Lab_Extract"] end
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