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DB1.json

1. @context

The @context section defines the prefixes used in the dataset, which help in abbreviating long URIs. These prefixes map to namespaces, enabling a more readable representation of data.

  • "rdf": Links to RDF (Resource Description Framework) syntax namespace.
  • "rdfs": Links to the RDF Schema namespace.
  • "skos": Links to the Simple Knowledge Organization System namespace.
  • "dcterms": Links to the Dublin Core Terms namespace.
  • "emmo": Links to the European Materials Modelling Ontology (EMMO) namespace.
  • "ex": A custom namespace, probably representing an example or a specific dataset.

2. @graph

The @graph section contains an array of nodes, each representing a resource (entity, concept, or relationship) in the dataset.

Entities (Items in the Graph)

Each entity is represented as a JSON object with attributes:

  • @id: A unique identifier for the resource, often using the custom ex namespace.
  • @type: Indicates the type or class of the resource, often using the emmo namespace.
  • skos:prefLabel: A human-readable label for the resource, using the SKOS vocabulary.

Examples of Entities:

  • ex:Pt_C_Premetek: Represents "Pt/C (Premetek)", a material or substance.

    • @type: emmo:EMMO_4207e895_8b83_4318_996a_72cfb32acd94 (specific type in EMMO)
    • skos:prefLabel: "Pt/C (Premetek)"

  • ex:Nafion_solution_DuPont: Represents a Nafion solution.

    • @type: emmo:EMMO_4207e895_8b83_4318_996a_72cfb32acd94
    • skos:prefLabel: "Nafion solution (5% v/v, DuPont)"

  • ex:Ethanol: Represents Ethanol.

    • @type: emmo:EMMO_4207e895_8b83_4318_996a_72cfb32acd94
    • skos:prefLabel: "Ethanol"

There are also more specific entities related to physical properties (e.g., dielectric constants, boiling points) and process parameters (e.g., sonication time, flow rate).

Relationships (Links in the Graph)

The relationships between entities are described using RDF Schema properties:

  • rdfs:domain: The subject of the relationship.
  • rdfs:range: The object of the relationship.
  • @type: Indicates the type of relationship, often using the emmo namespace.

Examples of Relationships:

  • Relationship 1:

    • @type: emmo:EMMO_e1097637
    • rdfs:domain: ex:Pt_C_Premetek
    • rdfs:range: ex:MEA_Fabrication
    • Meaning: The entity ex:Pt_C_Premetek is involved in the process or context of ex:MEA_Fabrication.

  • Relationship 2:

    • @type: emmo:EMMO_m87987545
    • rdfs:domain: ex:Electrochemical_Testing
    • rdfs:range: ex:Dielectric_constant_24_3
    • Meaning: The entity ex:Electrochemical_Testing is related to a dielectric constant with a value of 24.3.

3. Purpose and Usage

This JSON-LD file is likely used to represent a knowledge graph in a specific domain, such as materials science or chemical processes. It describes entities like substances, processes, and their properties, along with the relationships between them. The use of namespaces like emmo and skos suggests it adheres to established ontologies, facilitating interoperability and data sharing.

4. Integration with Other Data

The structure of this file allows it to be integrated with other Linked Data on the web. By using standard vocabularies and ontologies, it ensures that the data can be understood and reused by other systems and datasets, potentially linking to broader knowledge graphs in the same domain.

5. Troubleshooting

If you encounter issues with this data in your application, they might stem from inconsistencies in the structure (e.g., unexpected data types or missing relationships). Ensuring the data aligns with the expected ontology structure is crucial for seamless integration.

DB2.json

This JSON-LD (JavaScript Object Notation for Linked Data) file defines a graph-based representation of materials, manufacturing processes, properties, and parameters, and how they are related. It uses the EMMO (European Materials Modelling Ontology) as its underlying ontology. Below is a detailed breakdown of each section:

1. @context

The @context section defines the prefixes and shorthand notations used throughout the document to refer to various concepts, properties, and relationships.

  • rdf, rdfs, skos: These are standard vocabularies from the W3C used for describing resources, classes, and simple knowledge organization systems.
  • dcterms: Refers to Dublin Core Metadata Terms, used for describing properties like titles, creators, and subjects.
  • ex: A custom prefix for the example.com domain, likely representing the namespace for custom identifiers in this context.
  • emmo: The namespace for the EMMO ontology, which provides the vocabulary for describing materials, properties, processes, etc.
  • @vocab: Sets a default vocabulary for the document (in this case, the EMMO vocabulary).
  • Custom properties: Properties like has_property, is_manufacturing_input, etc., are defined with EMMO vocabulary identifiers.

2. @graph

The @graph section contains the core data, represented as a collection of interconnected nodes, each defined by an @id and an @type.

Materials

  • ex:Material_001 (Pt/Nafion electrodes)

    • @type: Represents this as an instance of a material class in EMMO.
    • skos:prefLabel: Human-readable label for the material.
    • Relationships:
      • is_manufacturing_input: Indicates this material is an input for a manufacturing process (ex:Manufacturing_001).
      • has_manufacturing_output: Indicates this material is an output of the same manufacturing process.
      • has_property: Lists the properties (ex:Property_001, ex:Property_002, ex:Property_003) associated with this material.

  • ex:Material_002 (catalyst/ionomer ink)

    • Similar to Material_001 but connected to multiple manufacturing processes (ex:Manufacturing_002, 003, 004, 005), and with additional properties.

Manufacturing Processes

  • ex:Manufacturing_001 (MEA manufacturing)

    • @type: Represents this as an instance of a manufacturing process class in EMMO.
    • skos:prefLabel: Human-readable label for the process.

  • Other Manufacturing Processes (002-005)

    • These represent various stages or types of manufacturing processes, each with a specific label and potential input or output relationships with materials.

Properties

  • ex:Property_001 to Property_011
    • Each of these represents a specific material property (e.g., hydrophobicity, pore structure, viscosity) with an @type linking them to a property class in EMMO.
    • skos:prefLabel: Provides a human-readable name for each property.

Parameter

  • ex:Parameter_001
    • Represents a specific parameter ("composition of the solvent used to prepare the ink") and is associated with multiple manufacturing processes through the has_parameter property.

Nanoscale Polymer Materials (and associated processes/properties)

  • ex:nanoscalePolymerMaterials
    • Represents a specific material class related to nanoscale polymer materials.
    • Relationships:
      • has_property: Associates this material with properties such as hydrophobicity, pore structure, and Pt/carbon ratio.
      • is_manufacturing_input: Links this material to the processes like MEA manufacturing and preparation of inks.
      • is_measurement_input: Indicates this material is an input for measurement processes like characterization, in situ analysis, and mathematical modeling.

Summary

This JSON-LD file models a complex relationship between materials, manufacturing processes, and their properties using the EMMO ontology. Each material is linked to its relevant properties and manufacturing stages, reflecting a structured and interconnected dataset. The usage of EMMO ensures that the concepts are well-defined within a broader context of material science ontologies.

DB4.json

This JSON-LD file defines a detailed data model for a series of manufacturing and measurement processes, specifically focused on the creation of a Membrane Electrode Assembly (MEA) and related materials, using the European Materials & Modelling Ontology (EMMO). JSON-LD (JavaScript Object Notation for Linked Data) is a method of encoding linked data using JSON, which allows data to be interconnected and readable both by humans and machines.

Breakdown of the JSON-LD File

1. @context Section

The @context section defines the prefixes (namespaces) and terms used throughout the document to provide context and meaning to the data:

  • rdf, rdfs, skos, dcterms: These are standard vocabularies from W3C (World Wide Web Consortium) that provide foundational terms and relationships for describing data models.
  • ex: A custom namespace, likely representing a specific domain or project (http://example.com/).
  • emmo: The namespace for the European Materials & Modelling Ontology (EMMO), providing specialized terms related to materials science and manufacturing.

The context also maps specific EMMO terms to custom labels used in the graph:

  • is_manufacturing_input: Represents an input to a manufacturing process.
  • has_manufacturing_output: Represents an output from a manufacturing process.
  • is_measurement_input: Represents an input to a measurement process.
  • has_measurement_output: Represents an output from a measurement process.
  • has_property: Links a material or substance to one of its properties.
  • has_parameter: Links a process to its parameters, which are factors that can affect the outcome.

2. @graph Section

The @graph section is where the main content resides, describing different entities (materials, processes, measurements) and their relationships.

Materials:
  • Pt/C (Platinum on Carbon): (@id: "ex:Pt_C") A specific material used in manufacturing, identified by its preferred label.
  • Ionomer: (@id: "ex:Ionomer") Another material involved in the process.
  • Solvent(s): (@id: "ex:Solvent") Represents solvents used in the manufacturing process.
Manufacturing Processes:

  • Catalyst Ink Preparation: (@id: "ex:CatalystInkPreparation")

    • Type: This is a manufacturing process identified by the EMMO type emmo:EMMO_a4d66059_5dd3_4b90_b4cb_10960559441b.
    • Inputs: The process uses Pt/C, Ionomer, and Solvent as inputs.
    • Outputs: It produces outputs related to the catalyst ink, such as its composition, solid content, and dispersion.

  • Catalyst Layer (CL) Formation: (@id: "ex:CatalystLayerFormation")

    • Inputs: The inputs are the outputs from the Catalyst Ink Preparation process (e.g., Catalyst Ink Composition).
    • Outputs: The output is the multiscale structure of the catalyst layer (CL).
    • Parameters: The process parameters include the same inputs, affecting the formation of the CL.

  • MEA Fabrication: (@id: "ex:MEA_Fabrication")

    • Inputs: Utilizes substrate properties as inputs.
    • Outputs: Produces the final Membrane Electrode Assembly (MEA).
    • Parameters: Substrate properties are also used as parameters, indicating that they influence the fabrication process.

  • Coating Process: (@id: "ex:CoatingProcess")

    • Inputs: Takes in parameters like coating uniformity and catalyst loading.
    • Outputs: Produces a coated substrate.
    • Parameters: The inputs are also used as parameters to control the process.

  • Drying Process: (@id: "ex:DryingProcess")

    • Inputs: Involves the drying method and solvent evaporation rate.
    • Outputs: Results in a dried coated substrate.
    • Parameters: The drying method and evaporation rate are parameters influencing the process outcome.
Measurement Processes:

  • Uniformity Measurement: (@id: "ex:UniformityMeasurement")

    • Inputs: Materials such as Pt/C, Ionomer, and Solvent are measured to assess uniformity.
    • Outputs: Produces a measurement result for coating uniformity.

  • Thickness Measurement: (@id: "ex:ThicknessMeasurement")

    • Inputs: Again, Pt/C, Ionomer, and Solvent are inputs for the measurement.
    • Outputs: The measurement output is the multiscale structure of the catalyst layer (CL).
Properties:

  • Dielectric Constant: (@id: "ex:DielectricConstant")

    • Property: Linked to the solvent, indicating the solvent's dielectric constant is an important property.

  • Solubility Parameter: (@id: "ex:SolubilityParameter")

    • Property: Represents the solubility parameter of the solvent, another key property.
Parameters and Other Entities:

  • Catalyst Ink Composition: (@id: "ex:CatalystInkComposition")

    • Type: Classified as an entity in the EMMO ontology, representing the composition of the catalyst ink.

  • Catalyst Ink Solid Content: (@id: "ex:CatalystInkSolidContent")

    • Type: Represents the solid content of the catalyst ink, which is a crucial factor in the manufacturing process.

Understanding the Relationships

  • is_manufacturing_input: Describes which materials or components are required as inputs for a manufacturing process.
  • has_manufacturing_output: Describes the products or results generated from a manufacturing process.
  • is_measurement_input: Identifies what materials or aspects are being measured.
  • has_measurement_output: Specifies the results of the measurement process.
  • has_property: Connects a material to its specific properties.
  • has_parameter: Indicates parameters that influence a process.

Example:

In the Catalyst Ink Preparation process:

  • Inputs include Pt/C, Ionomer, and Solvent.
  • Outputs include Catalyst Ink Composition, Solid Content, and Dispersion. This data structure clearly outlines how different materials and processes are interconnected, which is critical for understanding and optimizing the manufacturing process of the MEA.

Conclusion:

This JSON-LD file serves as a structured and machine-readable description of various materials, manufacturing, and measurement processes within a specific domain, likely related to fuel cell or battery technology. The use of EMMO ontology ensures that the data is semantically rich and interoperable across different systems.

DB5.json

This JSON-LD (JavaScript Object Notation for Linked Data) document represents a structured description of data related to the manufacturing and simulation of catalyst layers, which are likely used in fuel cells or similar applications. The document employs the principles of Linked Data to describe various entities and their relationships using standardized vocabularies.

1. @context Section

The @context section defines the prefixes (namespaces) and their corresponding URIs, which are used throughout the document to ensure that the terms are uniquely identifiable across different data sources.

  • rdf, rdfs, skos, dcterms: These are common RDF (Resource Description Framework) vocabularies:

    • rdf: Provides the basic building blocks for RDF data, such as rdf:type.
    • rdfs: RDF Schema, which provides mechanisms for defining classes and properties.
    • skos: Simple Knowledge Organization System, used for defining concepts, labels, and relationships.
    • dcterms: Dublin Core Metadata Terms, a standard for metadata terms.

  • ex: A prefix representing the example namespace, "http://example.com/". It's a placeholder and typically used to illustrate how data should be structured.

  • emmo: Refers to the European Materials Modelling Ontology (EMMO), a standard ontology for materials science. This namespace is used to define specific terms relevant to the domain.

2. @graph Section

The @graph section contains a list of entities and their properties, representing the main content of the document. Each entity is described using an @id, which is a unique identifier, and an @type, which defines the class to which the entity belongs.

Entities:

  1. ex:carbon_supports

    • Type: emmo:EMMO_4207e895_8b83_4318_996a_72cfb32acd94
    • Label: "carbon supports"
    • Describes the carbon material used as support in the catalyst layer.

  2. ex:Pt_catalysts

    • Type: Same as above
    • Label: "Pt catalysts"
    • Describes platinum-based catalysts.

  3. ex:ionomer

    • Type: Same as above
    • Label: "ionomer"
    • Describes the ionomer material, which is likely used to bind the catalyst particles and conduct ions.

  4. ex:Reconstruction_of_the_catalyst_layer

    • Type: emmo:EMMO_a4d66059_5dd3_4b90_b4cb_10960559441b
    • Label: "Reconstruction of the catalyst layer"
    • emmo:is_manufacturing_input: Refers to carbon_supports, Pt_catalysts, and ionomer as inputs in the process.
    • emmo:has_parameter: Refers to parameters like Pt_loading, ionomer_to_carbon_weight_ratio, and aggregation_degree_control_parameter, which are relevant to the manufacturing process.

  5. ex:Optimized_stochastic_reconstruction_method

    • Type: Same as above
    • Label: "Optimized stochastic reconstruction method"
    • Describes a specific method used in the reconstruction process.

  6. ex:Pore_scale_simulation

    • Type: emmo:EMMO_463bcfda_867b_41d9_a967_211d4d437cfb
    • Label: "Pore-scale simulation"
    • emmo:is_measurement_input: Inputs include carbon_supports, Pt_catalysts, and ionomer.
    • emmo:has_measurement_output: Outputs effective_oxygen_diffusivity, which measures how easily oxygen diffuses through the material.

  7. ex:Lattice_Boltzmann_method_simulation

    • Type: Same as above
    • Label: "Lattice Boltzmann method simulation"
    • emmo:is_measurement_input: Uses catalyst_layer_structures as input.
    • emmo:has_measurement_output: Outputs include volume_fraction_of_carbon_supports, Pt_volume_fraction, and ionomer_volume_fraction, representing the material compositions.

  8. ex:Bruggeman_correlation_benchmark

    • Type: Same as above
    • Label: "Bruggeman correlation benchmark"
    • emmo:is_measurement_input: Inputs the catalyst_layer_microstructure.
    • emmo:has_measurement_output: Outputs several properties, such as thickness_of_catalyst_layer, and densities of Pt, carbon, and ionomer.

Properties:

  • emmo:is_manufacturing_input: Indicates materials or inputs used in a manufacturing process.
  • emmo:has_parameter: Represents parameters relevant to the process.
  • emmo:is_measurement_input: Inputs used in a measurement or simulation.
  • emmo:has_measurement_output: Results or outputs from a measurement or simulation.

Example Properties and Parameters:

  • ex:effective_oxygen_diffusivity: Describes how effectively oxygen can diffuse through the material, with a value range provided.
  • ex:Pt_loading: The amount of platinum loaded onto the support material.
  • ex:ionomer_to_carbon_weight_ratio: The ratio of ionomer to carbon by weight, which is critical in determining the structure and performance of the catalyst layer.
  • ex:aggregation_degree_control_parameter: A parameter controlling the degree of aggregation in the material, affecting its overall structure.

Summary

This JSON-LD document is a detailed representation of materials and processes related to the manufacturing and simulation of catalyst layers in a technical domain, likely related to fuel cell technology. It uses standard vocabularies to describe the relationships between different materials, processes, and their resulting properties, enabling data interoperability and reuse in scientific and engineering contexts.

DB14.json

This JSON-LD (JavaScript Object Notation for Linked Data) file describes a set of entities, properties, and their relationships related to a scientific or industrial process, possibly in materials science or manufacturing. Here's a detailed breakdown:

1. @context Section

The @context section defines the vocabulary (namespaces) and terms used in the JSON-LD document. It establishes the meanings of the terms and how they are connected to specific identifiers (URIs).

  • @vocab: Specifies the default vocabulary namespace as "http://emmo.info/emmo#", which is likely the European Materials Modelling Ontology (EMMO). All terms without a prefix will be assumed to belong to this namespace.
  • ex: Short for "http://example.com/", a placeholder namespace commonly used in examples.

Several specific terms are defined in the context with @type set to @id:

  • is_manufacturing_input, has_manufacturing_output, is_measurement_input, has_measurement_output, has_property, has_parameter: These terms are mapped to specific EMMO identifiers and indicate relationships between entities. The @type: @id means that the values for these properties are expected to be identifiers (URIs) of other entities.

2. @graph Section

The @graph section contains a list of entities and their properties. Each entity is identified by an @id, which is a unique identifier within the namespace, and an @type, which defines the class of the entity.

Entities:

  1. ex:1 (Ionomer)

    • @type: EMMO_4207e895_8b83_4318_996a_72cfb32acd94
    • skos:prefLabel: "Ionomer"
    • is_measurement_input: Points to ex:2 (Carbon) and ex:3 (Pt/C Agglomerates), indicating that these are inputs in the measurement process involving the Ionomer.
    • has_property: Lists properties ex:4, ex:5, and ex:6, likely representing different characteristics or steps in a process involving the Ionomer.
    • is_manufacturing_input: Points to ex:7 (Local Thickness Measurement), indicating that this is an input in the manufacturing process.

  2. ex:2 (Carbon)

    • @type: Same as above.
    • skos:prefLabel: "Carbon"
    • is_measurement_input: Points to ex:8 (Pore Size Distribution Measurement), suggesting that Carbon is an input in this measurement.
    • is_manufacturing_input: Points to ex:9 (Ionomer Coverage), indicating its role in manufacturing.

  3. ex:3 (Pt/C Agglomerates)

    • @type: Same as above.
    • skos:prefLabel: "Pt/C Agglomerates"
    • is_measurement_input: Points to ex:10 (Proton Conductivity).
    • is_manufacturing_input: Points to ex:11 (Ionomer Film Thickness).

  4. ex:4 (Image Generation Workflow)

    • @type: EMMO_a4d66059_5dd3_4b90_b4cb_10960559441b
    • skos:prefLabel: "Image Generation Workflow"
    • has_manufacturing_output: Points to ex:12 (I Ratio), indicating that this is an output of the manufacturing process.
    • has_parameter: An empty array, meaning no specific parameters are listed.

  5. ex:5 (Structure Formation during Ink Stage)

    • @type: Same as above.
    • skos:prefLabel: "Structure Formation during Ink Stage"
    • has_manufacturing_output: Points to ex:13 (Initial Ionomer Film Thickness).
    • has_parameter: Points to parameters ex:14, ex:15, and ex:16.

  6. ex:6 (Proton Conductivity Calculation)

    • @type: EMMO_463bcfda_867b_41d9_a967_211d4d437cfb
    • skos:prefLabel: "Proton Conductivity Calculation"
    • has_measurement_output: Points to ex:17, which likely represents the result or outcome of this calculation.

  7. ex:7 (Local Thickness Measurement)

    • @type: Same as above.
    • skos:prefLabel: "Local Thickness Measurement"
    • has_measurement_output: Points to ex:18.

  8. ex:8 (Pore Size Distribution Measurement)

    • @type: Same as above.
    • skos:prefLabel: "Pore Size Distribution Measurement"
    • has_measurement_output: Points to ex:19.

Other Entities and Properties:

  • ex:9 (Ionomer Coverage), ex:10 (Proton Conductivity), ex:11 (Ionomer Film Thickness): These entities represent specific properties related to the manufacturing or measurement processes. They are associated with the inputs or outputs in the processes described.

  • ex:12 (I Ratio) and ex:13 (Initial Ionomer Film Thickness): These are outputs from the manufacturing processes, indicating specific outcomes or characteristics obtained from those processes.

  • ex:14 (Ionomer Dispersion Parameter), ex:15 (Length Conversion Factor): Parameters that are likely used in the simulation, manufacturing, or measurement processes. The rdfs:label attached to ex:15 provides a specific value, "(2 nm)^3".

Summary

This JSON-LD document is a detailed and structured representation of entities and processes related to a specific scientific or industrial domain, likely materials science or manufacturing. It leverages the EMMO ontology to define the relationships between entities, including inputs and outputs for manufacturing and measurement processes, as well as the properties and parameters involved in these processes. The document is designed to ensure data interoperability and reusability across different systems and datasets, which is crucial in scientific research and industrial applications.

DB16.json

This JSON-LD file represents structured data describing various materials, manufacturing processes, measurements, properties, and parameters within a specific domain. It uses the EMMO (European Materials & Modelling Ontology) as the vocabulary to define types and relationships. Let’s break down each part:

1. @context:

The @context section maps terms used in the JSON-LD document to their corresponding IRIs (Internationalized Resource Identifiers). This ensures that the terms are interpreted consistently across different datasets. Here's what each mapping does:

  • "emmo": This defines the base IRI for the EMMO ontology.
  • "is_manufacturing_input", "has_manufacturing_output", "is_measurement_input", "has_measurement_output", "has_property", "has_parameter": These map to specific EMMO concepts that represent relationships between entities, such as inputs and outputs in manufacturing or measurement processes, properties of materials, and parameters of processes.
  • "Material", "Manufacturing", "Measurement", "Property", "Parameter": These define the types of entities in the graph, corresponding to materials, manufacturing processes, measurements, properties, and parameters in the domain.

2. @graph:

The @graph section contains a list of nodes that describe individual entities (materials, processes, measurements, properties, etc.) and their relationships. Each node is defined by:

  • @id: A unique identifier for the entity.
  • @type: The type of the entity (e.g., Material, Manufacturing, Measurement).
  • Additional properties, which define relationships to other entities or literal values.

Materials:

  • "ex:Material1" to "ex:Material7": These are materials used or produced in the processes. Each material has a label (e.g., "H2/Ar atmosphere", "Pt3Co/O–C catalyst").

Manufacturing Processes:

  • "ex:Manufacturing1" to "ex:Manufacturing3": These nodes represent specific manufacturing processes. Each process has:
    • A label (e.g., "Pre-oxidizing treatment", "Grinding-heat method").
    • is_manufacturing_input: References to the materials used in the process.
    • has_manufacturing_output: The material produced by the process.
    • has_parameter: Parameters that define specific conditions for the process (e.g., temperature, atmosphere).

Measurements:

  • "ex:Measurement1" to "ex:Measurement3": These represent measurement techniques used to characterize the materials. Each measurement has:
    • A label (e.g., "X-ray diffraction (XRD)", "Transmission electron microscopy (TEM)").
    • is_measurement_input: The materials being measured.
    • has_measurement_output: The properties measured (e.g., particle size, interplanar spacing).

Properties:

  • "ex:Property1" to "ex:Property6": These nodes define specific properties of materials, such as particle size, interplanar spacing, Pt loading, and more. Each property includes:
    • A label (e.g., "Particle size").
    • emmo:has_numeric_value: The measured value of the property.
    • emmo:has_unit: The unit of the measured value (e.g., "nm", "wt%").

Parameters:

  • "ex:Parameter1" to "ex:Parameter5": These represent specific parameters used in manufacturing processes. Each parameter includes:
    • A label (e.g., "Pre-oxidizing temperature").
    • emmo:has_numeric_value: The value of the parameter.
    • emmo:has_unit: The unit of the parameter (e.g., "°C", "M HNO3").

Summary:

  • The JSON-LD file models a domain related to material manufacturing and characterization, with detailed descriptions of the materials involved, the processes they undergo, and the measurements used to evaluate them.
  • Each entity is connected to others through well-defined relationships, allowing for a clear and structured representation of the information. This structure enables interoperability and facilitates the integration of this data with other datasets that use the same or similar ontologies.

DB20.json

This JSON-LD file represents structured data about a research article involving materials, manufacturing processes, measurements, properties, and parameters, using terms defined in the European Materials & Modelling Ontology (EMMO). The structure is designed to describe relationships between these entities, allowing for semantic interpretation.

1. @context:

The @context section maps prefixes and terms to their corresponding IRIs, ensuring consistent interpretation:

  • "emmo": The base IRI for the EMMO ontology, providing the namespace for specific terms.
  • "ex": A namespace for example entities, which are likely specific to the particular dataset or example.

2. @graph:

The @graph section contains a list of entities, each described by its properties and relationships. The entities include materials, processes, measurements, properties, and parameters.

Entities:

Each entity in the graph is identified by:

  • @id: A unique identifier within the example namespace (e.g., ex:38127, ex:Material_20wtPtC).
  • @type: The type of the entity, defined by an EMMO concept (e.g., emmo:EMMO_a4d66059_5dd3_4b90_b4cb_10960559441b for a research article).

Main Entities:

  • Research Article:

    • "@id": "ex:38127": Represents a research article.
    • "@type": "emmo:EMMO_a4d66059_5dd3_4b90_b4cb_10960559441b": Indicates it is of the type defined in EMMO.
    • "skos:prefLabel": "Research Article": The preferred label for this entity.

  • Materials:

    • "ex:Material_20wtPtC": Represents a "20 wt % Pt/C catalyst".
    • "ex:Material_5wtNafion": Represents a "5 wt % Nafion solution".
    • "ex:Material_MQWater": Represents "Milli-Q water".

  • Manufacturing Process:

    • "ex:Manufacturing_UltrasonicDispersion": Represents the process "Ultrasonic Dispersion".

  • Measurement:

    • "ex:Measurement_ECSA": Represents the measurement of "Electrochemical Surface Area (ECSA)".

  • Property:

    • "ex:Property_AvgCrystalliteSize": Represents the property "average crystallite size".

  • Parameter:

    • "ex:Parameter_PtCToNafionWeightRatio": Represents the parameter "Pt/C to Nafion weight ratio".

Relationships:

The relationships between these entities are defined using specific EMMO properties:

  • Material to Manufacturing:

    • "ex:Material_20wtPtC" has a manufacturing relationship to "ex:Manufacturing_UltrasonicDispersion" using "emmo:e1097637". This indicates that the material "20 wt % Pt/C catalyst" is used as an input in the "Ultrasonic Dispersion" process.

  • Manufacturing Output:

    • "ex:Manufacturing_UltrasonicDispersion" produces "ex:Material_DispersedCatalystIonomerInk" as output using "emmo:e1245987".

  • Material to Measurement:

    • "ex:Material_20wtPtC" is used as an input in the measurement "ex:Measurement_ECSA" using "emmo:m5677989".

  • Measurement Output:

    • "ex:Measurement_ECSA" produces a measurement value "ex:Property_ECSAValue" using "emmo:m87987545".

  • Property Relationship:

    • "ex:Material_Glycerol" is related to the property "ex:Property_LowChargeTransferResistance" using "emmo:p5778r78".

  • Manufacturing Parameter:

    • "ex:Manufacturing_UltrasonicDispersion" is associated with the parameter "ex:Parameter_PtCToNafionWeightRatio" using "emmo:p46903ar7".

Summary:

  • Research Article: The central entity is a research article, which references different materials, processes, measurements, properties, and parameters.
  • Materials: The materials involved include catalysts, solutions, and water, each connected to manufacturing processes or measurements.
  • Processes: A specific process, Ultrasonic Dispersion, is described with its input materials and output product.
  • Measurements: The file includes a description of an Electrochemical Surface Area (ECSA) measurement and the properties it outputs.
  • Properties and Parameters: The file describes properties like crystallite size and parameters like weight ratios, linking them to relevant materials and processes.

This structured data allows machines to interpret the relationships between materials, processes, measurements, and their outcomes, making it easier to share and reuse the information across different platforms.