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Brain-Computer Interaction (BCI) Ontology
Last uploaded:
June 6, 2018
Acronym | BCI-O |
Visibility | Public |
Description | The BCI ontology specifies a foundational metadata model set for real-world multimodal Brain-Computer Interaction (BCI) data capture activities. Its structure depicts a conceptual framework that BCI applications can extend and use in their implementations, to define core concepts that capture a relevant and interoperable metadata vocabulary. This ontology is aligned to the Semantic Sensor Network Ontology (SSN): a domain-independent and end-to-end model for sensor/actuator applications. Hence, its structure has been normalized to assist its use in conjunction with other ontologies or linked data resources to specify any particular definitions (such as units of measurement, time and time series, and location and mobility), that specialized applications in the BCI domain might need. Its spec provides general alignment data modeling guidelines for core concepts, to help BCI applications in their design. |
Status | Beta |
Format | OWL |
Contact | Sergio José Rodríguez Méndez, srodriguez@pet.cs.nctu.edu.tw |
Categories | Biomedical Resources, Experimental Conditions, Health, Human, Imaging, Neurologic Disease, Neurological Disorder, Upper Level Ontology, Vocabularies |
Version | Released | Uploaded | Downloads |
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0.9.6 (Parsed, Indexed, Metrics, Annotator) | 06/06/2018 | 06/06/2018 | OWL | CSV | RDF/XML | Diff |
0.9.6 (Archived) | 05/20/2018 | 05/20/2018 | OWL |
0.9.6 (Archived) | 05/16/2018 | 05/16/2018 | OWL |
0.9.6 (Archived) | 05/13/2018 | 05/13/2018 | OWL |
0.9.6 (Archived) | 05/13/2018 | 05/12/2018 | OWL |
0.9.6.1 (Archived) | 05/13/2018 | 05/08/2018 | OWL |
more... |
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Id | https://w3id.org/BCI-ontology#Model
https://w3id.org/BCI-ontology#Model
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Preferred Name | model |
Definitions |
Describes a Machine Learning Model (commonly, a mathematical optimization or computational statistics algorithm for predictive analytics) that "detects something" in a DataSegment. A common name given for a Model is classifier.
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Type | http://www.w3.org/2002/07/owl#Class |
All Properties
definition | Describes a Machine Learning Model (commonly, a mathematical optimization or computational statistics algorithm for predictive analytics) that "detects something" in a DataSegment. A common name given for a Model is classifier. |
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preferred label | model
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prefLabel | model
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part | AnnotationTag
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note | Describes a Machine Learning Model (commonly, a mathematical optimization or computational statistics algorithm for predictive analytics) that "detects something" in a DataSegment. A common name given for a Model is classifier.
Right after a set of DataSegments is created, two consecutive tasks occur: (*) A set of editing processes is run on the recordings, which classify the data sets based on different Models. (*) A set of ResponseTags ;is created, which capture the information related to "what is so special about" a particular DataSegment.
In the BCI domain, a Model can generate many different results related to a ResponseTag: each one, can be depicted as a FeatureParameter.
Status: *STABLE*
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isDefinedBy | |
prefixIRI | bci:Model
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title | Model
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describedby | |
StillImage | Model_(SOSA-SSN).png
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subClassOf | |
editorial note | Right after a set of DataSegments is created, two consecutive tasks occur: (*) A set of editing processes is run on the recordings, which classify the data sets based on different Models. (*) A set of ResponseTags ;is created, which capture the information related to "what is so special about" a particular DataSegment.
In the BCI domain, a Model can generate many different results related to a ResponseTag: each one, can be depicted as a FeatureParameter.
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change note | Status: *STABLE*
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type | |
modified | April 16, 2018
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Add NCBO Web Widgets to your site for BCI-O
Widget type | Widget demonstration |
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Step 2: Follow the Instructions
For more help visit NCBO Widget Wiki |
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Example 1 (start typing the class name to get its full URI)
Example 2 (get the ID for a class) Example 3 (get the preferred name for a class) Step 2: Follow the Instructions
For more help visit NCBO Widget Wiki |
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Step 2: Follow the InstructionsCopy the code below and paste it to your HTML page <iframe frameborder="0" src="/widgets/visualization?ontology=BCI-O&class=http%3A%2F%2Fwww.ontologydesignpatterns.org%2Font%2Fdul%2FDUL.owl%23Transition&apikey=YOUR_API_KEY"></iframe> For more help visit NCBO Widget Wiki |
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Step 2: Follow the InstructionsCopy the code below and paste it to your HTML page <link rel="stylesheet" type="text/css" href="/widgets/jquery.ncbo.tree.css"> <script src="/widgets/jquery.ncbo.tree-2.0.2.js"></script> <div id="widget_tree"></div> var widget_tree = $("#widget_tree").NCBOTree({ apikey: "YOUR_API_KEY", ontology: "BCI-O" }); You can also view a detailed demonstration For more help visit NCBO Widget Wiki |