Re: [sdw] Homogeneity of an ObservationCollection

About your questions:


a) Is there anything in common within the kind of collection that you envisage? Answer: Yes.

Reasoning: In the BCI domain, a single Session[1] groups multiple heterogenous observations (with different sensors, FoIs, and observable properties). All the observations that "belong to" (were observed during) a session, correspond to (common axes):
- exactly one Subject[2] (a human being or person), 
- performing exactly one Activity[3] (focus on the person's physical state),
- exactly one Context[4] (architectural description of the environment where the person performs the activity).

In a simple way: a session groups multiple heterogenous observations of the same person performing one activity in a specific context. All the observations are heterogeneous because they monitor different parts of the human body dynamics (brain, heart, etc.).

For example a session for monitoring Alice (subject) while (studying) in a coffee shop (context). For this session we could have the following observations:
- one observation that monitors the brain with FoI=Cognitive Aspect (learning)[5], ObservableProperty=EEG-ERP-SSVEP[6], Sensor=EEG-Sensor
- another observation that monitors the heart with FoI=Anxiety, ObservableProperty=ECG, Sensor=ECG-Sensor


b) If so, but it is not one of the properties already mentioned, then should something be added to the model to capture it?
Perhaps not. I think that the definition of "ultimate feature-of-interest" could capture the homogeneity of a BCI session.


c) If not, then how is the collection characterized?

>From the BCI domain, we may think that the "ultimate feature-of-interest" goes all the way up to the whole human being (a person). Although ultimately this is true, however, if we modeled it in that way it would be too vague and the semantics regarding classifying human dynamics and their signals (measurements) would get lost.

Also, in order to keep a characterization of the descriptive features about the metadata collected during a BCI session, we included the concepts of activity and context, due that the physical states of human beings vary in real-life situations (personal and circumstantial variations). This is useful to identify the profiles and trends of human dynamics (such as brain signals) among real-life activities.

Having said that, as you can see the homogeneity of a BCI session lies on the axes of person, activity, and context, which are out-of-scope in SSN/SOSA.

Based on the proposal [7], and from the perspective of BCI, one possibility would be to model a session as an ObservationCollection, where its homogeneity would be in the "ultimate feature-of-interest" axis, which would be a "subject-activity-context" composite entity (although this would not have a useful meaning just for the sake to align properly to [7]).

Last, I think that dividing the structural composition of the "ultimate feature-of-interest" it's entirely application dependent, in order to keep its intended semantics in its domain of discourse:
- BCI: "subject-activity-context" composite entity.
- Smart Living: "an entire building", etc.

A suggestion:
Would be useful to include some general guidelines (based on ontology design patterns) on how to model an "ultimate feature-of-interest"?

---
[1] [http://w3id.org/BCI-ontology#Session](http://w3id.org/BCI-ontology#Session)
[2] [http://w3id.org/BCI-ontology#Subject](http://w3id.org/BCI-ontology#Subject)
[3] [http://w3id.org/BCI-ontology#Activity](http://w3id.org/BCI-ontology#Activity)
[4] [http://w3id.org/BCI-ontology#Context](http://w3id.org/BCI-ontology#Context)
[5] [https://w3id.org/BCI-ontology#CognitiveAspect](https://w3id.org/BCI-ontology#CognitiveAspect)
[6] [https://w3id.org/BCI-ontology#EegModality](https://w3id.org/BCI-ontology#EegModality)
[7] [https://w3c.github.io/sdw/proposals/ssn-extensions/](https://w3c.github.io/sdw/proposals/ssn-extensions/)


-- 
GitHub Notification of comment by srodriguez142857
Please view or discuss this issue at https://github.com/w3c/sdw/issues/1028#issuecomment-385649758 using your GitHub account

Received on Tuesday, 1 May 2018 11:21:34 UTC