RE: Location range

Sefki,

Ø  Do we have a range function for geolocations?


The old ssn left the encoding of locations to external ontologies, although with particular reference to dul where (I am reasonably confident) such ranges can be encoded.
onPlatform
Relation between a System (e.g., a Sensor) and a Platform. The relation locates the sensor relative to other described entities entities: i.e., the Sensor s1's location is Platform p1. More precise locations for sensors in space (relative to other entities, where attached to another entity, or in 3D space) are made using DOLCE's Regions (SpaceRegion).

This is no longer really good enough – as we have removed the binding to dolce from ssn this should be reconsidered. And it most especially should be reconsidered in the light of our own “best practice” deliverable.  Perhaps there is something in the current sosa design? I expect not…but do please check

By this adding as an email to the tracker issue-50 “How do we replace those components of dul that seem to be core to ssn if dul is not being used?<https://www.w3.org/2015/spatial/track/issues/50>”

Maybe you could take an action to propose a solution????.


Ø  represent a sensory measurement that has been obtained using two sensor nodes

On the other hand (but harder)  you could describe the “virtual”  sensor as a composition of two  physical sensors which both have point locations you can do this in ssn and (less detailed) also in sosa. If this approach suits you then please ask again and I’ll try to help further.


-Kerry



From: Kolozali, Sefki [mailto:sefki.kolozali@kcl.ac.uk]
Sent: Tuesday, 24 January 2017 10:48 PM
To: SDW WG (public-sdw-wg@w3.org) <public-sdw-wg@w3.org>; Kerry Taylor <kerry.taylor@anu.edu.au>
Subject: Location range


Hi Kerry and All,

I was wondering whether or not with the new version of SSN ontology we will be able to represent a sensory measurement that has been obtained using two sensor nodes that are located in different places. Do we have a range function for geolocations?

Kind Regards,

Sefki Kolozali
Research Associate in Applied Big Data Analysis
Environmental Research Group, MRC-PHE Centre for Environment & Health
Analytical & Environmental Sciences, Faculty of Life Sciences & Medicine
King’s College London, Franklin-Wilkins Building
Room 4.189, 150 Stamford Street, London SE1 9NH, UK

E-mail: sefki.kolozali@kcl.ac.uk<mailto:sefki.kolozali@kcl.ac.uk>
https://kclpure.kcl.ac.uk/portal/sefki.kolozali.html

http://www.erg.kcl.ac.uk/

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