18:52:32 RRSAgent has joined #auto 18:52:32 logging to https://www.w3.org/2021/02/24-auto-irc 18:52:34 scribenick: ted 18:52:34 RRSAgent, make logs Public 18:52:35 Meeting: Automotive Working Group Teleconference 18:52:45 Meeting: VSSo and SOSA/Time 18:59:25 Present+ Ted 19:06:06 Introductions 19:07:08 Simon: geophysics background, transitioned towards enviromental sciences 19:07:28 … been working on originally UML then RDF/OWL for observation metadata 19:07:38 … acts of observation 19:08:01 … co-author of W3C SOSA/SSN and earlier worked on ISO and OGC versions 19:08:18 … worked in many different earth and energy models 19:08:54 Daniel: been at BMW for 9 years, Nokia before that 19:09:29 … data architecture centric, worked with Benjamin on VSSo. leading VSS/VSSo discussions at present 19:10:02 … we want a better information model across the company 19:10:51 Benjamin: I worked outside this topic at present, at VW subsidiary Carmeq 19:11:07 … worked with Daniel on VSSo based on VSS 19:11:38 … based on domain knowledge from VSS, core SOSA pattern for modeling observations for signals 19:12:35 Arman: I've been working on automotive cybersecurity with UL for three years before getting involved in W3C 19:12:46 … my main interest is in safety and security of connected 19:16:40 Topic: VSS2/VSSo history 19:18:05 Daniel shares screen 19:18:24 [reusing slides from last week's public working session] 19:19:03 Daniel: VSS is taxonomy of vehicle signals [slide 13] based on physical structure of the vehicle 19:19:14 … tree model with information down in the leaf level 19:19:48 … branching provides unique names. we differentiate between sensor and actuator, data type, unit and description 19:20:55 … we have 400 signals, number of which are repeated per door, seat, wheel... all of this is defined in YAML and from there we have csv, JSON (GraphQL, working on VSSo and soon protobuf) 19:21:48 Benjamin: we found three main patterns for vehicle signals. the taxonomy/tree shape based on physical characteristics of vehicle provides the underlying structure 19:22:04 … we wanted something lightweight for what a signal is, an observation from SOSA 19:22:32 … an attribute describes a car component and therefore a datatype property 19:22:42 … expressing values with units as a literal 19:23:04 … the use cases are mostly around telematics with ability to read and write 19:23:55 Simon: so you have a rich/full model of the vehicle physically and making observation of attributes at leaves 19:24:11 … and actuations? 19:24:18 Benjamin: yes 19:24:41 Simon: there are occuring patterns around actuation and observation, seems captured well 19:25:27 Daniel: we started with an earlier version of VSS when we created VSSo. some modeling choices were problematic but we were able to change them 19:25:45 … those changes were around instantiation for example (multiple wheels etc) 19:26:13 … we have three main use cases in mind. the one most interesting is dynamic vehicle data 19:26:29 … one dealing with interactions with eg WoT 19:26:43 … applicable to other interaction models 19:27:01 … we would appreciate your opinion on structuring 19:27:22 … for time based observations, I wanted to reflect the stream of observations 19:27:56 … but that is different than being a digital twin, is it an observation or more attached to current state 19:28:16 Simon: it may help if I can explain approach to SOSA 19:28:36 … you don't have to implement everything all the time and RDF world encourages this, allowing for assumptions 19:29:09 … goal of standardizing terminology in these spaces when you want to use one of these properties you have something you can take from either domain ontology or eg SOSA structure 19:29:44 … we worked early on with people doing weather forecasting, time properties involved 13 or so temporal properties coming from them 19:30:17 … we limited scope to two main temporal properties. in the ISO/OGC there was a third but didn't reflect that through. time when result was obtained and time it applies within the world 19:30:43 … if your application doesn't need it, you don't have to use it 19:31:30 … you will make selections. you will be transitioning from static and dynamic in some places 19:32:06 … what changes what viewpoint you take will be the time dimension. are you recording or reflecting current 19:32:20 … decide separately on what information to retain and discard 19:32:36 … you can use shape languages like SHACL 19:33:07 … when I was working in UML I said this is just a framework to do implementations within. goal is to provide people standard labels and slots for their data systems 19:33:32 … there may be multiple platforms involved, not necessarily even RDF based 19:34:00 … time scales (and volume of data) can range from milliseconds to years 19:34:21 … these models should not be taken as highly prescriptive but have sense you already understood this 19:34:43 … as Ted noted, also involved in Time space in addition to SOSA 19:35:18 … there are proposed extensions for both these ontologies which allow for patterns that are frequently coming up and worth describing and standardizing 19:35:47 … goal has been to use a mutual language 19:36:32 … I like what I'm seeing here and it makes sense to me 19:37:35 … encourage you to talk with Maxime who has more industrial space. my focus is more enviromental 19:38:08 … I haven't been involved in actuation 19:38:44 … that came from Maxime and his team 19:39:20 … regarding WoT is that coming from W3C or elsewhere? 19:39:41 Benjamin: yes, WoT being an interest 19:40:12 … we talked with Maxime back in 2019 but didn't look too much at the time in actuation, we were focused more on the time at observation 19:40:33 … we wanted to see if we could get alignment initially 19:40:55 … difficult to find direct link 19:41:22 … perhaps you can tell us more about 'feature of interest' 19:41:42 … car is a feature of interest as are its components... 19:41:53 Simon: that was how I understood what you have shown 19:42:13 … this word feature is a slightly strange use of the term, it comes from geospatial world 19:42:33 … makes less sense outside of geospatial. it is the thing you are making observations about 19:42:45 … your domain model recognizes these things as nested 19:43:14 … the domain model linking these components to vehicle as a whole. 'feature of interest' are just class of things we might make observations about 19:44:24 Daniel: right now we are thinking in the continuation of the ontology, taking the branches instead of referencing a given ECU 19:44:47 … 'feature of interest' fits pretty well to that, shows where the signal relates to 19:45:03 … we connected static and dynamic to vehicle itself 19:45:16 Simon: I am very comfortable with what I've seen and heard today 19:45:49 … this is how I would imagine the models/ontologies being applied to this knowledge domain. this is recognizably an appropriate use 19:46:18 Benjamin: regarding interacting with interaction with other domains, WoT has been our approach which has led to a bigger question 19:46:35 … how do you connect SOSA/SSN with other approaches? 19:47:16 … we have to make strong assumptions about a "Thing's" properties and events 19:47:55 … static maps to properties well. sensors more complicated and you need something specific to your use case 19:48:23 Daniel: what I don't get from WoT to Sensor is how to connect versus how to describe the world 19:48:44 … recording history of events SSN/SOSA makes sense 19:49:42 Simon: I'm not really familiar beyond background knowledge of WoT 19:50:09 … see how the views of the world are different but they don't seem incompatible 19:51:01 Simon: I haven't ingested VSSo yet 19:51:14 agenda: https://www.w3.org/community/autowebplatform/wiki/Vssosa 19:51:32 … this pulling in an existing domain ontology? 19:52:02 Daniel: gives GENIVI bg on VSS 19:54:23 Simon: and auto specific needs for Time extensions or we good there? 19:54:30 Ted on extensions for both@@ 19:55:31 Simon: correct, we do expect to fold the Time extensions in directly. my further understanding of using SOSA/SSN within environmental gives me pause about pushing into SOSA or keep as extension 19:55:49 … we have specific sampling requirements for ecological needs 19:56:44 Present+ Simon, DanielW, DanielA, Benjamin, Arman 19:58:32 Simon: time series can be an active observation over time. duration becomes metadata 19:59:18 DanielA: that helps. sometimes you can nudge processes or store data coming with high velocity and clear need of aggregating a time series 19:59:28 … stream observations or events over time 19:59:52 Simon: the language we use in this space is the result of the observation. the result can be the time series as a whole 20:00:20 DanielA: you observe sensor as unique. it can be useful to just annotate series for different use cases 20:00:29 … hard to find a model that suits better these needs 20:02:15 I have made the request to generate https://www.w3.org/2021/02/24-auto-minutes.html ted