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08:36:16 <Bert> Bert has joined #digital-transformation
08:36:44 <Bert> scribe: Bert
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08:38:59 <Bert> Dave shows some slides.
08:39:44 <Bert> dsr: First part is non-technical, about the motivation.
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08:40:45 <Bert> ... 2nd part is about making RDF easier, and about machine learning
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08:41:53 <Bert> ... Ditial Transformation is a hot topic, at least in Europe. This work is supported by a large EU project, called Boost.
08:42:07 <gkellogg> present+ Gregg_Kellogg
08:42:21 <Bert> ... DT is widely applicable.
08:43:40 <Bert> ... Modern car production is an example where it is already applied. E.g., individually adapted products, rather than mass production
08:44:33 <Bert> ... Required digital integration, from office floor to shop floor to manufacturing, via board room.
08:44:49 <Bert> s/Required/Requires
08:45:33 <Bert> ... Also integration in time, keeping history of a product, use and lifecycle.
08:45:37 <dezell> present+
08:46:46 <Bert> ... Hurdles: many companies still use paper forms, knowledge is in people's heads, (paper) documents are outdated...
08:48:01 <Bert> joemedley: Today's digital processes are often just the old paper processes done digitally.
08:48:49 <Bert> dsr: Diff. orgs. have different histories and different ways of talking about things.
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08:49:41 <Bert> ... Need an incremental approach, bring people along, capture knowledge.
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08:51:20 <Bert> ... DAMA Intl. developed a "data governance wheel" with things to consider. Data governance and data management not necessarily clearly differentiated.
08:52:05 <Bert> ... Graphs are a flexible way to represent knowledge. More flexible than a SQL database.
08:52:17 <phila> present+
08:53:23 <Bert> ... Knowledge Graphs (aka ontologies).
08:54:03 <Bert> ... There are many graph database vendors and the number is growing.
08:55:06 <Bert> ... Sentient Web is a watu to bring things together: sensors + graphs + rules for reasoning (AI, Machine Learning)
08:56:23 <Bert> ... No large org. has a single database, it is distributed.
08:57:17 <Bert> Phil: True, but you'd be surprised how many are trying make a "single source of truth" (without success).
08:57:32 <Bert> s/make/to make
08:57:50 <Bert> dsr: RDF foundation for data.
08:58:14 <Bert> ... W3C Graph Data workshop last March.
08:58:24 <Bert> ... Writing white paper.
08:59:01 <Bert> ... Expecting standardization work at W3C.
08:59:49 <Bert> ... W3C Business Group.
09:00:05 <Bert> dezell: A list of companies interested in the Bus. Group?
09:00:44 <Bert> dsr: We have been slow in talking to companies after the workshop. But let me know if you're interested.
09:01:10 <Bert> Phil: Interesting topic, but not sure I'll be able to join.
09:02:03 <Bert> dsr: Flip side of digital transformation is need for good security. But many orgs. still working with old computers.
09:02:33 <Bert> ... UK's NHS, e.g., very much based on paper processes.
09:03:14 <Bert> Phil: My org is trying to help them...
09:03:33 <phila> s/My org/NHSX/
09:03:49 <Bert> dsr: At least there is a common medical vocabulary.
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09:05:24 <Bert> -> https://www.w3.org/Data/events/tpac2019/digital-transformation.pdf Dave's slides
09:05:57 <Bert> dsr: Discussion topics:
09:07:03 <Bert> ... We can share use cases, collect ideas.
09:07:21 <Bert> ... 2nd part is technical details.
09:08:29 <Bert> ... Need ways to derive ontologies automatically, rather than by hand.
09:09:14 <Bert> ... "Easier RDF" project by David Booth.
09:10:34 <Bert> ... I did some hacking in August (during what W3C team calls "Geek Week").
09:11:14 <Bert> ... Simpler query languges.
09:11:35 <Bert> gkellogg: Did you look at GraphQL?
09:12:16 <Bert> dsr: Don't think I did, but th elist on my slide is not meant to be complete.
09:13:44 <Bert> Dave shows different queries (using Turtle syntax).
09:14:14 <Bert> Implementation runs in a browser.
09:15:03 <Bert> It fetches data and applies a query. Allows to step through the execution.
09:15:51 <Bert> dsr: Expressing both the rules and the data in RDF is meant to make machine learning easier.
09:16:46 <Bert> Phil: Is this really easier than Sparql?
09:17:04 <Bert> dsr: Don't know yet, needs experimenting.
09:17:33 <Bert> ... Sparql, like SQL, looks for patterns.
09:18:03 <Bert> ... The RDF approach allows building a state machine.
09:18:41 <Bert> ... Shacl could, with this approach, become a machine that does validation.
09:19:06 <Bert> ... RDF/Turtle not ideal. There may be easier ways.
09:19:55 <Bert> ... Looked at research in cognitive science, brain research.
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09:20:54 <Bert> ... Psychology uses the word "chunk" for a set of properties.
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09:22:51 <Bert> ... A link between chunks is also a (simple) chunk.
09:23:57 <Bert> ... But have to deal with noise, imprecise data. Need to combine symbolic and statistical approaches.
09:24:44 <Bert> ... Data is accessed via a small "buffer". Looks limiting, but allows scaling.
09:26:16 <Bert> Dave shows examples. One example is a model of how people count. You need rules that say which number follows which other number, it not not like a calculator.
09:27:00 <Bert> The demo shows how the rule that says 4 follows 3 is found and applied, then the next, etc.
09:27:21 <Bert> s/not/is not/
09:28:19 <Bert> Another demo shows a (simulated) car following a road.
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09:29:31 <Bert> dsr: Autonomous driving has rules that are spatial and temporal.
09:31:08 <Bert> ... There is a context as well. E.g., a book can describe a world that is like the real world, except for some rules.
09:32:11 <Bert> ... Imitiating human memory recall, finding probably useful information, dealing with noise.
09:33:34 <Bert> ... We can borrow from cognitive science, which has studied this since some time.
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09:34:58 <Bert> ... Learning and problem solving typically starts quite wild and gets more focused with experience.
09:36:01 <Bert> ... Use inspiration from brain, conscious and unconscious functions.
09:37:04 <Bert> ... Cognitive Agent could get info from distributed sources.
09:38:49 <Bert> ... Next steps? Collect use cases, data sets. Also figure out the economics, cost of collecting a data set.
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09:40:20 <Bert> Phil: Research organizations working together could do it.
09:40:48 <Bert> ... Sounds very advanced.
09:41:26 <Bert> dsr: Using the insights from research in other areas simplifies the problem.
09:41:35 <Bert> RRSAgent, make minutes v2
09:41:35 <RRSAgent> I have made the request to generate https://www.w3.org/2019/09/18-digital-transformation-minutes.html Bert
09:41:46 <Bert> present+
09:41:49 <Bert> RRSAgent, make minutes v2
09:41:49 <RRSAgent> I have made the request to generate https://www.w3.org/2019/09/18-digital-transformation-minutes.html Bert
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11:28:44 <dsr> rrsagent, make minutes
11:28:44 <RRSAgent> I have made the request to generate https://www.w3.org/2019/09/18-digital-transformation-minutes.html dsr
11:29:26 <dsr> s/Ditial/Digital/
11:29:36 <dsr> : rrsagent, make minutes
12:25:53 <Bert> Meeting: Breakout: Digital Transformation
12:26:09 <Bert> Chair: Dave Raggett
12:26:50 <Bert> -> https://w3c.github.io/tpac-breakouts/sessions.html#digital-transformation Session description
12:27:01 <Bert> RRSAgent, make minutes v2
12:27:01 <RRSAgent> I have made the request to generate https://www.w3.org/2019/09/18-digital-transformation-minutes.html Bert
12:28:02 <Bert> s/Ditial/Digital
12:28:50 <Bert> RRSAgent, make minutes v2
12:28:50 <RRSAgent> I have made the request to generate https://www.w3.org/2019/09/18-digital-transformation-minutes.html Bert
12:33:45 <Bert> s/: rrsagent, make minutes//
12:35:40 <Bert> s/th elist/the list
12:37:05 <Bert> RRSAgent, make minutes v2
12:37:05 <RRSAgent> I have made the request to generate https://www.w3.org/2019/09/18-digital-transformation-minutes.html Bert
12:38:17 <Bert> present+ joemedley
12:39:00 <Bert> present+ yoshiaki
12:40:10 <Bert> RRSAgent, make minutes v2
12:40:10 <RRSAgent> I have made the request to generate https://www.w3.org/2019/09/18-digital-transformation-minutes.html Bert
12:44:42 <Bert> present+ ??
12:44:45 <Bert> RRSAgent, make minutes v2
12:44:45 <RRSAgent> I have made the request to generate https://www.w3.org/2019/09/18-digital-transformation-minutes.html Bert
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