Thank you, Hans, for your reply, and I like the foundations of your
view. Your traffic example is of course also interesting. (01)
> ... By scope of the data sets I mean what portion of reality does the
> data set purport to represent. (02)
The "portion of reality" I have worked with mostly has been nomenclature
and ontology in health and social care. The scope of nomenclature in
health care is easier as it is rooted in WHO's references classification
together with the other classifications, where the scope then is
diagnosis, functioning, drugs, lab/markers, etc. The scope of
nomenclature is social care is harder as it indeed involves that
"functioning" and behaviour. This dialogue between nomenclatures is very
visible e.g. in the area of "active and healthy ageing". The more it's
seniors and older persons, clearly the more its medical than social,
because it moves more and more to severity of disorder. And similarly,
the more it's about "teeniors" ("teenaged" seniors), the more it goes
towards the "quantified self" movement, where emphasis is on
“empowerment” and citizens/patients “managing their own data”. Focus is
then not always just on health but on performance more in general. I
even see a golf score app as such a quantified self app where I can add
numbers in order to have golf shot stats and summaries about how I
behave from the tee and around the green. Apple’s new Health Kit is
launched as such a quantified self app and is made for promoting the use
of Apple’s mobile phone. Apple mentions Mayo as a partner and also the
Epic record system for potential integration but the profession is not
convinced. Google's GoogleFit is maybe response also to Samsung’s Sami.
Google’s approach is more device oriented than in Apple’s approach, and
so is Sami, but Samsung’s approach is integrated to their overall scope
of medical devices. Samsung has been working on medical devices already
for a long time and is in fact in the same league as Philips, Siemens
and GE. Microsoft’s HealthVault is closer to HealthKit but the ambition
is broader obviously since the Microsoft Health unit has been around for
quite a while. Microsoft understands health records better than Apple,
and Microsoft indeed is operating systems and computer languages more
than as compared to Apple, and more than Samsung. Another aspect here is
the emerging mHealth market, where “mobile medical” devices and
solutions will eventually need to go down the same path of approvals as
compared to other medical devices and drugs. The approval procedures
are, however, yet to be defined. (03)
Our logical approach to health nomenclature is part of several EU
activities (EIP AHA, AAL) and now also included in a number of H2020 PHC
(Personalized Health Care) proposals. (04)
To me this a fascinating scope since the logical approach can be
extended (I think) into "many related scopes" and ages, and also down
e.g. to assessment of adolescent learning. The "ontology dependent
industry" seems not fully to understand this need of being more formal
about the underlying structures, and I claim we focus too much on
natural language at large. (05)
As you may infer, I am indeed interested in understanding the relation
between physical and mental well-being, capacities to learn and
function, and as affecting individuals being part of group. We have a
long way still to go, and the "ontology dependent industry" seems
equally far away from broad solutions. (06)
So I think you are indeed perfectly right on target about that "portion
of reality". My take is to go from specific scopes, like health
ontology, and to generalize from there. I also want to say I am not very
fond of health ontology approaches like OpenClinical, OpenEHR or SNOMED
CT. They are "too relational" so "structure" is basically missing. It
becomes just graphs, and they do not possess explanatory power enough
e.g. for those reference classifications. (07)
> ... air traffic patterns from data sets ... differences in
> representation and complexity of such data by the different sources (08)
Some years ago I was involved in a larger project on crisis management
and our contribution was related to interoperability of the "blue
lights". Again we focus more on the emergency care "blue light" since
there we have already some nomenclature, guidelines and care processes
available. Anyway, the within and between blue lights dialogues are very
interesting all the way from first responders up to management. (09)
> ... how big a portion of what one is looking for does Big Data
> represent? ... I'm not sure this is totally a question of logic. (010)
I obviously agree on that "not totally", and saying logic is part of it,
even if I think it plays a very important part. Logic is indeed part of
the "logic of its ontology", and I mean logic in a much broader sense,
yet formal. We have developed a "lative" view of logic. This is not well
known, but it is our tools in what we do and develop. You will find a
bit of this under GLIOC (www.glioc.com). (011)
I often say we neglect "process" as in "information & process".
"Information and logic languages" are quite well developed, but "process
languages" are still in their infancy. We've used logic extension of
BPMN to encode clinical guidelines, but we also realize it can be done
in many different ways. When we speak of "big data" I indeed think we
have neglected almost completely all those "big processes" within which
"big information" is produced and utilized. (012)
Best, (013)
Patrik (014)
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