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Re: What would you build with a web of data? Decision support

From: Wolfgang Orthuber <orthuber@kfo-zmk.uni-kiel.de>
Date: Tue, 13 Apr 2010 18:08:48 +0100
Message-ID: <4BC4A520.30204@kfo-zmk.uni-kiel.de>
To: Georgi Kobilarov <georgi.kobilarov@gmx.de>
CC: public-lod@w3.org
Hi Georgi,

First let me underline that the following is not a detached theory, it 
is very practical:

The web of data can support the clinician in his cycle of decision:

(a)    The clinician makes measurements (in the broadest sense, also 
speaking with the patient and looking at a picture is a measurement).
(b)    The clinician focuses on those measurement results which are 
interesting for his therapeutic decisions (feature extraction).
(c)    The clinician compares these measurement results with experience. 
At this he may use rules or models which are derived from common experience.
(d)    The clinician decides for therapy, and measures the effect of his 
decision, i.e. the cycle starts again with (a).

Good and large experience is very important for step (c).

The cycle of decision (measurements - feature extraction - comparison 
with experience - decision) is also effective outside medicine: Before 
every conscious decision we *compare* decision relevant data with 
experience (or a model which is derived from common experience). 
Experience says, at *similar* situations possibility X yields better 
results than other possibilities, so we decide for possibility X. Even 
if we try to decide best, our decisions are suboptimal due to limited 
experience.

The web of data can be designed in a way, that it collects experiences 
(also decision relevant measurements of machines) in a precise and 
*comparable* way (much more precise and better comparable than text). So 
the web of data can summarize experiences in well defined comparable way 
for decision support.

For this a clear similarity relation is necessary. The natural way to do 
this is a vectorial description of resources, i.e. quantification of the 
resource's properties and regarding the result (a sequence of numbers) 
as vector. After defining an appropriate metric (distance function) we 
can calculate similarity of vectors by calculating the distance between 
them - the less the distance, the more similar are the vectors and (in 
case of good quantification) the original resources.     Using HTTP URIs 
allows that all domain name owners can define these vectors and 
optimized distance functions.

Therefore i suggest to introduce standardized "Vectorial Resource 
Descriptors" (VRDs) on the WEB - and it seems the best possibility to 
integrate these in Linked Data. The paper 
http://www.orthuber.com/wp1.pdf describes details. It is not completely 
up to date, and though the basal content of the VRDs (and Vector Space 
Descriptors - VSDs) is clear, I have not been sure about the syntax of 
the RDF examples (Chapters 2.2.2 and 2.2.3 currently) - and I would like 
to adapt the syntax to suggestions from the community.

So comments and suggestions are very welcome!

Best

Wolfgang


Georgi Kobilarov schrieb:
> Yesterday issued a challenge on my blog for ideas for concrete linked open
> data applications. Because talking about concrete apps helps shaping the
> roadmap for the technical questions for the linked data community ahead. The
> real questions, not the theoretical ones...
>
> Richard MacManus of ReadWriteWeb picked up the challenge:
> http://www.readwriteweb.com/archives/web_of_data_what_would_you_build.php
>
> Let's be creative about stuff we'd build with the web of data. Assume the
> Linked Data Web would be there already, what would build?
>
> Cheers,
> Georgi
>
> --
> Georgi Kobilarov
> Uberblic Labs Berlin
> http://blog.georgikobilarov.com
>
>
>
>
>   
Received on Tuesday, 13 April 2010 16:05:27 UTC

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