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Re: Trust in statements (still is BioRDF Brainstorming)

From: M. Scott Marshall <marshall@science.uva.nl>
Date: Wed, 13 Feb 2008 23:14:49 +0100
Message-ID: <47B36BD9.200@science.uva.nl>
To: Matt Williams <matthew.williams@cancer.org.uk>
CC: Alan Ruttenberg <alanruttenberg@gmail.com>, public-semweb-lifesci hcls <public-semweb-lifesci@w3.org>

Dear Matt,

I see 'trust' as a 'view' that can be produced by running a filter over
the data (provenance). The filter would implement my trust policy, or
one of them. In other words, my trust in a given 'agent' can be due to
the fact that it produces data using a certain algorithm. I also place a
certain level of trust in the instrumentation that produced the data,
the p-values of an analysis in the processing pipeline, human operators
involved, etc. So, the weights or confidence measures that you are
describing and that Alan is qualifying would be the *output* of such a
trust policy or filter. I would not besmirch the data with my own
personal trust models nor easily trust those of others. ;) I guess that
what I'm trying to say is equivalent to Alan's point: I would prefer to
keep facts and their evidence disclosed symbolically in the data so that
different 'views' can take them into account.

But, before I go to build such 'views' or filters, I will wait for that
sort of information to become machine-readable as data provenance. :)

However, I *can* try to make that sort of information available for data
that I am helping to manage or produce. It seems that having a triple
store (such as Virtuoso) with named graph support would make it possible
to produce several types of potentially useful data provenence.


M. Scott Marshall

Matt Williams wrote:
> Dear Alan,
> Thank you for making my point much more clearly than I managed. I'm a
> little wary of probabilities in situations like the one you describe, as
> it always seems a little hard to pin down what is meant by them. At
> least with the symbolic approach, you can give a short paragraph saying
> what you mean.
> I'll try and find a paper on the "p-modals" (possible, probable, etc.)
> and ways of combining them tomorrow and put a paragraph on the wiki.
> Matt
> Alan Ruttenberg wrote:
>> I'm personally fond of the symbolic approach - I think it is more
>> direct and easier to explain what is meant. It's harder to align
>> people to a numerical system, I would think, and also provides a false
>> sense of precision. Explanations are easier to understand as well: "2
>> sources thought this probable, and 1 thought is doubtful" can be
>> grokked more easily than score: 70%
>> -Alan
>> On Feb 12, 2008, at 4:03 PM, Matt Williams wrote:
>>> Just a quick note that the 'trust' we place in an agent /could/ be
>>> described probabilistically, but could also be described logically.
>>> I'm assuming that the probabilities that the trust annotations are
>>> likely to subjective probabilities (as we're unlikely to have enough
>>> data to generate objective probabilities for the degree of trust).
>>> If you ask people to annotate with probabilities, the next thing you
>>> might want to do is to define a set of common probabilities (10 - 90,
>>> in 10% increments, for example).
>>> The alternative is that one could annotate a source, or agent, with
>>> our degree of belief, chosen from some dictionary of options
>>> (probable, possible, doubtful, implausible, etc.).
>>> Although there are some formal differences, the two approaches end up
>>> as something very similar. There is of course a great deal of work on
>>> managing conflicting annotations and levels of belief in the literature.
>>> Matt
>>> --http://acl.icnet.uk/~mw
>>> http://adhominem.blogsome.com/
>>> +44 (0)7834 899570
Received on Wednesday, 13 February 2008 22:15:00 UTC

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