W3C home > Mailing lists > Public > public-prov-wg@w3.org > October 2011

Re: PROV-ISSUE-134: Non-Human Agent vs. Human Agent [Data Model]

From: Graham Klyne <GK@ninebynine.org>
Date: Tue, 25 Oct 2011 11:59:38 +0100
Message-ID: <4EA6969A.9090908@ninebynine.org>
To: public-prov-wg@w3.org
BTW, full citation for that paper:

Ryan Shaw, Raphaƫl Troncy and Lynda Hardman. LODE: Linking Open Descriptions of 
Events. In 4th Annual Asian Semantic Web Conference (ASWC'09), vol. LNCS 5926, 
pages 153-167, Shanghai, China, December 6-9, 2009, (doi).



On 25/10/2011 09:51, Graham Klyne wrote:
> This viewpoint is possibly supported by some work mentioned in a recent paper
> from the #derive2011 workshop(?):
> http://www.eurecom.fr/~troncy/Publications/Troncy_Shaw-aswc09.pdf (I don't have
> a formal citation for this yet, as the link came to me via a recent twitter
> conversation.)
> A number of the event ontologies surveyed seem to make a similar distinction.
> I think this whole area of event modelling is very relevant for provenance, as
> the more I look at the provenance model, the more it looks like an
> event-mediated structure for talking about the production of Entities. I think
> the survey in the above paper is worth reading.
> #g
> --
> On 24/10/2011 00:04, Provenance Working Group Issue Tracker wrote:
>> PROV-ISSUE-134: Non-Human Agent vs. Human Agent [Data Model]
>> http://www.w3.org/2011/prov/track/issues/134
>> Raised by: Reza B'Far
>> On product: Data Model
>> I propose to revisit the previously discussed, but not concluded, topic of
>> "Types" of Agents. I had brought up this topic and the following was suggested
>> as a reference -
>> http://sourceforge.net/apps/mediawiki/trdf/nfs/project/t/tr/trdf/7/7a/ProvenanceVocabularyOverview.png
>> There are a large set of use-cases (not just in my particular interest of
>> Governance) where, whether the actions of an agent are directly controlled by
>> a human being versus an automated mechanism makes a very significant
>> difference in inferencing over the available instance data. Examples:
>> 1. Human agent modifying a legal document versus the legal document being
>> modified by a system agent that converts data formats.
>> 2. Human agent modifying a setting in a system whose provenance model is
>> important for governing that system versus a system agent doing the same:
>> Example - Provenance of a "License" where Human agent expiring a license by
>> changing/enforcing a date is quite a different event than a system agent
>> changing/enforcing a date (say as a part of a mass/cascade update to a series
>> of records) that causes expiration of a license.
>> Other use-cases are available if need-be. I actually claim that the number of
>> such use-cases are increasing given the proliferation of pipe-and-filter
>> architectures being deployed within Big Data infrastructures (where either
>> pipes or filters can be Non-Human Agent/Actors). Furthermore, as another
>> evidence, there are other references to UML Use-Case and Sequence Diagrams
>> where the distinction is becoming prevalent.
>> As a solution, I suggest we take the same approach that the aforementioned URL
>> above has taken.
Received on Tuesday, 25 October 2011 11:58:26 UTC

This archive was generated by hypermail 2.4.0 : Friday, 17 January 2020 16:51:03 UTC