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

From: Provenance Working Group Issue Tracker <sysbot+tracker@w3.org>
Date: Sun, 23 Oct 2011 23:04:45 +0000
To: public-prov-wg@w3.org
Message-Id: <E1RI75x-0003PW-Fq@barney.w3.org>

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


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 -


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 Sunday, 23 October 2011 23:04:46 UTC

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