On 14 August 2015 at 12:56:24 am, Wyner, Adam Zachary (
azwyner@abdn.ac.uk ) wrote:
Hi Tara,
Thanks for the note and for the presentation at RuleML. And for the movie recommendation….
Some off-the-cuff (and defeasible) responses to your notes….
it is mentioned in in my bio here:
https://www.oasis-open.org/people/distinguished-contributor/monica-palmirani You know that LegalRuleML is like a "baby" for me.
I am preparing the new version of the documentation for the next meeting.
Some feedbacks from RuleML Symposium and from the tutorial session in order to take in care ?
I thought I sent this to the LegalRuleML list after the tutorial, but apparently I sent it to the wrong email address:
I got a lot of questions from the tutorial presentation.
There was interest in how LegalRuleML will be adapted to the individual legal systems, and then how would they interoperate.
As I understand it, LegalRuleML has no conception of 'individual legal systems' per se. Rather, all of the contextualisation components should be able to handle that. In addition, I understood the intention to be that laws no matter where would be expressed
in the 'language' of LegalRuleML. Interoperability is intended to be 'guaranteed' by having any law written in the same ML. However, it remains to be seen just how LegalRuleML is used and whether issues arise that require adaptation.
I agree with Adam. Indeed, we have to see if RuleML will be used to determine what adaptations are needed.
A student (Xin Sun) with some background in deontic knowledge wanted to know if our Permission concept is only positive permission. ( I waffled.) On Monday he presented a paper about STIT (
http://www.slideshare.net/ruleml2012/ruleml2015-inputoutput-stit-logic-inputoutput-stit-logic ),
which appears to be a deontic logic which adds agency to propositional logic.
STIT = "Sees to it that" is an early form of deontic logic, usually a generic _expression_ over actions and focusing on the result (meaning it does not specify what the action is that brings the result). This language has always had an agent as in "Bill
sees to it that the pizza is delivered to Jill". Doesn't LegalRuleML also tie an agent to an action and as the bearer of the modal role - Bill must pay the penalty to Jill - has Bill as the agent of paying the penalty and as the one who is obligated.
Indeed we have agency in LegalRuleML. I’m not sure I/O logics are really suitable for modelling real life norms. For example, you cannot have deontic operators in the input part.
There was a little confusion about the expressivity of an RDF-based syntax - it was necessary to explain that, like OWL in RDF/XML syntax, the expressivity is not limited by the utilization of an RDF metamodel. There was additionally interest in the application
of defeasibility at lower expressivitiies. After some discussion, we concluded that defeasibility is not relevant at the level of RDFS or less unless there is an explicit mechanism for asserting conflicts, which would increase the expressivity of the language.
Don't I understand the issue here.
There was also a question about the reasons for the selection of XML, especially since there was an earlier presentation by Geoff Sutcliffe in which he heavily critisised XML.
I'd have to understand the criticisms of XML.
There was a law student in the tutorial (Christine from Brazil) who is developing a legal ontology . She wanted to know if LegalRuleML would have its own legal ontology. I asked her to send me her papers.
LegalRuleML is not intended to have its own legal ontology, and we were deliberately neutral on this point. Yet, one wonders how long that position can be sustained.
The issue of ontologies is related to different legal systems. For example, the concept of “crime” in the Italian legal system is different form the concept of “crime” in the Australian legal system, and these are defined in Sections of Acts/Codes. Furthermore,
it Italy, the concept of crime is different in criminal law and in civil law, and both concepts are defined by articles of the Criminal Code and the Civil Code.
I met Sagar Sunkle from Tata Consultancy in India who is using DR-prolog for proofs of regulatory GRC (governance, risk and compliance). An interesting twist is the explanation of non-compliance for purpose of negations.
Sounds like a point worth expanding on.
Not sure to understand what you mean "explanation of non-compliance for purpose of negations”/ For what I know they look at norms represented as defeasible rules and given a case (set of facts) you use the rules to determine what are the obligations in force
for that cases. The explanation is to produce a derivations. The derivation is the explanation of the case. In LegalRuleML we have (legal) sources associated with rules, the explanation can be understand as which norms have been used, and whether they have
been violated or complied with.
All the best
Guido
I spoke to Tom Gordon this morning (who did not attend the LegalRuleML tutorial). He did attend the API4KP presentation, and managed to divert the Q&A period to a discussion with a question about the uptake of MOF metamodels, which was
answered at length by John Hall.
Chuckle.
Cheers,
Adam
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