RE: current uses cases

Hi all,

> The classificationb is usefull .. but it seems to be a combination of
2
> classification schemmes:
> - a first one after "rule language issues" such as scoped negation or
> frame-based representation
> - a second one after applications.
> May I suggest to give both, leaving some use cases unmentioned in one
> classification if information is missing?

Francois, that's the same conclusion I quickly came to when looking all
the use cases over.

Below (and attached) is the first use case classification scheme, i.e.
application. Some groupings are more natural than others (due to level
of abstraction, etc.), but hopefully the classification is still useful.

David

***

Classification Scheme 1: Applications

(The convention <organization>-<submission#>.<usecase#> is used for
those
submissions that include multiple use cases.)

Note that CG-1.4: Fuzzy Brain Anatomy is the same as IVML-NTUA-1



Academia (Education/Research)
       FZI-1 Ontology Mapping with OWL and Rules

       SB-2 Frame-based representation, Inheritance of defaults,
Reification


Business
       FZI-2 Enterprise Information Integration

       HP-1 Message transformation
       HP-2 Conditional message transformation
       HP-3 Data integration and query transformation

       ILOG-1 Import of Business Rules Defined by a Business Partner
into ILOG JRules

       NRC-1 Information integration with rules and taxonomies

       REWERSE-1.1 Negotiation I: Automated trust establishment for
eCommerce

       RuleML-1: e-Commerce Fraud Detection


Entertainment
       DERI-1 Internet search: combining query language, rule languages
and scoped negation


Medicine
       CG-1.1: A Web rule extension compatible with OWL DL
       CG-1.3: Safe integration of OWL DL with rules with clear
semantics
       CG-1.4 / IVML-NTUA-1 Fuzzy Reasoning with Brain Anatomical
Structures
       CG-1.5: a language combining ontology and rules for semantic
integration of heterogeneous information
       CG-1.6 Interoperating between ontology and rules
       CG-1.7 Combining ontologies and rules
       CG-1.8: Reasoning with rules for building and validating
ontologies

       REWERSE-1.2 Negotiation II: Automated trust establishment for
accessing medical records

       SB-1 Scoped negation, Encapsulation


Other
       CG-1.2 limitations of a "mapping" approach

       HP-4 Constraint expression
       HP-5 Definition/implementation of RDFS, SKOS and similar
semantics

       MITRE-1 Spectrum Policy Deployment  In The World of Cognitive
Radios


Personal Information Management
       NRC-2 FOAF rules

       REWERSE-1.5 Rule-based email manipulation


Travel
       FUB-1 Managing incomplete information

       REWERSE-1.3 Rule-based personalisation: Organising a vacation
with friends
       REWERSE-1.4 Rule-Based Intelligent Guiding
       REWERSE-1.6 Rule-based reactive organiser

-----Original Message-----
From: Francois Bry [mailto:bry@ifi.lmu.de] 
Sent: Friday, December 09, 2005 5:04 AM
To: Mei, Jing
Cc: public-rif-wg@w3.org; Hirtle, David
Subject: Re: current uses cases

Dear All,

The classificationb is usefull .. but it seems to be a combination of 2
classification schemmes:

- a first one after "rule language issues" such as scoped negation or
frame-based representation

- a second one after applications.

May I suggest to give both, leaving some use cases unmentioned in one
classification if information is missing?

Regards,

Francois (Bry)

Mei, Jing wrote:

>Hi, all,
>
>As it seems, there are currently 19 uses cases submitted to the RIF
list, as shown below. David Hirtle is looking into having a rough
classification of these into domain areas covered.
>
>Thanks,
>Jing
>
>
>HP (5)
>	Message transformation
>	Conditional message transformation
>	Data integration and query transformation
>	Constraint expression
>	Definition/implementation of RDFS, SKOS and similar semantics
>
>SB (2)
>	Scoped negation, Encapsulation
>	Frame-based representation, Inheritance of defaults, Reification
>
>FZI (2)
>	Ontology Mapping with OWL and Rules
>	Enterprise Information Integration
>
>NRC (2)
>	Information integration with rules and taxonomies
>	FOAF rules
>
>RuleML (1)
>	e-Commerce Fraud Detection
>
>FUB (1)
>	Managing incomplete information
>
>IVML-NTUA (1)
>	Fuzzy Reasoning with Brain Anatomical Structures
>
>REWERSE (1) (including 6 sub-usecases)
>	Negotiation I: Automated trust establishment for eCommerce
>	Negotiation II: Automated trust establishment for accessing
medical 
>records
>	Rule-based personalisation: Organising a vacation with friends
>	Rule-Based Intelligent Guiding
>	Rule-based email manipulation
>	Rule-based reactive organiser
>
>MITRE (1)
>	Spectrum Policy Deployment
>
>DERI (1)
>	Internet search: combining query language, rule languages and
scoped 
>negation
>
>ILOG (1)
>	Import of Business Rules Defined by a Business Partner into ILOG

>JRules
>
>University of Manchester (1)
>	Semantic Web Rules: Use Cases and Requirements for Health Care
and 
>Life Sciences
>
>  
>


--
Francois Bry
http://rewerse.net  scientific coordinator http://www.pms.ifi.lmu.de
head of unit