Permaculture Information Web

[Richard Morris <webmaster AT pfaf.org>]

Chad Knepp wrote:
> Marco Stahl writes:
>  > > Von: Sean Maley <semaley AT yahoo.com>
>  > > > Example:
>  > > > 
>  > > > entity | parent
>  > > > ---------------
>  > > > creature NULL
>  > > > animal   creature
>  > > > plant    creature
>  > > > bean     plant
>  > > > hemp     plant
>  > > 
>  > > Where searches represent the fundamental activity with
>  > > the dataset, OLAP, we may consider keeping the schema
>  > > denormalized; creature_type: A, M, V (animal, mineral,
>  > > vegetable) rather than get into hierarchical data
>  > > sets.
>  > > 
>  > > --------------------
>  > > |creature_dimension|
>  > > --------------------
>  > > |creature_key      | : hemp, bean, etc
>  > > |creature_type_key | : A, M, V
>  > > |ground_depth      |
>  > > |height            |
>  > > |....              |
>  > > --------------------
>  > 
>  > Thats for sure faster and easier to implement.
>  > But I'm a friend of putting so much knowlege as possible into the modell 
> and
>  > the "source database".
>  > (And i'm influenced maybe to much from objectorientated programming)
>  > 
>  > Something like 
>  > 
>  > entity     |  output
>  > ----------------------
>  > Leguminosae  nitrogen
>  > animal       shit
>  > 
>  > would simplefy the adding of new plants(and other entitys), creating
>  > patterns for groups of plants(and other entitys), adding/changing 
>  > properties/patterns for whole plant(entity)groups.
>
> My proposal attempts to solve this with the use of sets.  Example:
>
> entity              |  output
> --------------------------------------
> set(all Leguminosae)   nitrogen fixing
>
>  > If the system is to slow in the end, we can use cached demormalized , 
> "flat"
>  > entity/input/output/whatever-tables for increasing search-speed.
>  > There is no reason to go through the hierarchy every time but its good to
>  > have the hierarchy in the background.
>
> Premature optimization is the root of all evil ;-)
>
>  > Saludos, Marco
>
> Ok, I'm still not sure about why this is important but I see it at
> best as being 5-6 levels of hierarchy which will not affect
> performance.  Something like: 
>
>   entity | parent
>   ---------------
>   creature NULL
>   animal   creature
>   plant    creature
>   leguminosae plant
>   soya     leguminosae
>   max      soya
>   'Chiffumy' max
>
> The real problem with this is that entity will not be unique which
> requires you to know a little more about the entity than just the top
> level.  Starting with the just cultivar for example may lead to a
> tomato, an apple, and a flower.

The following is the types of relationship offered by the
OWL Web Ontology Language. These are generally the bits in the middle
of a relationship

Class (Thing, Nothing)
    * rdfs:subClassOf
    * rdf:Property
    * rdfs:subPropertyOf
    * rdfs:domain
    * rdfs:range
    * Individual
Allows an Object oriented structure to data.

(In)Equality:
    * equivalentClass
    * equivalentProperty
    * sameAs
    * differentFrom
    * AllDifferent
    * distinctMembers
Whether two plants are the same?


Property Characteristics:
    * ObjectProperty
    * DatatypeProperty
    * inverseOf
    * TransitiveProperty
    * SymmetricProperty
    * FunctionalProperty
    * InverseFunctionalProperty
These can express if a relationship is bidirectional or uni directional.


Property Restrictions:
    * Restriction
    * onProperty
    * allValuesFrom
    * someValuesFrom

Restricted Cardinality:
    * minCardinality (only 0 or 1)
    * maxCardinality (only 0 or 1)
    * cardinality (only 0 or 1)
Is this a 1 to 1 or 1 to many relationship?

Header Information:
    * Ontology
    * imports

Class Intersection:
    * intersectionOf

Versioning:
    * versionInfo
    * priorVersion
    * backwardCompatibleWith
    * incompatibleWith
    * DeprecatedClass
    * DeprecatedProperty

Annotation Properties:
    * rdfs:label
    * rdfs:comment
    * rdfs:seeAlso
    * rdfs:isDefinedBy
    * AnnotationProperty
    * OntologyProperty

Datatypes
    * xsd datatypes

OWL is generally used with RDF triples and provides a lot of the basic 
machinary needed to construct a sospticated structure.

Some of the above discssion seems to relate t some of the QWL concepts.

OWL constructs would allow us to express the different types of 
relationship. For examples
we could say that
        "Heigth is a property of a Plant"

It might make discussions easier as it gives a vocabulary for
discussing how to do relationships well.

        ttfn

        Rich