In SHOIN(D) that is equivalent to the DL family used by OWL-DL;
Is this expression legal:
F ⊑ (≤1 r. D) ⊓ (￢ (=0 r. D))
Where F, D are concepts, r is a role. I want to express that each instance of F is related to at most one instance of D through r, and not to zero instances.
In general, how to decide that some expression is legal w. r. t. a specific variation of DL? I thought that using BNF syntax of the variation may be what I'm targeting.
One easy way is to check whether you can write it in Protege. Most of the things that you can write in Protege will be legal OWL-DL. In Protege you can write:
F SubClassOf ((r max 1 D) and not(r exactly 0 D))
Of course, saying that something has at most 1 value, and not exactly one would be exactly the same as saying that it has exactly 1:
F SubClassOf r exactly 1 D
But there are a few things that you'll be able to do in Protege that won't be legal OWL-DL. The more direct way to find out what these are is the standard, specifically §11 Global Restrictions on Axioms in OWL 2 DL. Generally the only problems you might run into is trying to use composite properties where you're not allowed to.
If you don't want to check by hand, then you could try uploading your ontology into the OWL Validator and selecting the OWL2 DL profile.
Related
I am trying to understand the following axioms of OWL 2 but don't know what kind of axioms they are. here R is role and C is class
∃R ⊑ C
∃R ⊑ ∃R.C
C ⊑ ¬∃R
∃R ⊑ ¬C
As far i think 1 gives information about Range of R,but i am not sure. Thanks
The only way to make sense of these axioms is to understand the semantics of the Description Logic constructors used:
∃R is the short form of ∃R.T (where T refers to the top concept which represents the complete domain). Mathematically
(∃R.T)^I = {x ∈ δ^I | A y exists such that (x, y) ∈ R^I and y ∈ T^I}
This states that ∃R.T represents the set of individuals consisting of x such that x is associated via relation R to at least 1 individual y that is in top (the domain of discourse). If we had ∃R.C rather than T, y will be in C.
C ⊑ D states that all individuals of type C are also of type D. That is C is a subset of D.
∃R ⊑ C means all the individuals linked to at least 1 individual via relation R is a subset of C. That is why ∃R ⊑ C is also known as a domain axiom because it enforces that for all relations (x, y) in R, that x will be of type C.
¬C defines all the individuals that are not of type C in the domain of interpretation.
Going through the rest of these axioms in a similar way will help you to understand their meaning.
I'm revising for coming exams, and I am having trouble understanding an example question regarding the closure of attributes. Here is the problem:
AB→C
BE→I
E→C
CI→D
Find the closure of the set of attributes BE, explaining each step.
I've found many explanations of the method of closure when the given step is a single entity type, say 'C', using Armstrong axioms, but I don't understand how to answer for 'BE'.
First, you are confusing two very different things, attributes and entity types. Briefly, entity types are used to describe the real world entities that are modelled in a database schema. Attributes describe facts about such entities. For instance an entity type Person could have as attributes Family Name, Date of Birth, etc.
So the question is how to compute the closure of a set of attributes. You can apply the Armstrong’s axioms, trying at each step to apply one of them, until possible, but you can also simplify the computation by using the following, very simple, algorithm (and if you google "algorithm closure set attributes" you find a lot of descriptions of it):
We want to find X+, the closure of the set of attributes X.
To find it, first assign X to X+.
Then repeat the following while X+ changes:
If there is a functional dependency W → V such as W ⊆ X+ and V ⊈ X+,
unite V to X+.
So in your case, given:
AB → C
BE → I
E → C
CI → D
to compute BE+ we can procede in this way:
1. BE+ = BE
2. BE+ = BEI (because of BE → I)
3. BE+ = BEIC (because of E → C)
4. BE+ = BEICD (because of CI → D)
No other dependency can be used to modify BE+, so the algorithm terminates and the result is BCDEI. In terms of Armstrong’ axioms, the step 1 is due to Reflexivity, while the steps 2 to 4 are due to a combination of Transitivity and Augmentation.
As it says in the title I have trouble understanding why if we have X->A and Y->B then why is it wrong to write XY->AB. They way I understand it, if A is functionally dependent of X and B is functionally dependent of Y, then when we have XY on the left side we should have their corresponding values on the right side. Anyway my book says that this is wrong, so can anyone give me an example where this is proven wrong ? Thanks in advance :)
You're going about this the wrong way.
In order for "{X->A, Y->B}, therefore XY->AB" to be true, you need to prove that you can derive XY->AB from {X->A, Y->B}, using only Armstrong's axioms and the additional rules derived from Armstrong's axioms.
If X uniquely determines A and similarly Y uniquely determines B ,then any combination of XY uniquely determines AB.
Hence , X->A ,Y->B infers XY->AB is true.
More supporting links.
http://en.wikipedia.org/wiki/Functional_dependency…
See the composition rule here. Not crebile enough ?
Then in the following link , Slide 9 says that
Textbook, page 341: ”… X A, and Y B does not imply that XY AB.”
Prove that this statement is wrong.
http://www.ida.liu.se/~TDDD37/fo/fo-normalization
Moreover, Mike's answer is trying to prove the "vice versa" , which may not necessarily be true.
I have:
U-> PT….. 1
Q-> SU……2
etc...
in using the reflexivity axiom can I then say
Q-> S , Q-> U
Q-> PT
I trying to ask how this axiom works using the example above.
To derive
Q->S
Q->U
from
Q->SU
I'd use the decomposition rule, not the reflexivity axiom. Then I'd apply the transitivity axiom to Q->U, U->PT to derive Q->PT.
If you're asking what the reflexivity axiom means, it means
If Y is a subset of X, then X->Y.
In your example, it looks like you might be trying to say that
SU is a subset of Q, therefore Q->S and Q->U.
But it's not given that SU is a subset of Q. To make sure you get this point, Q->SU doesn't mean SU is a subset of Q.
For example, if you're in the military, your last name and blood type (among other things) are functionally dependent on your service number. Let's let the service number attribute be represented by "S", last name by "L", and blood type by "B". Then
S->LB
But neither "last name" nor "blood type" are subsets of "service number".
On the other hand, let's imagine that you're given this to start with.
U->PT
Q->SU
Q = {SUV} (New information!)
Since Q={SUV}, {S} is a subset of {SUV}, and {U} is a subset of {SUV}, then you can apply the reflexivity axiom to derive
Q->S (or SUV->S)
Q->U (or SUV->U)
But that axiom only applies in this example because you're given Q={SUV}.
I am half way reading the OWL2 primer and is having problem understanding the universal quantification
The example given is
EquivalentClasses(
:HappyPerson
ObjectAllValuesFrom( :hasChild :HappyPerson )
)
It says somebody is a happy person exactly if all their children are happy persons. But what if John Doe has no children can he be an instance of HappyPerson? What about his parent?
I also find this part very confusing, it says:
Hence, by our above statement, every childless person would be qualified as happy.
but wouldn't it violate the ObjectAllValuesFrom() constructor?
I think the primer actually does quite a good job at explaining this, particularly the following:
Natural
language indicators for the usage of
universal quantification are words
like “only,” “exclusively,” or
“nothing but.”
To simplify this a bit further, consider the expression you've given:
HappyPerson ≡ ∀ hasChild . HappyPerson
This says that a HappyPerson is someone who only has children who are also HappyPerson (are also happy). Logically, this actually says nothing about the existence of instances of happy children. It simply serves as a universal constraint on any children that may exist (note that this includes any instances of HappyPerson that don't have any children).
Compare this to the existential quantifier, exists (∃):
HappyPerson ≡ ∃ hasChild . HappyPerson
This says that a HappyPerson is someone who has at least one child that is also a HappyPerson. In constrast to (∀), this expression actually implies the existence of a happy child for every instance of a HappyPerson.
The answer, albeit initially unintuitive, lies in the interpretation/semantics of the ObjectAllValuesFrom OWL construct in first-order logic (actually, Description Logic). Fundamentally, the ObjectAllValuesFrom construct relates to the logical universal quantifier (∀), and the ObjectSomeValuesFrom construct relates to the logical existential quantifier (∃).
I am facing the same kind of issue while reading the "OWL 2 Web Ontology Language Primer (Second Edition - 2012)" and I am not convinced that the answer by Sharky clarifies the issue.
At page 15, when introducing the universal quantifier ∀, the book states:
"Another property restriction, called universal quantification is used to describe a class of individuals for which all related individuals must be instances of a given class. We can use the following statement to indicate that somebody is a happy person exactly if all their children are happy persons."
[I omit the OWL statements in the different sintaxes, they can be found in the book.]
I think that a more formal and may be less ambiguos representation of what the author states is
(1) HappyPerson = {x | ∀y (x HasChild y → y ∈ HappyPerson)}
I hope every reader understands this notation, because I find the notation used in the answer less clear (or may be I am just not accustomed to it).
The book proceeds:
"... There is one particular misconception concerning the universal role restriction. As an example, consider the above happiness axiom. The intuitive reading suggests that in order to be happy, a person must have at least one happy child [my note: actually the definition states that every children should be happy, not just at least one, in order for his/her parents to be happy. This appears to be a lapsus of the author]. Yet, this is not the case: any individual that is not a “starting point” of the property hasChild is a class member of any class defined by universal quantification over hasChild. Hence, by our above statement, every childless person would be qualified as happy . ..."
That is, the author states that (assume '~' for logical NOT), given
(2) ChildessPerson = { x | ~∃y( x HasChild y)}
then (1) and the meaning of ∀ imply
(3) ChildessPerson ⊂ HappyPerson
This does not seem true to me.
If it were true then every child, as far as s/he is a childless person, is happy and so only some parents can be unhappy persons.
Consider this model:
Persons = {a,b,c}, HasChild = {(a,b)}, HappyPerson={a,b}
and c is unhappy (independently from the close world or open world assumption). It is a possible model, which falsifies the thesis of the author.