### Formalizing GDPR Article 5(1)(a) in RuleML
Source: https://github.com/oasis-tcs/legalruleml/blob/master/usecases/usecase1.md
This RuleML snippet formalizes the obligation for a controller to implement measures ensuring lawfulness, fairness, and transparency of personal data processing. It requires specific setup for data processing, data subjects, and controllers.
```RuleML
a1
edp
z
x
t1
ep
w
y
a2
t2
ei
ec1
ec2
ec3
ed
em
el
ef
et
```
--------------------------------
### First-Order Functions with ruleml:Fun and ruleml:Expr
Source: https://context7.com/oasis-tcs/legalruleml/llms.txt
Encode numeric comparisons and computed values using ruleml:Expr wrapping ruleml:Fun. This is useful for legal thresholds like minimum ages or deadlines.
```xml
x
z
w
ep
16
```
--------------------------------
### Parental Consent Rule with ruleml:Fun
Source: https://context7.com/oasis-tcs/legalruleml/llms.txt
This rule establishes lawfulness for processing a minor's data if they are below the consent age and parental consent is given. It uses `dapreco:ageOf` and `dapreco:HolderOfPR` as functional terms within atoms.
```xml
w
z
x
c
ep
ehc
```
--------------------------------
### Universal Rule with ruleml:Rule
Source: https://context7.com/oasis-tcs/legalruleml/llms.txt
Represents legal if-then norms using `ruleml:Rule` with universal closure. Variables are scoped within `ruleml:Exists`, and conditions are conjoined using `ruleml:And`. Deontic modalities are applied externally via `lrml:Context`.
```xml
a1
ep
edp
w
z
x
i
t1
y
en
eat
ic
```
--------------------------------
### LegalRuleML Rule for Minimum Age for Consent
Source: https://github.com/oasis-tcs/legalruleml/blob/master/usecases/usecase1.md
This RuleML snippet defines the minimum age for giving consent to data processing as 16, unless a specific exception is met. The exception is triggered if the Member State's minimum age for consent is lower.
```xml
x
z
w
ep
16
```
--------------------------------
### Negation-as-Failure with ruleml:Naf
Source: https://context7.com/oasis-tcs/legalruleml/llms.txt
Use ruleml:Naf to express that a predicate is false by default, enabling closed-world negation and defeasible rules. This is crucial for encoding exceptions in legal rules.
```xml
w
z
y
x
c
ehc
ep
```
--------------------------------
### Obligation Rule with Temporal Ordering for GDPR Art. 5(1)(a)
Source: https://context7.com/oasis-tcs/legalruleml/llms.txt
This rule models GDPR Art. 5(1)(a) by asserting that a consequent event must occur strictly after an antecedent event using `ruleml:After`. It is used to enforce temporal sequencing of legal duties.
```xml
a1
x
z
t1
ep
a2
t2
em
el
ef
et
ei
y
```
--------------------------------
### RuleML Atom for Data Processing Conditions
Source: https://github.com/oasis-tcs/legalruleml/blob/master/usecases/usecase1.md
This RuleML Atom defines conditions for data processing, including measures and their relation to lawfulness, fairness, and transparency.
```xml
```
--------------------------------
### LegalRuleML Rule for Age Exception
Source: https://github.com/oasis-tcs/legalruleml/blob/master/usecases/usecase1.md
This RuleML snippet defines an exception condition related to the age of the data subject. If the data subject's age is below the minimum age for consent, this rule triggers an exception, potentially blocking other rules.
```xml
a1
t1
edp
w
z
```
--------------------------------
### RuleML: Icon Attached to Communication
Source: https://github.com/oasis-tcs/legalruleml/blob/master/usecases/usecase1.md
This RuleML snippet defines a rule where if an icon is attached to a communication, it must be in machine-readable form. It uses 'dapreco:AttachTo' and 'dapreco:Icon' predicates.
```RuleML
eat
ic
```
--------------------------------
### RuleML Rule for Lawfulness with Consent Exception
Source: https://github.com/oasis-tcs/legalruleml/blob/master/usecases/usecase1.md
This RuleML rule defines that data processing is lawful if consent is given, unless an exception related to age applies. The exception is handled using negation-as-failure.
```xml
a1
t1
ehc
eau
edp
w
z
y
x
epu
c
ep
```
--------------------------------
### RuleML: Obligation for Machine-Readable Icon
Source: https://github.com/oasis-tcs/legalruleml/blob/master/usecases/usecase1.md
This RuleML rule formalizes an obligation: if an icon is attached to a communication between a controller and data subject, the icon must be in machine-readable form. It involves multiple predicates related to data protection and communication.
```RuleML
a1
ep
en
eat
el
edp
w
z
y
x
i
t1
ic
emr
```
--------------------------------
### GDPR Article 12(7) - Permission to Attach Icon Rule
Source: https://github.com/oasis-tcs/legalruleml/blob/master/usecases/usecase1.md
This RuleML snippet formalizes the statement 'If the controller provides information to the data subject, he is permitted to attach an icon'. It uses a standard first-order logic implication tagged as permission via the LegalRuleML tag 'lrml:Context'. Deontic reasoning is handled externally.
```RuleML
a1
ep
edp
w
z
x
i
t1
en
y
```
--------------------------------
### Numeric Comparison Rule for GDPR Consent Age
Source: https://context7.com/oasis-tcs/legalruleml/llms.txt
This rule implements GDPR Art. 8(1) by checking if a data subject's age is less than or equal to the minimum age for consent. If true, it fires an exception that blocks the consent lawfulness rule. It uses SWRL built-in comparison relations.
```xml
w
z
x
ep
```