Kosmion Conceptual Foundations

gufo differentiates between comparative and material relationships. what is the benefit?

In gUFO, the distinction between comparative and material relationships provides a structured way to represent different types of relationships with distinct characteristics, helping to improve both semantic clarity and ontological rigor. Here’s a breakdown of the benefits of differentiating between these two types of relationships:

1. Comparative Relationships:

• Definition: Comparative relationships are used to describe relationships where the connection is established by comparing properties or states between entities. Examples include relationships like "taller than," "more experienced than," or "closer to."
• Benefits:
  • Simplifies Modeling Comparisons: By creating a distinct type for comparative relationships, it becomes easier to model and understand relationships based on relative characteristics. This distinction ensures that these relationships are represented more appropriately, without implying material interaction.
  • Prevents Confusion with Physical Relationships: Comparative relationships do not imply any physical, causal, or social interaction between entities. By having a separate class for them, it reduces potential confusion between mere comparisons and relationships that have more ontological implications.

2. Material Relationships:

• Definition: Material relationships represent actual interactions or connections between entities in a given context. These could include causal, social, or even physical relationships, such as "employed by," "married to," or "connected to."
• Benefits:
  • Captures Real Interactions: Material relationships are meant to capture meaningful connections or interactions that exist in the real world. This helps in representing the ontological reality more precisely.
  • Clearer Modeling of Dependency: Material relationships often come with implications for the dependencies or commitments between the entities involved. This is particularly important for modeling scenarios where a change in one entity impacts the other (e.g., a person being employed by a company has certain obligations and expectations).

Key Benefits of Differentiation:

1. Semantic Clarity:

   • Differentiating between comparative and material relationships adds semantic clarity to an ontology. This distinction ensures that different types of relationships are not misinterpreted, especially when dealing with complex models where both types of connections can occur.

2. Improved Reasoning:

   • By defining these distinctions explicitly, it becomes possible to improve the reasoning capabilities of an ontology. For instance, comparative relationships typically don’t imply direct changes to the state of an entity, whereas material relationships might. Having these clear distinctions can help reasoners to infer more accurate implications based on the type of relationship.

3. Enhanced Query Capabilities:

   • When querying an ontology, users can be more specific about the kinds of relationships they are interested in. For example, you could query only material relationships to find meaningful interactions, while ignoring comparative ones that might not imply a significant link.

4. Alignment with Foundational Ontologies:

   • Many foundational ontologies (like BFO or DOLCE) have similar distinctions to clearly model types of relations. Differentiating between comparative and material relationships helps align with these existing foundational models, making integration and interoperability with other ontologies smoother.

Applying to Kosmion:

In Kosmion, maintaining the differentiation between comparative and material relationships could enhance the ontology by allowing it to:

• Capture different levels of association between entities more accurately.
• Facilitate reasoning over whether a relationship implies an actual interaction or is just a relative comparison.
• Enhance modularity by allowing future extensions to specifically address either comparative or material relationships, depending on the intended use case.

For example, in Kosmion, if you have two individuals, you might use a material-relationship-type to model an employment contract (:person1 employedBy :company), whereas a comparative-relationship-type might model their height (:person1 tallerThan :person2). This differentiation helps prevent modeling confusion and makes sure that the intended meaning of each relationship is clear and appropriately represented.

what are some edge cases, where relations might be considered either (or both)

The distinction between comparative and material relationships can sometimes be ambiguous, and there are edge cases where a particular relationship could be viewed as either or even both, depending on the context. Here are some scenarios where the categorization might be unclear:

1. Family Relationships (e.g., "Sibling Of"):

• Material: Being a sibling can imply an actual, physical relationship, particularly if it involves shared upbringing, inheritance, or obligations.
• Comparative: It can also be seen as comparative if the relationship merely distinguishes certain characteristics (e.g., "older sibling" vs. "younger sibling") without implying a material interaction.

2. Spatial Proximity (e.g., "Next To"):

• Material: If two objects are physically placed next to each other, this can be seen as a material relationship since it involves the physical placement of objects in a spatial context.
• Comparative: However, describing one object as being "closer" or "further" compared to another object makes it more comparative. The relationship here doesn't imply any direct connection or influence, but rather a position relative to something else.

3. Employment Relationships (e.g., "Employed By"):

• Material: Employment is typically seen as a material relationship because it involves direct interaction and a reciprocal commitment (wages for work, obligations of employer and employee).
• Comparative: In some situations, one might compare employment status across individuals or organizations without focusing on the actual commitments (e.g., comparing rates of employment among different groups). This shifts the context to a comparative one, though not the usual intention of the employment relation.

4. Ownership and Possession (e.g., "Owns"):

• Material: Ownership implies certain rights and obligations, making it a material relationship when modeled between entities (e.g., a person owning a house).
• Comparative: However, if you are using ownership as a metric to compare individuals (e.g., "owns more properties than another person"), it becomes a comparative relationship. Here, the focus is on the relative quantity of possessions rather than a specific interactive connection.

5. Ranking Systems (e.g., "Ranked Higher Than"):

• Comparative: Ranking implies ordering based on some criteria (e.g., rank in a competition). It does not necessarily entail interaction but is based on comparing scores, abilities, or other properties.
• Material: However, in some contexts, ranks may imply material consequences, such as privileges or responsibilities (e.g., military ranks where being a "captain" comes with material responsibilities over a subordinate). This could be seen as having elements of both comparative and material relationships.

6. Social Roles in Organizations (e.g., "Manager Of"):

• Material: A manager has responsibilities for specific people or departments, making this a material relationship involving interaction and dependency.
• Comparative: The status of "manager" could also be used comparatively to distinguish someone's position from others in the hierarchy without implying direct interaction (e.g., "is more senior than other staff members").

Summary of Why Edge Cases Exist:

The distinctions can become blurry when relationships contain elements that are both interactions and comparisons:

• Material relationships generally imply direct interaction, obligations, or some physical or causal connection.
• Comparative relationships focus on relative properties between entities, without necessarily implying a concrete interaction.

These edge cases illustrate that whether a relationship is considered material or comparative can depend largely on context and perspective. Sometimes, the same relationship can be viewed differently depending on whether we are focusing on its interactive aspect or its relative/comparative aspect.

For your Kosmion ontology, handling these edge cases might involve:

• Providing explicit definitions for each relationship type.
• Allowing dual classification in specific scenarios, or creating hybrid relationship types.
• Adding context metadata to clarify whether the relationship is being considered in a comparative or material capacity.

I found examples #2 and #5 most compelling. For now, let's get of comparative-relationship-type and material-relationship-type

I'm toying with the idea of "facet-orientation". Instead of gufo's "types" (which can be stereotyped as kind, sub-kind, etc), I'm thinking about making everything have facets, so eschewing most or all of the Sortal stereotypes, and just keeping the nonsortals and aspects.

The idea of "facet-orientation" you're toying with could offer a novel and flexible way of modeling entities by eschewing sortal stereotypes and focusing on facets that describe multiple characteristics or dimensions of a concept. In contrast to the sortal stereotypes (like kinds and sub-kinds) in gUFO, which often carry strict identity and rigidity rules, facet-orientation could allow for a more dynamic and multi-perspective representation of entities, similar to the way that nonsortals or aspects in gUFO are used. Here's how this approach might look and the possible benefits:

How Facet-Orientation Differs from Sortals and Types

• Sortal Types in gUFO, like kind, sub-kind, and role, come with identity conditions that define what makes an entity the kind of thing it is. For example, a Person as a kind has certain properties that rigidly define its identity.
• In a facet-oriented approach, instead of using rigid sortal stereotypes, entities could be defined by different facets that are orthogonal to one another. This allows for a more nuanced view where an entity might be understood through different characteristics or aspects, without necessarily being forced into a single sortal type.

Benefits of a Facet-Oriented Approach

1. Flexibility in Classification:

   • Instead of having a rigid identity condition as imposed by sortal stereotypes, entities could have multiple facets that represent different contexts or roles. For example, a person might have the facets of being a parent, an employee, and a mentor without these facets being mutually exclusive or strictly defining their identity.

2. Dynamic and Evolving Characteristics:

   • In contrast to sortals, which often imply rigidity, facets can be added, changed, or removed as the context of the entity changes. This fits well with open-world ontologies where the characteristics of entities are subject to evolution, without having to reclassify them entirely.

3. Emphasis on Nonsortals and Aspects:

   • By focusing on nonsortals and aspects, you can model entities in a way that emphasizes their relations and qualities without necessarily grounding them in a rigid class. Aspects like color, age, or location can serve as facets that describe an entity’s state or properties.
   • This fits well with relational ontologies, such as Kosmion, where the relationships between entities might be more critical to model than the entities themselves.

Example of Applying Facets in Kosmion

Suppose you have an entity like a person. Instead of defining that person as a kind (gufo:Kind), which would imply a strict identity condition, you could describe the person with various facets:

• Social-Facet: Has relationships such as friend, colleague, member.
• Temporal-Facet: Current age or lifecycle stage (e.g., child, adult, senior).
• Contextual-Facet: Employed by a company, living in a particular city.

Each of these facets can evolve independently, giving a more flexible and context-dependent description of the entity.

Challenges and Considerations

1. Complexity in Reasoning:
   • While facets provide flexibility, they may introduce complexity when it comes to reasoning about entities. Since facets don’t imply a strict identity, it may be harder for automated systems to infer unique characteristics of an entity.
2. Lack of Identity Constraints:
   • Without sortals, it may be harder to impose identity constraints on entities. This could be a problem in scenarios where you need to distinguish entities or track them over time with stable criteria.
3. Semantic Clarity:
   • It may be challenging to maintain semantic clarity without sortal stereotypes, as these often help to create clear boundaries between different types of entities. Careful use of facets and metadata would be needed to ensure clarity when defining relationships or dependencies between entities.

Moving Forward with Kosmion

If you decide to implement facet-orientation in Kosmion, you could:

• Define Facet Classes: Create different classes representing facets (e.g., kosm:social-facet, kosm:temporal-facet), each with its own properties.
• Attach Facets via Relators: Link entities to different facets through relators, which could themselves have facets describing temporal validity, context, etc.
• Avoid Sortal-Stereotyped Relationships: Eliminate the need for entities to have a primary sortal stereotype and instead allow multiple facets to coexist, representing different perspectives or contexts.

This approach might lead to a more relational and contextual way of describing entities, fitting well with the open, evolving nature of the Kosmion ontology.

OK, let's replace "kosm:type" with "kosm:facet"

Let's work on "facet stereotypes". So please create a facet-stereotype class. I think "Category" is an obvious stereotype. So it should be an instance of facet-stereotype. should it also be a class?

I've added a facet-stereotype class to your ontology, and made category an instance of facet-stereotype. Additionally, I've also made category a class itself, allowing it to classify other facets.

This structure should provide flexibility in defining facet stereotypes and enable category to serve dual roles: both as an instance and a class, depending on the context.

instead of "kosm:category a kosm:facet-stereotype, owl:Class ", maybe it should be a subClass of facet-stereotype? Let's discuss before you make changes.

If we consider making kosm:category a subclass of kosm:facet-stereotype, it would indicate that category is one of several possible types of facet-stereotypes. This aligns with the idea of hierarchical modeling, where category is a specific kind of facet-stereotype that can itself be instantiated or subclassed to represent more specific categories.

Benefits of Using kosm:category as a Subclass:

1. More Granular Representation:

   • By making category a subclass of facet-stereotype, you allow for more specific facet-stereotypes to be defined under category. This provides a better structure for creating different types of categories that can organize various facets.

2. Clearer Conceptual Hierarchy:

   • Defining category as a subclass also aligns with best practices for ontological design, where general concepts (like facet-stereotype) are refined into more specific types (like category). This approach makes the ontology more expressive without compromising on logical structure.

3. Consistency in Class Usage:

   • Keeping category as a subclass ensures consistency in how classes are used throughout the ontology. If facet-stereotypes are all classes, then category being a class and a subclass of facet-stereotype preserves this pattern, rather than making category both an instance and a class (which can lead to more complex reasoning, especially in OWL DL).

Challenges of the Current Instance Approach:

• Having kosm:category as both an instance and a class (owl:Class) is allowed in OWL Full due to the flexibility of punning but can introduce complexity for reasoners that operate in OWL DL, where having the same entity act as both a class and an instance can cause issues with inference and logic.
• This dual nature can also complicate the interpretation of categories: Are they concepts that define other classes, or are they objects that you instantiate?

Recommendation:

I recommend making kosm:category a subclass of kosm:facet-stereotype, as it would provide:

• A clean hierarchical structure that is easy to interpret.
• Ease of reasoning and compatibility with existing tools and reasoners.
• Flexibility in extending the ontology, allowing you to add other facet-stereotypes or subcategories of category.

Let me know if you'd like to proceed with this change, and I can make the necessary updates!

I agree it should be a subclass, but should it still be an instance of facet-stereotype as well? my brain is starting to hurt.

The idea of making kosm:category both a subclass and an instance of kosm:facet-stereotype is indeed complex, but it can be understood through the lens of punning and meta-modeling.

Pros of Keeping kosm:category as Both an Instance and a Subclass:

1. Meta-Level Modeling:

   • Having kosm:category as both an instance and a subclass allows you to treat categories as something that can be categorized themselves and also serve as categories for other facets.
   • This can be useful in meta-modeling, where you want to allow facets of facets or allow recursive classification.

2. Flexibility in Conceptualization:

   • By defining category as an instance, you are giving it a concrete role within the facet-stereotype framework.
   • Simultaneously, having it as a subclass allows for the creation of more specific types of categories within the ontology. This dual role provides greater flexibility for future extensions.

Cons and Challenges:

1. Increased Complexity:

   • Having kosm:category be both a class and an instance can introduce complexity for reasoning in an ontology, especially if you plan to use tools that rely on OWL DL. Such tools may struggle with entities that occupy multiple levels of abstraction simultaneously, which could hinder inference.
   • This complexity can also make the conceptual model more difficult to understand for people not deeply familiar with meta-modeling.

2. Punning:

   • Using punning in OWL Full allows kosm:category to be treated both as an individual (instance of kosm:facet-stereotype) and as a class (subclass of kosm:facet-stereotype). This can be very powerful, but it may make the ontology harder to reason over for standard tools that are optimized for OWL DL.

Recommendation:

• Keep kosm:category as a Subclass Only:

  • If you want to avoid complexity and ensure better compatibility with reasoners, I recommend making kosm:category only a subclass of kosm:facet-stereotype. This approach still allows categories to be further specialized without the potential pitfalls of making them both classes and instances.

• Dual Role Only if Necessary:

  • If you really need kosm:category to act as both a subclass and an instance (e.g., for meta-level classification purposes), then keeping both roles could be justified. This approach is more expressive and suitable for complex ontological models, but you should be prepared to work with OWL Full and understand that this might limit the tools and reasoners available to you.

Next Steps:

• If you decide to proceed with kosm:category as a subclass only, I can update the ontology accordingly.
• Alternatively, if you want to explore keeping it as both, I can help refine the approach to manage the potential complexity.

Let me know your preference, and I'll make the appropriate adjustments!

what are some examples where kosm:category could be used as an instance?

If kosm:category were to be used as an instance of kosm:facet-stereotype, it would represent a particular type of stereotype within the facet-stereotype framework. Here are some scenarios where treating kosm:category as an instance could make sense:

1. Meta-Classification of Facet Types:

• In a meta-modeling context, kosm:category could serve as an instance that helps classify facets. For example, it could indicate that a given facet is of type category, while other stereotypes might be aspect, role, or state. This way, kosm:category can help in tagging or grouping facets under a broader conceptual umbrella.

2. Annotation or Documentation:

• When used in documentation or as part of metadata in an ontology, kosm:category can provide additional information about the facet. For instance, kosm:category could be used to denote that a particular facet itself belongs to the broader "category" type.
• Example:

  kosm:facetA a kosm:facet ;
     kosm:category kosm:category ;
     rdfs:label "Facet A" ;
     rdfs:comment "An example facet that is categorized under the category stereotype." .
  

  In this case, kosm:category acts as an instance of kosm:facet-stereotype to provide annotation about the nature of kosm:facetA.

3. Facet-Type Instance for Reasoning:

• If you want to allow for reasoning that distinguishes between different kinds of facet stereotypes, having kosm:category as an instance helps make that explicit. For instance, a reasoner could use the fact that kosm:category is an instance to make meta-level inferences about which other facets are categorized similarly.
• You could have rules that apply to all facets that are categorized as kosm:category, thereby making inferences about their behavior or properties.

4. Schema-Level Annotations:

• Using kosm:category as an instance could also be useful in schema-level annotations. For example, if you were describing or generating a UI that helps users interact with the ontology, kosm:category as an instance can be used to define the grouping or categorization structure in that context.
• Example:

  kosm:categoryInstance a kosm:category ;
     rdfs:label "Person Categories" ;
     rdfs:comment "Categorization for all facets related to person entities." .
  

  Here, kosm:categoryInstance is an individual instance that provides categorization for person-related facets under the kosm:category stereotype.

Summary:

• Using kosm:category as an instance makes sense in contexts where you want to annotate, meta-classify, or add schema-level meaning to facets.
• It provides a way to deal with meta-information about facets and helps in reasoning at a higher level without explicitly linking everything in a strict class hierarchy.
• The trade-off is complexity, particularly for reasoners, which may need to navigate the punned nature of kosm:category.

Given these examples, if you find these types of meta-level annotations and schema-level flexibility useful, it could be justified to keep kosm:category as both a subclass and an instance of kosm:facet-stereotype. However, if these scenarios are not central to your current use case, making it a subclass only might simplify the ontology and improve reasoner compatibility.

I didn't find your examples compelling. I believe you can make annotations about classes as well as instances, right? But if we're going to categorize the facet-stereotypes, e.g. as sortals, non-sortals, and aspects they'd have to be instances? Especially if we attach those meta-categories with relators.

You’re absolutely right; if we want to categorize the facet-stereotypes (e.g., into sortals, nonsortals, and aspects), they would need to be instances to properly serve in that meta-categorization role. This is particularly true if we intend to attach those meta-categories with relators, which is consistent with your relator-based modeling approach.

Here are some specific reasons why having facet-stereotypes as instances could be beneficial when applying meta-categories:

1. Meta-Category Assignment with Relators

• By making facet-stereotypes like category an instance, we can attach relators to them, allowing us to describe how these stereotypes relate to meta-categories such as sortal, nonsortal, or aspect.
• For instance, you could create a relator like kosm:categorized-as that links an instance of kosm:facet-stereotype (e.g., kosm:category) to a meta-category (e.g., kosm:nonsortal). This allows a very flexible way of building and extending the ontology without rigidly enforcing class-subclass hierarchies.

Example:

kosm:category a kosm:facet-stereotype ;
    kosm:categorized-as kosm:nonsortal .

This way, category is described as being a nonsortal, and these relationships can be updated or extended through relators without altering the core hierarchy of the ontology.

2. Simpler and More Flexible Annotation:

• If facet-stereotypes are instances, we can easily annotate them with additional properties using datatype properties or object properties. This would be simpler compared to adding annotations directly on classes, which could otherwise complicate the model if many annotations are needed.
• Making facet-stereotypes instances allows them to have their own metadata, like definitions, creation dates, or external references, without making them formal OWL classes with all the entailments that come with it.

3. Enhanced Reasoning and Meta-Level Querying:

• Treating facet-stereotypes as instances allows for meta-level reasoning. For example, we can make inferences about all nonsortal facet-stereotypes by querying instances rather than trying to navigate a class hierarchy.
• This distinction also makes it easier to query for specific stereotypes (e.g., “list all facet-stereotypes categorized as nonsortal”) without needing to worry about hierarchical inferences that might complicate things in OWL DL.

4. Flexibility for Multiple Facet Categories:

• If facet-stereotypes are instances, you can assign multiple categories to them, if necessary, which would be more complex to achieve in a strict class hierarchy. For example, a particular facet-stereotype could be both an aspect and a nonsortal, depending on the context, and you can model this through multiple relators linking to different meta-categories.

Proposed Update:

• Keep kosm:category as an instance of kosm:facet-stereotype to represent its meta-level categorization.
• Also make kosm:category a subclass if you want it to classify other facets that belong specifically to the category type.

This approach provides the best of both worlds: you get the flexibility of instances for meta-categorization while still retaining hierarchical modeling when needed.

Would you like me to proceed with making these adjustments to kosm:category, or would you like to define any meta-categories or relators that we can use to link these facet-stereotypes further?

Maybe a facet only ever would have one stereotype? Can you think of examples of facets that would have multiple stereotypes.

If we consider whether a facet might have multiple stereotypes, it seems plausible but not necessarily common. Let's explore some scenarios where it could make sense:

Potential Scenarios for Multiple Stereotypes:

1. Mixed Characteristics of Sortal and Aspect:

   • Suppose you have a facet that represents physical presence. This facet could be seen as an aspect (a quality that can change over time) but also as having a sortal nature since it might define identity conditions that are associated with presence (e.g., being a "resident").
   • In this case, the physical presence facet might need to be treated both as an aspect (describing some state or quality of an entity) and as a sortal (implying specific identity conditions or constraints).

2. Temporary Roles that Impact Identity:

   • Consider a facet representing a professional role that an entity can occupy. For example, the role of manager could be stereotyped as:
     • Nonsortal: Since a professional role like manager is temporary and does not define an entity's essential identity.
     • Aspect: If this role impacts specific attributes or influences other relationships within the organization, it could also be considered an aspect of the person's career.
   • Thus, the manager facet might need to be categorized under both nonsortal and aspect stereotypes.

3. Contextualized Aspects with Shared Identity:

   • If you have a contextual facet like ownership in a cooperative organization, this facet could simultaneously have aspects of both:
     • Aspect: Because ownership could be a changeable quality (e.g., the percentage of ownership may change).
     • Nonsortal: Since being an owner might not rigidly define the identity of an entity but instead add a role or capacity within a specific context.
   • Such a facet could therefore embody characteristics that make it both an aspect and a nonsortal, depending on how the ownership is conceptualized.

Considerations for Kosmion:

• Avoiding Overcomplication: Assigning multiple stereotypes to a single facet might add complexity to the model, which could impact reasoning and ease of understanding. Keeping one stereotype per facet makes it easier to categorize, reason over, and maintain.
• Clarity in Modeling: The use of multiple stereotypes could potentially blur the purpose of the facets. It might be more beneficial to split complex facets into separate facets, each with a distinct stereotype, rather than attempting to categorize a single facet in multiple ways.

Proposed Approach:

• It may be best to assume that each facet has only one stereotype for clarity and simplicity.
• If a facet seems to require multiple stereotypes, it might be a sign that it is too broad and should be divided into distinct facets that each focus on a more specific aspect or role.

Would you like to proceed with keeping facets to one stereotype each, or explore other ways to handle facets that might require multiple characteristics?

maybe valid-time is a facet?

Valid-time as a facet is an interesting and potentially useful way to handle the temporal aspects of your ontology, especially given your focus on bitemporality. Here's why modeling valid-time as a facet could make sense:

Why Valid-Time as a Facet?

1. Temporal Characteristic:

   • Valid-time represents the time period during which a given relator or entity is valid in the real world. By treating it as a facet, you can clearly articulate that temporal applicability is just one of the dimensions or characteristics of an entity.
   • This approach aligns well with your facet-oriented modeling, allowing temporal validity to be handled in a consistent way alongside other facets like context.

2. Flexible Categorization:

   • As a facet, valid-time can be categorized under a specific facet stereotype (e.g., as an aspect). This categorization makes it easy to distinguish temporal facets from other types of facets (such as roles or contexts).
   • By doing this, you gain the ability to handle time in a modular way, where different entities may or may not have valid-time, depending on their role in a given scenario.

3. Associating with Relators:

   • Relators can have multiple facets associated with them, and valid-time can be one of those facets. This allows a relator to explicitly reference when it applies without embedding that information in metadata or attributes directly.
   • For instance, a relationship like "owns a house" might only be valid for a specific time range. Treating valid-time as a facet means you can describe its temporal applicability as a characteristic separate from the relationship itself.

Example Addition to the Ontology:

We can define kosm:valid-time as a facet and link it to kosm:relator. Here’s how it might look:

# Define the valid-time facet
kosm:valid-time a kosm:facet ;
    rdfs:label "valid time" ;
    rdfs:comment "A facet representing the temporal validity of an entity or relator." .

# Attach valid-time to relators using a relator facet relationship
kosm:relator a owl:Class ;
    rdfs:label "relator" ;
    rdfs:comment "A class representing relators, which describe relationships (including unary relationships) among entities." ;
    kosm:has-facet kosm:valid-time .

In this example:

• kosm:valid-time is defined as a facet that represents the temporal validity of entities or relationships.
• We add a link from the relator class to valid-time via kosm:has-facet, signifying that valid-time is a characteristic of relators.

How This Helps:

• Clear Separation: Instead of treating valid-time as metadata or forcing it into every relator, it's treated as an optional facet. This makes it clear and modular, so only those entities or relationships that require a valid-time need to reference it.
• Facilitates Reasoning: By making valid-time a facet, you allow reasoners to infer and categorize temporal applicability separately, which could enhance querying and reasoning about entities based on their valid period.

Potential Challenges:

• Facet Stereotyping: Valid-time would need a stereotype to categorize it. It would likely fit under an aspect stereotype, as it describes a state or condition that applies to entities over time.
• Consistency: You’d need to make sure that valid-time is handled consistently across different types of entities, relators, or contexts, ensuring the facet model remains cohesive.

Conclusion:

Modeling valid-time as a facet is a good fit for your facet-oriented ontology, especially given its temporal focus. It allows you to manage temporal validity in a flexible and expressive way, making it easier to apply bitemporality and to extend the model as needed. If you'd like, I can help integrate this concept into your current Kosmion ontology document.

doing modular ontologies seems confusing. If you import another ontology, won't you need to use different prefixes?

You're absolutely right, managing prefixes when importing multiple modular ontologies can indeed be confusing. Here are a few points to consider:

Issues with Prefixes in Modular Ontologies

1. Unique Prefixes Required:

   • When you import another ontology, you need to use a different prefix for each imported ontology to avoid collisions between terms. This ensures that all IRIs (Internationalized Resource Identifiers) are distinct. This can make querying and referencing a bit cumbersome, especially if you have to frequently refer to concepts from multiple ontologies with different prefixes.

2. Namespace Management:

   • Different ontologies will often use different namespaces as prefixes. When combining them, this can lead to longer, inconsistent prefixes, making the modeling experience more cumbersome. For example, importing both gUFO and another ontology might lead to having to use gufo: alongside another distinct prefix (like ex: for a new ontology) every time you reference a class.

3. Human Readability:

   • Having multiple prefixes in a document can reduce readability for humans, as it becomes harder to track where each concept originates. If every ontology brings in its own set of prefixes, you end up with a document full of different prefixes, making it easy to get confused about which concept is from which ontology.

Possible Solutions for Prefix Management

1. Prefix Aliasing:

   • One common approach to simplifying prefixes is to use aliasing. When importing an ontology, you can define a short alias for it, which makes it easier to reference throughout the document. This keeps the prefixes short and consistent, improving readability.

2. Merging Concepts Using Common Namespaces:

   • Another approach is to use a common namespace for similar concepts across different ontologies. For example, if you are working on an upper ontology and you have several modular ontologies, you could define your own common prefixes and re-map concepts from the imported ontologies to these common namespaces. This helps unify the vocabulary, although it may require some reengineering and careful checking for semantic differences.

3. Use of Metadata Comments:

   • When importing different ontologies, it can be helpful to use comments to annotate which ontology a particular prefix corresponds to. This can help keep track of the origin of terms for future maintenance and for others who may need to understand the ontology.

Example Consideration for Kosmion

In the case of the Kosmion ontology:

• You currently use kosm: as your main namespace prefix. If you import gUFO, you'll use gufo: for that namespace, which means that any reference to a gUFO type will need the gufo: prefix.
• For example, gufo:Type and kosm:facet would both need distinct prefixes. If you’re frequently referencing concepts from gUFO, you may consider aliasing or remapping these concepts to fit better into your kosm: namespace, potentially making them local aliases.

Pros and Cons of Modular Ontologies with Multiple Prefixes

• Pros:
  • Reusability: Modular ontologies can be reused across different projects, allowing for greater flexibility.
  • Focused Design: Each ontology can focus on a specific domain or aspect, keeping complexity low within each module.
• Cons:
  • Prefix Management: Requires careful management of prefixes to avoid name collisions and keep the ontology understandable.
  • Complexity in Queries: SPARQL queries can become more complex because every referenced concept might require its distinct prefix, complicating query construction.

Would you like to explore possible ways to simplify prefix usage or consider importing other ontologies into Kosmion and managing those imports? I can help outline a strategy to handle modular imports effectively.

It's so annoying that applications and the semantic web community seem to refer to instance data as an ontology

I completely understand the frustration here. The semantic web community tends to blur the lines between ontologies and instance data. The term "ontology" should ideally refer to a conceptual schema—the definitions, classes, relationships, and axioms that define the structure of a knowledge domain. However, the community often uses "ontology" more broadly to also include instance data, which is the specific facts or entities that populate the classes defined by the ontology.

This can be confusing for several reasons:

1. Conceptual vs. Actual Data:

   • Ontologies are supposed to define the concepts and the relationships between those concepts in a given domain. Instance data, on the other hand, populates these concepts with real-world information.
   • When people refer to instance data as part of the ontology, they’re mixing the conceptual schema (T-Box in description logic terminology) with the assertional or instance data (A-Box). In theory, these should be clearly distinguished.

2. Practical Use in Tools:

   • Tools like Protege handle both ontologies (conceptual structures) and individuals (instance data) within the same environment. This often leads to users referring to the combined schema and data as an "ontology." This is especially true for OWL ontologies, where the same RDF framework can represent both the T-Box (conceptual model) and A-Box (instance data).

3. Naming Issues:

   • In practice, importing an "ontology" often brings in both concepts and instance data, which leads to referring to the entire dataset as an "ontology," regardless of whether it contains just schema definitions or also includes entities and individuals. This makes the lines between the abstract and concrete levels very blurry.

4. The RDF Data Model:

   • In RDF and OWL, there isn’t a strong formal distinction between classes, properties, and individuals at the data model level. Since everything is ultimately represented as triples, instance data and ontological definitions are treated similarly. This contributes to the tendency of referring to both as an "ontology" since the toolset doesn’t enforce a distinction.

Possible Solutions:

• Separate Ontology and Instance Files: When designing an ontology, you can create separate files for the schema and the instance data. This allows you to more clearly differentiate the conceptual definitions from the facts.
• Naming Conventions: Use distinct naming conventions or prefixes for ontological definitions and instance data to help maintain clarity.
• Explicit Documentation: In your ontology documentation, explicitly differentiate between the conceptual schema (ontology) and the instance data. Tools like Protege allow you to define these separately, even though they are handled within the same environment.

If you want to take a more modular approach for Kosmion, you could develop distinct conceptual modules (like kosm:facet and kosm:relator definitions) and create separate datasets for the instance-level data, possibly referencing these modules without blending them together.

what is the relationship between OntoUML's class stereotypes and relationship stereotypes?

seems like most upper and foundational ontologies define a "base" concept. e.g. gUFO has Individual and Type. I suspect that with a facet-based approach, that's not necessary? other than facet, of course.

The idea of not having a base "thing" or top-level concept in Kosmion makes a lot of sense in the facet-based approach you are exploring. Let's analyze why this might be the case and how it differs from the more conventional sortal-based approaches:

1. Conventional Upper Ontologies with Base Concepts:

• Many upper or foundational ontologies like gUFO, BFO (Basic Formal Ontology), and SUMO (Suggested Upper Merged Ontology) define top-level base concepts such as "Individual", "Entity", "Object", or "Type".
• These base concepts are intended to provide a starting point or root for categorizing everything else, giving a hierarchical structure to the ontology. For example:
  • gUFO has Individual and Type, which are fundamental building blocks for distinguishing between concrete instances and conceptual definitions.
  • BFO has concepts like "Continuant" and "Occurrent" that provide broad categorizations of what exists either as a persistent entity or an event.

2. Facets vs. Base Concepts:

• In your facet-based approach, there’s less emphasis on establishing a single hierarchical root. Instead, everything can be described using facets, which act as characteristics or perspectives rather than as rigid categories.
• Facets themselves are inherently modular and context-dependent, which allows entities to be described in a more compositional manner. Rather than determining "what an entity fundamentally is," the focus is on which facets apply to it.

3. Why a Base Concept May Not Be Necessary:

• Facets Enable Flexibility: By using facets to describe entities, you avoid the need to explicitly classify entities under a root concept like "Individual" or "Entity". This fits well with the idea that different aspects of an entity can be relevant in different contexts, without assuming an ontological base for all instances.
• No Rigid Classification: Unlike sortal approaches, which often have identity criteria tied to base classes, the facet-based model allows entities to acquire characteristics dynamically through the facets they possess. Thus, there isn’t a strict need for every entity to fall under an overarching class—each entity is defined by its collection of facets.
• No Explicit Subsumption Hierarchy: Facets do not imply subsumption (i.e., they do not inherently classify entities in a strict type hierarchy), which means that concepts don’t need to fit neatly under a single base type. This keeps the ontology open-ended and more flexible for different contexts and purposes.

Potential Downsides to Not Having a Base Concept:

1. Lack of Standardization: Without a base concept, it may be harder to enforce certain standardized constraints across the entire ontology. For example, global properties that apply to all individuals may need to be handled differently without a top-level class to attach them to.
2. Query Complexity: In some cases, SPARQL queries or other reasoning tasks may become more complex since there isn’t a single "root class" to use for selecting all entities.

Practical Considerations:

• In Kosmion, you could still add a very minimal base concept if you find that it helps with certain consistency or reasoning tasks. This could be something like an abstract "kosm:thing" class that serves as an anchor without imposing rigid requirements.
• Alternatively, facets themselves could serve as the common ground that all entities must have—essentially, every entity needs to have at least one facet. This would functionally serve as your base requirement, without needing a conventional sortal root.

If you decide that a minimal base is useful after all, it could be purely for technical convenience rather than conceptual necessity, which keeps the facet-oriented spirit intact while addressing practical concerns. Would you like me to explore adding such a minimal root, or are you leaning towards continuing without one?

I think the potential downside are mitigated by the fact that kosmion is already non-standardized, and aims for interoperability. Maybe domain applications should define their own top-level constructs, and they can just implement facets instead of having to instantiate someone else's preconceptions. domain model first?

Your approach—domain model first—makes a lot of sense, particularly for Kosmion, where the goal is to be non-standardized and to focus on interoperability. Here’s why I think this approach could work really well in your ontology:

Why Domain Applications Should Define Their Own Top-Level Constructs:

1. Avoiding Imposed Semantics:

   • By not having a rigid upper-level concept like "Individual" or "Entity," you avoid imposing any predefined semantics on domain applications. This allows each domain to define what makes sense in their context without inheriting assumptions from a foundational ontology that might not align with their specific needs.
   • This aligns with the principle of facets: instead of forcing domain-specific constructs to fit into an overarching type hierarchy, facets provide a modular way of defining properties and relationships that make sense locally.

2. Interoperability Through Facets:

   • Facets are inherently modular, which helps in building interoperable models. By allowing domain-specific models to implement facets rather than instantiating someone else’s rigid concept of a top-level entity, different domains can interoperate more easily by mapping shared facets rather than reconciling different top-level taxonomies.
   • For instance, if a domain ontology defines its top-level concept, like "Character" for a role-playing context, it can still implement facets like context or temporal aspects without having to fit into another ontology's conception of entity types.

3. Facilitating Customization:

   • With a domain model first approach, the domain ontologies can define their own high-level categories that make sense for their specific context, whether they want to define physical entities, abstract entities, or even more specialized types.
   • They can then add facets as needed, making it easy to customize the ontology for the specific requirements of the domain without having to inherit any top-level entity that might add unwanted complexity or assumptions.

4. Avoiding the "One-Size-Fits-All" Problem:

   • One of the biggest challenges with foundational ontologies is that they often adopt a "one-size-fits-all" approach, which can be restrictive. Domains like medicine, geography, and fantasy role-play each have very different needs. By allowing domains to define their own top-level constructs and use facets to extend them, you avoid forcing all these diverse domains into the same high-level schema.

Implications for Kosmion:

• Kosmion would effectively provide a set of facets that any domain-specific ontology could choose from. It’s a toolkit rather than a blueprint, meaning that domain ontologies can pick and choose which facets they need without worrying about fitting into an existing high-level hierarchy.
• Facets like context, temporal aspects, or relationship descriptors can be seen as interoperable modules that any domain can apply, and these can serve as the common ground for cross-domain integration.

Example:

• Suppose you have a domain ontology for urban planning. Instead of classifying everything under a foundational concept like "Entity" or "Object", the domain ontology can define its top-level classes, such as "Infrastructure", "Service", or "Citizen".
• Each of these entities can then implement facets like "valid-time", "context", or "category", which allows them to align with other domains that use similar facets without enforcing any kind of common root.

"Domain Model First" and Kosmion’s Development:

• This approach also helps when designing Kosmion itself. Since Kosmion is designed to provide relators and facets, it acts as an interoperable foundation that different domains can use and extend.
• The fact that it doesn’t have a strict top-level concept also aligns well with its non-standardized, open-ended goals. It essentially pushes the burden of meaning onto the domain-specific ontologies, which allows Kosmion to remain lightweight and flexible.

Next Steps:

• Focus on Facets: Continue focusing on defining useful facets that can be used across different domains. These should be modular and interoperable to maximize flexibility.
• Domain Implementation: Let domains develop their own top-level concepts and simply implement facets as needed. This will keep Kosmion adaptable and suitable for many different contexts.

Would you like me to make changes in the current ontology to emphasize this facet-only approach, or perhaps add a comment or metadata indicating this domain-first philosophy?

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Backlinks

• 2024-10-18: What’s the Best Semantic Web Authoring Tool? desc: a grim survey of RDF data management apps