Template:All modeling issues

From Odp

(Difference between revisions)
Jump to: navigation, search
m (Protected "Template:All modeling issues" [edit=sysop:move=sysop])
Line 4: Line 4:
  [[Domain::*| Domains]]
  [[Domain::*| Domains]]
</ask>
</ask>
 +
<noinclude>
 +
{{#ask:[[Category:ModelingIssue]]|?Description=Brief description|?Domain=Domains|format=table}}
 +
</noincude>

Revision as of 07:35, 12 February 2009

There are no modeling issues

Brief description Domains
AcademicRoles I need to represent people of the academic staff. Each person can play different roles in different contexts.
Causal information and proportionality Consider the following paragraph:

The logistics of carrying out metabolism set limits on cell size.

Metabolic requirements also impose upper limits on the size that is practical for a single cell. As an object of a particular shape increases in size, its volume grows proportionately more than its surface area. Metabolic requirements also impose upper limits on the size that is practical for a single cell. As an object of a particular shape increases in size, its volume grows proportionately more than its surface area. Thus, the smaller the object, the greater its ratio of surface area to volume. A high surface-to-volume ratio facilitates the exchange of materials between a cell and its environment.
Climbing-related products The goal is to build a web application that tracks safety information about products typically used in bouldering, rock climbing, alpinism, and mountaineering. Generally speaking, products in this domain are highly specialized and technical in nature. The ability to model failure points in individuals - eg, "My harness broke at the belay loop" (potentially deadly) versus "My harness broke at the gear loop" (potentially inconvenient) - is an important capability. The model must support effective inferencing, though possibly from specialized reasoners. The model must also take into account the myriad attributes that can be associated with different product classes: sizing, gender, year of production, weight, materials, etc, etc.
Data production I would need to describe the following pattern:

"A device/sensor/software application produces a piece of data (e.g., a measure for a sensor, a computation for an application).

More generally, how to describe the information producer/consumer model?
Data type values in DOLCE It happens often that some entity has attributes that are simply strings, an array of characters like the title of a book or the name of a person. It is not clear what pattern should be used in DOLCE (also DUL) in these cases. In a pattern it is suggested to use the data type property dul:hasDataValue to attach a value to an instance, but that should mean that, for a dul:Person, a Name class must be created in advance related to the dul:Person. Another pattern suggests to use dul:Region but it seems quite awkward for names, last names etc. that are not defined in a dimensional space. In the case in which there are too many possible values and we are not interested to link these values to another object it is allowed to use simple data type properties.
Describing Lists and Sublists An ontology for describing lits and sublists
Different types of relationships In real applications, we need a flexible ontology editor that helps the user represent taxonomies based on different types of relationships between concepts and with specific features, constraints and rules for each type of relationship. E.g., specialization (is-a) taxonomies, composition (part-whole) taxonomies, lists, etc. The reason is that some features for the specialization taxonomies (represented by the existing editors, e.g., the property inheritance) are not always appropriate for taxonomies based on other types of relationships.

Also, the editor should be flexible enough to represent taxonomies based on new types of relationships and specific features, proposed by the user.

Our solution for a project in progress was to build an editor that allows the user choose the type of taxonomy and that automatically applies the property inheritance only for the specialization taxonomies. For the composition taxonomies, the concept properties are inherited on demand. And for the list-like taxonomies the inheritance is applicable only for properties defined at the ontology level (inherited by all concepts). The editor is not yet flexible enough to help the user add taxonomies based on new relationship types and with features he needs for an application.
FSDAS Scenario FSDAS simple scenarios for extracting competency questions to be used in the design of the FSDAS application ontology network. Formulated by Yves Jaques (UN-FAO).
FSDAS Scenario 2 Massaged scenarios based on modeling issues Community:FSDAS Scenario
Finding Rateable Properties of Ontologies For the use in Open Rating Systems, I need to define which properties of an ontology are considered rateable by experts or users.
HasHabitat a competency question for fsdas
Mathematical expressions I wish to be able to express:

- "gross income" calculatedBy ("yield" multipliedBy "price")

- "net income" calculatedBy ("gross income" minus " cost product")
Metrics This problem originates from the work of the W3C Decision Incubator group. However, the problem could be applicable to other areas than decision-making. The problem concerns how to model metrics that can be applied in decision-making situations. A metric is a way to assess options, to make a decision. If a metric is formally described, it can be better understood, reused, and in some cases applied automatically. We would also like to be able to detect possible metrics automatically, i.e., given a dataset we would like to be able to determine what metrics could be applied to it.
Modelling Questions This problem came up in the context of the W3C Decision Incubator activity, however, it is more general than the decision-making domain. It is about how to formally represent questions in OWL.

For instance, if I ask a question like "Where did this emergency occur?" I could simply represent it as a string. However, the question contains a lot of information, so in some cases one might want to represent it formally, and possibly reason on the question itself. For instance, we may want to derive that the answer should be of type "location" from the fact that the question uses the keyword "where".

We have identified two main aspects of this modeling issue:

  1. How can we refer to the detailed description of the question?
  2. How can we model the semantics of the question itself?

The first issue concerns the case when we would like to include both the question as a string, i.e., the human readable version of the question, and the question as a formal model. In this case we may have a class "Question", with a string property containing its representation in natural language. How do we now link also a formal description of this question, i.e., a set of triples, to the question class?

The second issue concerns how to represent the semantics of the question itself, i.e., an ontology for modeling those triples we wanted to refer to above. We would like to model things such as, the variable of the question, the expected answer type, any other constraints set in the question etc. For instance, in order to be able to ask questions such as: What is the expected answer type of this question? Is this answer correct with respect to the constraints of this question?

There exist some question classifications originating in expert systems and question answering, however, we are not aware of any OWL models.
Multiple Alternative Classification Criteria This modelling issue describes a specific, very recurrent modeling scenario in ontology development, subject to the vulnerability of ad-hoc modeling practices that could potentially lead to unexpected or undesirable results in ontology artifacts. The scenario consists of domain-specific concepts that can be represented according to multiple alternative classification criteria.
Ontology-based models Patterns for building ontology-based models for applications, by inter-ontology relationships, constraints and rules. General patterns for inference and search on ontology-based models.
Ordered Lists This problem originates from the W3C Decision Incubator activity, however it is not restricted to the decision-making domain, but more general.

The problem is how to best represent ordered lists in RDF/OWL. In the decision representation domain the problem arises when modeling options, where one of the options will be selected, i.e., it will be the decision.

RDF contains native constructs for sets and lists. There are also some proposals for OWL models of sets and lists to be found at http://swan.mindinformatics.org/spec/1.2/collections.html What would be the best way to model this?
Overloading OWL sameAs General Issue: owl:sameAs is being used in the linked data community in a way that is inconsistent with its semantics.
Parts that create compartments in an entity Consider the sentence: ``Internal membranes compartmentalize the functions of a eukaryotic cell. The existing ontologies provide ways of stating parts of an entity. But in this example, we need to state parts that create disjoint compartments within an entity.
Patronkh mon patron de test
Pattern Based Ontology Transformation Pattern based ontology transformation, I think it can be considered as reengineering pattern, where we have source ontology A, target ontology B and an ontology pattern P. Each time P is met in A we do the required transformation.

For example if the pattern was (this is informally written): "replace each two equivalent classes with a single one". We will search in A for each match(i.e. two equivalent classes) and replace them with one class in B. patterns are expressed using SPARQL. I need this pattern for the following reason: I was wondering if cardinalities in ontology can be included in a pattern. Actually I'm on an issue that uses ontology as conceptual formalization of relational data sources and I want to apply some transformations to handle some situations (e.g transform many-to-many to another type) on the conceptual model, which needs handling the cardinalities in the ontology. Is this topic covered somewhere in some design pattern?

Thanks in advance
PharmaceuticalProducts Composition The pharmaceutical products or drugs are chemical products composed by a set of ingredients (substances).

The ingredients are substances in a concrete dosage. The ingredients are divided in one main ingredient (mainly an active ingredient) and a set of excipients (other substances) The drugs are uniques based on their concrete composition.

I checked the Parts and Collections patterns, but I'm not pretty sure to use the Composition or Constituency in this case
Proliferation of URIs, Managing Coreference General Issue: There are some negative consequences to the current proliferation of new URIs being minted for the same things. The issue is how to avoid or manage this.
Representing Negation Consider the following example sentences:

The Golgi apparatus consists of stacks of flattened sacs, or cisternae, which, unlike ER cisternae, are not physically connected.

The centrioles are not essential for cell division.

The usual replication machinery provides no way to complete the 5' ends of daughter DNA strands.

Temomeres do not contain genes.

The special base triplets UAA, UAG, and UGA do not code for amino acids but instead act as signals to stop translation.

Both nucleoli and ribosomes, unlike most other organelles, are not enclosed in membrane.

Prokaryotes do not have mitotic spindle.

Because bacteria lack nuclei, their DNA is not segregated from ribosomes and the other protein-synthesizing equipment.


The leader and trailer are not translated, nor is the poly(A) tail.

This means that most eukaryotic genes and their RNA transcripts have long noncoding stretches of nucleotides, regions that are not translated.

Molecules of tRNA are not all identical.





Neither synapsis nor chiasma formation occurs during mitosis.
Representing Species How should species be represented?
Resource multiple attribution General Issue: How to attribute a single resource with two values of the same property in one document
Sex (of those who are not angels) Sex, or more properly genre, can be used to separate a species into two disjoint subsets: male and female. The two properties (in the sense of DOLCE) are rigid (by nature at list). So it seems to make sense to model the genre of a species, human for example, as two subproperties (subclasses) of dul:NaturalPerson: Woman and Man. An other approach could be tu create a :Genre as a quality and then two qualia :Male and :Female. The :Genre dul:isQualityOf dul:NaturalPerson while :Male and :Female should be values available for :Genre. The problem with this approach is that DUL doesn't have Quale as property and there is not a relation between a dul:Quality and some other entity that could be a quale. In DOLCE a dol:quality and a dol:quale could be linked through the dol:hasQuale relation.
Situation classification Classical problem-solving in AI and knowledge engineering requires a full-fledged knowledge representation system, including languages for representing the domain and the axioms/rules that hold for it (the problem space), as well as algorithms to find a solution to that problem, if any. Classical approaches use different languages for the representation of the problem versus the representation of the solution, e.g. declarative vs. procedural.

However, there are many requirements in domain modelling which require to talk about both the problem and solution spaces within a same universe of discourse. This is the case of legal knowledge (factual knowledge and legal cases vs. normative knowledge), services, planning and control knowledge (actual facts vs. expected facts), diagnostic knowledge and situational awareness (e.g. bare facts vs. typically unwanted facts), etc. All those cases fit into the abstract task of "classifying a situation" according to possibly incomplete, alternative or loose constraints, where those constraints must be explicit and explicitly linked to the representation of a situation. There are content patterns for representing situation classification, such as descriptionandsituation.owl, which relies on reification of conepts and relations. These patterns can represent situations and descriptions, and their given links (e.g. entities of a situation that play roles from a description, values of a situation that fit parameters from a description, etc.). But it's very hard to represent in general (not based on locally defined axioms, e.g. owl:equivalentClass axioms for a particular situation/description pair) how to:

1) make a situation emerge out of scattered facts 2) decide if a situation (or a set of facts) can be (partly or fully) classified under a description 3) evaluate which description fits best a certain set of facts etc.

Classical approaches represent situation classification within some algorithm or in the semantics of some appropriate meta-model. The modeling issue here is:

---) can we approximate generalized representations, for at least some situation classification tasks, by using OWL2 (e.g. with features such as punning, property chains, reflexivity) and regular description logic reasoners. In other words, is it possible to represent situation classification so that it reduces to a concept classification problem?
SnomedCTToOWL In the context of the Semantic Nomenclature case study, we need to extract a light ontology module from Snomed CT and convert it to OWL. We need on the one hand to use the Snomed CT classes for modeling the pharmaceutical clinical product and the dosage, plus some classes around. We plan to take a small set of instances of Snomed for experimentation. This will be the first step in order to map the resulting ontology to the Semantic Nomenclature ontology network. The focus is on semantic interoperability among different pharma terminologies.
Using SKOS Concept General Issue: When should something be an instance of SKOS:Concept?
Versioning and URIs General Issue: When and whether to make new URIs for different versions of things.
View Inheritance Representation of the multiple alternative criteria available to classify the abstractions of a certain ontology domain concept.

</noincude>

Personal tools
Quality Committee
Content OP publishers