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ontodm-core [2014/09/15 14:38]
admin
ontodm-core [2016/04/12 10:56] (current)
admin [Release version 1]
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 For representing the mining of structured data, we import the [[ontodt|OntoDT ontology of datatypes]]. Classes that are referenced and reused in OntoDM-core are imported into the ontology by using the [[http://​obi-ontology.org/​page/​MIREOT|Minimum Information to Reference an External Ontology Term (MIREOT) principle]] ​ and extracted using the [[http://​ontofox.hegroup.org|OntoFox]] web service. For representing the mining of structured data, we import the [[ontodt|OntoDT ontology of datatypes]]. Classes that are referenced and reused in OntoDM-core are imported into the ontology by using the [[http://​obi-ontology.org/​page/​MIREOT|Minimum Information to Reference an External Ontology Term (MIREOT) principle]] ​ and extracted using the [[http://​ontofox.hegroup.org|OntoFox]] web service.
 =====Ontology Structure===== =====Ontology Structure=====
-For the domain of DM, we propose a horizontal description structure that includes three layers: ​+For the domain of DM, we propose a [[layers|horizontal description structure that includes three layers]]
   * a specification layer, ​   * a specification layer, ​
   * an implementation layer, and    * an implementation layer, and 
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 Having all three layers represented separately in the ontology will facilitate different uses of the ontology. For example, the specification layer can be used to reason about data mining algorithms; the implementation layer can be used for search over implementations of data mining algorithms and to compare various implementations;​ and the application layer can be used for searching through executions of data mining algorithms. ​ Having all three layers represented separately in the ontology will facilitate different uses of the ontology. For example, the specification layer can be used to reason about data mining algorithms; the implementation layer can be used for search over implementations of data mining algorithms and to compare various implementations;​ and the application layer can be used for searching through executions of data mining algorithms. ​
  
-This description structure is based on the use of the upper-level ontology [[http://​www.ifomis.org/​bfo/​|BFO]] and the extensive reuse of classes from the mid-level ontologies [[http://​obi-ontology.org/​page/​Main_Page|OBI]] and [[https://​code.google.com/​p/​information-artifact-ontology/​|IAO]]. The proposed three layer description structure is orthogonal to the vertical ontology architecture which comprises ​ an:  
-  * upper-level, ​ 
-  * a mid-level, and  
-  * a domain level. ​ 
-This means that each vertical level contains all three description layers. ​ 
-==== Layers ==== 
-{{ ::​fig1-page1.png?​400|}} 
-The specification layer contains //BFO: generically dependent continuants//​ at the upper-level,​ and //IAO: information content entities// at the mid-level. In the domain of data mining, example classes are //data mining task// and //data mining algorithm//​. ​ 
  
-The implementation layer describes //BFO: specifically dependent continuants//,​ such as //BFO: realizable entities// (entities that are executable in a process). At the domain level, this layer contains classes that describe the implementations of algorithms. ​ 
- 
-The application layer contains classes that aim at representing processes, e.g., extensions of //BFO: processual entity//. Examples of (planned) process entities in the domain of data mining are the execution of a data mining algorithm and the application of a generalization on new data, among others. 
-==== Relations between layers ==== 
- 
-The entities in each layer are connected using general relations, that are layer independent,​ and layer specific relations. Examples of general relations are //is-a// and //​part-of//:​ they can only be used to relate entities from the same description layer. For example, an information entity (member of the specification layer) can not have as parts processual entities (members of the application layer). Layer specific relations can be used only with entities from a specific layer. For example, the relation //​precedes//​ is only used to relate two processual entities. The description layers are connected using cross-layer relations. An entity from the specification layer //​is-concretized-as//​ an entity from the implementation layer. Next, an implementation entity //​is-realized-by//​ an application entity. Finally, an application entity, e.g., a planned process //​achieves-planned-objective//,​ which is a specification entity. 
 =====Key OntoDM-core classes===== =====Key OntoDM-core classes=====
-The ontology includes the representation of the following entities: [[data|data]],​ [[data mining task|data mining task]], [[generalization|generalization]],​ [[data mining algorithm|data mining algorithm]],​ [[constraints|constraints and constraint based data mining tasks and algorithms]],​ and [[data mining scenario|data mining scenario]]. +The ontology includes the representation of the following entities: ​ 
-{{ :​ontodm-coreentities.png?​direct&​600 |}} +{{ :​ontodm-coreentities.png?​600|}} 
- +  * [[data|data]], ​ 
- +  * [[data mining task|data mining task]], ​ 
- +  * [[generalization|generalization]], ​ 
- +  * [[data mining algorithm|data mining algorithm]], ​ 
 +  * [[constraints|constraints and constraint based data mining tasks and algorithms]],​ and  
 +  * [[data mining scenario|data mining scenario]].
  
 +===== Ontology evaluation =====
 +We assess the quality of OntoDM-core from three different evaluation aspects:
 +  * [[ontology metrics|we analyze a set of ontology metrics]]; ​
 +  * [[design criteria assessment|assess how well the ontology meets a set of predefined design criteria and ontology best practices]];​ and 
 +  * [[competency questions assessment|assess the ontology toward a set of competency questions]].
  
  
-==== Data mining scenario ==== 
-A scenario is [[http://​oxforddictionaries.com/​definition/​scenario|"​a postulated sequence or development of events"​]]. Therefore, a data mining scenario comprises a logical sequence of actions to infer some type of generalization from a dataset, a sequence of actions for applying a generalization on a new dataset, and a sequence of actions for evaluating the obtained generalizations. OntoDM-core represents a data mining scenario in three different description layers in the ontology: ​ 
-  * data mining scenario (as a specification), ​ 
-  * data mining workflow (as an implementation),​ and  
-  * data mining workflow execution (as an application). 
  
-In OntoDM-core,​ a //data mining scenario// is an extension of the OBI class //​protocol//​. It includes as parts other information entities such as: //title of scenario//, //scenario description//,​ //author of scenario//, and //​document//​. From the protocol class it also inherits as parts //objective specification//​ and //action specification//​. A //data mining workflow// is a concretization of a data mining scenario, and extends the //plan// entity (defined by OBI). Finally, a data mining workflow is realized (executed) through a //data mining workflow execution// process. 
  
-OntoDM-core does not represent scenarios and workflows that belong to other phases of the Knowledge Discovery process, such as application understanding,​ data understanding,​ data preprocessing,​ data mining process evaluation, and deployment. These are the subjects of representation in the [[ontodm-kdd|OntoDM-KDD ontology]]. Because both OntoDM-core and [[ontodm-kdd|OntoDM-KDD]] are built by using the same design principles, the same upper-level ontology, and same type of relations they can be used together to represent the complete knowledge discovery process. 
  
-==== Constraints and constraint-based data mining tasks and algorithms ==== 
-Constraints play a central role in data mining and constraint-based data mining (CBDM) is now growing in importance. A general statement of the problem involves the specification of a language of generalization and a set of constraints that a generalization needs to satisfy. In CBDM, constraints are propositions or statements about generalizations. They can be classified along three dimensions: ​ 
-  - primitive and composite constraints; ​ 
-  - language and evaluation constraints;​ and  
-  - hard (Boolean) constraints,​ soft constraints and optimization constraints. 
  
-=== Taxonomy of constraints === 
  
-A //​constraint specification//​ is defined in OntoDM-core as a sub-class of OBI //data representational model// and is the top-level class of a taxonomy of constraints that we propose. At the first level of the taxonomy, we have the //​primitive//​ and //complex constraints//​. Primitive constraints are based on atomic and complex constraints on non-atomic propositions. //Complex constraints//​ have as parts //primitive constraints//​ and a //​combination function specification//​ that defines how the primitive constraints are combined to form a complex constraint. ​ 
  
-At the second level, if we focus on the primitive constraints,​ we have //primitive language constraints//​ and //primitive evaluation constraints//​. //Language constraints//​ concern the representation of a generalization and only refer to its form. Commonly used types of language constraints are //​subsumption constraints//​ (e.g., all itemsets must contain the item '​bread`) and language cost constraints (e.g., itemsets should contain at most three items). //​Evaluation constraints//​ concern the semantics of a generalization when applied to a dataset. They usually include evaluation functions, where the evaluation functions measure the validity of a generalization on a given dataset (e.g., classification accuracy). ​ 
  
-At the last level the //primitive language cost-function constraint//​ is extended with three sub-classes that include: //primitive hard language cost-function constraint//,​ //primitive soft language cost-function constraint//,​ and //primitive optimization language cost-function constraint//​. //Hard constraints//​ represent boolean functions on generalizations and the constraint can be either satisfied or not satisfied. Soft constraints do not dismiss a generalization that violates a constraint, but rather penalize it for violating a constraint. //​Optimization constraints//​ ask for a  fixed-size set of generalizations that have some extreme values for a given cost or evaluation function. In a similar way, we define the sub-classes of the //primitive evaluation constraint//​ class. 
  
-=== Constraint-based data mining task === 
-  
-The task of CBDM is to find a set of generalizations that satisfy a set of constraints,​ given a dataset that consists of examples of a specific datatype, a data mining task, a generalization specification and a specifications of the set of constraints. In the OntoDM-core ontology, we represent a CBDM task as a sub-class of the //objective specification//​ class (reused from IAO). It has as parts a //data mining task// and a set of c//​onstraint specifications//​. We further define a //CBDM algorithm// as an algorithm that solves a CBDM task . Finally, this structure allows us to form a taxonomy of CBDM tasks, where at the first level of the taxonomy the basic CBDM task classes that are aligned with the fundamental data mining tasks, and then at the next levels depend on the data specification and the type of constraints. 
  
  
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 {{ :​file_structure.jpg?​direct&​300|}} {{ :​file_structure.jpg?​direct&​300|}}
   * All files in one zip archive{{:​ontodm_v_1_r.zip|OntoDM-coreV1.zip}}   * All files in one zip archive{{:​ontodm_v_1_r.zip|OntoDM-coreV1.zip}}
-  * OntoDM-core main file [[http://kt.ijs.si/panovp/​OntoDM/​OntoDM.owl|OntoDM-core.owl]] +  * OntoDM-core main file [[http://ontodm.com/ontodm-core/​OntoDM.owl|OntoDM-core.owl]] 
-  * File that OntoDM-core imports directly and contains external classes [[http://kt.ijs.si/panovp/​OntoDM/​external.owl|external.owl]] +  * File that OntoDM-core imports directly and contains external classes [[http://ontodm.com/ontodm-core/​external.owl|external.owl]] 
-  * File that external file imports and contains OBI classes[[http://​kt.ijs.si/panovp/​OntoDM/​external-OBI.owl|external-OBI.owl]] +  * File that external file imports and contains OBI classes [[http://ontodm.com/ontodm-core/​external-OBI.owl|external-OBI.owl]] 
-  * OntoDT ontology of datatypes [[http://kt.ijs.si/panovp/​OntoDM/​OntoDT.owl|OntoDT.owl]]+  * OntoDT ontology of datatypes [[http://ontodm.com/ontodm-core/​OntoDT.owl|OntoDT.owl]]
   * {{:​clus_instances.owl}}   * {{:​clus_instances.owl}}
   * {{:​clus_inferred.owl}}   * {{:​clus_inferred.owl}}

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