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ontodm-kdd [2015/05/04 14:12]
admin
ontodm-kdd [2016/04/12 11:00] (current)
admin [Release version 1]
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 OntoDM-KDD is expressed in [[http://​www.w3.org/​TR/​owl-guide|OWL-DL]],​ a de facto standard for representing ontologies. The ontology is being developed using the [[http://​protege.stanford.edu|Protege]] ontology editor. ​ OntoDM-KDD is expressed in [[http://​www.w3.org/​TR/​owl-guide|OWL-DL]],​ a de facto standard for representing ontologies. The ontology is being developed using the [[http://​protege.stanford.edu|Protege]] ontology editor. ​
 {{ :​dminvestigation.png?​direct&​600 |}} {{ :​dminvestigation.png?​direct&​600 |}}
-===== Versions and Download =====+ 
 +===== OntoDM-KDD Structure ===== 
 +The [[http://​www.google.si/​url?​sa=t&​rct=j&​q=crisp-dm&​source=web&​cd=7&​cad=rja&​ved=0CEcQFjAG&​url=http%3A%2F%2Fwww.the-modeling-agency.com%2Fcrisp-dm.pdf&​ei=Za4CUYrwIaji4QSX9YHgCA&​usg=AFQjCNFTNXE36E5pSvSvKi_8QhAv2w0ay|CRISP-DM methodology]] process model, at the top level, is organized into six phases: business understanding phase, data understanding phase, data preparation phase, modeling phase, evaluation phase, and deployment phase. It defines the outputs of each CRISP-DM phase and the second-level generic tasks. For example, the data understanding phase consists of four generic tasks: collect initial data, describe data, explore data, and verify data quality. The level of specialized tasks (third level) describes ​ how the generic tasks should be carried out in specific situations, in terms of activities. For example, the describe data task includes activities for volumetric analysis of data, assessment of the attribute types and values, etc. The fourth level, the level of process instances, describes the actions, decisions and results of an actual data mining investigation performed in the domain of interest. 
 + 
 +For the purpose of representing data mining investigations,​ it is very important to have the ability to represent entities that deal with information,​ such as data, documents, reports, models, algorithms, protocols, etc. We thus incorporate and further extend some classes of the IAO ontology. The IAO ontology is a mid-level ontology describing information content entities (e.g., documents), processes that consume or produce information content entities (e.g., documenting),​ material bearers of information (e.g., journals), and relations in which one of the relata is an information content entity (e.g., is-about).  
 + 
 +Another important representational aspect is representation of processes. In OntoDM-KDD, we use and further extend classes from the OBI ontology, such as the OBI process taxonomy, which includes general processes such as documenting,​ planing, validation, etc. The OBI ontology aims to provide a standard for the representation of biological and biomedical investigations. It supports consistent annotation of biomedical investigations regardless of the particular field of study  and  is fully compliant with the existing formalisms in biomedical domains \cite{BrinkmanEtAl10OBIcaseStudy}. In addition, OBI defines an investigation as a process with several parts, including the planning of an overall study design, executing the designed study, and documenting the results. Finally, in OntoDM-KDD we include the SWO class \ontoclass{Information processing}{\swo} that represents processes in which input information is analysed or transformed in order to produce an output information. 
 +==== Description Layers ==== 
 + 
 +In OntoDM-KDD we distinguish two description layers ​ based on the mid-level ontologies that it extends (Fig.\ref{fig:​layers}). The first layer is the specification layer, that deals with information entities needed to describe and represent the DM investigations. The second layer is the application layer that deals with processual entities in order to represent processes that occur in a DM investigation. 
 +=== Specification Layer === 
 +The specification layer consists of classes that are extensions of the IAO class //​information content entity//. At the top level, it includes classes such as //data item//, //directive information entity//, //​document//,​ //document part// and //textual entity//. The //directive information entity// class is further extended with //action specification//,​ //data format specification//,​ //objective specification//,​ and //plan specification//​. In addition, ​ we also reuse the //study design// and //​protocol//​ classes from the OBI ontology. 
 +=== Application layer === 
 +The application layer consists of classes that are extensions of the OBI class //planned process//. These include general classes of processes such as: //​validation//,​ //​planning//,​ //​interpreting data//, //​information processing//,​ //​selection//,​ //​identification//,​ //​documenting//,​ and //​acquisition//​. Finally, the application layer includes the OBI //​investigation//​ class, which we further extend to define and represent a //data mining investigation//​. 
 + 
 +====== Versions and Download ​======
 ==== Release version 1 ==== ==== Release version 1 ====
  
-  * [[http://kt.ijs.si/​panovp/OntoDM/​OntoDM-KDD.owl|OntoDM-KDD.owl]]+  * [[http://ontodm.com/ontodm-kdd/​OntoDM-KDD.owl|OntoDM-KDD.owl]]
 ===== Publications ===== ===== Publications =====
   * Panče Panov, Larisa Soldatova, Sašo Džeroski. [[http://​link.springer.com/​chapter/​10.1007/​978-3-642-40897-7_9|OntoDM-KDD:​ Ontology for Representing the Knowledge Discovery Process]]. Discovery Science 2013, Lecture Notes in Computer Science Volume 8140, pp 126-140, 2013   * Panče Panov, Larisa Soldatova, Sašo Džeroski. [[http://​link.springer.com/​chapter/​10.1007/​978-3-642-40897-7_9|OntoDM-KDD:​ Ontology for Representing the Knowledge Discovery Process]]. Discovery Science 2013, Lecture Notes in Computer Science Volume 8140, pp 126-140, 2013

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