DMOP Browser and Download Page

This page is your entry point to the e-LICO Ontology for Data Mining Optimization (DMOP).  If this is your first visit, please read the brief description below before going to the browser.

 

Run the DMOP Browser


Alternatively, you can download the DMOP files if you prefer to browse the ontology offline using an ontology editor like Protégé:

The DMOP ontology is a collection of four files:

DMOP.owl contains all the DMOP classes and axioms, and defines the major concepts of the data mining domain, such as Task, Algorithm, AlgorithmAssumption, Data, Model, Operator, OptimizationProblem, CostFunction, etc., as well as axioms defining their properties and relationships. As such, it can be viewed as the terminological core of the ontology. You can use DMOP alone or you can import it through DMKB.owl.

DMKB.owl contains descriptions of instances of concepts defined in DMOP, such as individual algorithms and their implementations (Operators)  in popular data mining software such as RapidMiner and Weka. It stands for Data Mining Knowledge Base and aims to be a compendium of current knowledge on algorithms and models for knowledge discovery. It imports two other files, RMOperators.owl and WekaOperators.owl. The operator files are typically accessed by importing them from DMKB. If you find that DMKB loads too slowly, it's because the reasoner must plod through more than 1800 individual assertions concerning the different algorithms and their corresponding implementations (called Operators) in RapidMiner and Weka.You don't need to import them if you just want to browse the algorithm descriptions in DMKB.

DMEX-DB.owl is not part of the DM ontology and knowledge base, but is an illustrative file that gives an idea of what the Data Mining Experiments database will be.  The schema of this database will be based on DMOP and DMKB. It will contain records of all data mining experiments conducted in the e-LICO project. Each experiment represents the execution of a specific workflow and all its components: the user goal specification, the dataset used, and a description of each workflow step -- the specific task addressed (e.g., discretization, feature selection, classification), the operator selected to do the task, and the parameters, input and output of the operator execution.

As a sneak preview of the true DMEX database, DMEX-DB.owl contains a description of the characteristics of the Iris dataset as well as individual assertions concerning mock executions of operators such as Weka_NaiveBayes. Based on an execution's parameter settings,  the underlying ontology reasoner infers the specific NaiveBayes variant (e.g., NaiveBayesNormal, NaiveBayesKernel) implemented by the operator and thus gives the user access to an in-depth characterization of the underlying algorithm.

The DMEX database, grounded on DMOP and DMKB, will be the source of training metadata for the e-LICO Meta-Miner, whose goal is to optimize workflows and thereby improve the performance of the e-LICO DM lab's Intelligent Discovery Assistant. As its name indicates, the specific goal of DMOP is workflow optimization through meta-learning, in addition to its more theoretical goal of providing a unified conceptual framework for the study of data mining and knowledge discovery.

DMOP is in its early stages of development and many parts of the ontology are currently placeholders awaiting volunteer developers. We suggest that you explore the more developed ontological regions concerning classification algorithms and models, e.g.,  Support Vector Classifiers and their underlying assumptions, optimization problems, objective functions, constraints, and optimization strategies.

We would appreciate all comments and suggestions on this initial version, from data mining as well as ontology engineering specialists. We would also gratefully consider all collaboration offers to participate in the development of the DM Ontology by annotating algorithms that you have authored or of which you have extensive knowledge. Please send your comments and suggestions to Melanie[dot]Hilario[at]unige[dot]ch.