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Ontology of core data mining entities

Data Mining and Knowledge Discovery volume 28, pages 1222–1265 (2014)Cite this article

Abstract

In this article, we present OntoDM-core, an ontology of core data mining entities. OntoDM-core defines the most essential data mining entities in a three-layered ontological structure comprising of a specification, an implementation and an application layer. It provides a representational framework for the description of mining structured data, and in addition provides taxonomies of datasets, data mining tasks, generalizations, data mining algorithms and constraints, based on the type of data. OntoDM-core is designed to support a wide range of applications/use cases, such as semantic annotation of data mining algorithms, datasets and results; annotation of QSAR studies in the context of drug discovery investigations; and disambiguation of terms in text mining. The ontology has been thoroughly assessed following the practices in ontology engineering, is fully interoperable with many domain resources and is easy to extend. OntoDM-core is available at http://www.ontodm.com.

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Notes

  1. OBO: http://www.obofoundry.org (accessed 1 June 2014).

  2. GO: http://www.geneontology.org (accessed 1 June 2014).

  3. NCI Thesaurus: http://ncit.nci.nih.gov (accessed 1 June 2014).

  4. FMA: http://sig.biostr.washington.edu/projects/fm(accessed 1 June 2014).

  5. SNOMED-CT: http://www.ihtsdo.org/snomed-ct (accessed 1 June 2014).

  6. OBI: http://www.obi-ontology.org (accessed 1 June 2014).

  7. BioPortal: http://bioportal.bioontology.org (accessed 1 June 2014).

  8. BFO: http://www.ifomis.org/bfo (accessed 1 June 2014).

  9. RO: http://obofoundry.org/ro (accessed 1 June 2014).

  10. PMML: http://www.dmg.org/ (accessed 1 June 2014).

  11. DOLCE: http://www.loa.istc.cnr.it/old/DOLCE.html (accessed 1 June 2014).

  12. IAO: http://code.google.com/p/information-artifact-ontology (accessed 1 June 2014).

  13. OWL-DL: http://www.w3.org/TR/owl-guide (accessed 1 June 2014).

  14. Protégé: http://protege.stanford.edu (accessed 1 June 2014).

  15. OBO Foundry principles: http://obofoundry.org/crit.shtml (accessed 1 June 2014).

  16. In Table 7 from the Appendix, we list all relations used in OntoDM-core.

  17. OntoFox: http://ontofox.hegroup.org (accessed 1 June 2014).

  18. In the remainder of the article, italic formatting denotes ontology class.

  19. Table 8 in the Appendix lists the typical competency questions OntoDM-core is designed to answer.

  20. Oxford dictionary: http://oxforddictionaries.com/definition/scenario (accessed 1 June 2014).

  21. Clus: http://sourceforge.net/projects/clus/ (accessed 1 June 2014).

  22. Clus OntoDM-core instances: http://ontodm.com/lib/exe/fetch.php?media=clus_instances.owl (accessed 1 June 2014).

  23. Hermit reasoner: http://www.hermit-reasoner.com/ (accessed 1 June 2014).

  24. OntoDM-core inferred segment: http://ontodm.com/lib/exe/fetch.php?media=clus_inferred.owl (accessed 1 June 2014).

  25. BioPortal SPARQL endpoint: http://sparql.bioontology.org (accessed 1 June 2014).

  26. OWL2Query: http://krizik.felk.cvut.cz/km/owl2query/index.html (accessed 1 June 2014).

  27. SPARQLer: http://www.sparql.org/sparql.html (accessed 1 June 2014).

  28. Robot Scientist Project: http://goo.gl/6wazqw and http://goo.gl/Iq6WGS (accessed 1 June 2014).

  29. BAO: http://bioassayontology.org (accessed 1 June 2014).

  30. QSAR Chemoinformatics repository: http://cheminformatics.org/datasets/#qsar (accessed 1 June 2014).

  31. Example MDL Molfile http://mychem.sourceforge.net/doc/apes06.html (accessed 1 June 2014).

  32. CHEMBLE repository: https://www.ebi.ac.uk/chembl/doc/inspect/CHEMBL1135798 (accessed 1 June 2014).

  33. A pair of molecules consisting of one chiral molecule and the mirror image of this molecule. The molecules making up an enantiomeric pair rotate the plane of polarized light in equal, but opposite, directions.

  34. ART: http://www.aber.ac.uk/en/cs/research/cb/projects/art/art-corpus (accessed 1 June 2014).

  35. NACTEM centre: http://www.nactem.ac.uk/cheta (accessed 1 June 2014).

  36. ChEBI: http://www.ebi.ac.uk/chebi (accessed 1 June 2014).

  37. FIX: http://obofoundry.org/cgi-bin/detail.cgi?fix (accessed 1 June 2014).

  38. REX: http://www.obofoundry.org/cgi-bin/detail.cgi?id=rex (accessed 1 June 2014).

  39. OGMS: www.obofoundry.org/cgi-bin/detail.cgi?id=OGMS (accessed 1 June 2014).

  40. CEO: http://goo.gl/AUktCK (accessed 1 June 2014).

  41. WSMO: http://www.wsmo.org (accessed 1 June 2014).

  42. DMO Jamboree 2010: http://kt.ijs.si/janez_kranjc/dmo_jamboree/ (accessed 1 June 2014).

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Acknowledgments

We would like to acknowledge the support of the European Commission through the project MAESTRA—Learning from Massive, Incompletely annotated, and Structured Data (Grant Number ICT-2013-612944).

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Authors and Affiliations

  1. Department of Knowledge Technologies, Jožef Stefan Institute, Jamova cesta 39, 1000 , Ljubljana, Slovenia

    Panče Panov & Sašo Džeroski

  2. Department of Computer Science, Brunel University, Uxbridge, London , UB8 3PH, UK

    Larisa Soldatova

  3. Jožef Stefan International Postgraduate School, Jamova cesta 39, 1000 , Ljubljana, Slovenia

    Sašo Džeroski

  4. Centre of Excellence for Integrated Approaches in Chemistry and Biology of Proteins, Jamova cesta 39, 1000 , Ljubljana, Slovenia

    Sašo Džeroski

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  1. Panče Panov
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Correspondence to Panče Panov.

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Responsible editor: Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Železný

Appendix

Appendix

Table 7 Relations used in the OntoDM-core ontology
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Table 8 Examples of OntoDM-core competency questions
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Table 9 Scope and structure assessment
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Table 10 Naming and vocabulary assessment
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Table 11 Documentation and collaboration assessment
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Table 12 Availability, maintenance and use assessment
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Table 13 Formalization of the OntoDM-core competency questions using the SPARQL-DL language
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Panov, P., Soldatova, L. & Džeroski, S. Ontology of core data mining entities. Data Min Knowl Disc 28, 1222–1265 (2014). https://doi.org/10.1007/s10618-014-0363-0

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Keywords

  • Ontology of data mining
  • Mining structured data
  • Domain ontology