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Top Level Ontologies Ontologies and Ontology Engineering Ekhiotz Vergara and Maria Vasilevskaya Dept. of Computer & Information Science Linköping University.

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Presentation on theme: "Top Level Ontologies Ontologies and Ontology Engineering Ekhiotz Vergara and Maria Vasilevskaya Dept. of Computer & Information Science Linköping University."— Presentation transcript:

1 Top Level Ontologies Ontologies and Ontology Engineering Ekhiotz Vergara and Maria Vasilevskaya Dept. of Computer & Information Science Linköping University 14 th June 2011

2 2 Outline Introduction  Definition  Goals  Main principle  Some existing ontologies Upper Level Distinctions Selected ontologies  Cyc  DOLCE  SUMO Application of Upper Ontologies Merging or Upper Ontologies Results of comparison 14/6/11

3 3 Outline Introduction  Definition  Goals  Main principle  Some existing ontologies Upper Level Distinctions Selected ontologies  Cyc  DOLCE  SUMO Application of Upper Ontologies Merging or Upper Ontologies Results of comparison 14/6/11

4 Definition “An attempt to create an ontology which describes very general concepts that are the same across all domains. The aim is to have a large number on ontologies accessible under this upper ontology” [Wikipedia] “The very first kind” [Philosophical view] Similar concepts: Top, Foundation, Upper 4 14/6/11

5 Goals Semantic interoperability  To interpret information properly by the receiving system in the same sense as intended by the transmitting systems Ontologies matching/alignment  To find correspondence among sets of ontologies 5 14/6/11 Ontologies communication

6 Main principle Ontology communication 6 Domain ontology A Domain ontology B Domain ontology C Upper ontology Categories refer to Specific terms Abstract terms refer to 14/6/11

7 Some existing ontologies DOLCE (Descriptive Ontology for Linguistic and Cognitive Engineering) SUMO (Suggested Upper Merged Ontology) BFO (Basic Formal Ontology) GFO (General Formal Ontology) Cyc PROTON (PROTo ONtology) Sowa’s ontology 7 14/6/11

8 8 Outline Introduction  Definition  Goals  Main principle  Some existing ontologies Upper Level Distinctions Selected ontologies  Cyc  DOLCE  SUMO Application of Upper Ontologies Merging or Upper Ontologies Results of comparison 14/6/11

9 Aristotle’s categories Influence in the current understanding of ontologies Kategoria  Kinds of predicates/predication Different interpretations 10 categories: 14/6/11 9

10 Individuals and categories Individuals: entity that cannot be instantiated Examples:  Category: Dog, Electron, Red…  Individual: the red of an apple, my dog Wolfy.. 14/6/11 10 Individual Category Instance-of

11 Time and space Time points and intervals  Ontologies based on time points  Ontologies based on intervals Time intervals meet other intervals  Mixed approach, time intervals and boundaries Brentano-time Boundaries can coincide Spatial point and region 14/6/11 11 Time ab (a,b) e(a,e) )e,b)

12 Objects and processes Based on a space and time ontology, different categories of individuals can be derived Ontologies with time points as primitives  Continuant / endurant: Persistence through time Identity condition  property assigned to identify it Instance of an continuant at some time point  Occurrants: Temporal, unfold through time E.g. processes  Continuants may participate in continuants 14/6/11 12

13 Objects and processes Ontologies based on time intervals  Temporally extended objects as primitives and derive objects at time points  General Process Theory  All entities temporally extended E.g. properties as layer of processes Ontologies based on mixed approach  Brentano-time/space  Presentials in the boundaries  Persistance category to define identity criteria over time Abstract entities  Independent of space and time 14/6/11 13

14 Examples Basic Formal Ontology  Non-abstract individuals  Real numbers to model time and space  Continuants and occurrants DOLCE  Individuals, abstract and concrete  Real numbers to model time and space  Continuants, occurrants and abstract individuals General Formal Ontology  Categories and individuals  Brentano-time/space  Processes, presentials and abstract individuals  Classification of ontological categories 14/6/11 14

15 15 Outline Introduction  Definition  Goals  Main principle  Some existing ontologies Upper Level Distinctions Selected ontologies  Cyc  DOLCE  SUMO Application of Upper Ontologies Merging or Upper Ontologies Results of comparison 14/6/11

16 Cyc “Formalised representation of facts, rules of thumb and heuristics for reasoning about objects and events of everyday life” 14/6/11 16

17 DOLCE Description Descriptive Ontology for Linguistic and Cognitive Engineering Semantic Web Cognitive bias  Natural language  Human commonsense Mesoscopic level Descriptive  Assist in making already formed conceptualizations explicit Particulars (individuals) Distinction between:  Continuants  Occurrents 14/6/11 17

18 DOLCE Top level 14/6/11 18

19 DOLCE Refined top level 14/6/11 19

20 SUMO Suggested Upper Merged Ontology The largest formal public ontology Created by merging several ontologies:  Sowa’s upper-level ontology  Russell and Norvig’s upper-level ontology  James Allen’s temporal axioms  Casati and Varzi’s formal theory and holes  … 20 14/6/11

21 SUMO High Level Distinctions 21 SUMO ontology Engineering Components Geography Government Military Finance … Communication, Distributed Computing Countries and Regions, Economy, North American Industrial Classification System MILO (Mid-Level Ontology) 14/6/11

22 SUMO High Level Distinctions ‘Physical’ (things which have a position in space/time) and ‘Abstract’ (things which don’t) Partition of ‘Physical’ into ‘Objects’ and ‘Processes’ 22 Entity Physical Abstract Physical ObjectsProcesses 14/6/11

23 SUMO Top Level Structure Physical Object SelfConnectedObject Substance CorpuscularObject Region Collection Process DualObjectProcess InternalChange ShapeChange IntentionalProcess Motion Abstract SetOrClass Relation Proposition Quantity Number PhysicalQuantity Attribute Graph GraphElement 23 14/6/11

24 SUMO Validation Mapping to all of WordNet lexicon  A check on coverage and completeness (at a given level of generality) Peer review  Open source since its inception Formal validation with a theorem prover  Free of contradictions (within a generous time bound for search) Application to dozens of domain ontologies 24 14/6/11

25 25 Outline Introduction  Definition  Goals  Main principle  Some existing ontologies Upper Level Distinctions Selected ontologies  Cyc  DOLCE  SUMO Application of Upper Ontologies Merging or Upper Ontologies Results of comparison 14/6/11

26 Applications Automatic ontology matching  Finding correspondences between entities belonging to two or more ontologies DOLCE  LOIS project  SmartWeb  Language Technology for eLearning  AsIsKnown SUMO  More than 100 papers using it  Mostly in linguistics 14/6/11 26

27 27 Outline Introduction  Definition  Goals  Main principle  Some existing ontologies Upper Level Distinctions Selected ontologies  Cyc  DOLCE  SUMO Application of Upper Ontologies Merging or Upper Ontologies Results of comparison 14/6/11

28 Merging Upper Level Ontologies COSMO (COmmon Semantic MOdel)  Lattice of ontologies that will serve as a set of basic logically-specified concepts that can be specified in domain ontologies  Contains: OpenCyc SUMO Some concepts of DOLCE and BFO MSO (Multi-Source Ontology)  Large knowledge server Lexical ontology OntoMap  Semantic framework on conceptual level  No maintenance 14/6/11 28

29 29 Outline Introduction  Definition  Goals  Main principle  Some existing ontologies Upper Level Distinctions Selected ontologies  Cyc  DOLCE  SUMO Application of Upper Ontologies Merging or Upper Ontologies Results of comparison 14/6/11

30 30 Results of comparison 14/6/11

31 31 Results of comparison 14/6/11

32 32 References Mascardi, V.; Locoro, A.; Rosso, P.;, "Automatic Ontology Matching via Upper Ontologies: A Systematic Evaluation," Knowledge and Data Engineering, IEEE Transactions on, vol.22, no.5, pp.609-623, May 2010 Ian Niles and Adam Pease. 2001. Towards a standard upper ontology. In Proceedings of the international conference on Formal Ontology in Information Systems - Volume 2001 (FOIS '01), Vol. 2001. Viviana Mascardi, Valentina Cordì and Paolo Rosso. A comparison of upper ontologies. Technical report. 2006 Aldo Gangemi, Nicola Guarino, Claudio Masolo, Alessandro Oltramari, and Luc Schneider. 2002. Sweetening Ontologies with DOLCE. In Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web (EKAW '02), Springer-Verlag, London, UK, 166-181. D. B. Lenat and R. V. Guha. Building large knowledge-based systems: representation and inference in the cyc project. Journal of Artificial Intelligence. 1990. Pierre Grenon and Barry Smith and Louis Goldberg. Biodynamic Ontology: Applying BFO in the Biomedical Domain. 2004. Ontogenesis. What is an upper level ontology? 2011. Ontogenesis. What is an upper level ontology? Ludger Jansen. Chapter 8, Categories: The top-level ontology. 14/6/11

33 33 Thanks! 14/6/11


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