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DOLCE and its comparison with SUMO Group No 5 Shweta Ghonge(113050054) Subhasmita Mahalik(113050073) Debashee Tarai(1130

DOLCE and its comparison with SUMO Group No 5 Shweta Ghonge(113050054) Subhasmita Mahalik(113050073) Debashee Tarai(113050078). Introducing Upper Ontologies. Role of Ontologies. Ontologies are the basic infrastructure for the Semantic Web.

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DOLCE and its comparison with SUMO Group No 5 Shweta Ghonge(113050054) Subhasmita Mahalik(113050073) Debashee Tarai(1130

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  1. DOLCE and its comparison with SUMO Group No 5 • Shweta Ghonge(113050054) • Subhasmita Mahalik(113050073) • Debashee Tarai(113050078)

  2. Introducing Upper Ontologies

  3. Role of Ontologies • Ontologies are the basic infrastructure for the Semantic Web. • The very idea of the Semantic Web hinges on the possibility to use shared vocabularies for describing resource content and capabilities, whose semantics is described in unambiguous and machine-processable form. • Describing this semantics, what is sometimes called the intended meaning of vocabulary terms, is exactly the job, ontologies do for the Semantic Web.

  4. Motivation • T: Deadly Nightshade is one of the most toxic plants found in the Western hemisphere. • H: Belladonna is one of the most toxic plants found in the Western hemisphere. T = H The text entailment relation between the above two sentences is caused by the fact that Deadly Nightshade and Belladonna are synonyms.

  5. Thus, the success of Semantic Web largely depend upon the success of underlying Ontology.

  6. Introduction to DOLCE • DOLCE was developed as a starting point for comparing and elucidating the relationships with other future modules of the Wonder Web library. • DOLCE has a clear cognitive bias. It aims at capturing the ontological categories underlying natural language and human commonsense. • A basic choice we make in DOLCE is the so-called multiplicative approach: different entities can be co-located in the same space-time.

  7. Descriptive Ontology(Commonsense)distinguishes between things and events. According to these revisionist researchers, everything extends in space and time, and the distinction between things and events is irrelevant. DOLCE adopts Descriptive approach. Descriptive vs Revisionist Ontology

  8. Reductionist vs multiplicative Ontology • Reductionist : Minimal number of primitives (i.e. basic concepts) to model all the concepts. • Multiplicative : Maximal expressivity, using a large number of basic concepts. Example: ”vase that is made from an amount of clay” Are clay and the vase two different entities ???

  9. ”vase that is made from an amount of clay” Are clay and the vase two different entities ??? Reductionist Ontology:YES Multiplicative Ontology:NO DOLCE adopts multiplicative approach. Example

  10. Endurants and Perdurants • Endurants (also called continuants) are characterized as entities that are ‘in time’ and they are ‘wholly’ present at any time of their existence. • Perdurants (also called occurrents) are entities that ‘happen in time’, they extend in time by accumulating different ‘temporal parts.

  11. Example • The book you are holding now can be considered an endurant because (now) it is wholly present. • “Your reading of this book” is a perdurant because, your “reading” of the previous section is not present now.

  12. Actualism and Possibilism • Actualism claims that only what is real exists, while possibilism admits possibilia (situations or worlds) as well. • In the first case ,one can state the expression “It is possible that John is ill” . • In the other approach, one can rephrase the expression i.e.“There is a world in which it is possible that John is ill”. DOLCE adopts possibilism approach.

  13. Example • DOLCE includes modal and temporal operators and therefore supports possibilism approach. • We quantify over a constant domain in every possible world (all axioms and theorems are necessarily true even if the necessity box is not present in front of the formulas). • NEP(ф) Ξ Эx(ф(x)) .. (ф is non-empty)

  14. Hierarchy of concepts in DOLCE Endurant Quality Physical Physical Amount of matter Spatial location Physical object ... Feature Temporal Non-Physical Temporal location Mental object ... Social object Abstract ... Perdurant Abstract Static Quality region State Time region Process Space region Dynamic Color region Achievement ... Accomplishment ...

  15. Example of mapping a domain ontology to DOLCE Case study: Landscape Domain Ontology

  16. Why A Foundational Ontology of the Landscape? • Different languages and cultures recognize different kinds and characteristics of landforms in the landscape. Landscape concepts and their lexicalization also vary. • This if explicitly aligned with an appropriate domain-independent, upper-ontology will greatly facilitate interoperability and integration with the semantic web. • The following are the constituents of the landscape ontology: 1. Physical geographic entity: the earth’s surface.

  17. 2. Entities (e.g., trees, roads, and buildings) which are physically attached to the surface. 3.Surface features (protuberance, peak,ridgeline, fault, layer, hollow, depression, cliff, incline, slope break, edge, etc.) 4.Physical characteristics such as location, shape,size, elevation, gradient, depth, color, material. 5.Spatial and temporal relations between surface features (e.g.,proximity, direction, topology, temporal overlap, composition, parthood, etc.).

  18. Selection of an Upper-Ontology We need to formalize these ideas using an upper ontology so that our landscape ontology can be ontologically consistent and can be integrated with ontologies of other environmental domains. The DOLCE provides modules which can be imported; until a more comprehensive foundational ontology of the geographic domain becomes available.

  19. Landscape Ontology Modeling with DOLCE • DOLCE identifies four top level particulars: endurant,perdurant, quality, and abstract. • Endurants are further specialized into physical, non-physical.Physical endurants, in turn, can be arbitrary amounts of matter, physical objects, or features. • Qualities can be abstract, physical, or temporal. Every quality must inhere in some entity, while every entity must possess some quality.

  20. Interpreting the foundational landscape ontology in DOLCE parlance • 1. Planet earth and its physical surface (part) are non-agentive physical objects. • 2. All physical characteristics mapped to physical quality. • 3.Location of qualities or surface features can be classified as spatial location (a direct subclass of physical quality). • 4.The spatial and temporal relations between surface features would be decribed in DOLCE, particulars can only participate in (instances of) these relations.

  21. Comparing DOLCE and SUMO

  22. Basic ontological choices in DOLCE • DOLCE is a descriptive ontology, as dictated by its cognitive bias. • DOLCE adopts the multiplicative approach. • DOLCE models both endurants and perdurants with the main relation between them of participation. This means that DOLCE's orientation can be 3D as well as 4D.

  23. DOLCE uses "the simplest quantified modal logic” i.e it assumes a possibilist view. • DOLCE is not sub-divided into modules.

  24. Basic ontological choices in SUMO • SUMO is neither explicitly descriptive nor revisionist. • SUMO is neither explicitly a multiplicative nor a reductionist approach" but the major part of its theories commits to a ” multiplicative stance." • SUMO is an ontology of both particulars and universals. SUMO classifies a number of universals as well.

  25. The lack of modal logic suggests that SUMO tends towards actualism. • SUMO is divided into SUMO itself, middle level ontology and domain ontology.

  26. Table : Comparison of SUMO and DOLCE ontological choices SUMO DOLCE descriptive / revisionist tends towards descriptive descriptism reductionist / multiplicative Reductionist and multiplicative multiplicativism actualism / possibilism tends towards possibilism actualism universals or particulars? yes only particulars endurantism (3D) / 3D 3D as well as perdurantism (4D) 4D

  27. Conclusion: • DOLCE cognitive modal description reflects semantics more precisely. • DOLCE is conceptually sound but does not provide a detailed • taxonomy as SUMO. • DOLCE is used as a foundation for a diverse range of ontologies in different area where as SUMO is mostly used as a source of formal semantics in linguistics and NLP.

  28. References: • Claudio Masolo, Stefano Borgo,Aldo Gangemi, Nicola Guarino, Alessandro Oltramari , WonderWeb Deliverable D18, Ontology Library,2003. • Gaurav Sinha, David Mark, Toward A Foundational Ontology of the Landscape ,2000. • Daniel Oberle, Anupriya Ankolekar,Pascal Hitzler,Philipp Cimiano, DOLCE ergo SUMO:On Foundational and Domain Models in SWIntO(SmartWeb Integrated Ontology) , 2003.

  29. References: • Aldo Gangemi, Nicola Guarino, Claudio Masolo,Alessandro Oltramari, Luc Schneider,Sweetening Ontologies with DOLCE , 2000. • Salim K. Semy, Mary K. Pulvermacher, Leo J. Obrst, Toward the Use of an Upper Ontology for U.S. Government and U.S. Military Domains: An Evaluation,2004. • Bachelorarbeit zur Erlangung des akademischen Grades Bachelor of Arts (B.A.) , Foundational Ontologies – What for?Motivations for SUMO and DOLCE,2009.

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