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Ontologies for Reasoning, Action and Interaction in Space John Bateman University of Bremen SOCop Meeting: 12 th November 2009.

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Presentation on theme: "Ontologies for Reasoning, Action and Interaction in Space John Bateman University of Bremen SOCop Meeting: 12 th November 2009."— Presentation transcript:

1 Ontologies for Reasoning, Action and Interaction in Space John Bateman University of Bremen SOCop Meeting: 12 th November 2009

2 I1-[OntoSpace] Overview of talk Context of the work within our Collaborative Research Center: Spatial Cognition and my work within that Representations of Space Results and Conclusions Proposals for Ontology Best Practice Next targets and challenges 2

3 I1-[OntoSpace] 3 Areas : spatial reasoning, representation, action and communication Organisation: Collaborative Research Center Bremen / Freiburg funded by: Deutsche Forschungsgemeinschaft (DFG: German Research Council ) 3 Phases 1 st phase: : 12 projects 2 nd phase: : 18 projects 3 rd phase: being proposed Spatial Cognition: SFB/TR8

4 I1-[OntoSpace] 4 Spatial Assistance Mobility support Spatially-embedded tasks Descriptions of spatial situations verbally visually Exploration Navigation Dialogic interaction

5 I1-[OntoSpace] 5 Qualitative Information In front to the right is the seminar room Quantitative information Symbolic information [door_1 recognized] Bremen Autonomous Wheelchair: Rolland : Rolland

6 I1-[OntoSpace] Test-Bed: BAALL Bremen Ambient Assisted Living Lab Environment heating, lighting safety soft / hard / middleware interaction Appliances refrigerator cooker cupboards, drawers washing machine, microwave TV, PC, … mobile phone doors Autonomous assistance devices wheelchairs walkers Health monitoring Architecture

7 I1-[OntoSpace] Sensor data: free-space maps 7

8 I1-[OntoSpace] 8 Voronoi map From SFB/TR8 project: A1-[RoboMap] Voronoi calculation on a scanned floor plan where are you?

9 I1-[OntoSpace] 9 Unnatural / unhelpful descriptions 25.4 m NW of you GPS: 34° 15´ N / 3° 27´ E 3.45m away from edge 98 (with 80% certainty)

10 I1-[OntoSpace] 10 Natural route descriptions Leave the room and turn right into the corridor. Go to the window and then turn left. Follow the corridor and Im in the last room on the left. Many problems of semantic interpretation involved here...

11 I1-[OntoSpace] Context-specific way-finding assistance Kai-Florian Richter, Thomas Barkowksy et al. 11 "At the next junction go straight on, and then, turn right before a map. Keep following the river until a Telekom sign, and then, turn left after the Telekom sign. Go towards the Universum until a bus stop, and then, turn right after the bus stop." schematization

12 I1-[OntoSpace] 12 Sources of relevant knowledge Location-based services Geographic Information Systems Commonsense objects and activities Spatial awareness and understanding Natural language capabilities Robot perception

13 I1-[OntoSpace] 13 Basic problem Getting these diverse areas of expertise to talk to each other is a serious issue different communities different interests different representations The kinds of knowledge maintained by such systems are very different

14 I1-[OntoSpace] Consequences Component specifications are developed again and again (and again and again) Each community of practice defines them slightly differently (or not, it is difficult to tell) Each standardisation group has little time to look at parallel activities and must reflect the demands of its own community before considering others Lack of foundation leads to a proliferation of standardisation efforts 14

15 I1-[OntoSpace] Research Foci: John Bateman Computational Linguistics Multilingual natural language generation Interfaces between language technology and world/domain knowledge Development of linguistically-motivated ontologies Formal Ontology General design principles for ontology Relations between differently motivated ontologies Spatial representation and language Dialogic natural language interaction Spatial language

16 I1-[OntoSpace] 16 Solution we are pursuing High degree of interoperability between diverse knowledge-rich systems is to be achieved by ontological engineering, taking in: knowledge of the human world (commonsense) knowledge of the robot world (programmed, emergent) geo-knowledge (GML, other standards) spatial knowledge (spatial calculi, spatial ontologies) knowledge of language (linguistics)

17 I1-[OntoSpace] ONTOLOGY 1ONTOLOGY 2 Goals Achieving interaction between system modules using ONTOLOGIES DOMAINS ONTOLOGIES inter-ontology mediation HIGHLY STRUCTURED AND MOTIVATED SEMANTICS 17

18 I1-[OntoSpace] SPATIAL REPRESENTATIONSLINGUISTIC REPRESENTATIONS Goals Achieving interaction between system modules using ONTOLOGIES DOMAINS ONTOLOGIES inter-ontology mediation 18

19 I1-[OntoSpace] SPATIAL REPRESENTATIONSGENERAL ONTOLOGY Goals Achieving interaction between system modules using ONTOLOGIES DOMAINS ONTOLOGIES inter-ontology mediation 19

20 I1-[OntoSpace] ROUTE GRAPH R3: GVGROUTE GRAPH A1: PATH Goals Achieving interaction between system modules using ONTOLOGIES DOMAINS ONTOLOGIES inter-ontology mediation 20

21 I1-[OntoSpace] Ontologies but where to start?

22 I1-[OntoSpace] 22 Fundamental issue The ontologies present are diverse: different methodologies different motivations different domains of application different worlds different purposes different communities

23 I1-[OntoSpace] Representations of Space Ontology and Space Qualitative Spatial Representation and Reasoning Language GIS

24 I1-[OntoSpace] Representations of Space 24 physical mathematical Geometry ontology Foundational Ontologies Qualitative Spatial Reasoning + Representation Linguistics R3R3

25 I1-[OntoSpace] Ontology + QSR: Varying primitives 25 Bateman/Farrar (2006) Spatial Ontology Baseline

26 I1-[OntoSpace] Spatial Representations Ontology Qualitative Spatial Reasoning and Representation Language 26

27 I1-[OntoSpace] Ontologies: SUMO 27

28 I1-[OntoSpace] Ontologies: SUMO Shape: internal attribute (inheres in some entity) Position: relational attribute 28

29 I1-[OntoSpace] Ontologies: SUMO Spatial Relations 29

30 I1-[OntoSpace] Ontologies: Cyc 30

31 I1-[OntoSpace] Ontologies: Cyc 31

32 I1-[OntoSpace] Ontologies: Cyc 32

33 I1-[OntoSpace] Ontologies: Cyc: Paths 33

34 I1-[OntoSpace] Navigation: route graphs Graph Route MZH 3rdFloor kitchen MZH 3100MZH

35 I1-[OntoSpace] Ontologies: DOLCE basic categories 35

36 I1-[OntoSpace] DOLCE basic categories Rooms, offices, buildings, tables, chairs,... 36

37 I1-[OntoSpace] DOLCE basic categories Events, happenings, movements, changes 37

38 I1-[OntoSpace] DOLCE basic categories Agents, states of belief, plans, goals 38

39 I1-[OntoSpace] DOLCE inter-entity relationships Feature (F) Non-Agentive Physical Object (NAPO) Amount of Matter (M) Physical Endurant (PED) Physical Quality (PQ) OGD GK MSD S Mutual specific spatial dependence One-sided generic constant dependence Generic constant constitution Quality (Q) 39 corner of a table curve of a bay table coast wood rocks, sand, water heavy pebbly

40 I1-[OntoSpace] Spatial Representations Ontology Qualitative Spatial Reasoning and Representation Language 40

41 I1-[OntoSpace] 41 QSR: Region-Connection Calculus with 8 base relations Randell, Cohn, Cui 1992: RCC8

42 I1-[OntoSpace] 42 QSR: Region-Connection Spaces: RCC-5, RCC-8, 9+, etc. Randell, Cohn, Cui 1992 etc. / Egenhofer

43 I1-[OntoSpace] QSR: Reasoning by Composition 43 Composition table for RCC-8

44 I1-[OntoSpace] 44 QSR: Double cross calculus: Freksa / Zimmermann (1996) Qualitative description of position relative to a directed line segment

45 I1-[OntoSpace] 45 QSR: Reasoning by Composition ab:c bc:d ab:d Composition for reasoning

46 I1-[OntoSpace] 46 QSR: Reasoning by Composition Composition with additional relations Homing, Shortcut, Inverse, Homing- Inverse,Shortcut-inverse

47 I1-[OntoSpace] QSR: Star Calculus 47 Renz/Mitra 2004

48 I1-[OntoSpace] QSR: Dipole 48 Moratz et al. 2000

49 I1-[OntoSpace] QSR: OPRA 49 Moratz et al. 2005

50 I1-[OntoSpace] QSR: QTC 50 Van de Weghe et al. Qualitative Trajectory Calculus single object moving two objects moving

51 I1-[OntoSpace] Spatial Representations Ontology Qualitative Spatial Reasoning and Representation Language 51

52 I1-[OntoSpace] 52 Linguistic usage evidence… Herskovits (1986) what does on mean?

53 I1-[OntoSpace] 53 And more usage evidence… Herskovits (1986) what does in mean?

54 I1-[OntoSpace] 54 Herskovits (1986:125) The cat is in the table what does in mean? And more usage evidence…

55 I1-[OntoSpace] 55 Herskovits (1986) The potato is in the bowl what does in mean? And more usage evidence…

56 I1-[OntoSpace] Relating calculi and language Egenhofer and colleagues 56

57 I1-[OntoSpace] 57 Spatial Language extremely flexible sensitive to function and purpose Coventry, Garrod and others

58 I1-[OntoSpace] Many types of spatial information Ontology Qualitative calculi: RCC-n, Dipoles, Doublecross, etc. Way-finding abstractions: choremes Free-space representations (Voronoi) Natural language descriptions Metric maps With different reasoning methods, different coverage, different strengths and weaknesses 58

59 I1-[OntoSpace] Representations of Space 59 physical mathematical Geometry ontology Foundational Ontologies Qualitative Spatial Reasoning + Representation Linguistics BFODOLCEGFORCCDCOPRA9+GUM-Space alignment ???? R3R3

60 I1-[OntoSpace] 60 Methodological conclusion and starting point There is no sense in which a simple merging of all of the above is a sensible strategy to follow

61 I1-[OntoSpace] 61 Distinct facets or theories rather than inheritance lake geographical region obstacle recreational area source of pure water link in transit system (ferry)

62 I1-[OntoSpace] 62 Many perspectives on reality: many ontologies event time space-1 space-2 event Ontologically diverse

63 I1-[OntoSpace] 63 Ontological diversity inter-ontology mappings Way description time landmarks choremes event types CASL route graphs CASL

64 I1-[OntoSpace] Mapping between modules problem area time points of interest directions road conditions health status Hyperontology 64

65 I1-[OntoSpace] 65 Essential properties we are currently developing Perspectivalism Objects Activities Artifacts: spatial artifacts Language Granular partitions Plug-and-play spatial theories

66 I1-[OntoSpace] 66 Essential ingredients we are drawing on Existing ontologies Existing formal tools Extensions for the specific problem of combining information flexibly Combining distinct reasoning possibilities

67 I1-[OntoSpace] 67 Essential ingredients we are drawing on Existing ontologies DOLCE (for cross-category binding and axiomatization) BFO (for sites, niches and places and for SNAP/SPAN) GUM (generalized upper model for linguistic semantics)

68 I1-[OntoSpace] DOLCE basic categories 68

69 I1-[OntoSpace] 69 I1-[OntoSpace] Defining Qualities Quality Space Gärdenfors: Geometric Fauconnier: Logical

70 I1-[OntoSpace] 70 I1-[OntoSpace] Defining Qualities Quality Space Gärdenfors: Geometric Fauconnier: Logical Goguen: algebraic theory Theory

71 I1-[OntoSpace] GREY GREEN YELLOW ORANGE RED VIOLET HUE CHROMATICNESS From: Gärdenfors (2000, p10) Color Space (1): Color wheel 71

72 I1-[OntoSpace] RED YELLOW GREEN BLUE BLACK WHITE From: Gärdenfors (2000, p11) CHROMATICNESS Color Space (2) 72

73 I1-[OntoSpace] 73 RED YELLOW GREEN BLUE BLACK WHITE Defining Qualities Quality Space

74 I1-[OntoSpace] Dolce treatment of qualities Qualia: the position of an individual quality within a quality space ), t) 74

75 I1-[OntoSpace] DOLCE: spatial information For DOLCE, space is also a quality... 75

76 I1-[OntoSpace] DOLCE: relevant for space Physical Objects Physical Endurants (PED) Spatial Location Space Region 76

77 I1-[OntoSpace] DOLCE: relevant for space Physical Objects Physical Endurants (PED) Spatial Location Space Region 77

78 I1-[OntoSpace] Dolce treatment of qualities Qualia: the position of an individual quality within a quality space ), t) 78

79 I1-[OntoSpace] 79 Dolce treatment of qualities Qualia: the position of an individual quality within a quality space Space Region

80 I1-[OntoSpace] Valuable for `swappable treatments of space PED PQ qt ql Physical Endurant Physical QualityQuality Space: quale 80

81 I1-[OntoSpace] `Swappable treatments of space PED PQ qt ql RCC-5,7,8,10,15,23 Dipoles: D 14, DRA 14 DRA fp Cardinal directions Double Cross Formalized modules Should be possible to select formalization for the reasoning task at hand 81

82 I1-[OntoSpace] 82 Essential ingredients we are drawing on Formal and computational tools CASL Common Algebraic Specification Language (for specification, structuring and relating) HETS Heterogeneous Tool Set (for connecting to a range of reasoners)

83 I1-[OntoSpace] Standardised first-order specification language designed by CoFI Common Framework Initiative for algebraic specification and development since 1995 de facto standard approved by IFIP WG 1.3 Foundations of Systems Specifications (1998), extensive documentation (LNCS 2900, 2960) extensive User Manual and Reference Manual now available from Springer (LNCS 2900, LNCS 2960) supports structured specifications including imports, hiding, renaming, union, extensions, etc. Formalization choice: CASL Common Algebraic Specification Language

84 I1-[OntoSpace] The Tool HeTS Institution Theory

85 I1-[OntoSpace] CASL language constructs Structuring mechanisms: potentially applicable to any specification language as an additional layer of meta- organisation for semantic modularity OWL, UML, CommonLogic, etc.

86 I1-[OntoSpace] 86 Formalization choice: CASL Common Algebraic Specification Language Extensions : we have now added OWL-DL to the family of logics supported we are exploring combining the structuring principles of CASL and description logics we are progressively formalizing the entire family of qualitative spatial calculi

87 I1-[OntoSpace] 87 Lüttich & Mossakowski (FOIS 2004) Axiomatized Ontology in CASL GenParthood Primitives DOLCE

88 I1-[OntoSpace] 88 Lüttich & Mossakowski (FOIS 2004) GenMereology GenParthood DOLCE

89 I1-[OntoSpace] 89 spec MEREOLOGY = PRIMITIVES then %Ad7, Ad8, Ad9 and Ad10 are generated by % instantiation of GenMereology GENMEREOLOGY [sort T] then GENMEREOLOGY [sort S] then GENMEREOLOGY [sort PD] end Lüttich & Mossakowski (FOIS 2004) GenMereology GenParthoodPrimitives Mereology

90 I1-[OntoSpace] 90 The DOLCE ontology in CASL spec PreDolce = Mereology_and_TemporalPart and Temporary_Mereology and Participation and Constitution and Dependence and Direct_Quality and Temporary_Quale and Immediate_Quale end spec Dolce = PreDolce and Taxonomy end work continuing...

91 I1-[OntoSpace] 91 Lüttich & Mossakowski (FOIS 2004) Development Graph showing dependencies between specifications and proof obligations Links: theory morphisms imports of theories relative interpretations of theories open proved

92 I1-[OntoSpace] Reasoning First-Order Reasoning with CASL/HETS reasoners Description logic reasoning with DL reasoners Spatial Reasoning with specialized spatial reasoners: SparQ, GQR 92

93 I1-[OntoSpace] Reasoning: SparQ 93 Frank Dylla, Lutz Frommberger, Jan Oliver Wallgrün, and Diedrich Wolter

94 I1-[OntoSpace] Lessons drawn 94 Idea: Providing channels to ontologies provides access to detailed contextual world-knowledge that does not then have to be worked out again… Application Ontology

95 I1-[OntoSpace] Sharing knowledge and achieving interoperability Many projects, many products, many information providers now constructing ontologies BUT: proliferation of unrelated designs, impoverished or application-specific semantics, roll your own ignoring previous attempts lack of interoperability... which was precisely what ontologies were meant to provide! 95

96 I1-[OntoSpace] Metamodels: commonly restricted to ensuring translatability across formal languages not content Horiuchi modelling language dependence

97 I1-[OntoSpace] LOA, Dolce group: EU WonderWeb Project 97

98 I1-[OntoSpace] Problems... Looseness of definition Sparseness of definition does not give much to get hold of for relating distinct accounts/levels of abstraction 98

99 I1-[OntoSpace] Conclusions: Ontology Best Practice Light ontologies: semantic web... Heavy ontologies: Rich axiomatization Formal principles Well-defined design criteria 99

100 I1-[OntoSpace] Lessons drawn Ontological best design principles axiomatization modularity heterogeneity perspectivalism 100

101 I1-[OntoSpace] 101 Ontology construction Axioms are grouped into logically appropriate theories Theories may be extended via parameterization to achieve semantic re-use Theories may be created and related by views: theory morphisms Only with this availability of working with meaningful interrelationships can the complexity of distinct axiomatized ontologies really be harnessed.

102 I1-[OntoSpace] Where next? Geospatial Information set to become the next major area of ontological development? However, just converting existing schema to OWL is probably not going to be adequate 102

103 I1-[OntoSpace] Questions: modularity? 103 OpenGIS® City Geography Markup Language (CityGML) Encoding Standard (2008)

104 I1-[OntoSpace] Questions: modularity? 104 Geometry to BDM to IFC

105 I1-[OntoSpace] Selected Application Scenarios assisted ambient living (AAL) ADL, spatial activities,... geographic information science (GIS) OpenGIS, OGC, CityML, OpenStreetMap,... assisted architectural design (AAD) IFC, BIM,... In each application area, we want to interact directly with the appropriate national and international standards Our Next Steps 105

106 I1-[OntoSpace] Geographic Information Systems Ontologies Our Next Steps framework for connecting distinct geographic layers modular breakdown of relevant knowledge improving re-use relation to non-geographic modeling relation to qualitative representations relation to existing standards support for verbalisation and visualisation OpenStreetMap … 106

107 I1-[OntoSpace] and we can only do that in cooperation with those with the detailed expert knowledge! 107

108 I1-[OntoSpace] 108 Acknowledgements The entire SFB/TR8 team!

109 I1-[OntoSpace] 109 Advertisement International Research Training Group: semantic integration of geospatial information Application deadline soon! PhD training program


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