1. Geographical Ontologies: An Overview Gilberto Camara National Institute for Space Research, Brazil Licence: Creative Commons ̶̶̶̶ By Attribution ̶̶̶̶ Non Commercial ̶̶̶̶ Share Alike http://creativecommons.org/licenses/by-nc-sa/2.5/

2. What’s out there?

3. Hic sunt leones et dragonesWhat’s out there?

4. fonte: Carlos Nobre What’s out there?

5. Reality What’s out there?

6. Data GIS A GIS B Format A Format B Lake Habitat

7. The realist perspective (John Searle) 1. There is a real world that exists independently of us, our experiences, our thoughts and our language. 2. We have direct perceptual access to that world through our senses and our measurement devices. 3. Words in our language can be used to refer to real objects in the world. 4. Our statements are typically true of false depending on whether they correspond to the facts in the real world. 5. Some features of the world exist independently of us, such as mountains and lakes. Some features of the world are dependent on a socially-constructed agreements, such as boroughs and land parcels.

8. Humans before language: cave paintings 17,000 BCE, Lascaux, France

9. It all begins with observations… What’s out there? We use words in our language to describe the world

10. What’s out there?

11. From analogue spaces to digital spaces

12. social network sensors everywhere mobile devices ubiquitous imagery Mobile devices, crowdsourcing, massive Earth observation sets: new technologies, new challenges

13. Geoinformatics enables crucial links between nature and society Nature: Physical equations Describe processes Society: Decisions on how to Use Earth´s resources

14. EVENTS / POINT SAMPLES SURFACES / REGULAR GRIDS AREA DATA / POLYGONS FLUX DATA / NETWORKS X,Y,Z From data to computer representations

15. 1991 iex Digital spaces: Social exclusion in São Paulo 2000

16. Digital space: Flows in networks

17. Digital spaces: Crime mapping in Calgary (CA)

19. Representation The Medieval King has in him two Bodies: a Body natural, and a Body politic. Representations of the King fulfill a key political function

20. Representation The King had two bodies: Otho III, holding a royal orb, inside a mandorla. Vivet et non vivit

21. Representation "Mosaic in the Martorana at Palermo, representing the coronation of King Roger II at the hands of Christ, where the desired effect of making the God manifest in the king was achieved by a striking facial resemblance between Roger and Christ." Ernst H. Kantorowicz, The King's Two Bodies: A Study in Mediaeval Political Theology (Princeton: 1957) 65

22. Conceptual models: built from abstractions

23. Spatial Data Natural Domain Human Domain IMAGES -planes -satellites ENVIRONMENTAL DATA -topography -soils -temperature -hidrography -geology CADASTRAL DATA -parcels -streets -land use CENSUS DATA -Demographics -Economics INFRASTRUCTURE -roads -utilities -dams System designer view of spatial data

24. A geographical ontology Geographical reality Natural objectsSocial objects boundariespropertiesidentity

25. Geographical reality Natural objectsSocial objects boundaries identity Geo-objects observations attributesFields properties

26. Boundaries: a key concept of social objects

27. The enclaves of Baale-Hartog

28. India-Bangladesh enclaves

29. Dahala Khagrabari: a 3 rd order enclave

30. Büsingen in Germany

31. What makes a sovereign state?

32. Republic of Crimea?

33. It all begins with observations… What’s out there? The continuously changing landscape of the Earth (topography) Mountains with names (Alps, Mont Blanc)

34. It all begins with observations… What’s out there? The continuously changing landscape of the Earth (topography) Mountains with names (Alps, Mont Blanc) Fields (coverages) objects

35. What about objects? Mont Blanc Objects are language constructs, built upon observations They require both an external reality and a conscious act to identify their existence

36. Objects as mental constructions derived from physical reality Mont Blanc “Mont Blanc” is a socially-accepted name for a specific topographic feature Where does “Mont Blanc” start and “Dôme du Goûter” end?

37. Objects as mental constructions derived from physical reality Walrus W1 To understand animal behaviour, we tag them and assign them an identity

38. Objects as mental constructions derived from physical reality Walrus W1 To understand animal behaviour, we tag them, assign them an identity and track their movements

39. Objects as mental constructs derived from social reality “Germany (1914)” is a geographical object whose existence is defined by laws and treaties Die Proklamation des Deutschen Kaiserreiches 1871

40. Objects as mental constructs derived from social reality “Germany (2013)” is a geographical object whose existence is defined by laws and treaties Einigunsvertrag 1990 Two-plus-Four Agreement 1990

41. Was Germany a nation before it were a state? Germania, in a 1834 fresco. When did Germany start to exist? What were the boundaries of Germany when Goethe lived?

42. The trajectory of German borders

43. Boundaries of natural and social objects may coincide (but are not the same) The boundaries of the Republic of Cuba are not the boundaries of the island of Cuba (think of Guantánamo)

44. Natural objects: we measure properties in reality… Map showing main topographical features in Europe.

45. …but always inside a bounding space… Map showing main topographical features in Europe. Where is Europe in this map?

46. Temperature, Water ph, soil acidity... The natural world has continuous spatial variation

47. Properties of natural objects can be continuous Map showing main topographical features in Europe. For every point inside Europe, there is a height measurement

48. Soils map of Europe

49. How real are those boundaries?

50. Gilberto Camara, Max J. Egenhofer, Karine Ferreira, Pedro Andrade, Gilberto Queiroz, Alber Sanchez, Jim Jones, and Lubia Vinhas image: INPE Fields as a Generic Data Type for Big Spatial Data

51. How can we best use the information provided by big data sources? Big data requires new conceptual views Image source: Geoscience Australia

52. Everything starts with measurements (Kuhn) “All information ultimately rests on observations, whose semantics is physically grounded in processes and mathematically well understood. Exploiting this foundation to understand the semantics of information derived from observations would produce more powerful semantic models”.

53. An example of big geospatial data image source: NOAA ARGO buoys - 3,500 floats 120,000 temp, salinity, depth profiles/year

54. ARGO buoys: innovative technology Sensors measure down to 2,000 m, 10-Day Cycle Floating buoys measuring properties of the oceans images source: NOAA

55. Another example: Free and big Earth Observation data Image source: NASA Open access data (US, EC, BR, CH): 5Tb/day

56. Earth observation satellites provide key information about global change … … but that information needs to be modeled and extracted

57. To deal with big geospatial data, we need to reassess the core concepts of Geoinformatics

58. Premise 1: Reality exists independently of human representations and changes continuously

59. Premise 2: We have access to the world through our observations

60. Premise 3: Computer representations of space and time should approximate the continuity of external reality

61. Temperature, Water ph, soil acidity... Natural world has continuous spatial variation

62. Conjecture 1: Data models for space-time data should be as generic as possible We need to represent volume, variety, velocity

63. Conjecture 2: Space-time data models need observations as their building blocks An observation is a measure of a property in space-time

64. Conjecture 3. Sensors only provide samples of the external reality To represent the continuity of world, we need more! Willis Eschenbach

65. temp = (2 + sin(2 π* (julianday + lag)/365.25)) ˆ1.4 Willis Eschenbach Conjecture 4: Approximating external reality needs space-time data samples and estimators

66. Conjecture 5: Fields = Sensor data + Estimators A field estimates values of a property for all positions inside its extent (fields simulate the continuity of external reality)

67. Fields as a Generic Data Type estimate: Position  Value Positions at which estimations are made Values that are estimated for each position

68. Fields as a Generic Data Type estimate: Position  Value Positions are generic locations is space-time Values are generic estimates for each position

69. Fields as a Generic Data Type estimate: Position  Value Instances of Position: space, time, and space-time Instances of Value: numbers, strings, space-time

70. An Australian Geoscience Data Cube A time series field (tsunami buoy) positions: time values: wave height image: Buoy near the coast of Japan

71. An Australian Geoscience Data Cube A coverage field (remote sensing image) image: USGS positions: 2Dspace values: soil reflectance

72. An Australian Geoscience Data Cube coverage set images: USGS A field of fields positions: time values: coverages (2DSpace  number)

73. A trajectory field positions: time values: space  8/8/99  11/7/03 Japan/East Sea Russia Japan Argo float UW 230 deployed 02.08.1999 10-day interval data until 07.11.2003 source: Stephen Riser University of Washington

74. A field of fields (Argo floats in Southern Ocean) Positions: space Values: trajectories (time  space)

75. External Reality Observ. Fields Objects Events Conjecture 6: To identify objects and events in our descriptions of reality, we need first to define fields

76. Geographical reality Natural objectsSocial objects boundaries identity Geo-objects observations attributesFields properties

77. Conclusion 1: The Fields data type is a generic model for different kinds of big space-time data image: INPE

78. Conclusion 2: The Fields data type enables a better description of of big space-time data than the layer view image: INPE

79. Conclusion 3: The Fields data type may foster a new generation of GISs that deal with big space-time data image: INPE