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Published in:

2015 | OriginalPaper | Chapter

# Outline of a Formal Theory of Processes and Events, and Why GIScience Needs One

Author : Antony Galton

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## Abstract

It has often been noted that traditional GIScience, with its focus on data-modelling functions such as the input, storage, retrieval, organisation, manipulation, and presentation of data, cannot readily accommodate the process-modelling functions such as explanation, prediction, and simulation which it is increasingly acknowledged should form an essential element of the GI scientist’s toolkit. Although there are doubtless many different reasons for this seeming incompatibility, this paper singles out for consideration the different views of time presupposed by the two kinds of function: on the one hand, the ‘frozen’ historical time required by data modelling, and on the other, the ‘fluid’ experiential time required by process modelling. Whereas the former places an emphasis on events as discrete completed wholes, the latter is concerned with on-going continuous processes as they evolve from moment to moment. In order to reconcile the data-modelling and process-modelling requirements of GIScience, therefore, a formal theory of processes and events is developed, within which their fundamental properties can be made explicit independently of any specific implementation context, and their relationships systematically investigated.
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Footnotes
1
The term ‘analysis’ could perhaps be included with the second set of functions as well: it is a broad term which covers a range of different activities. However, many traditional GIS functions such as interpolation, overlay, and generalisation are often described as ‘analytical’, and many, though not all, of the functions described by O’Sullivan and Unwin in their book on Geographic Information Analysis [23] belong with the ‘traditional GIS functions’ rather than the ‘more advanced capabilities’.

2
In some more recent treatments, place and time are amalgamated, and the nature of the theme is made more explicit, as in the geo-atom of Goodchild et al., which takes the form $$\langle \mathbf{x},Z,z(\mathbf{x})\rangle$$, where ‘$$\mathbf x$$ defines a point in space-time, Z identifies a property, and $$z(\mathbf{x})$$ defines the particular value of the property at that point’ [18].

3
Cf. [10]: ‘An event is an individual episode with a definite beginning and end ...’.

4
These are similar to what Aitken and Curtis [3] call Scripts: ‘A Script is a typical pattern of events that can be expected to re-occur: “dining in a restaurant” and “brushing one’s teeth” being well known examples’ (the restaurant example comes from the original exposition of the Script concept by Shank and Abelson [27]).

5
Cf. [33]: ‘[C]omputational processes are rather like computer programs, which when executed result in occurrents’. Here it is the program execution itself that is described as an occurrent, not the outputs resulting from it.

6
In [14], these are called ‘open’ and ‘closed’ processes respectively.

7
Note: This must be construed carefully: it is the type of event that is repeated, each individual event occurs just once.

8
It is instructive in this connection to compare Fig. 2 in [21] with Fig. 1 in [35], focussing particularly on the role assigned to the term ‘Event’ in the two diagrams.

9
It is important to note that the general theory has to handle event-types rather than specific unique occurrences. In defining what is meant by a chunk of some process, for example, we are characterising a type of event, not an individual event. There may be many different individual occurrences which come under this description (or only one, or none), whereas an individual event is by nature unique. If we say ‘It happened twice’ or ‘It happened again’, by ‘it’ we can only mean an event-type, of which we are reporting another occurrence.

10
As distinct from ‘globally finite’, which would mean there is a time before which the process is never active, and a time after which it is never active.

11
I have not proved this; it is a conjecture based on experiments with a number of plausible candidate definitions.

12
The first conjunct of the definiens is required to ensure that chunk(P) satisfies AxOcc.

13
The legitimacy of this definition depends on the fact, easily proved, that dechunk(E), so defined, satisfies AxAct.

Literature
1.
Abler, R., Adams, J.S., Gould, P.: Spatial Organization: The Geographer’s View of the World. Prentice-Hall International, Englewood Cliffs (1971)
2.
Adaikkalavan, R., Chakravarthy, S.: SnoopIB: interval-based event specification and detection for active databases. In: Kalinichenko, L.A., Manthey, R., Thalheim, B., Wloka, U. (eds.) ADBIS 2003. LNCS, vol. 2798, pp. 190–204. Springer, Heidelberg (2003) CrossRef
3.
Aitken, S., Curtis, J.: Design of a process ontology: Vocabulary, semantics, and usage. In: Gómez-Pérez, A. (ed.) Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management (EKAW02), pp. 108–113 (2002)
4.
Batty, M.: Geocomputation using cellular automata. In: Openshaw, S., Abrahart, R.J. (eds.) GeoComputation, pp. 95–126. Taylor and Francis, London (2000)
5.
Bivand, R., Lucas, A.: Integrating models and geographical information systems. In: Openshaw, S., Abrahart, R.J. (eds.) GeoComputation, pp. 331–363. Taylor and Francis, London (2000)
6.
Bregt, A.K., Bulens, J.: Integrating GIS and process models for land resource planning. In: Heineke, H., et al. (eds.) European Soil Bureau Research Report No. 4, pp. 293–304. Laboratory of GeoInformation Science and Remote Sensing, Wageningen University, The Netherlands (1998)
7.
Brown, D.G., Riolo, R., Robinson, D.T., North, M., Rand, W.: Spatial process and data models: towards integration of agent-based models and GIS. J. Geogr. Syst. 7, 25–47 (2005) CrossRef
8.
Claramunt, C., Parent, C., Thériault, M.: Design patterns for spatio-temporal processes. In: Spaccapietra, S., Maryanski, F. (eds.) Searching for Semantics: Data Mining, Reverse Engineering, pp. 415–428. Chapman and Hall, New York (1997)
9.
Couclelis, H.: Cellular worlds: a framework for modeling micro-macro dynamics. Environ. Plann. A 17, 585–596 (1985) CrossRef
10.
Reis Ferreira, K., Camara, G., Monteiro, A.M.V.: An algebra for spatiotemporal data: from observations to events. Trans. GIS 18(2), 253–269 (2014) CrossRef
11.
Galton, A.: The Logic of Aspect: An Axiomatic Approach. Clarendon Press, Oxford (1984)
12.
Galton, A.: Dynamic collectives and their collective dynamics. In: Cohn, A.G., Mark, D.M. (eds.) COSIT 2005. LNCS, vol. 3693, pp. 300–315. Springer, Heidelberg (2005) CrossRef
13.
Galton, A.: Eventualities. In: Fisher, M., Gabbay, D., Vila, L. (eds.) Handbook of Temporal Reasoning in Artificial Intelligence, pp. 25–58. Elsevier, New York (2005) CrossRef
14.
Galton, A.: Experience and history: processes and their relation to events. J. Logic Comput. 18, 323–340 (2008)
15.
Galton, A.: States, process and events, and the ontology of causal relations. In: Donnelly, M., Guizzardi, G. (eds.) Formal Ontology in Information Systems: Proceedings of the 7th International Conference (FOIS 2012), pp. 279–292 (2012)
16.
Galton, A., Worboys, M.: Processes and events in dynamic geo-networks. In: Rodríguez, M.A., Cruz, I., Levashkin, S., Egenhofer, M. (eds.) GeoS 2005. LNCS, vol. 3799, pp. 45–59. Springer, Heidelberg (2005) CrossRef
17.
Gehani, N.H., Jagadish, H.V., Shmueli, O.: Event specification in an active object-oriented database. ACM SIGMOD Rec. 21(2), 81–90 (1992) CrossRef
18.
Goodchild, M.F., Yuan, M., Cova, T.J.: Towards a general theory of geographic representation in GIS. Int. J. Geogr. Inf. Sci. 21(3), 239–260 (2007) CrossRef
19.
Harel, D.: Dynamic logic. In: Gabbay, D., Guenthner, F. (eds.) Handbook of Philosophical Logic. volume II: Extensions of Classical Logic, pp. 497–604. Reidel, Dordrecht (1984) CrossRef
20.
Hazelton, N.W.J., Leahy, F.J., Williamson, I.P.: Integrating dynamic modeling and geographic information systems. URISA J. 4(2), 47–58 (1992)
21.
Langran, G., Chrisman, N.R.: A framework for temporal geographic information. Cartographica 25(3), 1–14 (1988) CrossRef
22.
Moens, M., Steedman, M.: Temporal ontology and temporal reference. Comput. Linguist. 14, 15–28 (1988)
23.
O’Sullivan, D., Unwin, D.J.: Geographic Information Analysis. Wiley, Hoboken (2003)
24.
Peuquet, D.J.: It’s about time: a conceptual framework for the representation of temporal dynamics in geographic information systems. Ann. Assoc. Am. Geogr. 84, 441–461 (1994) CrossRef
25.
Peuquet, D.J., Duan, N.: An event-based spatiotemporal data model (ESTDM) for temporal analysis of geographical data. Int. J. Geogr. Inf. Syst. 9(1), 7–24 (1995) CrossRef
26.
Raper, J., Livingstone, D.: Development of a geomorphological data model using object-oriented design. Int. J. Geogr. Inf. Syst. 9, 359–383 (1995) CrossRef
27.
Shank, R.C., Abelson, R.: Scripts, plans, goals and understanding. Erlbaum, Hillsdale (1977)
28.
Snodgrass, R.T.: Temporal databases. In: Frank, A.U., Formentini, U., Campari, I. (eds.) GIS 1992. LNCS, vol. 639, pp. 22–64. Springer, Heidelberg (1992) CrossRef
29.
Takeyama, M., Couclelis, H.: Map dynamics: integrating cellular automata and GIS through geo-algebra. Int. J. Geogr. Inf. Sci. 11, 73–91 (1997) CrossRef
30.
Tobler, W.R.: Cellular geography. In: Gale, S., Olsson, G. (eds.) Philosophy in Geography, pp. 379–386. D. Reidel, Dordrecht (1979) CrossRef
31.
Torrens, P.M.: Process models and next-generation geographic information technology. ArcNews Online, Summer 2009. http://​www.​esri.​com/​news/​arcnews/​summer09articles​/​process-models.​html
32.
Torrens, P.M., Benenson, I.: Geographic automata systems. Int. J. Geogr. Inf. Sci. 19(4), 385–412 (2005) CrossRef
33.
Worboys, M.: Event-oriented approaches to geographic phenomena. Int. J. Geogr. Inf. Sci. 19, 1–28 (2005) CrossRef
34.
Worboys, M.F., Hornsby, K.: From objects to events: GEM, the geospatial event model. In: Egenhofer, M., Freksa, C., Miller, H.J. (eds.) GIScience 2004. LNCS, vol. 3234, pp. 327–343. Springer, Heidelberg (2004) CrossRef
35.
Yuan, M.: Representing complex geographic phenomena in GIS. Cartography Geogr. Inf. Sci. 28(2), 83–96 (2001) CrossRef
Metadata
Title
Outline of a Formal Theory of Processes and Events, and Why GIScience Needs One
Author
Antony Galton
Copyright Year
2015
DOI
https://doi.org/10.1007/978-3-319-23374-1_1