Geoscience Reference
In-Depth Information
16.1 INTRODUCTION
The most profound technologies are those that disappear.
They weave themselves into the fabric of everyday life
until they are indistinguishable from it.
Mark Weiser (1991, p. 94)
Although GeoComputation (GC) has been part of the scientific lexicon for over 16 years, its precise
meaning has yet to be settled as reflected by the great variety of definitions adopted by practitioners
since the early days of GC all the way through to the contributors of this latest book (Gahegan, 1999;
Ehlen et al., 2000; Fischer and Leung, 2010). Indeed, GC has meant different things to different
people. Defining GC is, in many interesting ways, just like defining
geography
; it has become
increasingly difficult and challenging due to the influence of centrifugal driving forces behind its
development. Perhaps Longley's (1998) more liberal definition - GC is what GC practitioners do -
captures the dynamics and diversity of the field better than any of the restrictive definitions so far
(Couclelis, 1998; Openshaw and Abrahart, 2000). Recent developments in spatial computing further
complicate the task of precisely defining GC (Yang et al., 2011, 2012; Agouris et al., 2012).
This chapter takes a more inclusive definition of GC: any form of computing that is motivated/
inspired by geographical/spatial concepts/theories or deals with geographical/spatial aspects of
reality. The primary goal here is to discuss the field of GC in the broader context of ubiquitous com-
puting (ubicomp) and the emergence of spatial big data. Ubicomp, also known as pervasive comput-
ing, refers to a new mode of computing in which information processing is embedded into everyday
objects, activities and environments. In doing so, I aim to open a discussion on the implications
of ubicomp for the next phase of GC development. In a broader sense, GC is intimately linked to
ubicomp - both literally and physically, simply because in Latin, ubi literally means
everywhere
,
which already implies
geo
or
spatial
. Unlike Couclelis (1998), this chapter does not make an explicit
distinction between
computing
and
computation
, thus using the two words interchangeably.
The rest of this chapter is organised as follows. After a brief introduction, Section 16.2 gives
an overview of the recent developments in ubicomp, followed by an introduction of location tech-
nologies in ubicomp and how to design ubicomp to facilitate GC in Section 16.3. Section 16.4 is
devoted to problems and prospects as provided by ubicomp for GC in the context of the big data
deluge. Inspired by the spirit of emergent open science, this section also discusses how an open GC
approach may better help practitioners deal with the challenging issues posed by the big data deluge.
The last section contains a summary and conclusions.
16.2 UBICOMP AND THE EMERGENCE OF AMBIENT INTELLIGENCE:
FROM CARDIAC PACEMAKERS TO A SMART PLANET
Since Stan Openshaw, who is generally recognised as being the
father of GC
(Openshaw, 2014),
first raised the banner of GC in the mid-1990s, the fields of both geography (especially in terms of
the location/positioning technologies) and computing have undergone dramatic changes. As far as
computing is concerned, perhaps one of the most profound changes is that information processing
capacity has been increasingly embedded in the environment around us (Mostéfaoui et al., 2008).
Indeed, the tools we invented to study the world have increasingly become an integral part of the
world (Sui and Morrill, 2004). In the early days of the twenty-first century, fewer than a quarter of
the computer chips produced by Intel were destined for desktops. Instead, more and more computer
chips are being embedded in the environment as sensors or other consumer products and household
items (Kitchin and Dodge, 2011). Furthermore, computing devices are not only a repository of data
but also communicate and process information. No longer confined to mainframes, server farms or
desktops - typically housed in climate-controlled, weather-proof data centres - computing has become
more mobile, embedded, distributed and disassembled (Figure 16.1) (Pierre, 2010). Along with the
