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Ubicomp's impacts on human health, such as exposure to non-ionising radiation through ubicomp
devices or psychological effects of implantable chips, have also been discussed in the literature. One
promising avenue of research is ecological computing (part of nature-inspired computing), which
is not only concerned with environmental impacts of computing technologies but also how to cre-
atively use ecological principles to design and develop computing systems (Zhuge and Shi, 2004;
Briscoe, 2012; Zhao and Brown, 2001).
16.4.3 P roSPectS : t owardS o Pen g eo c oMPutation
To effectively address these multiple challenges, we need to rethink the way GC has been practised so
far. In particular, we need to think about the ways ubicomp and spatial big data are changing how we
do science. The broader scientific community's push for a new paradigm under the general umbrella
open science deserves our attention. As reflected in the presentations made during the recent Open
Science Summit (opensciencesummit.com), exciting advances are being made every day in diverse
scientific fields ranging from mathematics (the Polymath project), astronomy (Galaxy Zoo, Sloan
Digital Sky Survey) and geology (the OneGeology project) to environmental science (Water Keeper,
Global Community Monitoring), health and medicine (the HapMap project, CureTogether).
Efforts devoted to open science are quickly fleshing out the details of emerging data-intensive
inquiries, otherwise known as the fourth paradigm. The fourth paradigm was originally advocated
by Jim Gray (2007) at IBM. According to Gray (2007), scientific discoveries until recently (the early
days of the twenty-first century) have been driven by three dominant paradigms: the empirical (by
describing natural phenomena), the theoretical (by using and testing models and general laws) and
the computational (by simulating complex phenomena using fictional/artificial or small real-world
data sets) approaches. Unlike these three paradigms, the fourth paradigm is data intensive, often
dealing with data in peta- or even exabytes of different varieties (numbers, text, image and video)
updated rapidly (in some cases, even real time).
Despite diverse interpretations of the precise meaning of open science (e.g. open source, open
data, open access, open notebook or networked science), we can safely claim that the emerging
paradigm, in a nutshell, includes the following elements (Gezelter, 2009): (1) transparency in
methods of data collection, observation and experiments; (2) public availability and reusability of
scientific data to facilitate reproducibility (see Brunsdon, 2014); (3) public accessibility of scientific
communication and publication; and (4) mass collaboration involving both experts and amateurs/
citizens using web-based tools.
While ubicomp and big data are creating a new terra incognita , maybe even too big to know
(Weinberger, 2012), Nielsen (2012) argues that these four basic principles of open science may serve
to best guide new scientific discovery. Indeed, we need such signposts; as the stream of geospatial
data rapidly merges with the big data deluge, and as open science is promoted as the Noah's ark in
which everyone is to survive the current information flood, it is natural that the next episode for GC
is moving towards an open GC.
In fact, I must say that the geospatial community had been working on big data in the spirit
of open science long before it became the talk of the town . As a result, the geospatial commu-
nity is well positioned to ride the current wave of open science because of our collective efforts
in promoting data sharing, open-source software development and participatory sensing/mapping
(citizens as sensors). For example, the Open Geospatial Consortium (opengeospatial.org) has been
a pioneer in developing open standards to facilitate interoperability of geospatial data across plat-
forms. Also notable, the FOSS4G (Free and Open Source Software for Geospatial) Conference
has - since 2006 - been serving as the primary forum to promote the development of free and open-
source software (foss4g.org). According to Steiniger and Hunter (2012), we now have a plethora of
free and open software tools, ranging from web map servers for managing data and images (such as
mapserver.org, geoserver.org), web GIS servers for data processing (52north.org, zooproject.org)
and data storage software/spatial DBMS (postgis.refractions.net, mysql.com) to registry/catalogue
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