See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/263078531
Space-Time Representation and Analytics
Article in Annals of GIS · January 2014
DOI: 10.1080/19475683.2013.862301
CITATIONS READS
3 88
3 authors:
May Yuan Atsushi Nara
University of Texas at Dallas University of Oklahoma
67 PUBLICATIONS 1,019 CITATIONS 16 PUBLICATIONS 94 CITATIONS
SEE PROFILE SEE PROFILE
James Bothwell
University of Oklahoma
7 PUBLICATIONS 15 CITATIONS
SEE PROFILE
All in-text references underlined in blue are linked to publications on ResearchGate, Available from: May Yuan
letting you access and read them immediately. Retrieved on: 14 April 2016
This article was downloaded by: [University of Oklahoma Libraries], [Dr May Yuan]
On: 16 April 2014, At: 11:49
Publisher: Taylor & Francis
Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House,
37-41 Mortimer Street, London W1T 3JH, UK
Annals of GIS
Publication details, including instructions for authors and subscription information:
http://www.tandfonline.com/loi/tagi20
Space time representation and analytics
May Yuana, Atsushi Naraa & James Bothwella
a
Center for Spatial Analysis, University of Oklahoma, 301 David L. Boren Blvd, Norman, OK
73019, USA
Published online: 10 Jan 2014.
To cite this article: May Yuan, Atsushi Nara & James Bothwell (2014) Space time representation and analytics, Annals of GIS,
20:1, 1-9, DOI: 10.1080/19475683.2013.862301
To link to this article: http://dx.doi.org/10.1080/19475683.2013.862301
PLEASE SCROLL DOWN FOR ARTICLE
Taylor & Francis makes every effort to ensure the accuracy of all the information (the  Content ) contained
in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no
representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the
Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and
are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and
should be independently verified with primary sources of information. Taylor and Francis shall not be liable for
any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever
or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of
the Content.
This article may be used for research, teaching, and private study purposes. Any substantial or systematic
reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any
form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http://
www.tandfonline.com/page/terms-and-conditions
Annals of GIS, 2014
Vol. 20, No. 1, 1 9, http://dx.doi.org/10.1080/19475683.2013.862301
Space time representation and analytics
May Yuan*, Atsushi Nara and James Bothwell
Center for Spatial Analysis, University of Oklahoma, 301 David L. Boren Blvd, Norman, OK 73019, USA
(Received 1 October 2013; accepted 30 October 2013)
This paper discusses philosophical and methodological considerations of space time representation and analytics. Central to
our premise is that how we conceptualize space and time has profound influence on the way in which we represent and
analyse spatiotemporal data. Four approaches in space time representation are discussed based on two sets of space time
dichotomies: absolutism versus relationalism and realism versus idealism. We elaborate on the philosophical inquiries
related to the dichotomies and discuss approaches taken in GIScience research. Since most GIS studies to date align well
with the absolutism realism approach to space time representation, we discuss examples that adopt absolutism idealism,
relationalism realism, and relationalism idealism approaches. We argue that multiple perspectives of space and time can
bring rich insights into understanding geographic phenomena. All four approaches of space time representation and
ensuing analytical methods should be broadly explored in GIScience research.
Keywords: space time; representation; analytics
1. Introduction
or time? Are space and time causally inert and
Space and time, hereafter space-time, are fundamental yet
therefore imperceptible? If so, it would be impos-
complex subjects that have stimulated fascinating debates
sible to represent space and time. Is the origin of
among philosophers, physicists, geographers, historians
space time representation constrained by spatio-
and scholars in many other fields. Most of the ontological
temporal objects? Or is it possible to have a repre-
and epistemological questions concerning space and time
sentation of space and time themselves? Are space
from Kant and his fellow philosophers (Janiak 2012)1
and time dependent upon the mind for their exis-
remain relevant to geographic information science
tence? Realists consider relations are mind-inde-
(GIScience) research today:
pendent; for idealists, relations are mind-
dependent. Is the dependence suggested by the
(1) Question about the ontology and substance prop- origin or the content of our space time
erty metaphysical framework: Is space time a sub- representation?
stance in its own right or a property of some (3) Question about the content of space time repre-
substance? The question inquires the relationship sentation: Does our idea about space reflect what
of space time to physical objects, contrasting we know from Euclidean Geometry? Can space
views of absolutism (viz. space time points time be an empirical concept derived from outer
exist) and relationalism. Absolutism views experiences? Can the content of a representation
space time as an object-independent framework, guide us to its possible origin? Can the origin of
whereas relationalism considers space time as the a representation lead to its potential content? If
order of possible relations among objects. we represent space containing an infinite number
(2) Question about the origin of space time represen- of places within it, each of the places would also
tation: Where do our ideas about space and time have an infinite number of subordinate concepts
come from? Do the ideas of space and time origi- about space. Hence, a concept contains an infinite
nate from the perceptions and experiences of spa- number of concepts, each of which has an infinite
tial or temporal relations? Is there any distinct number of constituents of sub-concepts and
issue about space time from ordinary physical recursive sub-concepts, and eventually the con-
objects? While we can represent space as empty cept of space lacks determinant content and
of objects, can we represent the absence of space therefore is deemed incomprehensible. If our
*Corresponding author. Email: [e-mail]
© 2013 Taylor & Francis
Downloaded by [University of Oklahoma Libraries], [Dr May Yuan] at 11:49 16 April 2014
2 M. Yuan et al.
representation of space is not a concept, is it an a form of geographic information (Goodchild et al. 2007). A
priori intuition? geo-atom is a space time point with semantic properties and
associated values for the properties. When geo-atoms are
These philosophical inquiries nurture our thinking about bounded by the same identity over space and time, these
space time, and our space time conceptualization influ- geo-atoms represent a geo-object. When geo-atoms are
ences how we construct geographic representation and bounded by the same property over space and time, these
consequently constrains what analytics we can perform geo-atoms represent a geo-field. Various means of aggrega-
and what insights we can gain from research. For philo- tion and agglomeration of geo-atoms in space and time form
sophers, a representation is  an image, concept, or thought representations of complex geographic phenomena. When
in the mind as representing an object or state of affairs in the ontology of geographic information is the focus, such a
the world (c.f. Oxford English Dictionary Third Edition, bottom-up approach is realized by observation-driven ontol-
December 2009). The object of a representation captures ogy engineering according to sensors, observation proce-
semantic properties, such as content, truth-conditions and dures and observations (Janowicz 2012).
truth-value, philosophically speaking. In the context of Relationalism and idealism of space and time are yet to
GIScience, space time representation encapsulates in flourish in GIScience research. Some research in GIS data
forms of data objects the essential characteristics of enti- modelling touched on the idea that vector data models only
ties, facts, concepts, and states of affairs on Earth (or include space occupied by geometric objects and therefore
simply things on Earth). dismiss the possibility of empty space, hence that space can-
Things on Earth, abstract or concrete, can be challen- not be a substance in its own right (Couclelis 1999). However,
ging to conceptualize and consequently difficult to repre- the underlying geographic coordinate framework very much
sent. On the other hand, scientific research relies upon grounds the space where the objects occupy, so, in essence,
observations and therefore is bound by means that we can vector data models remain fundamentally absolutistic and
express our observations, quantitatively or qualitatively. substantivalistic. From a relational perspective, the existence
Taking the absolutist s view, GIScientists represent space of space time depends on possible objects and relations. GIS
as a collection of lattice points, for example, with semantic examples of space time relationalism are address-matching
properties at locations and then expand the lattice orthogon- and routing, in which locations and paths can only exist in
ally to a cube to incorporate the temporal dimension. Such a relation to street networks. Idealism views space time as an a
space time cube representation can be traced back to prior intuition, i.e. a non-empirical, singular, immediate repre-
Hägerstrand s time geography (Hägerstrand 1970) and is sentation of space that cannot be derived from outer experi-
shown effective in information visualization (Kristensson ence but arises from the mind-dependent perception of spatial
et al. 2009), spatiotemporal analysis and synthesis (Nakaya relations. While virtual space, social space and political space
2013), visual exhibition exploration (Windhager and Mayr may not be intuitive, these spaces are idealistic in nature.
2012), space time data modelling and mathematical mod- Regarding time, psychological time and parallel time are
elling (Gatalsky, Andrienko, and Andrienko 2004). In fact, examples of idealistic time which are not elements of reality
most space time research in GIScience and related fields but relations added by the mind. A growing number of critical
adopts the view of absolutism that space time is an object- GIS studies take feminist and qualitative approaches that are
independent framework (e.g. a cube), existing on its own as mostly aligned with the idealistic view of space and time
a container populated with space time points or objects. (Kwan 2007; Cope and Elwood 2009). With the emphases
The absolutist s view is often accompanied with the of knowledge production different from the objective and
idea of realism in which things on Earth are perceived and quantitative trajectories, critical GIS pushes for the values of
experienced as fields and objects. Consequently, geo- social theory and neogeography in support of local epistemol-
ontology studies decipher categories of geographic phe- ogy on life-worlds (Sheppard 2005).
nomena to various kinds of fields and various kinds of This paper examines the four quadrants of space time
objects in space and time (Galton 2003) or theorize the representation (Table 1) in GIScience: absolutism realism,
ontological hierarchy of geographic information that con- absolutism idealism, relationalism realism and relational-
nects existence, observable, class, simple object, compo- ism idealism, and how representation influences space
site object, function, and purpose levels of representations time analytics. While there are rich research programmes in
(Couclelis 2010). Human experiences position objects and critical GIS, this paper limits discussions from a scientific
fields in the pre-defined space time framework. The and computational perspective on space time representation.
values of space and time for a given thing (object or Ontological issues from social theory and critical theory
field) depend on the location and chronological time of perspectives on realism, empiricism and idealism are beyond
observations. In other words, space and time are pre- the scope of the discussions here. The premise is that our
defined, regardless of the existence of objects and fields. thinking and questioning about space time inspire the way
An alternative  bottom-up thinking of geographic repre- in which we construct representation, and furthermore, con-
sentation starts with the idea of geo-atom, the very primitive strain what analytics we can do and conclusions we can draw
Downloaded by [University of Oklahoma Libraries], [Dr May Yuan] at 11:49 16 April 2014
Annals of GIS 3
Table 1. Four quadrats of space time representation (Janiak 2012).
1. Absolutism Relationalism
Realism Space is an object-independent framework for object relations. Space is the order of possible relations among objects
Relations are mind-independent Relations are mind-independent.
Idealism Space is an object-independent framework for object relations. Space is the order of possible relations among objects.
Relations are mind-dependent Relations are mind-dependent
property value is recorded for the theme of interest, such as
temperature. Animation is a common technique to visualize
temporal changes captured in the data, and map algebra and
matrix calculations by mathematical and statistical opera-
tions at pre-defined space and time. An idealistic view will
look beyond space time data records to conceptualize
higher-level phenomenal constructs out of the recorded prop-
erty, such as heat waves out of temperature observations. By
conceptualizing and representing heat waves or heat flows,
we enhance our intuited space time perception of the world.
Such abstract, mind-constructed objects can be very effective
in eliciting hidden patterns in space time data.
Figure 1. Conceptualization, representation and analytics.
The use of heat flows has been shown to be effective
in comparison of temperature projections between two
(Figure 1). Absolutism realism of space and time is well
general circulation models: the CNRM-CM3 model by
represented in a wide range of GIS studies, such as in land- Centre National de Recherches Meteorologiques
use and land-cover change and spatial ecology. It may be fair
(CNRM), Meteo France and the CCSM3 model by
to say that the dominant majority of GIS projects assume
National Center for Atmospheric Research (NCAR) in
absolute space time based on a Cartesian coordinate system
the United States (Bothwell and Yuan 2010). Instead of
and solar calendar with clock time. The other three views of
representing temperature values at grid cells and a given
space time deserve additional attention. The following three
time, the conceptualization of heat flows results in flow
sections will present a study in each section to highlight
vectors across grid cells over time. Flow vectors may be
absolutism idealism, relationalism realism and relational- defined in different ways. One can be the direction and
ism idealism, respectively, in space time representation
shortest distance to the cell of the same value at the next
and analytics. In this paper, the purpose of these examples
time-stamped snapshot. Another possible definition of
is to illustrate the conceptual differences in treatments of
flow vectors could be that each grid cell records a vector
space and time and how a novel conceptualization of space
with direction to the adjacent cell with the largest tem-
and time will lead to effective representation and analytics
perature gradient and the magnitude of the temperature
for new insights about geographic dynamics. Technical
difference. Regardless of flow vector definitions, the ima-
details on algorithmic and computational procedures are
ginary vectors provide direct mapping to concepts like
beyond the scope of the paper. Readers who are interested
expansion, retreat, divergence and convergence.
in the technical details should consult the cited references in
For global temperature projections, heat flow vectors
the respective section. This paper will conclude with a synth- moving northwards or southwards from the equator corre-
esis of findings from the three studies and new perspectives
spond to warming effects (Figure 2). When they move
to space time representation and analytics.
towards the equator, it suggests a cooling effect. When heat
flow vectors serve as the primitives in representing tempera-
ture over space and time, we can query flow vectors based on
2. Absolutism idealism of space time
the moving direction of interest to reveal warming or cooling
Absolutism idealism posits that space time is an object- dominant regions. For example,  heat flows moving towards
independent framework for mind-dependent object relations.
the poles (northwards in the northern hemisphere or south-
The space time framework is conceptualized as a container
wards in the southern hemisphere) suggest a warming trend
to position and reference things of interest. Environmental
(e.g. a and b in Figure 2). Accordingly, Figure 2 shows that
remote-sensing data and model outputs are good examples,
the NCAR model suggests a much wider spread of warming
in that data are recorded at a pre-defined regular grid space
in the southern hemisphere during 2030 2090 than what is
and regular time intervals. Space time is conceptualized as a
predicted by the CNRM model. We can also calculate spatial
series of time-stamped spatial grids and at each grid point, a
variability of moving directions and temperature differences
Downloaded by [University of Oklahoma Libraries], [Dr May Yuan] at 11:49 16 April 2014
4 M. Yuan et al.
Figure 2. Decipher temperature change over space and time using mind-dependent heat flows. In (A) and (B), dark-shaded colour
corresponds to flows to the south, and light-shaded colour, to the north. In (C) and (D), dark-shaded colour corresponds to flows to the
west, and light-shaded colour, to the east.
to identify mixing zones. Moreover, we can analyze the mind-independent. Since space time depends on the existence
direction and magnitude of changes in flow vectors to reveal of the objects of interest, space time analysis can only work
areas of transition zones where temperature change goes from where and when there are objects. Spatial and temporal refer-
slow to fast, convergent zones where temperature change ences of an object are relative to other known objects in the
converges to a hot spot or cold spot, and divergent zones system. Track analysis is used here to demonstrate the space
where warm or cold temperature expands outwards. By relat- time representation from the perspective of relationalism and
ing coastlines to flow vectors, we can also determine land sea realism. A conventional approach to track analysis puts a great
temperature relationships, such as a cooling effect from sea to emphasis on trajectory density and clustering analysis (Kwan
land. Based on c and d in Figure 2, CNRM model suggests a 2004; Li, Han, and Kim 2006; Palma et al. 2008; Li et al. 2011),
stronger regional moment of heat flows easterly, and sea to which follows the absolutism realism view. A relationalism
land flows in east Brazil, as opposed to land to sea movement realism approach will focuses on the relationship among tracks
suggested by NCARmodel. to discern potential patterns or implications.
This example adopts an absolute space time framework Using global positioning system (GPS) points taken
in which space is set at an absolute grid of 1° latitude × 1° for an individual from 1 May to 31 October 2009, we
longitude cells, and time is set at 60 years of monthly attempt to show a relationalism realism space time
temperature estimates. Space time relations are constructed approach for track analysis. Detailed algorithms and ana-
idealistically based on the concept of heat flowing from lyses are available in Yuan and Nara (Forthcoming).
high to low temperature across space over time. The object Figure 3 shows the 21,160 GPS points only during the
 heat flow is imaginary and constructed in mind as a month of September for the individual. The massive GPS
surrogate for understanding temperature change and its points obscure meaningful movement patterns. Taking a
patterns. Beyond mapping and visualization, each cell in relationalism approach, we compare stops made on a day
the grid is associated with the data that record the direction to those closest stops made on the previous day and
and distance of movement. Therefore, query and analysis analyse accumulative distance of the stop pairs for differ-
can be performed to discern locations with fastest spreading ent days of the week over the 6-month period (1 May
of warming or reveal pronounced differences between the 2009 31 October 2009). If the individual has a weekly
estimates from the two models. routine of stops (such as going to work), there will be
some regularity in the fluctuation of the accumulative
distance among closest stops the next day over time.
Figure 4 summarizes the result and shows the following.
3. Relationalism realism of space time
The relationalism realism view of space time posits that
space time is the order of relations among objects, and (1) The individual stopped at nearby locations Saturday
objects are observable and measurable, and therefore to Wednesday and Thursday to Friday in general.
Downloaded by [University of Oklahoma Libraries], [Dr May Yuan] at 11:49 16 April 2014
Annals of GIS 5
Figure 3. GPS points taken for an individual from 1 September 2009 to 30 September 2009 as an example.
(2) On Thursdays and Saturdays, the individual Figure 6 summarizes the track differences to the previous
tended to stop by locations away from stops day throughout the 6-month period. The darker shade in
made on Wednesdays and Fridays. the image corresponds to smaller differences in tracks. A
distinctive pattern is the repetitive pattern of two white
Likewise, we can also compare track differences to discern lines separated by a black line throughout the study per-
meaningful patterns. Because GPS points were taken at iod. These white-black-white patterns corresponded to
different times, resampling was used to derive tracks of tracks taken on Thursdays, Fridays and Saturdays. That
locations at equal time intervals (Figure 5). We can com- the individual had days off on Thursdays and Fridays and
pare tracks taken weekly at the same day of the week to resumed work on Saturdays resulted in a large difference
examine, for example, if the individual generally took the in tracks between Wednesdays and Thursdays, similar
same journey every Monday. We can compare a track to tracks on Thursdays and Fridays and again large differ-
the one taken on the previous day to assess how the ence between Fridays and Saturdays. In the early dates,
individual might adhere to a daily commute pattern. there was no clear pattern, which might be indicative of
Figure 4. Individual stop comparison over a 6-month period (Adapted from Yuan and Nara, Forthcoming).
Downloaded by [University of Oklahoma Libraries], [Dr May Yuan] at 11:49 16 April 2014
6 M. Yuan et al.
Figure 5. Resampling using a mean filter to match locations along tracks for comparison.
the period in which the individual was new to the town 4. Relationalism idealism of space time
and was looking for work (the top circle in Figure 6). The
While still using space time as the order of possible
space time track image also suggests that the individual
relations, a relationalism idealism approach examines
took outings around 20:00 on workdays in four separate
the relations among objects that are intuitive and mind-
weeks starting in late May and then in August, September
dependent. As such, the space time representation relies
and October, but usually returned home by 22:00 (the four
upon abstract constructs conceptualized in human minds
small circles in Figure 6). Furthermore, the individual
prior to the formation of space time concepts. Spatial
went out frequently around midnight on Thursdays.
social network analysis is a good example of relational-
The track analysis above provides an example of the
ism idealism approaches. A social network is a social
relationalism realism approach, in which we considered
phenomenon with entities tied with interactions or inter-
space time as the order of possible relations among GPS
dependence (Borgatti et al. 2009; Carpenter, Li, and
observations to elicit meaningful patterns from the massive
Jiang 2012). Space time in a social network is deter-
data points. Specifically, we applied time as the first order
mined by the member activities in the network, and
of relations among observations, and considered space
space time makes the connections among the members
based on the distance among points and tracks to discern
and their activities. Social network data analytics
further relations. Rather than investigating into the density
assumes potential links among individuals and explores
or clustering of GPS points or tracks, we mined the data to
the characteristics of the network as a whole or its
reveal deviations and periodicities of stops and tracks over
compositions (Aggarwal 2011). Nevertheless, a social
time to understand movement patterns, detect irregular out-
network is an abstract construct that provides an intuitive
ings and recognize possible emergence of new routines.
surrogate for analysis and reasoning of the social
Figure 6. A temporal image of track differences (Adapted from Yuan and Nara, Forthcoming).
Downloaded by [University of Oklahoma Libraries], [Dr May Yuan] at 11:49 16 April 2014
Annals of GIS 7
phenomena of interactions or interdependence. Our
example below assumes that the existence of social net-
works of potential interactions may be identified by
space time proximity of individuals.
We used GPS data from 2795 individuals in Oklahoma
from 23 February 2009 to 22 January 2011 to uncover
social networks of potential interactions (Yuan and Nara,
Forthcoming). Synchronous presence thresholds were set
at a space time proximity of 45 m and 30 minutes.
Relations among the individuals were determined by
their space time proximity. Only individuals with GPS
points recorded in the defined thresholds were considered
Figure 7. The estimated social networks of potential interac-
related and therefore included in the social network of
tions among 2795 individuals in Oklahoma based on their GPS
potential interactions. Among the 2795 individuals, GPS
points. Each node corresponds to each individual and its shade
points from 373 individuals fell within the space time
represents an individual s total potential interaction duration. The
proximity that created 54 social networks of potential
thickness of the links corresponded to the frequency of synchro-
interactions (Figure 7).
nized presence.
Figure 8 shows one of the largest networks that
involves 78 individuals. In the network, we can identify of potential interactions were very similar. Such long
three distinctive sub-networks with one-to-one (Figure 8A), space time coexistence indicates kinship and strong friend-
one-to-many (Figure 8B) and many-to-many (Figure 8C) ship. In the one-to-many example, a central node in the
relations. In the one-to-one relation, ID1 and ID2 have a
network (ID3) had all weak relations with 21 individuals,
strong relation, in which both trajectories and stops on days where each potential interaction event was in a short
Figure 8. The estimated social network of potential interactions involving 78 individuals in Oklahoma and examples of their
trajectories, stops and potential interaction locations on days of their potential interactions.
Downloaded by [University of Oklahoma Libraries], [Dr May Yuan] at 11:49 16 April 2014
8 M. Yuan et al.
duration. As shown in the Figure 8B, the ID3 s trajectories abstract constructs). The combination of the two
covered across a wide area; therefore, the individual had dichotomies resulted in four possible space time represen-
more opportunities to interact with other individuals. This tations: absolutism realism, absolutism idealism,
weak relationship could be explained by a post person who relationalism realism and relationalism idealism. GIS
would have frequent interactions with people at many research commonly adopts the absolutism realism
delivery locations. In Figure 8C, five individuals have approach to space time representation. This is evident
strong relations with each other, creating a pentagon- that conventional GIS applications analyses, computes
shaped network. On the map, there is one potential inter- and maps data in a Cartesian system with pre-defined
action location pointed by an outlined grey arrow that is for time intervals. Examples of such GIS applications include
multi-individual congregation. This location could corre- thematic mapping, crime density analysis and site suitability
spond to their social activities, such as visiting a common modelling. This paper offers three examples to demonstrate
friend, hanging out at a bar, or attending meetings. the other three approaches of space time representation.
The social network example illustrates two key The absolutism idealism approach was demonstrated
notions of relationalism idealism with respective to by the representation of heat flows as an integral concept
space time representation and analytics. First, the of space time temperature change to compare predictions
assumed existence of social networks of potential interac- from two general circulation models. Common approaches
tions sets the scope to which space and time should be would follow an absolutism realism framework to com-
conceptualized and analysed. There are four different pare temperature differences at the pre-defined locations
kinds of interactions according to constraints of synchro- (e.g. grid cells or climate stations) over time. Using the
nized vs. asynchronized space and time (Janelle 1995). abstract concept of heat flows that represent the magnitude
The example only considers social networks of potential and direction of imagery movements along the maximum
interactions that are synchronized in space and time. If temperature gradient at the pre-defined locations, we are
asynchronized interactions are of interest, the treatment of able to discern patterns that correspond to warming, cool-
space and time in the analysis will need to be significantly ing and divergence or convergence of hot spots.
rethought. Therefore, the representation of space and time As an example of relationalism realism approaches,
depends upon the conceptualization of social networks of we analyzed GPS points of an individual collected over
interest in prior. Second, once the nature of social net- a 6-month period. Instead of density or clustering pat-
works of interest is determined, space time is conceptua- terns of the points and tracks, we related points and
lized in the framework of object activities. Considerations tracks spatially and temporally to seek implications for
are only given to where and when recorded in GPS data. potential routine and incongruent activities. Space time
Comparative measures of space and time determine the representation functioned as measures of similarity and
relations among objects, and space time connections of all ordering of relations among the points and tracks.
related objects form social networks that can only be Finally, we took a relationalism idealism approach to
idealized in human minds. elicit social networks of possible interactions based on
GPS data of 50 individuals. Relations among the indi-
viduals were determined by the proximity of their GPS
5. Conclusions
points. Space time set the proximity thresholds for pos-
Central to the paper is the idea that space time representation sible interactions in building social networks. The
sets the foundation for space time analytics and consequently abstract concepts of social networks were conceived
analytical outcomes. We revisited key philosophical questions prior to the conceptualization of space and time and
about space and time and explored GIS studies that were subsequently the analytical procedures to reveal the
aligned with different thoughts of space time representation. potential links among the individuals.
Specifically, the three key questions were discussed on Our premise posits that the four views of space time
the ontological basis, origin and content of space and time, representation offer profound perspectives for GIS
and these questions ramified themselves in two dichoto- research. Our conceptualization of space time leads us to
mies: (1) about the space time existence in terms of different strategies in space time representation and ana-
absolutism and relationalism; and (2) about the origin lytics, and consequently draws insights from multiple
and content of space time in terms of realism and perspectives. Currently, most GIS applications subscribe
idealism. Absolutism contrasts relationalism by the view to absolutism realism thinking of space and time and have
that space time exists in its own right (i.e. an object- been productive in analysing objects or fields from which
independent framework) rather than as properties of data were collected. What relationalism and idealism sug-
physical objects (i.e. the order of possible relations gest are rich suites of new possibilities by considering
among objects). Realism contrasts idealism by the abstract constructs of rich semantics that can be built
view that space time and objects are mind-independent from space time data based on the relations among things
(e.g. physical objects) rather than mind-dependent (e.g. on Earth.
Downloaded by [University of Oklahoma Libraries], [Dr May Yuan] at 11:49 16 April 2014
Annals of GIS 9
Acknowledgements Goodchild, M. F., M. Yuan, and T. Cova. 2007.  Towards a
General Theory of Geographic Representation in GIS.
Moreover, we can analyse the direction and magnitude of changes
International Journal of Geographical Information Science
in flow vectors to reveal areas of transition zones where temperature
21 (3): 239 260.
change goes from slow to fast, convergent zones where temperature
Hägerstrand, T. 1970.  What about People in Regional Science?
change converges to a hot spot or cold spot and divergent zones
Papers in Regional Science 24 (1): 7 24.
where warm or cold temperature expands outwards.
Janelle, D. G. 1995.  Metropolitan Expansion, Telecommuting,
and Transportation. In The Geography of Urban
Transportation, edited by S. Hanson, 407 434. New York,
Funding
NY: The Guilford Press.
This material is based upon work supported by the National
Janiak, A., ed. 2012. Kant s Views on Space and Time. The Stanford
Science Foundation [grant number OCI 0941501] and National
Encyclopedia of Philosophy (Winter 2012 Edition), The
Institute of Justice [award number 2010-DE-BX-K005]. Any
Metaphysics Research Lab, Center for the Study of Language
opinions, findings and conclusions or recommendations
and Information. Stanford, CA: Stanford University.
expressed in this article are those of the authors and do not
Janowicz, K. 2012.  Observation-Driven Geo-Ontology
necessarily reflect the views of the National Science
Engineering. Transactions in GIS 16 (3): 351 374.
Foundation or National Institute of Justice.
Kristensson, P. O., N. Dahlback, D. Anundi, M. Bjornstad, H.
Gillberg, J. Haraldsson, I. Martensson, M. Nordvall, and J.
Stahl. 2009.  An Evaluation of Space Time Cube
Note
Representation of Spatiotemporal Patterns. IEEE
Transactions on Visualization and Computer Graphics 15
1. The questions are summarized from Stanford Encyclopedia
(4): 696 702.
of Philosophy (SEP) on Kant s views on space and time
Kwan, M.-P. 2004.  GIS Methods in Time-Geographic Research:
(http://plato.stanford.edu/entries/kant-spacetime/ accessed
Geocomputation and Geovisualization of Human Activity
July 30, 2013). SEP lists five distinct questions. In this
Patterns. Geografiska Annaler Series B: Human
paper, we merged the questions on ontology and the sub-
Geography 86 (4): 267 280.
stance property framework as well as questions on the ori-
Kwan, M.-P. 2007.  Affecting Geospatial Technologies: Toward
gin of space time representation and views of realism and
a Feminist Politics of Emotion. The Professional
idealism for their highly related nature of inquiries.
Geographer 59 (1): 22 34.
Li, X., J. Han, and S. Kim. 2006.  Motion-Alert: Automatic
Anomaly Detection in Massive Moving Objects. In
References
Intelligence and Security Informatics, edited by S.
Mehrotra, D. Zeng, H. Chen, B. Thuraisingham, and F.-Y.
Aggarwal, C. C. 2011.  An Introduction to Social Network Data
Wang, 166 177, Vol. 3975. Berlin: Springer.
Analytics. In Social Network Data Analytics, edited by
Li, Z., M. Ji, J. G. Lee, L. A. Tang, Y. Yu, and J. Han. 2011.
C. C. Aggarwal, 1 15. New York: Springer.
 MoveMine: Mining Moving Object Data for Discovery of
Borgatti, S. P., A. Mehra, D. J. Brass, and G. Labianca. 2009.
Animal Movement Patterns. ACM Transactions on
 Network Analysis in the Social Sciences. Science 323
Intelligent Systems and Technology 2 (4): 1 32.
(5916): 892 895.
Nakaya, T. 2013.  Analytical Data Transformations in Space
Bothwell, J., and M. Yuan. 2010.  Apply Concepts of Fluid
Time Region: Three Stories of Space Time Cube. Annals of
Kinematics to Represent Continuous Space Time Fields in
the Association of American Geographers 103 (5):
Temporal GIS. Annals of GIS 16 (1): 27 41.
1100 1106.
Carpenter, M. A., M. Li, and H. Jiang. 2012.  Social Network
Palma, A. T., V. Bogorny, B. Kuijpers, and L. O. Alvares.
Research in Organizational Contexts: A Systematic Review
2008.  A Clustering-Based Approach for Discovering
of Methodological Issues and Choices. Journal of
Interesting Places in Trajectories. In Proceedings of the
Management 38 (4): 1328 1361.
2008 ACM Symposium on Applied Computing, 863 868.
Cope, M., and S. Elwood. 2009. Qualitative GIS: A Mixed
Ceara: ACM.
Methods Approach. Los Angeles, CA: Sage.
Sheppard, E. 2005.  Knowledge Production through Critical
Couclelis, H. 1999.  Space, Time, Geography. Geographical
GIS: Genealogy and Prospects. Cartographica: The
Information Systems 1: 29 38.
International Journal for Geographic Information and
Couclelis, H. 2010.  Ontologies of Geographic Information.
Geovisualization 40 (4): 5 21.
International Journal of Geographical Information Science
Windhager, F., and E. Mayr. 2012.  Cultural Heritage Cube. A
24 (12): 1785 1809.
Conceptual Framework for Visual Exhibition Exploration. In
Galton, A. 2003.  Desiderata for a Spatio-temporal Geo-ontology.
16th International Conference on Information Visualisation
In Spatial Information Theory. Foundations of
(IV), Montpellier. Los Alamitos, CA: IEEE Computer Society.
Geographic Information Science, edited by W. Kuhn, M.
Yuan, M., and A. Nara. (Forthcoming)  Space-time Analytics
Worboys, and S. Timpf, 1 12, Vol. 2825. Berlin: Springer.
of Tracks for the Understanding of Patterns of Life. In
Gatalsky, P., N. Andrienko, and G. Andrienko. 2004.  Interactive
Space-Time Integration in Geography and GIScience:
Analysis of Event Data Using Space-Time Cube. In
Research Frontiers in the US and China, edited by M.-P.
Proceedings of Eighth International Conference on
Kwan, D. Richardson, D. Wang, and C. Zhou. Dordrecht:
Information Visualisation (IV), London. Los Alamitos, CA:
Springer.
IEEE Computer Society.
Downloaded by [University of Oklahoma Libraries], [Dr May Yuan] at 11:49 16 April 2014
Downloaded by [University of Oklahoma Libraries], [Dr May Yuan] at 11:49 16 April 2014