18,822 research outputs found
Wholeness as a Hierarchical Graph to Capture the Nature of Space
According to Christopher Alexander's theory of centers, a whole comprises
numerous, recursively defined centers for things or spaces surrounding us.
Wholeness is a type of global structure or life-giving order emerging from the
whole as a field of the centers. The wholeness is an essential part of any
complex system and exists, to some degree or other, in spaces. This paper
defines wholeness as a hierarchical graph, in which individual centers are
represented as the nodes and their relationships as the directed links. The
hierarchical graph gets its name from the inherent scaling hierarchy revealed
by the head/tail breaks, which is a classification scheme and visualization
tool for data with a heavy-tailed distribution. We suggest that (1) the degrees
of wholeness for individual centers should be measured by PageRank (PR) scores
based on the notion that high-degree-of-life centers are those to which many
high-degree-of-life centers point, and (2) that the hierarchical levels, or the
ht-index of the PR scores induced by the head/tail breaks can characterize the
degree of wholeness for the whole: the higher the ht-index, the more life or
wholeness in the whole. Three case studies applied to the Alhambra building
complex and the street networks of Manhattan and Sweden illustrate that the
defined wholeness captures fairly well human intuitions on the degree of life
for the geographic spaces. We further suggest that the mathematical model of
wholeness be an important model of geographic representation, because it is
topological oriented that enables us to see the underlying scaling structure.
The model can guide geodesign, which should be considered as the
wholeness-extending transformations that are essentially like the unfolding
processes of seeds or embryos, for creating beautiful built and natural
environments or with a high degree of wholeness.Comment: 14 pages, 7 figures, 2 table
Planetary Science Virtual Observatory architecture
In the framework of the Europlanet-RI program, a prototype of Virtual
Observatory dedicated to Planetary Science was defined. Most of the activity
was dedicated to the elaboration of standards to retrieve and visualize data in
this field, and to provide light procedures to teams who wish to contribute
with on-line data services. The architecture of this VO system and selected
solutions are presented here, together with existing demonstrators
Depicting urban boundaries from a mobility network of spatial interactions: A case study of Great Britain with geo-located Twitter data
Existing urban boundaries are usually defined by government agencies for
administrative, economic, and political purposes. Defining urban boundaries
that consider socio-economic relationships and citizen commute patterns is
important for many aspects of urban and regional planning. In this paper, we
describe a method to delineate urban boundaries based upon human interactions
with physical space inferred from social media. Specifically, we depicted the
urban boundaries of Great Britain using a mobility network of Twitter user
spatial interactions, which was inferred from over 69 million geo-located
tweets. We define the non-administrative anthropographic boundaries in a
hierarchical fashion based on different physical movement ranges of users
derived from the collective mobility patterns of Twitter users in Great
Britain. The results of strongly connected urban regions in the form of
communities in the network space yield geographically cohesive, non-overlapping
urban areas, which provide a clear delineation of the non-administrative
anthropographic urban boundaries of Great Britain. The method was applied to
both national (Great Britain) and municipal scales (the London metropolis).
While our results corresponded well with the administrative boundaries, many
unexpected and interesting boundaries were identified. Importantly, as the
depicted urban boundaries exhibited a strong instance of spatial proximity, we
employed a gravity model to understand the distance decay effects in shaping
the delineated urban boundaries. The model explains how geographical distances
found in the mobility patterns affect the interaction intensity among different
non-administrative anthropographic urban areas, which provides new insights
into human spatial interactions with urban space.Comment: 32 pages, 7 figures, International Journal of Geographic Information
Scienc
Visualising the structure of document search results: A comparison of graph theoretic approaches
This is the post-print of the article - Copyright @ 2010 Sage PublicationsPrevious work has shown that distance-similarity visualisation or âspatialisationâ can provide a potentially useful context in which to browse the results of a query search, enabling the user to adopt a simple local foraging or âcluster growingâ strategy to navigate through the retrieved document set. However, faithfully mapping feature-space models to visual space can be problematic owing to their inherent high dimensionality and non-linearity. Conventional linear approaches to dimension reduction tend to fail at this kind of task, sacrificing local structural in order to preserve a globally optimal mapping. In this paper the clustering performance of a recently proposed algorithm called isometric feature mapping (Isomap), which deals with non-linearity by transforming dissimilarities into geodesic distances, is compared to that of non-metric multidimensional scaling (MDS). Various graph pruning methods, for geodesic distance estimation, are also compared. Results show that Isomap is significantly better at preserving local structural detail than MDS, suggesting it is better suited to cluster growing and other semantic navigation tasks. Moreover, it is shown that applying a minimum-cost graph pruning criterion can provide a parameter-free alternative to the traditional K-neighbour method, resulting in spatial clustering that is equivalent to or better than that achieved using an optimal-K criterion
How can heat maps of indexing vocabularies be utilized for information seeking purposes?
The ability to browse an information space in a structured way by exploiting
similarities and dissimilarities between information objects is crucial for
knowledge discovery. Knowledge maps use visualizations to gain insights into
the structure of large-scale information spaces, but are still far away from
being applicable for searching. The paper proposes a use case for enhancing
search term recommendations by heat map visualizations of co-word
relation-ships taken from indexing vocabulary. By contrasting areas of
different "heat" the user is enabled to indicate mainstream areas of the field
in question more easily.Comment: URL workshop proceedings: http://ceur-ws.org/Vol-1311
Revisiting Guerry's data: Introducing spatial constraints in multivariate analysis
Standard multivariate analysis methods aim to identify and summarize the main
structures in large data sets containing the description of a number of
observations by several variables. In many cases, spatial information is also
available for each observation, so that a map can be associated to the
multivariate data set. Two main objectives are relevant in the analysis of
spatial multivariate data: summarizing covariation structures and identifying
spatial patterns. In practice, achieving both goals simultaneously is a
statistical challenge, and a range of methods have been developed that offer
trade-offs between these two objectives. In an applied context, this
methodological question has been and remains a major issue in community
ecology, where species assemblages (i.e., covariation between species
abundances) are often driven by spatial processes (and thus exhibit spatial
patterns). In this paper we review a variety of methods developed in community
ecology to investigate multivariate spatial patterns. We present different ways
of incorporating spatial constraints in multivariate analysis and illustrate
these different approaches using the famous data set on moral statistics in
France published by Andr\'{e}-Michel Guerry in 1833. We discuss and compare the
properties of these different approaches both from a practical and theoretical
viewpoint.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS356 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
- âŠ