scholarly journals MAP-Vis: A Distributed Spatio-Temporal Big Data Visualization Framework Based on a Multi-Dimensional Aggregation Pyramid Model

2020 ◽  
Vol 10 (2) ◽  
pp. 598
Author(s):  
Xuefeng Guan ◽  
Chong Xie ◽  
Linxu Han ◽  
Yumei Zeng ◽  
Dannan Shen ◽  
...  
Keyword(s):  
High Performance ◽  
Visual Analysis ◽  
Interactive Visualization ◽  
Temporal Data ◽  
Time Space ◽  
Big Data Visualization ◽  
Spatio Temporal ◽  
And Performance ◽  
Open Datasets ◽  
Map Data

During the exploration and visualization of big spatio-temporal data, massive volume poses a number of challenges to the achievement of interactive visualization, including large memory consumption, high rendering delay, and poor visual effects. Research has shown that the development of distributed computing frameworks provides a feasible solution for big spatio-temporal data management and visualization. Accordingly, to address these challenges, this paper adopts a proprietary pre-processing visualization scheme and designs and implements a highly scalable distributed visual analysis framework, especially targeted at massive point-type datasets. Firstly, we propose a generic multi-dimensional aggregation pyramid (MAP) model based on two well-known graphics concepts, namely the Spatio-temporal Cube and 2D Tile Pyramid. The proposed MAP model can support the simultaneous hierarchical aggregation of time, space, and attributes, and also later transformation of the derived aggregates into discrete key-value pairs for scalable storage and efficient retrieval. Using the generated MAP datasets, we develop an open-source distributed visualization framework (MAP-Vis). In MAP-Vis, a high-performance Spark cluster is used as a parallel preprocessing platform, while distributed HBase is used as the massive storage for the generated MAP data. The client of MAP-Vis provides a variety of correlated visualization views, including heat map, time series, and attribute histogram. Four open datasets, with record numbers ranging from the millions to the tens of billions, are chosen for system demonstration and performance evaluation. The experimental results demonstrate that MAP-Vis can achieve millisecond-level query response and support efficient interactive visualization under different queries on the space, time, and attribute dimensions.

scholarly journals RESEARCH ON CONSTRUCTION METHOD OF SPATIO-TEMPORAL DATA MODEL BASED ON BEHAVIOR-EVENT

2020 ◽  
Vol XLII-3/W10 ◽  
pp. 591-594
Author(s):  
J. W. Li ◽  
Y. Ma ◽  
J. W. Jiang ◽  
W. D. Chen ◽  
N. Yu ◽  
...  
Keyword(s):  
Data Model ◽  
Logical Structure ◽  
Physical Structure ◽  
Temporal Data ◽  
Model Based ◽  
Time Space ◽  
Before And After ◽  
Spatio Temporal ◽  
Temporal Objects ◽  
Organic Combination

Abstract. Starting from the object-oriented idea, this paper analyses the existing event-based models and the logical relationship between behavioral cognition and events, and discusses the continuity of behavioral cognition on the time axis from the perspective of temporal and spatial cognition. A geospatial data model based on behavioral-event is proposed. The physical structure and logical structure of the model are mainly designed, and the four-dimensional model of “time, space, attribute and event” is constructed on the axis. The organic combination of the four models can well describe the internal mechanism and rules of geographical objects. The expression of data model based on behavior-event not only elaborates the basic information of geospatial objects, but also records the changes of related events caused by the changes of geographic Entities' behavior, and expresses the relationship between spatial and temporal objects before and after the changes of behavior cognition. This paper also designs an effective method to organize spatio-temporal data, so as to realize the effective management and analysis of spatio-temporal data and meet the requirements of storage, processing and mining of large spatio-temporal data.

scholarly journals Using treemaps for variable selection in spatio-temporal visualisation

2008 ◽  
Vol 7 (3-4) ◽  
pp. 210-224 ◽  
Author(s):  
Aidan Slingsby ◽  
Jason Dykes ◽  
Jo Wood
Keyword(s):  
Variable Selection ◽  
Visual Analysis ◽  
Temporal Distribution ◽  
Temporal Data ◽  
Data Set ◽  
Raster Maps ◽  
Categorical Attributes ◽  
Interactive Interfaces ◽  
Road Maps ◽  
Spatio Temporal

We demonstrate and reflect upon the use of enhanced treemaps that incorporate spatial and temporal ordering for exploring a large multivariate spatio-temporal data set. The resulting data-dense views summarise and simultaneously present hundreds of space-, time-, and variable-constrained subsets of a large multivariate data set in a structure that facilitates their meaningful comparison and supports visual analysis. Interactive techniques allow localised patterns to be explored and subsets of interest selected and compared with the spatial aggregate. Spatial variation is considered through interactive raster maps and high-resolution local road maps. The techniques are developed in the context of 42.2 million records of vehicular activity in a 98 km2 area of central London and informally evaluated through a design used in the exploratory visualisation of this data set. The main advantages of our technique are the means to simultaneously display hundreds of summaries of the data and to interactively browse hundreds of variable combinations with ordering and symbolism that are consistent and appropriate for space- and time-based variables. These capabilities are difficult to achieve in the case of spatio-temporal data with categorical attributes using existing geovisualisation methods. We acknowledge limitations in the treemap representation but enhance the cognitive plausibility of this popular layout through our two-dimensional ordering algorithm and interactions. Patterns that are expected (e.g. more traffic in central London), interesting (e.g. the spatial and temporal distribution of particular vehicle types) and anomalous (e.g. low speeds on particular road sections) are detected at various scales and locations using the approach. In many cases, anomalies identify biases that may have implications for future use of the data set for analyses and applications. Ordered treemaps appear to have potential as interactive interfaces for variable selection in spatio-temporal visualisation.

scholarly journals Merging diaries and GPS records: The method of data collection for spatio-temporal research

2015 ◽  
Vol 23 (2) ◽  
pp. 12-25
Author(s):  
Martin Šveda ◽  
Michala Madajová
Keyword(s):  
Data Collection ◽  
Traditional Method ◽  
Temporal Data ◽  
Proof Of Concept ◽  
Data Frame ◽  
Gps Technology ◽  
Time Space ◽  
Spatio Temporal ◽  
Transportation Research ◽  
Space Data

Abstract The results of a ‘proof-of-concept’ study that examined a new opportunity for using GPS technology in activity surveys are presented in this article. The aim is to demonstrate the method of collection and processing of individual time-space data via the dual records of a time-space diary and the GPS locator. The GPS technology here is not treated as a substitute for the traditional method of diaries; rather, the paper concentrates on the potential existing in a combination of these two techniques. The time-geographical approach and the corresponding methodology are used in order to assess the complexities of an individual’s everyday life, and to capture the spectrum of human activities in a data frame applicable to different analyses in behavioural, social and transportation research. This method not only improves the quality and robustness of spatio-temporal data, but also reduces under-reporting and the burdens on the respondents.

scholarly journals From the void, the night

IDEA JOURNAL ◽  
2017 ◽  
pp. 48-61
Author(s):  
Jen Archer-Martin ◽  
Lisa Munnelly
Keyword(s):  
Creative Thinking ◽  
Parallel Methods ◽  
Left Behind ◽  
Aotearoa New Zealand ◽  
Time Space ◽  
Binary Oppositions ◽  
Spatio Temporal ◽  
And Performance ◽  
Set Up ◽  
Definition Of

From the void, the night presents an unfolding encounter via a series of letters between two artist/designer/academics as they explore symbioses between their practices and thinking. The correspondence traverses topics that resonate with ideas of darkness, light, time, space, and sensation. Confronting spatial and epistemological boundaries, it begins to carve out a space of practice that embraces dark knowledge, material agency, and the unknown. The conversation begins with the discovery of an already-existing dialogue between bodies of work and thought stretching back to 2003-4, when, in separate efforts to transcend binary oppositions of figure/ground, inside/outside, nothingness/everything, two women made drawings on walls. 1 Unknown to one another at the time, both researchers were employing similar strategies to explore the embodied spatio-temporal performances of drawing and inhabitation – rhythm, repetition, sensation, and the field. These wall-drawings and the texts that accompanied them set up divergent practices that converged again in early 2017 at the Performing, Writing symposium. 2 Here, both undertook performance works 3 that employed drawing-as-writing, and sought to capture the spatial, temporal, material and affective unfoldings of durational practices. While the two works took very different forms, they shared parallel methods, establishing simple parameters for embracing the unknown of live practice. The six letters of the enclosed drawing-writing correspondence look to further this encounter, and explore how the two practices might rub against one another, approaching Tony Godfrey’s definition of a ‘drawing’ as ‘two objects or materials touch[ing] and evidence of their meeting [being] left behind.’ 4 The form of a ‘letter’ was taken loosely, considered as an assemblage that might contain writing, images, and other materials – a mode of ‘letter-writing’ that sits somewhere between writing, drawing and performance. Written over the course of two weeks in which they were the only form of communication between the pair, the letters are the raw product of an intensive creative exchange. While the authors are colleagues at the same College of Creative Arts, the correspondence presents a genuine temporal journey of getting to know one another’s creative thinking process, carving out a dynamic space of speculation about future practice. They reveal this process to be embodied and situated, with references to cultural events and indigenous understandings particular to Aotearoa New Zealand being entangled in the process of thinking-in-place. Intentionally presented here in their unrefined state, the letters are themselves a statement about resisting the pull of the light (of light-as-clarity). They are not writing-as-explanation but writing-as-drawing; a live material process of thinking-through and drawing-out. Gleefully inhabiting the dark space of not-knowing, they remain a dark, cloudy, lively mass of potential energy and material.          

Visual Analysis of Spatio-Temporal Data: Applications in Weather Forecasting

2015 ◽  
Vol 34 (3) ◽  
pp. 381-390 ◽  
Author(s):  
A. Diehl ◽  
L. Pelorosso ◽  
C. Delrieux ◽  
C. Saulo ◽  
J. Ruiz ◽  
...  
Keyword(s):  
Visual Analysis ◽  
Weather Forecasting ◽  
Temporal Data ◽  
Spatio Temporal

scholarly journals Dimensional Inconsistency Measures and Postulates in Spatio-Temporal Databases

2021 ◽  
Vol 71 ◽  
Author(s):  
John Grant ◽  
Maria Vanina Martinez ◽  
Cristian Molinaro ◽  
Francesco Parisi
Keyword(s):  
Real World ◽  
Knowledge Bases ◽  
Propositional Knowledge ◽  
Location Based Services ◽  
Temporal Databases ◽  
Temporal Data ◽  
Time Space ◽  
Spatio Temporal ◽  
Temporal Dimensions ◽  
Natural Measures

The problem of managing spatio-temporal data arises in many applications, such as location-based services, environmental monitoring, geographic information systems, and many others. Often spatio-temporal data arising from such applications turn out to be inconsistent, i.e., representing an impossible situation in the real world. Though several inconsistency measures have been proposed to quantify in a principled way inconsistency in propositional knowledge bases, little effort has been done so far on inconsistency measures tailored for the spatio-temporal setting. In this paper, we define and investigate new measures that are particularly suitable for dealing with inconsistent spatio-temporal information, because they explicitly take into account the spatial and temporal dimensions, as well as the dimension concerning the identifiers of the monitored objects. Specifically, we first define natural measures that look at individual dimensions (time, space, and objects), and then propose measures based on the notion of a repair. We then analyze their behavior w.r.t. common postulates defined for classical propositional knowledge bases, and find that the latter are not suitable for spatio-temporal databases, in that the proposed inconsistency measures do not often satisfy them. In light of this, we argue that also postulates should explicitly take into account the spatial, temporal, and object dimensions and thus define “dimension-aware” counterparts of common postulates, which are indeed often satisfied by the new inconsistency measures. Finally, we study the complexity of the proposed inconsistency measures.

scholarly journals Reckoning Examination for Precip Soothsaying

2019 ◽  
Vol 8 (9S3) ◽  
pp. 999-1002
Keyword(s):  
High Performance ◽  
Water Resource Management ◽  
Predictive Analytics ◽  
Change Scenario ◽  
Temporal Data ◽  
New Techniques ◽  
Rainfall Analysis ◽  
Rainfall Prediction ◽  
Multi Scale ◽  
Spatio Temporal

Rainfall is important for food production plan, water resource management. India is an agricultural country and its economy [1],[ 3],[5]is largely based upon productivity. Thus rainfall prediction becomes a significant factor in agricultural countries like India. On the growing importance of Rainfall studies in the climate change scenario and High Performance Computing, different Users starting from a farmer to a scientist to a policy maker needs the rainfall prediction well in advance for their application like crop planning, water storage etc. Data discovery from temporal, spatial and spatio- temporal data is critical for rainfall analysis. However, recent growth in observations and model outputs, combined with the increased availability of geographical data, presents new opportunities for the users to implement new techniques such as predictive analytics for developing a predictor which can be used for multi-scale forecasting of rainfall that is from 24 hour forecast to long-range forecast say 2-3 month in advance forecast. Hence we developed predictive analytics system for the efficient and real time prediction of rainfall over India. [2 ],[ 4],[6]

Geovisualization and harmonic analysis for the exploratory search of localized cyclic recurrences in spatio-temporal event data

GEOMATICA ◽  
2020 ◽  
pp. 1-23
Author(s):  
Jacques Gautier ◽  
Paule-Annick Davoine ◽  
Claire Cunty
Keyword(s):  
Visual Search ◽  
Harmonic Analysis ◽  
Ad Hoc ◽  
Visual Analysis ◽  
Spatial Clustering ◽  
Exploratory Analysis ◽  
Temporal Data ◽  
Event Data ◽  
Visual Approach ◽  
Spatio Temporal

Many geovisualization environments integrate graphical representations of time. Some of them include representation of both linear and cyclic aspects of time, providing an exploratory analysis of spatio-temporal data through several temporal cyclic scales. However, few of them provide an exploratory analysis of localized cyclic recurrences in spatio-temporal data. Ad hoc temporal diagrams, representing both linear and cyclic aspects of time, provide a visual search for cyclic recurrences in temporal data when the possibility is left to the user to perform a gradual modification of the represented cyclic scale’s duration. The combination of these graphic representations of time, with cartographic representations, displaying the spatial distribution of such cyclic recurrences, could provide an exploratory analysis of localized cyclic recurrences in spatio-temporal data. Mathematical tools coming from other scientific fields, such as the harmonic analysis, offer another way to identify cyclic behaviors in temporal data. Combining the visual approach offered by specifically designed geovisualization environments, with a harmonic analysis that suggests searching paths to the user during its exploratory analysis, can then improve the visual search for localized cyclic recurrences. We propose a geovisualization environment, which combines, on one hand, a visual analysis of localized cyclic recurrences in spatio-temporal data, using ad hoc temporal diagrams, cartographic representations, and specific semiologic rules, and on the other hand, mathematical tools, such as harmonic analysis and spatial clustering, that provide searching paths to the user for its visual analysis. This approach is supported by a geovisualization environment, GrAPHiST, which provides an exploratory analysis of spatio-temporal event data.

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