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 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 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 Fuzzy spatio-temporal data modeling based on XML schema

Filomat ◽  
2018 ◽  
Vol 32 (5) ◽  
pp. 1663-1677 ◽  
Author(s):  
Xu Chen ◽  
Li Yan ◽  
Weijun Li ◽  
Fu Zhang
Keyword(s):  
Data Model ◽  
Spatial Information ◽  
Meteorological Data ◽  
Rapid Development ◽  
Xml Schema ◽  
Temporal Data ◽  
Time Data ◽  
Big Data Applications ◽  
Spatio Temporal ◽  
Space Data

With the rapid development of Internet and Big data applications, massive time and space data need to be processed. In order to manage space and time data, the key point is to build a correct data model. There are a lot of fuzzy temporal and spatial information in the real world, and XML has been a useful technology for dealing with various information in the context of Web. In this paper, we first study the fuzzy spatio-temporal data tree by extending the XML Schema and then propose a fuzzy spatio-temporal data model based on XML. Finally, we use the meteorological data to illustrate the validity and usability of the model.

scholarly journals Correlated Spatio-Temporal Data Collection in Wireless Sensor Networks Based on Low Rank Matrix Approximation and Optimized Node Sampling

Sensors ◽  
2014 ◽  
Vol 14 (12) ◽  
pp. 23137-23158 ◽  
Author(s):  
Xinglin Piao ◽  
Yongli Hu ◽  
Yanfeng Sun ◽  
Baocai Yin ◽  
Junbin Gao
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Collection ◽  
Low Rank ◽  
Wireless Sensor ◽  
Temporal Data ◽  
Matrix Approximation ◽  
Rank Matrix ◽  
Spatio Temporal ◽  
Low Rank Matrix

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.

A Service-Oriented Spatio-Temporal Data Model of the Marine Environment

2014 ◽  
Vol 513-517 ◽  
pp. 4543-4546
Author(s):  
Zhao Li ◽  
Yong Xin Feng
Keyword(s):  
Marine Environment ◽  
Data Model ◽  
Data Organization ◽  
Temporal Data ◽  
Geography Markup Language ◽  
Organization And Management ◽  
Time Space ◽  
Efficient Data ◽  
Service Oriented ◽  
Spatio Temporal

On the basis of analyzing of the marine environment spatio-temporal data characteristics and the existing data model, proposes a conceptual model for marine environment data based on the feature and field to achieve integration of description and expression of feature, field, time, space and semantic domains. Designs and implements the service-oriented marine environment data organization and storage using Geography Markup Language (GML). Efficient data organization and management is crucial to marine environment visual services.

A Framework for Visualization and Exploration of Events

2007 ◽  
Vol 7 (2) ◽  
pp. 133-151 ◽  
Author(s):  
Kate Beard ◽  
Heather Deese ◽  
Neal R. Pettigrew
Keyword(s):  
Gulf Of Maine ◽  
Temporal Trends ◽  
Temporal Patterns ◽  
Sensor Data ◽  
Temporal Data ◽  
Spatial And Temporal Patterns ◽  
Interface Elements ◽  
Analysis Tools ◽  
Time Space ◽  
Spatio Temporal

The expanding deployment of sensor systems that capture location, time, and multiple thematic variables is increasing the need for exploratory spatio-temporal data analysis tools. Geographic information systems (GIS) and time series analysis tools support exploration of spatial and temporal patterns respectively and independently, but tools for the exploration of both dimensions within a single system are relatively rare. The contribution of this research is a framework for the visualization and exploration of spatial, temporal, and thematic dimensions of sensor-based data. The unit of analysis is an event, a spatio-temporal data type extracted from sensor data. The conceptual framework suggests an approach for design layout that can be flexibly modified to explore spatial and temporal trends, temporal relationships among events, periodic temporal patterns, the timing of irregularly repeating events, event–event relationships in terms of thematic attributes, and event patterns at different spatial and temporal granularities. Flexible assignment of spatial, temporal, and thematic categories to a set of graphical interface elements that can be easily rearranged provides exploratory power as well as a generalizable design layout structure. The framework is illustrated with events extracted from Gulf of Maine Ocean Observing System data but the approach has broad application to other domains and applications in which time, space, and attributes need to be considered in conjunction.

Spatial-temporal data collection process models using mobile sinks

2019 ◽  
Vol 942 (12) ◽  
pp. 22-28
Author(s):  
A.V. Materuhin ◽  
V.V. Shakhov ◽  
O.D. Sokolova
Keyword(s):  
Energy Consumption ◽  
Operation Time ◽  
Point Of View ◽  
Process Models ◽  
Temporal Data ◽  
Network Nodes ◽  
Mobile Sinks ◽  
Autonomous Operation ◽  
Data Collection Process ◽  
Spatio Temporal

Optimization of energy consumption in geosensor networks is a very important factor in ensuring stability, since geosensors used for environmental monitoring have limited possibilities for recharging batteries. The article is a concise presentation of the research results in the area of increasing the energy consumption efficiency for the process of collecting spatio-temporal data with wireless geosensor networks. It is shown that in the currently used configurations of geosensor networks there is a predominant direction of the transmitted traffic, which leads to the fact that through the routing nodes that are close to the sinks, a much more traffic passes than through other network nodes. Thus, an imbalance of energy consumption arises in the network, which leads to a decrease in the autonomous operation time of the entire wireless geosensor networks. It is proposed to use the possible mobility of sinks as an optimization resource. A mathematical model for the analysis of the lifetime of a wireless geosensor network using mobile sinks is proposed. The model is analyzed from the point of view of optimization energy consumption by sensors. The proposed approach allows increasing the lifetime of wireless geosensor networks by optimizing the relocation of mobile sinks.

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