A spatio-temporal data model for administrative division place names: a case study of Xiamen

2009 ◽  
Author(s):  
Liping Yang ◽  
Guangfa Lin ◽  
Ailing Chen ◽  
Youfei Chen ◽  
Xiaohuan Wen
Keyword(s):  
Data Model ◽  
Temporal Data ◽  
Place Names ◽  
Administrative Division ◽  
Spatio Temporal

Study of the Spatio-Temporal Data Model in Sea Battlefield

2012 ◽  
Vol 246-247 ◽  
pp. 744-748
Author(s):  
Yue Lin Sun ◽  
Lei Bao ◽  
Yi Hang Peng
Keyword(s):  
Data Model ◽  
Object Oriented ◽  
Space Time ◽  
Comprehensive Analysis ◽  
Temporal Data ◽  
Data Types ◽  
Spatio Temporal ◽  
The Right ◽  
Effective Analysis

An effective analysis of the battlefield situation and spatio-temporal data model in a sea battlefield has great significance for the commander to perceive the battlefield situation and to make the right decisions. Based on the existing spatio-temporal data model, the present paper gives a comprehensive analysis of the characteristics of sea battlefield data, and chooses the object-oriented spatio-temporal data model to modify it; at the same time this paper introduces sea battlefield space-time algebra system to define various data types formally, which lays the foundation for the establishment of the sea battlefield spatio-temporal data model.

scholarly journals Creating and evaluating web-based visualizations of multi-dimensional spatiotemporal data

2019 ◽  
Vol 2 ◽  
pp. 1-8
Author(s):  
Jan Wilkening ◽  
Keni Han ◽  
Mathias Jahnke
Keyword(s):  
Spatiotemporal Data ◽  
Weather Data ◽  
Temporal Data ◽  
Web Based ◽  
Animated Maps ◽  
Different Types ◽  
Weather Parameters ◽  
Spatio Temporal ◽  
The Web

<p><strong>Abstract.</strong> In this article, we present a method for visualizing multi-dimensional spatio-temporal data in an interactive web-based geovisualization. Our case study focuses on publicly available weather data in Germany. After processing the data with Python and desktop GIS, we integrated the data as web services in a browser-based application. This application displays several weather parameters with different types of visualisations, such as static maps, animated maps and charts. The usability of the web-based geovisualization was evaluated with a free-examination and a goal-directed task, using eye-tracking analysis. The evaluation focused on the question how people use static maps, animated maps and charts, dependent on different tasks. The results suggest that visualization elements such as animated maps, static maps and charts are particularly useful for certain types of tasks, and that more answering time correlates with less accurate answers.</p>

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.

A Semantic-based Spatio-temporal Data Model for Internet of Things

2013 ◽  
Vol 8 (6) ◽  
pp. 1159-1168
Author(s):  
Lingyun Yuan ◽  
Xingchao Wang ◽  
Jianhou Gan
Keyword(s):  
Internet Of Things ◽  
Data Model ◽  
Temporal Data ◽  
Spatio Temporal

3SST Model

2010 ◽  
pp. 1-14
Author(s):  
Andreea Sabau
Keyword(s):  
Data Model ◽  
Conceptual Modeling ◽  
Domain Model ◽  
Relational Model ◽  
Temporal Data ◽  
Spatio Temporal ◽  
Entity Relationship ◽  
Temporal Objects ◽  
Database Platform ◽  
Event Based

In order to represent spatio-temporal data, many conceptual models have been designed and a part of them have been implemented. This chapter describes an approach of the conceptual modeling of spatio-temporal data, called 3SST. Also, the spatio-temporal conceptual and relational data models obtained by following the proposed phases are presented. The 3SST data model is obtained by following three steps: the construction of an entity-relationship spatio-temporal model, the specification of the domain model and the design of a class diagram which includes the objects characteristic to a spatiotemporal application and other needed elements. The relational model of the 3SST conceptual model is the implementation of the conceptual 3SST data model on a relational database platform. Both models are characterized by generality in representing spatial, temporal and spatio-temporal data. The spatial objects can be represented as points or objects with shape and the evolution of the spatio-temporal objects can be implemented as discrete or continuous in time, on time instants or time intervals. More than that, different types of spatial, temporal, spatio-temporal and event-based queries can be performed on represented data. Therefore, the proposed 3SST relational model can be considered the core of a spatio-temporal data model.

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