Efficient index structures for spatio-temporal objects

2002 ◽  
Author(s):  
C. Kleiner ◽  
U.W. Lipeck
Keyword(s):  
Index Structures ◽  
Spatio Temporal ◽  
Temporal Objects

scholarly journals APPLICATION OF 3D SPATIO-TEMPORAL DATA MODELING, MANAGEMENT, AND ANALYSIS IN DB4GEO

2016 ◽  
Vol IV-2/W1 ◽  
pp. 163-170
Author(s):  
P. V. Kuper ◽  
M. Breunig ◽  
M. Al-Doori ◽  
A. Thomsen
Keyword(s):  
Water Supply ◽  
United Arab Emirates ◽  
Transport Systems ◽  
Reservoir Modeling ◽  
Future Research ◽  
Temporal Data ◽  
Temporal Dimension ◽  
Geospatial Database ◽  
Spatio Temporal ◽  
Temporal Objects

Many of today´s world wide challenges such as climate change, water supply and transport systems in cities or movements of crowds need spatio-temporal data to be examined in detail. Thus the number of examinations in 3D space dealing with geospatial objects moving in space and time or even changing their shapes in time will rapidly increase in the future. Prominent spatio-temporal applications are subsurface reservoir modeling, water supply after seawater desalination and the development of transport systems in mega cities. All of these applications generate large spatio-temporal data sets. However, the modeling, management and analysis of 3D geo-objects with changing shape and attributes in time still is a challenge for geospatial database architectures. In this article we describe the application of concepts for the modeling, management and analysis of 2.5D and 3D spatial plus 1D temporal objects implemented in DB4GeO, our service-oriented geospatial database architecture. An example application with spatio-temporal data of a landfill, near the city of Osnabrück in Germany demonstrates the usage of the concepts. Finally, an outlook on our future research focusing on new applications with big data analysis in three spatial plus one temporal dimension in the United Arab Emirates, especially the Dubai area, is given.

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 Retention and Meaning

1970 ◽  
Vol 43 (1) ◽  
pp. 41-51
Author(s):  
Vojislav Božičković
Keyword(s):  
Linguistic Meaning ◽  
Alternative View ◽  
Spatio Temporal ◽  
Temporal Objects ◽  
Belief States

Some philosophers have tried to account for belief retention and our belief states concerning days that we track and think of in terms of the linguistic meaning of the indexicals we use to refer to them such as ‘today’ and ‘yesterday’. In this paper I discuss a couple of representative attempts to show that this is the case and argue that they are implausible. I end up proposing an alternative view that explains the relevant data better. In so doing, both for illustrative and argumentative purposes, I show that in this respect the case concerning days is not different from the case featuring spatio-temporal objects.

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.

Spatio-temporal Objects

2008 ◽  
pp. 1122-1122
Author(s):  
Shashi Shekhar ◽  
Hui Xiong
Keyword(s):  
Spatio Temporal ◽  
Temporal Objects
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