• Korean Management Science Review
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• v.14 no.1
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• pp.87-105
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• 1997

There have been lots of research on temporal data management for the past two decades. Most of them are based on some logical data model, especially on the relational data model, although there are some conceptual data models which are independent of logical data models. Also, many properties or issues regarding temporal data models and temporal query languages have been studied. But some of them were shown to be incompatible, which means there could not be a complete temporal data model, satisfying all the desired properties at the same time. Many modeling issues discussed in the papers, do not have to be done so, if they take object-oriented data model as a base model. Therefore, this paper proposes a temporal data model, which is based on the object-oriented data model, mainly discussing the most essential issues that are common to many temporal data models. Our new temporal data model and query language will be illustrated with a small database, created by a set of sample transaction.

• Journal of the Korean Operations Research and Management Science Society
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• v.14 no.1
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• pp.87-87
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• 1989

There have been lots of research on temporal data management for the past two decades. Most of them are based on some logical data model, especially on the relational data model, although there are some conceptual data models which are independent of logical data models. Also, many properties or issues regarding temporal data models and temporal query languages have been studied. But some of them were shown to be incompatible, which means there could not be a complete temporal data model, satisfying all the desired properties at the same time. Many modeling issues discussed in the papers, do not have to be done so, if they take object-oriented data model as a base model. Therefore, this paper proposes a temporal data model, which is based on the object-oriented data model, mainly discussing the most essential issues that are common to many temporal data models. Our new temporal data model and query language will be illustrated with a small database, created by a set of sample transaction.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.1
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• pp.21-31
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• 2012

Recently, according to the development of ubiquitous computing technology, the efficient management of locations of moving objects is increasing rapidly in various fields. However, MODBMS and DSMS can not support the efficient real-time management of spatio-temporal stream data of moving objects. Therefore, this paper designed and implemented a spatio-temporal DSMS which can support the efficient real-time management of spatio-temporal stream data of moving objects. Especially, to develop the spatio-temporal DSMS, we extended STREAM of Stanford University and used GEOS that supports spatial data types and spatial operators of OGC. Finally, this paper proved the efficiency of the spatio-temporal DSMS by applying it to the real-time monitoring field which requires the real-time management of spatio-temporal stream data of moving objects.

• Journal of Information Technology Applications and Management
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• v.12 no.1
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• pp.35-48
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• 2005

An architectural framework is developed for integrating geospatial and temporal data with relational information from which a spatio-temporal data warehouse (STDW) system is built. In order to implement the STDW, a generic conceptual model was designed that accommodated six dimensions: spatial (map object), temporal (time), agent (contractor), management (e.g. planting) and tree species (specific species) that addressed the 'where', 'when', 'who', 'what', 'why' and 'how' (5W1H) of the STDW information, respectively. A formal algebraic notation was developed based on a triplet schema that corresponded with spatial, temporal, and relational data type objects. Spatial object structures and spatial operators (spatial selection, spatial projection, and spatial join) were defined and incorporated along with other database operators having interfaces via the generic model.

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.2
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• pp.139-158
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• 1995

A temporal database systems provides timing information and maintains history of data compared to the conventional database system. In this paper, we present a temporal relational database which use an interval-stamping method for instant-based events and for interval-based states. A set of temporal algebraic operators are developed on an instance of time and interval of time so that we can manipulate events and states at a same time. The set of operation is the basis for creating a relational algebra that is closed for temporal relations. And temporal SQL is also suggested as a temporal query relational language for our algebraic operations on temporal relations.

• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.43-54
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• 2009

As R&D(Research and Development) is going on actively to develop technologies for the ubiquitous computing environment, which Is the human-oriented future computing environment, GIS dealing with spatio-temporal data is emerging as a promising technology. This also increases the necessity of the middleware for providing services to give interoperability in various heterogeneous environments. The core technologies of the middleware are real-time processing technology of data streams coming unceasingly from positioning systems and data stream processing technology developed for non-spatio-temporal data. However, it has problems in processing queries on spatio-temporal data efficiently. Accordingly, this paper designed and implemented the spatio-temporal middleware that provides interoperability between a mobile spatio-temporal DBMS(DataBase Management System) and a server spatio-temporal MMDBMS(Main Memory DataBase Management System). The spatio-temporal middleware maintains interoperability among heterogeneous devices and guarantees data integrity in query processing through real-time processing of unceasing spatio-temporal data streams and two way synchronization of spatio-temporal DBMSs. In addition, it manages session for the connection of each spatio-temporal DBMS and manages resources for its stable operation. Finally, this paper proved the usability of the spatio-temporal middleware by applying it to a real-time position tracking system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.196-199
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• 2005

We propose a strategy to manage temporal data which are occurred on scientific applications. Firstly, We define LB and RB to separate temporal data, and entity versions to be stored in past, current, future segments. Also, We describe an algorithm to migrate temporal data with hotspot distribution among segments. The performance evaluation of average response time and space utilization is conducted. Average response time between two methods is similar, and spare is saved in proposed method.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.329-332
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• 2000

Research interests on temporal data have been almost focused on data models. There has been relatively less research in the area of temporal data management. In this paper, we propose two data migration strategies based on time-segmented storage structure: the migration strategy by Time Granularity, the migration strategy by LST-GET. We describe the criterion for data migration and moving process. We simulated the performance of the migration strategy by Time Granularity in order to compare it with non-segmentation method. We compared and analyzed two data migration strategies for temporal data.

• ETRI Journal
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• v.24 no.3
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• pp.226-238
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• 2002

A spatial object changes its states over time. However, existing spatial and temporal database systems cannot fully manage time-varying data with both spatial and non-spatial attributes. To overcome this limitation, we present a framework for spatio-temporal databases that can manage all time-varying historical information and integrate spatial and temporal relationship operators into the select statement in SQL3. For the purpose of our framework, we define three referencing macros and a history aggregate operator and classify the existing spatial and temporal relationship operators into three groups: exclusively spatial relationship operators, exclusively temporal relationship operators, and spatio-temporal common relationship operators. Finally, we believe the integration of spatial and temporal relationship operators into SQL3 will provide a useful framework for the history management of time-varying spatial objects in a uniform manner.

• The Transactions of the Korea Information Processing Society
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• v.5 no.6
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• pp.1418-1430
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• 1998

Temporal databases support an efficient historical management by means of valid time and transaction time. Valid time stands for the time when a data happens in the real world. And transaction time stands for the time when a data is stored in the database, Temporal Query Processing System(TQPS) should be extended so as tc process the temporal operations for the historical informations in the user query as well as the conventional relational operations. In this paper, the extended temporal query processing systems which is based on the previous temporal query processing system for TQuel(Temporal Query Language) consists of the temporal syntax analyzer, temporal semantic analyzer, temporal code generator, and temporal interpreter is to be described, The algorithm for additional functions such as transaction time management, temporal aggregates, temporal views, temporal joins and the heuristic optimization functions and their example how to be processed is shown.