Showing papers on "Spatiotemporal database published in 2005"

The Lowell database research self-assessment

Abstract: Database needs are changing, driven by the Internet and increasing amounts of scientific and sensor data. In this article, the authors propose research into several important new directions for database management systems.

Spatiotemporal aggregate computation: a survey

Abstract: Spatiotemporal databases are becoming increasingly more common. Typically, applications modeling spatiotemporal objects need to process vast amounts of data. In such cases, generating aggregate information from the data set is more useful than individually analyzing every entry. In this paper, we study the most relevant techniques for the evaluation of aggregate queries on spatial, temporal, and spatiotemporal data. We also present a model that reduces the evaluation of aggregate queries to the problem of selecting qualifying tuples and the grouping of these tuples into collections on which an aggregate function is to be applied. This model gives us a framework that allows us to analyze and compare the different existing techniques for the evaluation of aggregate queries. At the same time, it allows us to identify opportunities for research on types of aggregate queries that have not been studied.

Spatial Databases: Technologies, Techniques and Trends

Abstract: Section I: Modeling and Systems, Chapter I. Survey on Spatial Data Modeling Approaches, Chapter II. Integrating Web Data and Geographic Knowledge into Spatial Databases, Section II: Indexing Techniques, Chapter III. Object-Relational Spatial Indexing, Chapter IV. Quadtree-Based Image Representation and Retrieval, Chapter V. Indexing Multi-Dimensional Trajectories for Similarity Queries, Section III: Query Processing and Optimization, Chapter VII. Spatial Joins: Algorithms, Cost Models and Optimization Techniques, Section IV: Moving Objects, Chapter VIII. Applications of Moving Objects Databases, Chapter IX. Simple and Incremental Nearest-Neighbor Search in Spatiotemporal Databases, Chapter X. Management of Large Moving Objects Datasets: Indexing, Benchmarking and Uncertainty in Movement Representation, Section V: Data Mining, Chapter XI. Spatiotemporal Prediction using Data Mining Tools, Chapter XII. Mining in Spatiotemporal Databases, Chapter XIII. Similarity Learning in GIS: An Overview of Definitions, Prerequisites and Challenges

Building a Multi-Scale Database with Scale-Transition Relationships

Abstract: Building multiple representations is one of the key problems in GIS. To tackle this problem, we have chosen to connect geographic data from mono-scale representations to build a multi-scale database with scale-transition relationships. These scale-transition relationships connect two sets of elements (classes, types or objects) representing the same phenomenon of the real world and carry the sequence of multi-scale operations to navigate from one representation to another. From this concept, a process has been defined to build multi-scale databases, in three steps. The first step is dedicated to the declaration of correspondences and conflicts between input schemata by the means of scale-transition relationships. In the second step, conflicts are resolved and schemata are merged. Finally, the third step corresponds to data matching, with the help of geometric, topologic and semantic information. Scale-transition relationships between objects are created during this last step. To validate the process, a multi-scale database has been produced from two existing mono-scale sets of road network data. The first results of this kernel are satisfactory.

Resource Selection for Autonomic Database Tuning

Abstract: Database administrators should be aware of resource usages to maintain database system performance. As database applications become more complex and diverse, managing database systems becomes too costly and prone to error. Autonomic database tuning becomes more important than ever. This paper starts with an analysis on how resource usages respond by changing resource sizes in database systems. Then, we present a simple method that automatically selects resources that affect the system performance. An experiment using the TPC-C and TPC-W workloads has been carried out with a commercial database system. A preliminary analysis shows that our method works.

System and method for rapid database application deployment and use

Abstract: A system and a method for rapid database application deployment and use. A system includes a host server that includes a database and a database application framework. The database stores a virtual relational database structure and a virtual relational database implementation. The database may store the virtual relational database structure and virtual relational database implementation in an existing relational database structure. The virtual relational database structure includes one or more object types and one or more object properties. Object types are definitions of types of objects for which data may be stored in the database and object properties are definitions of types of data that may be stored for objects and are associated with the one or more object types. The virtual relational database implementation includes one or more actual objects that are based on the one or more object types and one or more populated properties that are based on the object properties and which include data for the one or more actual objects. The database application framework enables a user to define virtual relational database structures and create virtual relational database implementations. The database application framework communicates with the database and includes user interface software that creates and processes user interface displays that enable a user to view, edit and search the database and which adapt to changes to the virtual relational database structure to immediately reflect such changes on the user interface displays.

System and method to optimize database access by synchronizing state based on data access patterns

Abstract: A method, apparatus, and computer program product in a data processing system for avoiding excessive database round trips. A list of a database object fields affected by queries is compiled by analyzing instructions in a database query language. A list of database object fields affected by queries is also compiled by analyzing database object relationships. Using the combined list of affected database object fields, when a find operation is invoked, a determination is made as to whether the affected database object fields have been modified. Next, if the affected database object fields have been modified, database updates are generated for the affected database objects containing the affected database object fields. After that, the database updates are executed after all affected database object fields have been processed. Finally, the queries are submitted.

The Po-tree: a Real-time Spatiotemporal Data Indexing Structure

Abstract: This document describes the Po-tree, a new indexing structure for spatiotemporal databases with real-time constraints. Natural risks management and other system can use arrays of spatially referenced sensors, each of them sending their measurements to a central database. Our solution tries to facilitate the indexing of these data, while favoring the newer ones. It does so by combining two sub-structures for the spatial and temporal components. While Mobility is not yet supported, evolutions of the structures shall be able to deal with it.

Efficiently processing queries on interval-and-value tuples in relational databases

Abstract: With the increasing occurrence of temporal and spatial data in present-day database applications, the interval data type is adopted by more and more database systems. For an efficient support of queries that contain selections on interval attributes as well as simple-valued attributes (e.g. numbers, strings) at the same time, special index structures are required supporting both types of predicates in combination. Based on the Relational Interval Tree, we present various indexing schemes that support such combined queries and can be integrated in relational database systems with minimum effort. Experiments on different query types show superior performance for the new techniques in comparison to competing access methods.

Integrating Web Data and Geographic Knowledge into Spatial Databases.

Abstract: With the phenomenal growth of the World Wide Web, rich data sources on many different subjects have become available online. Some of these sources store daily facts that often involve textual geographic descriptions. These descriptions can be perceived as indirectly georeferenced data – for example, addresses, telephone numbers, zip codes and place names. In this chapter we focus on using the Web as an important source of urban geographic information and propose to enhance urban Geographic Information Systems (GIS) using indirectly georeferenced data extracted Alberto H.F. Laender, Federal University of Minas Gerais, Brazil Karla A.V. Borges, Federal University of Minas Gerais, Brazil & PRODABEL, Brazil Joyce C.P. Carvalho, Federal University of Minas Gerais, Brazil Claudia B. Medeiros, University of Campinas, Brazil Altigran S. da Silva, Federal University of Amazonas, Brazil Clodoveu A. Davis Jr., PRODABEL, Brazil & Catholic University of Minas Gerais, Brazil This chapter appears in the book Spatial Databases: Technologies, Techniques and Trends by Yannis Manalopoulos, Apostolos Papadopoulos and Michael Gr. Vassilakopoulos. C pyright © 2005, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. 701 E. Chocolate Avenue, Suite 200, Hershey PA 17033-1240, USA Tel: 717/533-8845; Fax 717/533-8661; URL-http://www.idea-group.com IDEA GROUP PUBLISHING 24 Laender, Borges, Carvalho, Medeiros, da Silva & Davis Copyright © 2005, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. from the Web. We describe an environment that allows the extraction of geospatial data from Web pages, converts them to XML format and uploads the converted data into spatial databases for later use in urban GIS. The effectiveness of our approach is demonstrated by a real urban GIS application that uses street addresses as the basis for integrating data from different Web sources, combining the data with high-resolution imagery.

Searching for related objects in relational databases

Abstract: To discover knowledge or retrieve information from a relational database, a user often needs to find objects related to certain source objects. There are two main challenges in building an effective object search system: the huge amount of objects in the database and the large number of different relationships between objects. In this paper we introduce Ross, an efficient and accurate relational object search system. Ross accepts complex queries that enable users to specify the relationships among objects. To measure the relationships of join paths, Ross considers the different semantics of different joins, and combines both selectivity and lengths of join paths to measure their strengths. A novel approach is used to find the best join paths between relations, which converts the database schema into a graph, so that the shortest paths in the graph correspond to best join paths in the database. Ross uses a stream-based system architecture to handle complex queries containing logical operators, which can find the most related objects upon users’ requests. Comprehensive experiments are conducted to show the high scalability and effectiveness of Ross.

A formal framework for database sampling

Abstract: Database sampling is commonly used in applications like data mining and approximate query evaluation in order to achieve a compromise between the accuracy of the results and the computational cost of the process. The authors have recently proposed the use of database sampling in the context of populating a prototype database, that is, a database used to support the development of data-intensive applications. Existing methods for constructing prototype databases commonly populate the resulting database with synthetic data values. A more realistic approach is to sample a database so that the resulting sample satisfies a predefined set of integrity constraints. The resulting database, with domain-relevant data values and semantics, is expected to better support the software development process. This paper presents a formal study of database sampling. A Denotational Semantics description of database sampling is first discussed. Then the paper characterises the types of integrity constraints that must be considered during sampling. Lastly, the sampling strategy presented here is applied to improve the data quality of a (legacy) database. In this context, database sampling is used to incrementally identify the set of tuples which are the cause of inconsistencies in the database, and therefore should be the ones to be addressed by the data cleaning process.

Database system and method for managing a database

Abstract: A database management system and method manages a database storing a plurality of entities related to each other by a plurality of relations. A user interface interfaces with the database in a situation. A context modeler models a context representation according to the situation using a semantic net. The semantic net includes a subset of entities that are identified by the context modeler as being relevant to the situation. When the context representation is applied to the database, the database is adapted to operate according to the situation.

A database evolution taxonomy for object-oriented databases

Abstract: Like any other database application, object database applications are subject to evolution. Evolution, however, is a critical requirement in object-oriented databases as it is a fundamental characteristic of complex applications such as computer-aided design and manufacturing (CAD/CAM) and office information systems. Object-oriented databases are inherently suited to supporting such applications. In this paper we present a database evolution taxonomy for object-oriented databases. We describe a conceptual database model and use it to define the taxonomy. We also present the various invariants and rules governing the various evolution operations. The execution sequence of rules is described. An implementation of the database model and the evolution taxonomy in the Semi-Autonomous Database Evolution System (SADES), is discussed. The implementation employs aspect-oriented programming techniques to provide a flexible means of transforming objects upon evolution, and implementing some application-specific evolution primitives. A case study compares the evolution taxonomy with existing evolution approaches. The comparison demonstrates that the taxonomy and its corresponding implementation in SADES provide improved coverage of the fundamental evolution operations to which an object database might be subjected. At the same time, erosion of the database structure is avoided by maintaining a coherent and comprehensible view of historical changes.

Some remarks on self-tuning logical database design

Abstract: Whereas self-tuning physical database design has received a lot of attention recently, self-tuning logical database design seems to be under-studied. Roughly speaking, database administrators (DBA) have to maintain on a daily basis "efficient databases", i.e. databases for which SQL queries have to perform effi- ciently for end-users, while keeping "coherent" databases, i.e. databases without update problems. Moreover, the huge number of null values occurring in practice may incur a significant overhead on his daily work, either to optimize the memory layout or to maintain (or design new) SQL queries. In order to reach a trade-off between the desire to maintain efficient databases and coherent databases, we propose a framework in which a database should be able to self-tuning its logical database schema with respect to SQL workloads and the data themselves. We discuss the main points of this framework, its feasibility and its relationships with some data mining problems.

A review on spatiotemporal data model for managing data movement in geographical information systems (GIS)

Abstract: This paper reviews the development of spatiotemporal data models. Geographic data encompasses all information related to phenomena in the real world including temporal information. In this paper, we focus on the spatiotemporal data where spatial data changes over time and involves geographic movement. From our review, we found twelve classifications of geographic movement. To manage geographic movement information we require a good data model. A good data model provides for good data management. The spatiotemporal data model is a suitable to use in GIS for making easy data management of geographic data to support spatiotemporal analysis. Our review revealed nine spatiotemporal data models which can be used to manage geographic movement data or change activities in the world. Some of the models are extended from the spatial data model by including time and some are new models based on the event. Spatiotemporal data models can be use to replace current spatial data models in the GIS. We have done a comparative study with the nine models and the results of this comparison are presented in this paper.

Boundary-Based time partitioning with flattened r-tree for indexing ubiquitous objects

Abstract: The advances of wireless communication technologies, personal locator technology, and global positioning systems enable a wide range of location-aware services. To enable the services, a number of spatiotemporal access methods have been proposed for handling timestamp and time interval queries. However, the performance of the existing methods of a single index structure quickly degrades as time progresses. To overcome the problem, we propose to employ time-based partitioning on the R-tree called time boundary-based partitioning with flattened R-tree (BPR-Tree). The proposed scheme employs a new insertion policy to reduce the height of the tree and a time grouping method in order to minimize the search time of various queries. Extensive computer simulation reveals that the proposed scheme significantly outperforms the existing schemes.

Reasoning the spatiotemporal relations between time evolving indeterminate regions

Abstract: Temporal and spatial reasoning are two important parts of Artificial Intelligence and they have important applications in the fields of GIS (geographic information system), Spatiotemporal Database, CAD/CAM etc. The development of temporal reasoning and spatial reasoning includes three aspects: Ontology, representation models and reasoning methods. This paper checks the correspondence between spatiotemporal relations and the 3D topological relations and presents a relation analysis model for indeterminate evolving 2D regions. It extends the 2D Egg/Yolk model into the third dimension that can describe the approximate topological relations for indeterminate evolving regions. The result is a collection of relation clusters that have different spatiotemporal natures.

Simple and Incremental Nearest-Neighbor Search for Spatiotemporal Databases.

Abstract: The efficient processing of nearest-neighbor queries in databases of moving objects is considered very important for applications such as fleet management, traffic control, digital battlefields and more. Such applications have been rapidly spread due to the fact that mobile computing and wireless technologies nowadays are ubiquitous. This chapter presents important aspects towards simple and incremental nearest-neighbor search for spatiotemporal databases. More specifically, we describe the algorithms that This chapter appears in the book Spatial Databases: Technol gi s, Techniques and Trends by Yannis Manalopoulos, Apost los Papado oulos and Michael Gr. Vassilakopoulos. Copyright © 2005, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. 701 E. Chocolate Avenue, Suite 200, Hershey PA 17033-1240, USA Tel: 717/533-8845; Fax 717/533-8661; URL-http://www.idea-group.com IDEA GROUP PUBLISHING Simple and Incremental Nearest-Neighbor Search in Spatio-Temporal Databases 205 Copyright © 2005, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. have already been proposed for simple and incremental nearest neighbor queries and present a new algorithm regarding that issue. Finally, we study the problem of keeping a query consistent in the presence of insertions, deletions and updates of moving objects.

From Conceptual Database Schemas to Logical Database Tuning

Abstract: This chapter revisits conceptual database design and focuses on the so-called “logical database tuning”. We first recall fundamental differences between constructor-oriented models (like extended Entity-Relationship models) and attribute-oriented models (like the relational model). Then, we introduce an integrated algorithm for translating ER-like conceptual database schemas to relational database schemas. To consider the tuning of such logical databases, we highlight two extreme cases: null-free databases and efficient — though non redundant — databases. Finally, we point out how SQL workloads could be used a posteriori as a help for the designers and/or the database administrators to reach a compromise between these extreme cases. While a lot of papers and books have been devoted for many years to database design, we hope that this chapter will clarify the understanding of database designers when implementing their databases and database administrators when maintaining their databases.

A spatio-temporal database prototype for managing moving objects in GIS

Abstract: The location technologies, such as GPS and telegraphy, are producing more and more data of moving objects. Spatio-temporal database is needed to manage these data, so as to solve the problems in spatio-temporal applications. However, there are few prototypes of spatio-temporal database systems yet. This is because attention is always paid on some specified aspects not the whole system. In this paper, we present the design and implementation of a spatio-temporal database prototype for managing moving objects. A Trajectory Model is proposed in this paper, where the moving objects' movements in 2D plane over time are treated as trajectories in the 3D spatio-temporal space. Referring to R tree and the trajectory oriented indexing method TB tree, a new indexing method: S-TB tree is proposed in the prototype. Distance based queries and trajectory topology based queries are all supported by the prototype. The distance based queries includes point queries, range queries. This paper also presents different strategies to process these queries. Finally, two application cases are presented: traffic control and historical queries of the storms on Earth.

A query system for spatiotemporal database applications

Abstract: In recent years, an increasing number of database applications deal with continuously changing data objects (CCDOs). In these applications, the underlying data management system must support new types of spatiotemporal queries that refer to CCDOs. The expressive power of the supported query language and the query processing algorithms determine the quality and the efficiency of the query system. In contrast to traditional data objects, CCDOs change continuously. Therefore, the relation between two CCDOs may change over time. We define a motion relation as a sequence of one or more distinct topological relations. This paper surveys existing spatiotemporal query types and proposes a powerful spatiotemporal database query language by defining a complete set of motion predicates that can fill the gap between space and time. In addition, the paper discusses how to efficiently process the proposed queries by utilizing existing indexing schemes.

A data schema and its query for modeling dynamic geographical world

Abstract: Researchers are paying more attention to the evolving nature phenomena with the development of spatiotemporal database modeling methods. However most of the researches have been focused on the treatment of discrete changes in spatial objects. Based on the study of versions, events and processes, which is introduced in another paper [S. Wang et al., 2005], we proposed a relational data schema to describe spatiotemporal phenomena. The data schema is adapted for the storage of continuous evolving information instead of discreet patterns. Its framework allows the representation of entities and processes within a GIS database and enable the expression of spatial queries related to changes in both space and time. The query called STFQL was discussed in detail to allow users to ask for changes in spatiotemporal relationships.

Benchmarking and Data Generation in Moving Objects Databases

Abstract: Moving objects databases (MODs) provide the framework for the efficient storage and retrieval of the changing position of continuously moving objects. This includes the current and past locations of moving objects and the support of spatial queries that refer to historical location information and future projections as well. Nowadays, new spatiotemporal applications that require tracking and recording the trajectories of moving objects online are emerging. Digital battlefields, traffic supervision, mobile communication, navigation systems, and geographic information systems (GIS) are among these applications. Towards this goal, during recent years many efforts have focused on MOD formalism, data models, query languages, visualization, and access methods (Guting et al., 2000; Saltenis & Jensen, 2002; Sistla, Wolfson, Chamberlain, & Dao, 1997). However, little work has appeared on benchmarking.

Research of Spatiotemporal Indexing Mechanism based on Snapshot-increment

Abstract: Indexing technology is the key part in database system. Existing spatiotemporal indexing methods have extended temporal or spatial index, where space or time as an attribute of the index. In this paper, a new indexing mechanism, based on snapshot-increment spatiotemporal index, is presented, where time and space are both same important dimensions. Thus, the efficiency of query is improved and the query time decreased.