L. M. Haas and W. F. Cody. Exploiting extensible dbms in integrated geographic information systems. In Proc. of Advances in Spatial Databases, LNCS 525, 1991.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....use of external memory techniques. GIS systems are used for scientific applications such as environmental impact, wildlife repopulation, epidemiologic analysis, and earthquake studies and for commercial applications such as market analysis, utility facilities distribution, and mineral exploration [17]. In support of these applications, GIS systems store, manipulate, and search through enormous amounts of spatial data [13, 18, 25, 27] NASA s EOS project GIS system [13] for example, is expected to manipulate petabytes (thousands of terabytes, or millions of gigabytes) of data Typical ....

L. M. Haas and W. F. Cody. Exploiting extensible dbms in integrated geographic information systems. In Proc. of Advances in Spatial Databases, LNCS 525, 1991.

....of external memory techniques. GIS systems are used for scientific applications such as environmental impact, wildlife repopulation, epidemiologic analysis, and earthquake studies and for commercial applications such as market analysis, utility facilities distribution, and mineral ex ploration [17]. In support of these applications, GIS systems store, manipulate, and search through enormous amounts of spatial data [13, 18, 25, 27] NASA s EOS project GIS system [13] for example, is expected to manipulate petabytes (thousands of terabytes, or millions of gigabytes) of data Typical ....

L. M. Haas and W. F. Cody. Exploiting extensible dbms in integrated geographic information systems. In Proc. of Advances in Spatial Databases, LNCS 525, 1991.

.... have focussed on the requirements for advanced data representation and access methods [9, 14, 15, 20] One set of work has, by and large, concentrated on extensible database technologies that can be used to encapsulate complex access methods over highly unstructured scientific data objects [9, 10, 20, 26]. A second set of work has focussed on appropriate visual interfaces and query language support for browsing highly unstructured information or formulating queries with incomplete information [1, 7, 12, 18, 19] A third set of work, and the primary focus of this research, concentrates on the ....

L. Haas and W. Cody, "Exploiting Extensible DBMS in Integrated Geographic Information Systems, In Proc. of 2nd Symposium Spatial Database Systems, pp. 423-449, Springer-Verlag LNCS 525, 1991.

....data types, like maps and satellite images. More recently, facilities for database management, such as support to multiple users, processing of large volumes of data and management of distributed information have been realized as important requirements for a GIS to be efficient and effective [8,10]. Unfortunately, the current Database Management Systems (DBMS) do not adequately support complex GIS applications that include data with spatial (3D) pictorial and temporal features. Control and data structures, languages for data definition and handling are not able to manage geographical ....

....(DBMS) do not adequately support complex GIS applications that include data with spatial (3D) pictorial and temporal features. Control and data structures, languages for data definition and handling are not able to manage geographical information, in relation to geometric and topologic aspects [8,18]. Many of the current efforts to extend or change DBMSs to better support GIS applications focus on the requirements for the representation of advanced data and on the access methods to them [2] Part of these efforts concentrated on technologies of extensible databases that can be used to ....

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HAAS, L. et.al. "Exploiting Extensible DBMS in Integrated Geographic Information Systems". In Proc. of the 2 nd Symposium on Spatial Database Systems. Pp 423-449. Lecture Notes in Computer Science 525, 1991.

....techniques. Existing DBMS do not manage constraints as persistent stored data 10 . Constraint Logic Programming [JL87, DHS 88, Col90] on the other hand, was not designed to deal with large amounts of persistent data. Extensions of DBMS with spatio temporal operators [OM88, Gut89, Wol89, HC91] typically (1) are limited to low (two or, at most three ) dimensional space, 2) have query languages restricted to predefined spatio temporal operators, and (3) lack global economical filtering and deep optimization. There has been work on the use of constraints in databases, earlier of which ....

L.M. Haas and W.F. Cody. Exploiting extensible dbms in integrated geographic information systems. In Proc. Advances in Spatial Databases, 2nd Symposium, volume 525 of Lecture Notes in Computer Science. Springer Verlag, 1991.

....the communication between internal and external memory, and not the internal computation time, is actually the bottleneck in the computation. Examples of large scale applications can e.g. be found in database systems [79, 110] spatial databases and geographic information systems (GIS) [52, 70, 84, 114, 124], VLSI verification [17] constraint logic programming [78, 79] computer graphics and virtual reality systems [60, 114] computational biology [135] physics and geophysics [47, 129] and in meteorology [47] The amount of data manipulated in such applications is too large to fit in main memory ....

....external memory techniques. GIS systems are used for scientific applications such as environmental impact, wildlife repopulation, epidemiology analysis, and earthquake studies and for commercial applications such as market analysis, facility location, distribution planning, and mineral exploration [70]. In support of these applications, GIS systems store, manipulate, and search through enormous amounts of spatial data [52, 84, 114, 124] NASA s EOS project GIS system [52] for example, is expected to manipulate petabytes (thousands of terabytes, or millions of gigabytes) of data Typical ....

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L. M. Haas and W. F. Cody. Exploiting extensible dbms in integrated geographic information systems. In Proc. of Advances in Spatial Databases, LNCS 525, 1991.

....independent interest. 1 Introduction In recent years there has been much effort in developing efficient external memory data structures for range searching, which is a fundamental primitive in several large scale applications, including spatial databases and geographic information systems (GIS) [13, 19, 25, 38, 42], graphics [16] indexing in object oriented and temporal databases [23, 34] and constraint logic programming [22, 23] Often the amount of data manipulated in such applications are too large to fit in main memory and must reside on disk, and in such cases the Input Output (I O) communication can ....

L. M. Haas and W. F. Cody. Exploiting extensible dbms in integrated geographic information systems. In Proc. of Advances in Spatial Databases, LNCS 525, 1991.

....for spatio temporal data and does not address the problem of integrating complex data from different application domains. The SAND (Spatial And Non spatial Data) system implements an open environment for developing applications involving both spatial and non spatial relational data. Reference [16] describes optimization strategies for spatial query processing providing equal opportunity for both the spatial and non spatial component to participate in query processing and optimization. Query execution plan generation and optimization will become a key issue for the implementation of a ....

Haas, L. M., and Cody, W. F. Exploiting extensible DBMS in integrated geographic information systems. In Proceedings of Advances in Spatial Databases (SSD '91) (Berlin, Germany, Aug. 1991), O. Guenther and H.-J. Schek, Eds., vol. 525 of LNCS, Springer, pp. 423-- 450.

.... Database Systems as Picture Retrieval Systems There has been a great interest in providing several extensions to the relational data model to overcome the limitations imposed by the at tabular structure of relations for geometric modeling, engineering and geographic applications [102, 86, 152, 80, 149, 103, 23]. The resulting data model is characterized by the addition of application specic components to an existing database system 11 Figure 2: System Architecture for Image Processing Graphics Systems with Database Functionality as Picture Retrieval Systems 12 Query Interface for Attribute Based ....

L. Hass and W. Cody. Exploiting extensible DBMS in integrated geographic information systems. In O. Guenther and H.-J Schek, editors, Advances in Spatial Databases, pages 423{ 450, Lecture Notes in Computer Science, Springer-Verlag, NY, 1991.

....the communication between internal and external memory, and not the internal computation time, is actually the bottleneck in the computation. Examples of large scale applications can e.g. be found in database systems [79, 110] spatial databases and geographic information systems (GIS) [52, 70, 84, 114, 124], VLSI verification [17] constraint logic programming [78, 79] computer graphics and virtual reality systems [60, 114] computational biology [135] physics and geophysics [47, 129] and in meteorology [47] The amount of data manipulated in such applications is too large to fit in main memory ....

....external memory techniques. GIS systems are used for scientific applications such as environmental impact, wildlife repopulation, epidemiology analysis, and earthquake studies and for commercial applications such as market analysis, facility location, distribution planning, and mineral exploration [70]. In support of these applications, GIS systems store, manipulate, and search through enormous amounts of spatial data [52, 84, 114, 124] NASA s EOS project GIS system [52] for example, is expected to manipulate petabytes (thousands of terabytes, or millions of gigabytes) of data Typical ....

[Article contains additional citation context not shown here]

L. M. Haas and W. F. Cody. Exploiting extensible dbms in integrated geographic information systems. In Proc. of Advances in Spatial Databases, LNCS 525, 1991.

....the use of tables with fixed number of attributes does not allow flexibility in the management of georeferenced data, nor the incremental development of applications. Thus, researchers have directed their attention to new architectures. New architectures rely on extensible relational (e.g. HC91, vOV91] object oriented (e.g, KT92, ZM92, SV92] or rule based (e.g. SA93, SRD 91] systems. A comparison in performance and flexibility of relational and extended relational systems is found in [SFGM93] Objectoriented systems are presented as a solution to the need for representing the ....

L. Haas and W. Cody. Exploiting Extensible DBMS in Integrated Geographic Information Systems . In Proc. 2nd Symposium Spatial Database Systems, pages 423--449. Springer Verlag Lecture Notes in Computer Science 525, 1991.

....] Theta Delta Delta Delta Theta [x d ; x 0 d ] The output of the query is the set of points in the data structure that are contained in ae. Range searching is a fundamental primitive in several large scale applications, including spatial databases and geographic information systems (GIS) [1, 4, 6, 9, 11], graphics [3] indexing in object oriented databases [5, 7] and constraint logic programming [7] When the data are too large to fit in main memory and must reside on disk, the Input Output (I O) communication can become a very severe bottleneck. In d dimensional space, we define a (s 1 ; s 2 ; ....

L. M. Haas and W. F. Cody. Exploiting extensible DBMS in integrated geographic information systems. In O. Gunther and H.-J. Schek, editors, Advances in Spatial Databases, Lecture Notes in Computer Science 525, pages 423--450. Springer-Verlag, 1991.

....] Theta Delta Delta Delta Theta [x d ; x 0 d ] The output of the query is the set of points in the data structure that are contained in ae. Range searching is a fundamental primitive in several large scale applications, including spatial databases and geographic information systems (GIS) [9, 6, 1, 11, 4], graphics [3] indexing in objectoriented databases [5, 7] and constraint logic programming [7] When the data are too large to fit in main memory and must reside on disk, the Input Output (I O) communication can become a very severe bottleneck. In d dimensional space, we define a (s 1 ; s 2 ; ....

L. M. Haas and W. F. Cody. Exploiting extensible DBMS in integrated geographic information systems. In O. Gunther and H.-J. Schek, editors, Advances in Spatial Databases, Lecture Notes in Computer Science 525, pages 423--450. Springer-Verlag, 1991.

....in 2D and 3D space; and structures for supporting geometric operations, which model geographic phenomena as points, line segments and polygons. Applications that motivate this research are mostly in the areas of cartography and environmental planning. Researchers consider that extensible (e.g. HC91] or object oriented models [KT92] may provide a good basis for developing gis applications, helping to solve many modelling and implementation problems posed by relational gis. Results are recent, and there is a lack of experience with real data. gis data can be classified in three main ....

L. Haas and W. Cody. Exploiting Extensible DBMS in Integrated Geographic Information Systems . In Proc. 2nd Symposium Spatial Database Systems, pages 423--449. Springer Verlag Lecture Notes in Computer Science 525, 1991.

....Either the integration is strong (no real external module, Figure 1.a) or it is weak (Figure 1.b) Note that the way from strong to weak integration is gradual. For instance, a solution in between is to consider an extensible DBMS (i.e. a DBMS with hooks for extensions at different levels, see [12]) so the DBMS plays the role of an integrator. In the case of strong integration, the potential of the underlying DBMS is exploited as much as possible, and all concepts are embedded within the same homogeneous environment. In particular, only one data model exist, and if the (virtual) external ....

L. Haas and W. Cody. Exploiting Extensible DBMS in Integrated Geographic Information Systems. In O. Gunther and H. J. Schek, editors, Advances in Spatial Databases (SSD'91). Lecture Notes in Computer Science No. 525, Springer-Verlag, Berlin, 1991.

....and object oriented models, in the sense that data nesting is allowed and procedures can be attached to relation fields. Data nesting helps handling vector data e.g. the value of one nested attribute may be a set of coordinates, representing a polygon. Examples of the use of this approach are [HC91], which describes the modelling and implementation of GIS using Starburst, and [vOV91] which add R tree and graphical display modules on top of POSTGRES. ffl object oriented model based on variations of the object oriented paradigm. There follows some examples of this type of GIS. Lor91] ....

L. Haas and W. Cody. Exploiting Extensible DBMS in Integrated Geographic Information Systems . In Proc. 2nd Symposium Spatial Database Systems, pages 423--449. Springer Verlag Lecture Notes in Computer Science 525, 1991.

....Existing DBMS do not deal with and manipulate constraints as stored data 2 . Constraint Logic Programming [JaL87, CHIP, Prolog3] on the other hand was not designed to deal with large amounts of stored data, and support spatio temporal features. Extensions of DBMS with spatio temporal operators [OrM88, Gut89, HaC91] are typically limited to low (two or, at most three ) dimensional space, have restrictions on using these operators in query languages, and lack global economical filtering and deep optimization. 2 Note, integrity constraints used in conventional databases are not data, but rather something ....

L.M. Haas, W.F. Cody, Exploiting extensible DBMS in integrated geographic information systems, Advances in Spatial Databases, Proc. 2nd Symp. on Spatial Databases, Lecture Notes in Computer Science 525, Springer Verlag, Berlin, 1991.

....use of external memory techniques. GIS systems are used for scientific applications such as environmental impact, wildlife repopulation, epidemiologic analysis, and earthquake studies and for commercial applications such as market analysis, utility facilities distribution, and mineral exploration [17]. In support of these applications, GIS systems store, manipulate, and search through enormous amounts of spatial data [13, 18, 25, 27] NASA s EOS project GIS system [13] for example, is expected to manipulate petabytes (thousands of terabytes, or millions of gigabytes) of data Typical ....

L. M. Haas and W. F. Cody. Exploiting extensible dbms in integrated geographic information systems. In Proc. of Advances in Spatial Databases, LNCS 525, 1991.

....large scale applications the communication between internal and external memory, rather than the internal computation time, is actually the bottleneck in the computation. As geographic information systems (GIS) frequently store, manipulate, and search through enormous amounts of spatial data [42, 56, 67, 80, 87] they are good examples of such large scale applications. The amount of data manipulated in such systems is often too large to fit in main memory and must reside on disk, hence the I O communication can become a very severe bottleneck. An especially good example is NASA s EOS project GIS system ....

L. M. Haas and W. F. Cody. Exploiting extensible dbms in integrated geographic information systems. In Proc. of Advances in Spatial Databases, LNCS 525, 1991.

....data, and another system processes spatial data [8] One example is the ARC INFO [46] commercial system, which combines thematic layers with the vector model. ffl extensible relational these rely on facilities provided by extensible relational models. Examples of the use of this approach are [30], who describe the modelling and implementation of gis using Starburst; 67] who add R tree and graphical display modules on top of POSTGRES; and [1] s spatial database toolkit. The TIGRIS system [31] though claiming to be object oriented, is in fact a modified relational system with handles. ....

L. Haas and W. Cody. Exploiting Extensible DBMS in Integrated Geographic Information Systems . In Proc. 2nd Symposium Spatial Database Systems, pages 423--449. Springer Verlag LNCS 525, 1991.

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Haas, L. and Cody, W. "Exploiting Extensible DBMS in integrated Geographic Information Systems". In Proc. 2 nd . Symposium Spatial Database Systems, pp. 423-449. Springer Verlag Lecture Notes in Computer Science 525. 1991.

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