Yuri Breitbart, Peter L. Olson, and Glen R. Thompson. Database integration in a distributed heterogeneous database system. In ICDE, pages 301-310, 1986.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....representation of (potentially the same) data and the semantic [7] interpretation of the data by the applications supported by these databases. Thus, a substantial research effort has been invested in integrating the schemas of heterogeneous databases or constructing unified views of their data [2,3,4] and creating new query languages to query distributed heterogeneous databases [10] Babel: An XML Based Application Integration provides support for specifying existing applications in terms of the functio 1 Motivation and Background A. Banks Pidduck et al. Eds. CAiSE 2002, LNCS 2348, pp. ....

Y. Breitbart, P. Olson, and G. Thompson, "Database integration in a distributed heterogeneous database system", Proceedings of the 2nd International Conference on Data Engineering, Los Angeles, CA, February 1986, pp. 301-310.

....external databases were mapped to schemas in the common data model, and similar schema constructs from di erent schemas were integrated into generalization hierarchies. Subsequently, many other systems were proposed or implemented with integration based on an outerjoin or generalization mechanism [1, 10, 11, 12, 13, 23, 31, 36, 33],aswell as systems which allowed for more general ways in which objects may be related or merged [5, 15, 24, 37, 42] The systems and techniques just referenced all provide support for what was referred to as data integration in the previous section. Data integration is the process of merging ....

Y. Breitbart, P. L. Olson,andG.R.Thompson.Database integration in a distributed heterogeneous databasesystem. In ##### ## ### ##### ##### ## #### ###########,pages 301-310, Los Angeles, Feb. 1986.

.... Lenzerini et al. 15] F F P P F F F Spaccapietra, Parent [41] F Gangopadhya, Barsalou [44] F F F Worboys and Deen [45] P P Salaco, Saltor et al. 33] P F Ventrone and Heiler [34] F Kim and Seo [18] F F F F F F F F F F Reddy, Prasad, Gupta [28] F F P F F F F F Breitbart, Olson et al. [42] F F F F F Fankhauser, Neuhold [35] P Sheth and Kashyap [36] F F F F F F F F Jeffery, Hutchinson et al. 26] P P F F F P F Deen, Amin. Taylor [25] P P P P F accessible in another in other words, finding attribute equivalences. The simplest form of heterogeneity in this regard is that of ....

....attribute integrity constraint conflicts and union compatibility conflicts. The data model heterogeneity is addressed by Cardenas [37] Thomas et al. 38] Ferrier and Stangret [39] Litwin and Abdellatif [40] Hurson and Bright [12] Spaccapietra and Parent [41] Breitbart, Olson et al. [42], Navathe and Savasere [27] while Bukhres et al. 14] also cover access heterogeneity. Apart from the heterogeneities covered in this paper, authors have also covered differences in the database management systems [32] differences in data models [43] differences in query languages and ....

Y. Breitbart, P.L. Olson, G.R. Thompson, Database integration in a distributed heterogeneous database system, Second IEEE Data Engineering International Conference, CS Press, Los Almitos, CA, 1986 pp. 301--310.

....from a collection of distributed, heterogeneous and overlapping databases. 1 A standard approach to this problem has been to integrate the independent databases by means of a comprehensive global scheme that models the information contained in the entire collection of databases (for example, [23, 38, 7, 30]) This global scheme is fitted with a mapping that defines the elements of the global scheme in terms of elements of the schemes of the member databases. Algorithms are designed to interpret queries on the global scheme. Such global queries are translated (using the information captured in the ....

....and the latter is a member database. This definition may be considered a formalization of virtual databases defined in [30] Scheme mapping may be considered an abstraction of different solutions that have been advanced to the task of relating global schemes to schemes of member databases (e.g. [23, 38, 7, 30]) 11 3.5 Integrability Assumptions The purpose of multidatabases is to integrate information from several, independent databases. Of course, the problem of integration is trivial, unless the information sources are inconsistent: i.e. a portion of the real world is described differently by ....

Y. Breitbart, P. L. Olson, and G. R. Thompson. Database integration in a distributed heterogeneous database system. In Proceedings of the IEEE Computer Society Second International Conference on Data Engineering (Los Angeles, California, February 5--7), pages 301--310, 1986.

....such conflicts when integrating data from different databases. A significant amount of previous work exists on these data integration problems. Some approaches use a generalization mechanism, typically implemented using an outerjoin operation, to combine types or relations from different schemas [3, 6, 7, 14, 29, 30], while other systems also have considered other ways that two or more relations or types might be combined [11, 39] Object identification is implicit in the primary key construct in each data model. For example, two objects would be determined to be the same if they had the same key. ....

Y.Breitbart,P.L.Olson,andG.R.Thompson.Databaseintegration in a distributed heterogeneous database system. In Proc. of the Int'l Conf. on Data Engineering, pages 301--310, Los Angeles, Feb. 1986.

....manipulation and management of different heterogeneous database systems. We divide the current approaches in the literature that deal with the problem of manipulating and managing different and multiple autonomous databases into two groups. The first group uses the idea of having a global schema [1, 11, 14, 23, 26, 30, 62, 67, 91, 97, 104] integrating all the databases in a logical single database. Hence, users may manipulate data of the global schema or of an external schema derived from it. As defined by Litwin [69] it is the reapplication of the database approach principle one level up, i.e. all data has to be converted into a ....

....the methodologies, algorithms and heuristics that help the integration process, it is necessary to havehuman assistance to support the resolution of conflicts (there is a lack of automatic processes) This assistance is only reasonable when the number of components is small. There are some systems [11, 14, 23, 30, 91, 97] that use an auxiliary database to assist 14 in the resolution of these incompatibilities. As outlined in [93] the results of a schema integration activity are not unique and cannot be generated totally automatically.The integration process needs information that goes further than synthesising ....

Y. Breitbart, P.L. Olson, and G.R. Thompson. Database integration in a distributed heterogeneous database system. In International Conference on Data Engineering, pages 301--310, Los Angeles, California, February 1986. IEEE Computer Society. 92

....however, in a multi organizational environment, the number of such databases can be tens or hundreds. Conventional FDBMs have been largely based on the well known schema integration approach, which requires the resolution of both semantic and structural differences among the component databases [1, 2, 3, 4, 14, 20, 21]. As we show in this paper, schema integration is difficult to maintain, and consequently lacks flexibility and scalability. We have proposed a new approach, called schema coordination, as a better alternative, for federated database systems in multi organizational environments [24, 25] In this ....

Yuri Breitbart, Peter L. Olson, and Glenn R. Thompson. Database Integration In A Distributed Heterogeneous Database System. In Proceedings of the Second International Conference on Data Engineering, pages 301--310, February 1986.

....and by supporting the Flex Transaction model [ELLR90] to coordinate concurrent executions. The problem of integrating pre existing systems, especially database systems, has been studied by many other researchers. Examples include Multibase [SBD 81] Mermaid [TLW87] MRDSM [Lit85] ADDS [BOT86] DATAPLEX [Chu90] and Pegasus [ASD 91] The focus of most of the above work is the logical level (i.e. database schema level) integration of existing database systems. For example, ADDS uses an extended relational data model to integrate relational, network, and hierarchical databases. ....

Y. Breitbart, P.L. Olson, and G.R. Thompson. Database Integration in a Distributed Heterogeneous Database Systems. In Proceedings of the 2nd International Conference on Data Engineering, pages 301--310, Los Angeles, CA, February 1986.

....due to Heterogeneity (representational structural) differences. While there is a significant amount of literature discussing schematic differences, work on semantic issues (e.g. Ken91] in the database context is scarce. Classification or taxonomies of schematic differences appear in [DH84, BOT86, CRE87, KLK91, KS91]. However, purely schematic considerations do not suffice to determine the similarity between objects [FKN91] SG89] In this paper we try to reconcile the two perspectives. We develop a semantic taxonomy emphasizing semantic similarities between objects and show its relationship to a structural ....

.... ffi partial 1 1 value mapping and Context = SAME = wrt which the mapping has been deduced and D 1 = f UG , Grad g and D 2 = f Grad g 6 Data Value Incompatibility Problem This class of conflicts covers those incompatibilities that arise due to the values of the data present in different databases [BOT86]. This class of conflict is different from the default value conflicts and attribute integrity constraint conflicts described in Section 4. The latter type of conflict is due to the definitions of the values of the attribute domains, whereas here we refer to the data values already existing in the ....

Y. Breitbart, P. Olson, and G. Thompson. Database Integration in a Distributed Heterogeneous Database System. In Proceedings of the 2nd IEEE Conference on Data Engineering, February 1986.

....can be contexts constructed using the various operations mentioned above. While there is a significant amount of literature discussing schematic differences, work on semantic issues (e.g. Ken91] in the database context is scarce. Classification or taxonomies of schematic differences appear in [DH84, BOT86, CRE87, KLK91, KS91]. In this paper we present what we believe is a comprehensive taxonomy of schematic conflicts which subsumes most of the taxonomies found in literature (Table 2 in Appendix A.5) However, purely schematic considerations do not suffice to determine the similarity between objects [FKN91] SG89] In ....

.... dealing with are: domain incompatibility, entity definition incompatibility, data value incompatibility, abstraction level incompatibility and schematic discrepancies (Figure 5) While the issue of schematic representational structural heterogeneity have been dealt with by a number of researchers [DH84, BOT86, CRE87, KLK91, KS91], the unique feature of our work is the strong tie between the semantic aspects defined above and the structural aspects. 6.1 Domain Incompatibility In this section we discuss the incompatibilities that arise between two domain types when they are differing definitions of semantically similar ....

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Y. Breitbart, P. Olson, and G. Thompson. Database Integration in a Distributed Heterogeneous Database System. In Proceedings of the 2nd IEEE Conference on Data Engineering, February 1986.

....in the literature. Summary: Pu has not yet discussed the issue of reliability. Further, Pu s research is not applicable to the environment consider in this thesis because modification of the DBMSs is necessary to provide the superdatabase with O elements. Breitbart and others: Breitbart et al. [7, 4, 5, 6] have undertaken research in database integration, query processing, architectures and transaction management on multidatabase systems. The following discussion will only consider the work as it relates to transaction management on multi4 The lock point occurs at the end of phase one of the ....

Y. Breitbart, P. Olson, and G. Thompson. Database integration in a distributed heterogeneous database system. In Proceeding of the 2nd International Conference on Data Engineering, pages 301--310, Los Angeles, CA., February 1986.

....can be decomposed and translated, and the local results can be synthesised automatically. 1 Introduction Due to the rapid advance in networking technologies and the requirement of data sharing among different organizations, federated systems have become the trend of future database developments [BOT86, LA86, Jo93, SK92, CW93, HLM94, RPRG94, KFMRN96]. The research on this issue can be roughly divided into two main categories: the tightly integrated approach that integrates databases by building an integrated schema and the loosely integrated approach that achieves interoperability by using a multidatabase language. The method proposed here ....

Y. Breitbart, P. Olson, and G. Thompsom. "Database integration in a distributed heterogeneous database system," in: Proc. 2nd IEEE Conf. Data Eng., 1986, pp. 301 - 310.

....dealing with are: domain incompatibility, entity definition incompatibility, data value incompatibility, abstraction level incompatibility and schematic discrepancies (Fig. 6) While the issues of schematic representational structural heterogeneity have been dealt with by a number of researchers [DH84, BOT86, CRE87, KLK91, KS91], the unique feature of our work is the strong correlation between the semantic aspects defined above and the structural aspects. 5.1 Domain incompatibility In this section, we discuss the incompatibilities that arise when two different domain types are used as different definitions of ....

....= SOME, M, D 1 , D 2 ) where M: STUDENT # GRAD STUDENT is a partial 1 1 value mapping and Context = SOME = type, graduate ) 5. 3 Data value incompatibility This class of conflicts covers those incompatibilities that arise due to the values of the data present in different databases [BOT86]. These conflicts are different from default value conflicts (Sect. 5.1.5) and attribute integrity constraint conflicts (Sect. 5.1.6) in that the latter are due to the differences in the definitions of the domain types of the attributes. Here, we refer to the data values already existing in the ....

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Breitbart Y., Olson P., Thompson G. (1986) Database integration in a distributed heterogeneous database system. In<F3.963e+05> Proceedings of the 2nd IEEE Conference on Data Engineering.<F3.733e+05>

....from object oriented concepts such as subclassing and object references available in the translated schema, resulting in simpler and semantically more expressive expressions. 1.4 Related work Query translation has been an important topic in federated database systems. However, existing work [3,7,20] is devoted to the run time translation of queries on the federated schema, expressed in the DML of the common data model, into queries on the underlying databases, expressed in the local DML. Whereas these approaches focus on implementing the data access operations specified at the federation ....

Y. Breitbart, P. L. Olson & G. R. Thompson, "Database integration in a distributed heterogeneous database system," in Proceedings Second International Conference on Data Engineering, Los Angeles, CA, February 5--7, 1986 , IEEE Computer Society Press, Washington, DC, 1986, 301--310.

....similarities and the schematic (representational structural) differences. While there is a significant amount of literature discussing schematic differences, work on semantic issues (e.g. Ken91] in the database context is scarce. Classification or taxonomies of schematic differences appear in [DH84, BOT86, CRE87, KLK91, KS91]. In this paper we present what we believe a comprehensive taxonomy of schematic conflicts which subsumes most of the taxonomies found in literature (refer to the table in the Appendix) Attempts have been made to represent structural similarities in [CHS91, SPD92, UW91, GB91] However, purely ....

.... Relationship) Semantic Relevance) Figure 7: Entity Definition Incompatibilities and the likely types of semantic proximities 8 Data Value Incompatibility Problem This class of conflicts covers those incompatibilities that arise due to the values of the data present in different databases [BOT86], and is different from the default value conflicts and attribute integrity constraint conflicts described in Section 5. The latter type of conflict is due to the definitions of the values of the attribute domains, whereas here we refer to the data values already existing in the database. Thus, ....

Y. Breitbart, P. Olson, and G. Thompson. Database Integration in a Distributed Heterogeneous Database System. In Proceedings of the 2nd IEEE Conference on Data Engineering, February 1986.

....similarities and the schematic (representational structural) differences. While there is a significant amount of literature discussing schematic differences, work on semantic issues (e.g. Ken91] in the database context is scarce. Classification or taxonomies of schematic differences appear in [DH84, BOT86, CRE87, KLK91, KS91]. In this paper we present what we believe a comprehensive taxonomy of schematic conflicts which subsumes most of the taxonomies found in literature (refer to the table in the Appendix) Attempts have been made to represent structural similarities in [CHS91, SPD92, UW91, GB91] However, purely ....

....which the mapping has been deduced and the schema correspondence defined above is associated with and depends on the above Context. 8 Data Value Incompatibility Problem This class of conflicts covers those incompatibilities that arise due to the values of the data present in different databases [BOT86], and is different from the default value conflicts Entity Definition Incompatibility Database Identifier Conflicts Naming Conflicts Homonyms Synonyms Union Compatibility Conflicts Schema Isomorphism Conflicts Missing Data Item Conflicts (Semantic Resemblance) Semantic Incompatibility) ....

Y. Breitbart, P. Olson, and G. Thompson. Database Integration in a Distributed Heterogeneous Database System. In Proceedings of the 2nd IEEE Conference on Data Engineering, February 1986.

....hardware, software, and network environments such as multidatabases. The problem of integrating pre existing database systems has been studied by many other researchers, and several other prototypes have also been developed. Examples include Multibase [LR82] Mermaid [TLW87] MRDSM [Lit85] ADDS [BOT86] and DATAPLEX [Chu90] Most of these approaches, however, are either a front end to multiple databases or support only logical level integration. Some, such as ADDS, do support system level integration. They are based on the traditional transaction model and transaction management strategy and ....

Y. Breitbart, P.L. Olson, and G.R. Thompson. Database Integration in a Distributed Heterogeneous Database Systems. In Proceedings of the International Conference on Data Engineering, pages 301--310, Los Angeles, CA, February 1986.

....adapters. Early results can be found in [BDB95] Work on distributed object management started before the Object Management Group (OMG) was formed. Research groups both in industry and academia began the task of developing architectures for systems integration in the mid 80 s [BK85, WK87, BOT86] These, however, have been rather ad hoc developments. In industry, for example, architectures have been designed with more emphasis on integration of legacy systems than interoperability of systems in heterogeneous environments. Our work builds upon previous research and extends it to cover ....

Y. Breitbart, P. Olson, and G. Thomson. Database integration in a distributed heterogeneous database system. In Proceedings 2nd IEEE International Conference on Data Engineering, 1986.

.... dealing with are: domain incompatibility, entity definition incompatibility, data value incompatibility, abstraction level incompatibility and schematic discrepancies (Figure 6) While the issue of schematic representational structural heterogeneity have been dealt with by a number of researchers [DH84, BOT86, CRE87, KLK91, KS91], the unique feature of our work is the strong correlation between the semantic aspects defined above and the structural aspects. 5.1 Domain Incompatibility In this section we discuss the incompatibilities that arise when two different domain types are used as different definitions of ....

....(Semantic Relationship) Semantic Relevance) Figure 8: Entity Definition Incompatibilities and the likely types of semantic proximities 5. 3 Data Value Incompatibility This class of conflicts covers those incompatibilities that arise due to the values of the data present in different databases [BOT86]. These conflicts are different from default value conflicts (Section 5.1.5) and attribute integrity constraint conflicts (Section 5.1.6) in that the latter are due to the differences in the definitions of the domain types of the attributes. Here we refer to the data values already existing in the ....

[Article contains additional citation context not shown here]

Y. Breitbart, P. Olson, and G. Thompson. Database Integration in a Distributed Heterogeneous Database System. In Proceedings of the 2nd IEEE Conference on Data Engineering, February 1986.

No context found.

Yuri Breitbart, Peter L. Olson, and Glen R. Thompson. Database integration in a distributed heterogeneous database system. In ICDE, pages 301-310, 1986.

No context found.

Yuri Breitbart, Peter L. Olson, and Glen R. Thompson. Database integration in a distributed heterogeneous database system. In ICDE, pages 301-310, 1986.

No context found.

Y. Breitbart, P. Olson, and G. Thompson. Database integration in a distributed heterogeneous database system. In Proceedings of the 2nd International Conference on Data Engineering, pages 301--310, Los Angeles, CA, Feb 1986.

No context found.

Breitbart, Y., P.L. Olson., and G.R. Thompson, "Database Integration in a Distributed Heterogeneous Database System," In Proceedings of the 2nd International Conference on Data Engineering, pp. 301-310, 1986.

No context found.

BOT86 Y. Breitbart, P. Olson, and G. Thompsom, "Database integration in a distributed heterogeneous database system," in Proc. 2nd IEEE Conf. Data Eng., 1986, pp. 301 - 310.

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