R. J. Miller, L. M. Haas, and M. A. Hernandez. Schema Mapping as Query Discovery. In Proc. VLDB 2000.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....including Business to Business Net Markets (or Hubs) 1, 32] whose business hinges on federating thousands of decentralized catalogs and other databases. Broadly considered, federated database technology [44] has been the subject of multiple research thrusts, including schema integration [6, 35], data transformation [2] as well as federated query processing and optimization. The query optimization work goes back as far as the early distributed database systems (R , SDD 1, Distributed Ingres [22, 14, 7] and most recently has been focused on linking data sources of various capabilities ....

R. J. Miller, L. M. Haas, and M. A. Hernandez. Schema mapping as query discovery. In VLDB, 2000.

....sch ema to a target sch ma. Because we wrap sources independently, source and target sch mas use di#erent structures and vocabularies. Automated schema matching techM ques h ve been proven to be successful in extracting mapping elements between two sch emas. RB01] surveysth ese tech niques. Clio [MHH00]h as an extensive tool set to aid users semi automatically generate mappings. XE02] provides many mappings automatically, with accuracies ranging from 92 100 ; th ese mappings are not just 1 1 mappings, but include many indirect mappings discussed later in th is paper. See Appendix A. Th us, ....

R. Miller, L. Haas, and M.A. Hernandez. Sch ema mapping as query discovery. n Proceedings of the 26th International Conference on Very Large Databases (VLDB'00), pages 77--88, Cairo, Egypt, September 2000.

....mapping from the exact mapping, which is the output of a matching process as would be performed by a human observer. Automatic matching may carry with it a degree of uncertainty since the syntactic representation of schemas and data do not completely convey the semantics of different databases [18] . As an example, consider name matching, a common method in tools such as Cupid [17] OntoBuilder [12] Protege [11] and Ariadne [16] With name matching, one assumes that similar attributes have similar (or even identical) names. However, the occurrence of synonyms (e.g. remuneration and ....

....on our experiences in Section 4. Our findings indicate that matching algorithms that generate monotonic mappings are well suited for automatic semantic reconciliation. Another outcome of the monotonicity principle is that a little benefit in this paper. Extensions to this basic model (e.g. [18]) are beyond the scope of this paper. good automatic semantic reconciliation algorithm would rank the e xact mapping relatively close to the best mapping, thus enabling an efficient search of the exact mapping [1] 2 Preliminaries We start by introducing the notions of attribute similarity ....

R.J. Miller, L.M. Haas, and M.A. Hernandez. Schema mapping as query discovery. In A. El Abbadi, M.L. Brodie, S. Chakravarthy, U. Dayal, N. Kamel, G. Schlageter, and K.-Y. Whang, editors, Proceedings of the International conference on very Large Data Bases (VLDB), pages 77--88. Morgan Kaufmann, 2000.

....over the local databases (defined as views over the global schema) using the same algorithm for di#erent combinations of queries and sources. The most important advantage of local as view approaches is that it allows an integrated system built this way easily handles dynamic environments. Clio [14, 20] introduced an interactive schema mapping paradigm in which users are released from the manual definition of integrated views in a di#erent way from IM. A graphical user interface allows users to specify value correspondences, that is, how the value of an attribute in the target schema is computed ....

R. J. Miller, L. M. Haas and M. A. Hernandez. Schema Mapping as Query Discovery. Proceedings of the 26th VLDB Conference. Cairo Egypt, 2000.

....they belong to different models in the schema conversion problem (e.g. relational and XML models) Schema matching problem itself is a difficult problem with many important applications and deserves special attention. For further discussion on the schema matching problem, refer to [6] survey) [7] (latest development) etc. Between XML and Non relational Models: Schema conversion between different models has been extensively investigated. Historically, the trend for schema conversion has always been between consecutive models or models with overlapping time frames, as they have evolved ....

Miller, R.J., Haas, L., Hernandez, M.A.: "Schema Mapping as Query Discovery". In: International Conference on Very Large Data Bases, Cairo, Egypt (2000)

....the target and source schemas. In a previous paper [9] we formalized the data exchange problem and embarked on an in depth investigation of the foundational and algorithmic issues that surround it. Our work has been motivated by practical considerations arising in the ongoing development of Clio [16, 19], a prototype system for schema mapping and data exchange between autonomous applications. A data exchange setting is a quadruple ( where is the source schema, is the target schema, is a set of source to target dependencies that express the relationship between is a set of ....

R. J. Miller, L. M. Haas, and M. Hernandez. Schema Mapping as Query Discovery. In VLDB, pages 77--88, 2000.

....the new ones. It forms a critical step in data warehousing and data mining, two important research and commercial areas since the early 1990s. In these applications, data coming from multiple sources must be transformed to data conforming to a single target schema, to enable further data analysis [MHH00, RB01] During the late 1980s and the 1990s, applications of representation matching arose in the context of knowledge base construction, which is studied in the AI community. Knowledge bases store complex types of entities and relationships, using extended database schemas called ontolo gies ....

....group seeks to automate the mapping process. Because the users must be in the loop, only semiautomatic methods can be considered. Numerous such methods have been developed, in the areas of databases, AI, e commerce, and the Semantic Web (e.g. MZ98, PSU98, CA99, LC00, PE95, CHR97, MBR01, MMGR02, MHH00, DR02, Cha00, MFRW00, NM00, MWJ, NM01, RHS01] see [RB01] for an excellent survey of automatic approaches developed by the database community) The proposed approaches have built efficient specialized mapping strategies, and significantly advanced our understanding of representation matching. ....

[Article contains additional citation context not shown here]

R. Miller, L. Haas, and M. Hernandez. Schema mapping as query discovery. In Proc. of VLDB, 2000.

....combinatorial. Our choice is partially dictated by the specific mechanisms for Web search (i.e. form filling in a Web setting) In this setting, instance based analysis (as employed in [31, 12, 6] for example) is not an option. Also, n: i matching, as was suggested as part of the Clio project [26, 21, 27] for extracting complex schema structures, involves either manual intervention or query analysis, which we generally restrict. In this work we have employed existing Information Retrieval (IR) techniques (e.g. 15, 14] for term and value extraction. The novelty of our approach in this respect ....

R.J. Miller, L.M. Haas, and M.A. Hern&ndez. Schema mapping as query discovery. In A. E1 Abbadi, M.L. Brodie, S. Chakravarthy, U. Dayal, N. Kamel, G. Schlageter, and K.-Y. Whang, editors, Proceedings of the International conference on very Large Data Bases (VLDB), pages 77-88. Morgan Kaufmann, 2000.

....as an integral part of the matching process and allow for efficient user interaction. For example, the system in [NM00] frequently solicits user feedback on its matching decisions (e.g. confirm or reject the decisions) then makes subsequent decisions based on the feedback. The Clio system [MHH00, YMHF01, PVH 02] focuses on very fine grained mappings, which are for example SQL or XQuery expressions that can be immediately executed to translate data from one representation to another. Clio makes two important contributions. First, it recognizes that creating such fine grained mappings ....

....deal with complex matching in the sense that such matchings are hard coded into rules. The rules are systematically tried on the elements of given representations, and when such a rule fires, the system returns the complex mapping encoded in the rule. As mentioned earlier, the Clio system [MHH00, YMHF01, PVH 02] creates complex mappings for relational and XML data. To create a complex mapping for a representation element, Clio assumes that the right attributes and formula have been given (either by the user, by data mining techniques, or by systems such as LSD) It then focuses on ....

R. Miller, L. Haas, and M. Hernandez. Schema mapping as query discovery. In Proc. of VLDB, 2000.

....types of schema heterogeneity in RDBs and OODBs. Another comprehensive work in this area is presented in [4] Both efforts address problems of schema heterogeneity, but do not distinguish between the schematic and semantic issues while we focus on the semantic problems here. Miller et al. in [15] distinguish schema integration from schema mapping. They focus on the mapping of data, taking the integrated schema for granted. Likewise, we consider phases of schema integration and data mapping. However, data mapping in our work is not yet as complete as the one in [15] and needs further ....

....here. Miller et al. in [15] distinguish schema integration from schema mapping. They focus on the mapping of data, taking the integrated schema for granted. Likewise, we consider phases of schema integration and data mapping. However, data mapping in our work is not yet as complete as the one in [15] and needs further investigations. Bergamaschi et al. 1] Palopoli et al. 16] and Medhavan et al. 13] propose approaches using thesaurus. Bergamaschi et al. introduced a semiautomatic approach assisting domain experts in extracting relations in the thesaurus from schema structure by help of ....

[Article contains additional citation context not shown here]

Rene J. Miller, Laura M. Haas, and Mauricio A. Hernndez. Schema mapping as query discovery. In Amr El Abbadi, Michael L. Brodie, Sharma Chakravarthy, Umeshwar Dayal, Nabil Kamel, Gunter Schlageter, and Kyu-Young Whang, editors, VLDB 2000.

....techniques( MZ98] NAM98] They observed that simple mappings, which simply copy records from one table to another, form a large volume of the mappings. The YAT system ( CDSS98] de nes a logic framework, which allows the mapping of object oriented schemas through a graphic interface. Clio ([MHH00]) is an interactive schema mapping creation system. It focuses on learning a certain class of view de nitions based on a concept called value correspondences. 10 ....

Renee J. Miller, Laura M. Haas, and Mauricio A. Hernandez. Schema mapping as query discovery. In Proceedings of the 26th International Conference on Very Large Data Bases, pages 77-88, 2000.

....is data translation [BKKK87, LCC94, SHT 77] Recent techniques, such as those of [CJR98, MZ98] are excellent test cases for a generic model management system. Schema integration: There are many approaches to schema integration which are candidate algorithms for Match [BCV99, JMN 99, MHH00, MWK00, PSU98, MMP95, DDL00] Information capacity of models [MIR93] may also be key to comparing among models. 7 Final Remarks In this paper, we presented an outline of a data model for model management, which has two main abstractions model, which captures the structure of engineered ....

Renee J. Miller, Laura Haas, and Mauricio Hernandez. Schema mapping as query discovery. In Proc. of VLDB, 2000.

....1 Introduction Schema matching is the problem of finding mappings between the attributes of two semantically related database schemas. The schema matching problem is an important, current issue for many database applications such as schema integration, data warehousing, and electronic commerce [12, 15]. Unfortunately, schema matching remains largely a manual, labor intensive process. Furthermore, the effort required is typically linear in the number of schemas to be matched; the next pair of schemas to match is not any easier than the previous pair. Thus, database applications that require ....

Ren'ee Miller, Laura Haas, and Mauricio Hern'andez. Schema mapping as query discovery. In Proceedings of the 26th International Conferences on Very Large Databases, pages 77--88, 2000.

....domain specific, and that data cleaning tools must handle these domains extensibly. A companion problem to data cleaning is the integration of schemas from various data sources. We intend to extend Potter s Wheel with a system that handles interactive specification of schema mappings (such as Clio [19]) Extracting structure from poorly structured data is increasingly important for wrapping data from web pages, and many tools exist in both the research and commercial world (e.g. 2, 12, 8] As discussed in Section 4.3, these tools typically require users to specify regular expressions or ....

R. J. Miller, L. Haas, and M. A. Hernandez. Schema mapping as query discovery. VLDB, 2000.

....to automate or at least support this process in as much as is possible. 1.2 State of the Art Schema Translation. ARTEMIS [2, 3] supports the analysis and reconciliation of sets of heterogeneous relational schemas by measuring the similarity of element names, data types, and structures. Clio [11, 21] uses reasoning about SQL queries to create initial mappings between relational schemas, then re nes these mappings using data examples. However, because relational schemas are at, neither Clio nor ARTEMIS can handle hierarchical XML schemas. TranScm [12] uses schema matching to derive an ....

R. Miller, L. Haas, and M. Hernandez. Schema mapping as query discovery. In VLDB, pages 77-88, 2000.

No context found.

R. J. Miller, L. M. Haas, and M. Hernandez. Schema Mapping as Query Discovery. In Proc. of the Int'l Conf. on Very Large Data Bases (VLDB), pages 77--88, Cairo, Egypt, September 2000.

No context found.

R. J. Miller, L. M. Haas, and M. Hern'andez. Schema Mapping as Query Discovery. In Proc. of the Int'l Conf. on VLDB, Cairo, Egypt, 2000.

No context found.

R. J. Miller, L. M. Haas, and M. Hernandez. Schema Mapping as Query Discovery. In Proc. of the Int'l Conf. on Very Large Data Bases (VLDB), pages 77--88, Cairo, Egypt, September 2000.

No context found.

R. J. Miller, L. M. Haas, and M. Hernandez. Schema Mapping as Query Discovery. In Proc. of the Int'l Conf. on Very Large Data Bases (VLDB), pages 77--88, Cairo, Egypt, September 2000.

....and for which queries can the certain answers be computed using just the materialized target instance Motivation from Clio. The results presented here were motivated by our experience with Clio, a prototype schema mapping and data exchange tool to whose development some of us have contributed [MHH00,PVM 02] In Clio, source totarget dependencies (forming a GLAV system) are (semi) automatically generated from a set of correspondences between the source schema and the target schema; these dependencies can then be used in a data integration system to compute the certain answers to target ....

R. J. Miller, L. M. Haas, and M. Hernandez. Schema Mapping as Query Discovery. In Proceedings of the International Conference on Very Large Data Bases (VLDB), pages 77--88, 2000.

....and for which queries can the certain answers be computed using just the materialized target instance Motivation from Clio. The results presented here were motivated by our experience with Clio, a prototype schema mapping and data exchange tool to whose development some of us have contributed [MHH00,PVM 02] In Clio, source totarget dependencies (forming a GLAV system) are (semi) automatically generated from a set of correspondences between the source schema and the target schema; these dependencies can then be used in a data integration system to compute the certain answers to target ....

R. J. Miller, L. M. Haas, and M. Hernandez. Schema Mapping as Query Discovery. In Proceedings of the International Conference on Very Large Data Bases (VLDB), pages 77--88, 2000.

....and for which queries can the certain answers be computed using just the materialized target instance Motivation from Clio. The results presented here were motivated by our experience with Clio, a prototype schema mapping and data exchange tool to whose development some of us have contributed [18,19]. In Clio, source to target dependencies are (semi) automatically generated from a set of correspondences between the source schema and the target schema; these dependencies can then be used in a data integration system to compute the certain answers to target queries. Most of the applications we ....

R. J. Miller, L. M. Haas, and M. Hernandez. Schema Mapping as Query Discovery. In VLDB, pages 77--88, 2000.

....to manually identify and specify the intricate details of a mapping, such as the generation of keys, references, join conditions, etc. To shield the user from writing complex queries or programs for every translation problem at hand, we advocate the use of a high level schema mapping tool like Clio[1], where users are guided towards the specification of a high level mapping using value correspondences. Informally, value correspondences specify how values for a target attribute are generated by one or more source attributes. Given this high level mapping, Clio s mapping engine discovers a ....

R. J. Miller, L. M. Haas, and M. A. Hernandez. Schema Mapping as Query Discovery. In VLDB 2000.

....and for which queries can the certain answers be computed using just the materialized target instance Motivation from Clio. The results presented here were motivated by our experience with Clio, a prototype schema mapping and data exchange tool to whose development some of us have contributed [MHH00, PVM 02] In Clio, source to target dependencies are (semi) automatically generated from a set of correspondences between the source schema and the target schema; these dependencies can then be used in a data integration system to compute the certain answers to target queries. Most of the ....

R. J. Miller, L. M. Haas, and M. Hernandez. Schema Mapping as Query Discovery. In Proceedings of the International Conference on Very Large Data Bases (VLDB), pages 77--88, 2000.

....and for which queries can the certain answers be computed using just the materialized target instance Motivation from Clio. The results presented here were motivated by our experience with Clio, a prototype schema mapping and data exchange tool to whose development some of us have contributed [18, 19]. In Clio, source to target dependencies are (semi) automatically generated from a set of correspondences between the source schema and the target schema; these dependencies can then be used in a data integration system to compute the certain answers to target queries. Most of the applications we ....

R. J. Miller, L. M. Haas, and M. Hernandez. Schema Mapping as Query Discovery. In VLDB, pages 77--88, 2000.

....of the source and has no independent semantics of its own. Even our own earlier work on schema mapping considered the problem of mapping a source schema (with a rich logical structure) into a flat (single table) target schema with no constraints, thus ignoring half of the more general problem [12]. In contrast, Section 2 gives a semantic translation algorithm that preserves semantic relationships during the translation from source to target, where the source and Alternatively, in a local as view approach each source schema is modeled as a view on the target schema [8] the target schemas ....

R. J. Miller, L. M. Haas, and M. Hernandez. Schema Mapping as Query Discovery. In k'LDB, pages 77-88, 2000.

....semantics of the source and has no independent semantics of its own. Even our own earlier work on schema mapping considered the problem of mapping asourceschema(witharichlogicalstructure)intoa flat (single table) target schema with no constraints, thus ignoring half of the more general problem [12]. In contrast, Section 2 gives a semantic translation algorithm that preserves semantic relationships during the translation from source to target, where the source and Alternatively, in a local as view approach each source schema is modeled as a view on the target schema [8] the target ....

R. J. Miller, L. M. Haas, and M. Hernandez. Schema Mapping as Query Discovery. In VLDB, pages 77--88, 2000.

....tool integration however, this is not sufficient. Each tool requires data in a specified format or schema. The warehouse schema and data must be mapped and transformed into the required tool format. We have experimented with the use IBM s Clio schema integration tool to perform this integration [33]. The promising results of this study are reported elsewhere [33] ffl Scalability Reverse Engineering tools use plain files or database management systems (DBMS) to store the artifacts and data generated by the parser 8 [5, 4] Even tools that store low level component data within a DBMS, often ....

....data in a specified format or schema. The warehouse schema and data must be mapped and transformed into the required tool format. We have experimented with the use IBM s Clio schema integration tool to perform this integration [33] The promising results of this study are reported elsewhere [33]. ffl Scalability Reverse Engineering tools use plain files or database management systems (DBMS) to store the artifacts and data generated by the parser 8 [5, 4] Even tools that store low level component data within a DBMS, often represent views and view definitions in data structures or files ....

R. J. Miller, L. M. Haas, and M. Hern'andez. Schema Mapping as Query Discovery. In Int'l Conf. on Very Large Data Bases, Sept. 2000.

No context found.

R. J. Miller, L. M. Haas, and M. A. Hernandez. Schema Mapping as Query Discovery. In Proc. VLDB 2000.

No context found.

Miller, Ren ee J., Laura M. Haas, and Mauricio A. Hern andez. Schema Mapping as Query Discovery. Proc. VLDB Conf., pp. 77-88, Cairo, Egypt, 2000.

No context found.

R. Miller, L. M. Haas, and M. Hern andez. Schema mapping as query discovery. In VLDB, 2000.

No context found.

R. Miller, L. M. Haas, and M. Hern andez. Schema mapping as query discovery. In VLDB, 2000.

No context found.

R. Miller, L. Haas, and M. Hernandez. Schema mapping as query discovery. In Proc. of VLDB, 2000.

No context found.

R. J. Miller, L. M. Haas, and M. Hern andez. Schema Mapping as Query Discovery. In Proceedings of the International Conference on Very Large Data Bases (VLDB), pages 77--88, 2000.

No context found.

R. J. Miller, L. M. Haas, and M. Hern andez. Schema Mapping as Query Discovery. In VLDB, pages 77--88, 2000.

No context found.

R. Miller, L. Haas, and M.A. Hernandez. Schema mapping as query discovery. In Proceedings of the 26th International Conference on Very Large Databases (VLDB'00), pages 77--88, Cairo, Egypt, September 10--14 2000.

No context found.

R. Miller, L. Haas, and M. Hernandez. Schema mapping as query discovery. In Proc. of VLDB, pages 77--88, 2000.

No context found.

Renee J. Miller, L. M. Haas, and M. Hernandez. Schema Mapping as Query Discovery. In Proceedings of the 26th International Conference on Very Large Data Bases, pages 77--88, Cairo, Egypt, Sept 2000.

No context found.

R. J. Miller, L. M. Haas, and M. Hern andez. Schema Mapping as Query Discovery. In VLDB, pages 77--88, Cairo, Egypt, Sept. 2000.

No context found.

R.J. Miller, L.M. Haas and M. Hernndez. "Schema Mapping as Query Discovery". Proc VLDB'00, Cairo, Egypt, pp.77-88 (2000).

No context found.

R.J. Miller, L.M. Haas, and M.A. Hernandez. Schema Mapping as Query Discovery. In Proc. VLDB'00, pages 77--88, 2000. 20

No context found.

R. J. Miller, L. M. Haas, and M. Hernandez. Schema Mapping as Query Discovery. In International Conference on Very Large Data Bases (VLDB), pages 77--88, 2000.

No context found.

R. J. Miller, L. M. Haas, and M. Hern andez. Schema Mapping as Query Discovery. In VLDB, pages 77--88, Cairo, Egypt, Sept. 2000.

No context found.

R. J. Miller, L. M. Haas, and M. Hern andez. Schema Mapping as Query Discovery. In VLDB, pages 77--88, Cairo, Egypt, September 2000.

No context found.

R.J. Miller, L.M. Haas, and M.A. Hernandez. Schema mapping as query discovery. In A. El Abbadi, M.L. Brodie, S. Chakravarthy, U. Dayal, N. Kamel, G. Schlageter, and K.-Y. Whang, editors, Proceedings of the International conference on very Large Data Bases (VLDB), pages 77--88. Morgan Kaufmann, 2000.

No context found.

Miller, R.J., Haas, L., Hernandez, M.A.: "Schema Mapping as Query Discovery". In: VLDB, Cairo, Egypt (2000)

No context found.

R. Miller, L. Haas, and M.A. Hernandez. Schema mapping as query discovery. In Proceedings of the 26th International Conference on Very Large Databases (VLDB'00), pages 77--88, Cairo, Egypt, September 2000.

No context found.

R. Miller, L. Haas, and M. Hernandez. Schema mapping as query discovery. In Proc. of VLDB, 2000.

No context found.

1L J. Miller, L. M. Haas and M. Hernfindez. Schema Mapping as Query Discovery. VLDB 2000.

No context found.

Miller, R., Haas, L. & Hernandez, M., Schema Mapping as Query Discovery, Proceedings of 26 nl International Conference on Very Large Data Bases (VLDB), pp. 77-88, Cairo, Egypt, 2000

First 50 documents  Next 50

Online articles have much greater impact   More about CiteSeer.IST   Add search form to your site   Submit documents   Feedback  

CiteSeer.IST - Copyright Penn State and NEC