V. Kashyap and A. Sheth. Schematic and semantic similarities between database objects: a context-based approach. The Very Large Database Journal, 5(4):276--304, 1996.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....name, grade) pD 2 . student(id, name, score) score grade(score, grade) score grade(4, A ) score grade(3, B ) score grade(2, C ) score grade(1, D ) score grade(0, F ) One important type of conflicts mentioned in literature in business applications is aggregation conflict [19]. Aggregation conflicts arise when an aggregation is used in one database to identify a set of entities in another database. For example, in a transactional database, there is a relation sales(date, customer, part, amount) that stores the sales of parts during the year. In an executive ....

V. Kashyap, A. Sheth, Schematic and semantic similarities between database objects: a context-based approach, VLDB Journal 5 (4) (October 1996) 276 -- 304.

....surround a reasoning process [20, 25, 26] Recent studies on data semantics and interoperability have stressed the importance of context to describe data content. In this domain, context is the knowledge needed to reason about another system [27] the intentional descriptions of database objects [21], and the extent of validity for an ontology [28] For information retrieval, context provides a framework for well defined queries and consequently, it improves the matching process between a users query and the data stored in a database [22] Following the ideas of Naive Physics [29] and Naive ....

Kashyap, V. and A. Sheth, 1996, Schematic and Semantic Similarities between Database Objects: A Context-based Approach. Very Large Database Journal 5(4): 276304.

....assumes that the initial query contains enough information to find the relevant parts of the ontology. Then the IceBerg broker uses the different contexts related to that part of the ontology to help the user formulate a request corresponding to his needs. In the work of Kashyap and Sheth (e.g. Kashyap et al. 1995, Mena et al. 1999) the query has its own context which determines the semantics of the query and which is used directly to match with possible contexts of the different databases. In IceBerg, the interactive query formulation leeds to a query with a unique context as well. Although the role of ....

Kashyap, V., and Sheth, A. (1995), Schematic and Semantic Similarities between Database Objects: A Context based Approach, Technical Report TR-CS-95-001, LSDIS Lab, Department of Computer Science, University of Georgia.

....mediators [9] rules are mainly designed in order to reconcile structural heterogeneity. Discovering semantic heterogeneity problems and their reconciliation play a subordinate role. But for the reconciliation of the semantic heterogeneity problems, the semantical level also has to be considered [12, 7, 14]. Contexts are one possibility to describe the semantical level. A context [13] contains meta data 115 relating to its meaning, properties (such as its source, quality, and precision) and organization [17] A value has to be considered in its context and may be transformed into another ....

V. Kashyap and A. Sheth. Schematic and semantic similarities between database objects: A context-based approach. Number TR-CS-95-001, LSDIS Lab, Univ. of GA, 1995.

....name, grade) S . student(id, name, score) score grade(score, grade) score grade(4, A ) score grade(3, B ) score grade(2, C ) score grade(1, D ) score grade(0, F ) One important type of conflicts mentioned in literature in business applications is aggregation conflict (Kashyap Sheth 1996). Aggregation conflicts arise when an aggregation is used in one database to identify a set of entities in another database. To be able to define conversion rules for attributes involving aggregation conflicts, we can extend the traditional datalog to include aggregate functions. For example, ....

Kashyap, V. & Sheth, A. (1996), `Schematic and semantic similarities between database objects: A context-based approach', VLDB Journal 5(4).

....mediators, rules are mainly designed in order to reconcile structural heterogeneity. Discovering semantic heterogeneity problems and their reconciliation play a subordinate role. But for the reconciliation of the semantic heterogeneity problems, the semantical level also has to be considered [8, 5]. Contexts are one possibility to describe the semantical level. A context contains meta data relating to its meaning, properties (such as its source, quality, and precision) and organization [12] A value has to be considered in its context and may be transformed into another context ....

....specified meta attributes. In the example given in figure 4, the price currency conversion rule is applicable to all information containing the meta attribute currency and value dollar in their context in spite of the other meta attributes in the context of the template. 4 Kashyap and Sheth [8] even argue that every integration has to be considered with respect to a context. The other meta attributes in the context remain unchanged by the conversion. Other context rules affect other meta attributes. For example, another replacement rule can focus on the scaling factor in a context. In ....

V. Kashyap and A. Sheth. Schematic and semantic similarities between database objects: A contextbased approach. Number TR-CS-95-001, LSDIS Lab, Univ. of GA, 1995.

....unlikely that the sources SignificantEarthquakesDB and EarthquakesAfter3 990 will have exact same values for the attribute region. The value available from one source could be Nevada, USA and that from another source could be NV, USA . The two are semantically equal but syntactically unequal. [KS96] Another important advantage of using operations is that the system can support complex post processing of data. An interesting form of post processing is the use of simulation programs. These independent programs can be integrated with the system. For instance, researchers in the field of ....

V. Kashyap, A. Sheth. Schematic and Semantic Similarities between Database Objects: A Context-based Approach - in the VLDB Journal 5 (4).

....techniques which go beyond the structural and representational components of data and focus on the application of those techniques to structured databases. Different types of metadata may be stored in the system (e.g. indices, schema information) The Rufus [SLS 93] and the InfoHarness [SSKS95] systems use automatically generated metadata to access and retrieve heterogeneous information independent of type, representation and location. In Section 2, we discuss the different kinds of metadata and present an informal classification. We identify and propose domain specific metadata as the ....

.... Content based Content Classification Metadata [BR] MultiMedia Domain Specific Document Composition Metadata [BR] MultiMedia Domain Independent Metadata Templates [OM93] Media Independent Domain Specific Land Cover, Relief [SK96] Media Independent Domain Specific Parent Child Relationships [SSKS95] Text Domain Independent Contexts [SSR92, KS94a] Structured Databases Domain Specific Concepts from Cyc [CHS91] Structured Databases Domain Specific User s Data Attributes [SLS 93] Text, Structured Databases Domain Specific Domain Specific Ontologies [MKSI96] Media Independent Domain ....

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V. Kashyap and A. Sheth. Schematic and Semantic Similarities between Database Objects: A Context-based Approach. Technical Report TR-CS-95-001, LSDIS Lab, University of Georgia, January 1995. Available at http://lsdis.cs.uga.edu/~amit/66-contextalgebra. ps; An abridged version [KS96] appears in the VLDB Journal.

....is the specificity relationship. Given two contexts C 1 and C 2 , C 1 # C 2 if C 1 is at least as specific as C 2 . This is useful when objects defined in a particular context have to transcend [McC93] to a more specific or general context. This is discussed in detail with examples in [KS95b]. It is also the case that two contexts may not be comparable to each other, i.e. it may not be possible to decide whether one is more general than the other or not. Thus, the specificity relationship gives us a partial order. For every two contexts, we define the glb of two contexts as ....

....is then computed by conditioning the original student abstraction with respect to this new context. Since every abstraction mapping is associated with a context, the change in the abstraction as a result of the change in the associated context is called conditioning and is discussed in detail in [KS95b]. semPro(STUDENT, GRAD STUDENT) Entity Definition Incompatibility Database Identifier Conflicts Naming Conflicts Homonyms Synonyms Schema Isomorphism Conflicts Missing Data Item Conflicts (Semantic Resemblance) Semantic Incompatibility) Semantic Equivalence) Semantic Relationship) Semantic ....

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Kashyap V., Sheth A. (1995) Schematic and semantic similarities between database objects: a context-based approach. Technical Report TR-CS-95-001, LSDIS Lab, University of Georgia

....context has been recognized as a key component of semantics (and we view it as something that underpins the semantics of an object represented in the model world) it was not adequately addressed by the panel. There are many widely differing notions of contexts (e.g. for extended discussion, see Kashyap and Sheth (1995)) including one presented by Michael Siegel (Daruwala et al. 1995) as well as in the keynote by Foley as mentioned in Section 2. Navathe identified several modeling abstractions or mechanisms that can be used to represent semantics and pointed out the papers presented at this conference that ....

Kashyap, V. and Sheth, A. (1995) Schematic and Semantic Similarities between Database Objects: A Context-based Approach, Technical Report TR-CS-95-001, LSDIS Lab, Dept.

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V. Kashyap and A. Sheth. Schematic and semantic similarities between database objects: a context-based approach. The Very Large Database Journal, 5(4):276--304, 1996.

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Kashyap, V. and A. Sheth, 1996, Schematic and Semantic Similarities between Database Objects: A Context-based Approach. Very Large Database Journal 5(4): 276-304.

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