Strong functional dependencies and their application to normal forms in XML

Vincent, Millist W.; Liu, Jixue; Liu, Chengfei

doi:10.1145/1016028.1016029

Cited by 151 publications

(110 citation statements)

References 13 publications

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“…While Vincent et al extend the notion of Fds to XML data [132], Yu et als [140] present an approach for discovering redundancies based on identified XML Fd. There have also been adaptations of unique and key discovery concepts and algorithms to XML data [22].…”

Section: Xmlmentioning

confidence: 99%

Profiling relational data: a survey

Abedjan¹,

2015

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Profiling data to determine metadata about a given dataset is an important and frequent activity of any IT professional and researcher and is necessary for various use-cases. It encompasses a vast array of methods to examine datasets and produce metadata. Among the simpler results are statistics, such as the number of null values and distinct values in a column, its data type, or the most frequent patterns of its data values. Metadata that are more difficult to compute involve multiple columns, namely correlations, unique column combinations, functional dependencies, and inclusion dependencies. Further techniques detect conditional properties of the dataset at hand. This survey provides a classification of data profiling tasks and comprehensively reviews the state of the art for each class. In addition, we review data profiling tools and systems from research and industry. We conclude with an outlook on the future of data profiling beyond traditional profiling tasks and beyond relational databases.

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Section: Xmlmentioning

confidence: 99%

Profiling relational data: a survey

Abedjan¹,

2015

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“…However, without knowledge of the semantics hidden in XML data, it is not possible to retrieve correct XML structures. For example, Figure 9 shows invalid tuples (colored in blue) that connect irrelevant task and employee nodes (18,24) and (22,20). To resolve this problem, we need information of data semantics, such as each task belongs to a project and is assigned to an employee.…”

Section: Functional Dependenciesmentioning

confidence: 99%

Relational-style XML query

Saito

Morishita

2008

Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data

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We study the problem of querying relational data embedded in XML. Relational data can be represented by various tree structures in XML. However, current XML query methods, such as XPath and XQuery, demand explicit path expressions, and thus it is quite difficult for users to produce correct XML queries in the presence of structural variations.To solve this problem, we introduce a novel query method that automatically discovers various XML structures derived from relational data. A challenge in implementing our method is to reduce the cost of enumerating all possible tree structures that match the query. We show that the notion of functional dependencies has an important role in generating efficient query schedules that avoid irrelevant tree structures.Our proposed method, the relational-style XML query, has several advantages over traditional XML data management. These include removing the burden of designing strict tree-pattern schemas, enhancing the descriptions of relational data with XML's rich semantics, and taking advantage of schema evolution capability of XML. In addition, the independence of query statements from the underlying XML structure is advantageous for integrating XML data from several sources. We present extensive experimental results that confirm the scalability and tolerance of our query method for various sizes of XML data containing structural variations.

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“…If there was a widely accepted data model, with a set of defined operations it would be possible to show properties such as, whether data is lost during the transformations specified and it would also be possible to reason about what constraints are lost in the transformations. The kinds of formal definitions that we have seen to date in the normalization area include [7,5,8,6].…”

Section: Related Workmentioning

confidence: 99%

Research into Verifying Semistructured Data

Dobbie

Sun

et al. 2006

Distributed Computing and Internet Technology

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Abstract. Semistructured data is now widely used in both web applications and database systems. Much of the research into this area defines algorithms that transform the data and schema, such as data integration, change management, view definition, and data normalization. While some researchers have defined a formalism for the work they have undertaken, there is no widely accepted formalism that can be used for the comparison of algorithms within these areas. The requirements of a formalism that would be helpful in these situations are that it must capture all the necessary semantics required to model the algorithms, it should not be too complex and it should be easy to use. This paper describes a first step in defining such a formalism. We have modelled the semantics expressed in the ORA-SS (Object Relationship Attribute data model for SemiStructured data) data modelling notation in two formal languages that have automatic verification tools. We compare the two models and present the findings.

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Strong functional dependencies and their application to normal forms in XML

Cited by 151 publications

References 13 publications

Profiling relational data: a survey

Profiling relational data: a survey

Relational-style XML query

Research into Verifying Semistructured Data

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