A tool for data cube construction from structurally heterogeneous XML documents

Näppilä, Turkka; Järvelin, Kalervo; Niemi, Timo

doi:10.1002/asi.20756

Cited by 15 publications

(18 citation statements)

References 15 publications

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“…In [28], [35], and [36] it is shown that XQuery is not the most suitable query language for this purpose. This is because the effective use of path expressions necessitates fairly extensive advance knowledge of the structures and naming conventions in the underlying documents.…”

Section: Extraction Strategies For Xml Datamentioning

confidence: 99%

A relational data harmonization approach to XML

Niemi

Näppilä

Järvelin

2009

Journal of Information Science

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There are numerous approaches for integrating data from heterogeneous data sources. A common background assumption is that the data sources remain quite stable and are known in advance. Hence an integration system can be built to manipulate them. In practice there is, however, often a demand for supporting ad hoc information needs concerning unexpected autonomous data sources containing volatile data. A different approach is therefore needed. We propose that semantically similar data are harmonized when extracting data from XML-based data sources. We introduce a constructor algebra, which is a powerful tool in the harmonization of XML data. This algebra is able to form for any XML data source a unique relational representation, called an XML relation. We demonstrate that the XML relation representation supports grouping and aggregation of data needed, for example, in OLAP (online analytical processing) -style applications.

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Section: Extraction Strategies For Xml Datamentioning

confidence: 99%

A relational data harmonization approach to XML

Niemi

Näppilä

Järvelin

2009

Journal of Information Science

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“…In particular they propose SLCA [41] and MLCA [25] whose general intuition is that the LCA must be minimal. However, in [28,32] they showed that these approaches still produced undesired combinations between data items in some cases (e.g. when a data item needs to be combined with a data item at a lower level of the document hierarchy).…”

Section: Related Workmentioning

confidence: 99%

Building data warehouses with semantic web data

NebotVictoria

BerlangaRafael

2012

Decision Support Systems

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The Semantic Web (SW) deployment is now a realization and the amount of semantic annotations is ever increasing thanks to several initiatives that promote a change in the current Web towards the Web of Data, where the semantics of data become explicit through data representation formats and standards such as RDF/(S) and OWL. However, such initiatives have not yet been accompanied by efficient intelligent applications that can exploit the implicit semantics and thus, provide more insightful analysis. In this paper, we provide the means for efficiently analyzing and exploring large amounts of semantic data by combining the inference power from the annotation semantics with the analysis capabilities provided by OLAP-style aggregations, navigation, and reporting. We formally present how semantic data should be organized in a well-defined conceptual MD schema, so that sophisticated queries can be expressed and evaluated. Our proposal has been evaluated over a real biomedical scenario, which demonstrates the scalability and applicability of the proposed approach.

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“…This is due to the fact that the element product-set (row 2) is the ancestor for the two product elements (in rows 7 and 13) that have sub-elements whose labels match to the searched keywords and thus, based on the rule (2), the element product-set is excluded from the query result. Näppilä et al (2008) introduced the SPC semantics as an answer to the problems related to SLCA and MLCA semantics. Since it is problematic for these kinds of data extraction strategies to return the best LCA nodes or sub-trees rooted by them, the SPC semantics instead returns only the exact data related to the nodes corresponding to the searched keywords.…”

Section: Xml Data Extractionmentioning

confidence: 99%

A query language for selecting, harmonizing, and aggregating heterogeneous XML data

Näppilä

Moilanen

Niemi

2011

International Journal of Web Information Systems

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Purpose -The purpose of this paper is to introduce an expressive query language, called relational XML query language (RXQL), capable of dealing with heterogeneous Extensible Markup Language (XML) documents in data-centric applications. In RXQL, data harmonization (i.e. the removal of heterogeneous factors from XML data) is integrated with typical data-centric features (e.g. grouping, ordering, and aggregation). Design/methodology/approach -RXQL is based on the XML relation representation, developed in the authors' previous work. This is a novel approach to unambiguously represent semistructured data relationally, which makes it possible in RXQL to manipulate XML data in a tuple-oriented way, while XML data are typically manipulated in a path-oriented way. Findings -The user is able to describe the result of an RXQL query straightforwardly based on non-XML syntax. The analysis of this description, through the mechanism developed in this paper, affords the automatic construction of the query result. This feature increases significantly the declarativeness of RXQL compared to the path-oriented XML languages where the user needs to control the construction of the result extensively. Practical implications -The authors' formal specification of the construction of the query result can be considered as an abstract implementation of RXQL. Originality/value -RXQL is a declarative query language capable of integrating data harmonization seamlessly with other data-centric features in the manipulation of heterogeneous XML data. So far, these kinds of XML query languages have been missing. Obviously, the expressive power of RXQL can be achieved by computationally complete XML languages, such as XQuery. However, these are not actual query languages, and the query formulation in them usually presupposes programming skills that are beyond the ordinary end-user.

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A tool for data cube construction from structurally heterogeneous XML documents

Cited by 15 publications

References 15 publications

A relational data harmonization approach to XML

A relational data harmonization approach to XML

Building data warehouses with semantic web data

A query language for selecting, harmonizing, and aggregating heterogeneous XML data

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