XML-Based Approaches for the Integration of Heterogeneous Bio-Molecular Data

Mesiti, Marco; Jiménez-Ruiz, Elena; Sanz, Ismael; Berlanga, Rafael; Valentini, Giorgio; Perlasca, Paolo; Manset, David

doi:10.1201/b13131-13

Cited by 2 publications

(2 citation statements)

References 90 publications

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“…However, in this paper we adopt a different integration architecture (see right hand side of Figure 1), which follows the current trends in biomedical [13] and bioinformatics data integration [27], and relies entirely on SW technology. In this architecture, the integrated data model is defined as an application ontology that models the health care scenario (e.g.…”

Section: Application Scenariomentioning

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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Section: Application Scenariomentioning

confidence: 99%

Building data warehouses with semantic web data

NebotVictoria

BerlangaRafael

2012

Decision Support Systems

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“…First of all, the existing data sources are very heterogeneous, in some cases as a consequence of a lack of standards for structure and content (Mesiti et al, 2009) and in other cases because the community does not use the available standards. The integration of biomedical data among resources distributed over the web is a major challenge.…”

Section: Introductionmentioning

confidence: 99%

A semantic approach for the requirement-driven discovery of web resources in the Life Sciences

et al. 2012

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Abstract. Research in the Life Sciences depends on the integration of large, distributed and heterogeneous web resources (e.g. data sources and web services). The discovery of which of these resources are the most appropriate to solve a given task is a complex research question, since there are many candidate resources and there is little, mostly unstructured, metadata to be able to decide among them.In this paper we contribute with a semi-automatic approach, based on semantic techniques, to assist researchers in the discovery of the most appropriate web resources to fulfill a set of requirements. The main feature of our approach is that it exploits broad knowledge resources in order to annotate the unstructured texts that are available in the emerging web-based repositories of web resource metadata.The results show that the web resource discovery process benefits from a semanticbased approach in several important aspects. One of the advantages is that the user can express her requirements in natural language avoiding the use of specific vocabularies or query languages. Moreover, the discovery exploits not only the categories or tags of web resources, but also their description and documentation.

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XML-Based Approaches for the Integration of Heterogeneous Bio-Molecular Data

Abstract: Background: The today's public database infrastructure spans a very large collection of heterogeneous biological data, opening new opportunities for molecular biology, bio-medical and bioinformatics research, but raising also new problems for their integration and computational processing.

Cited by 2 publications

References 90 publications

Building data warehouses with semantic web data

Building data warehouses with semantic web data

A semantic approach for the requirement-driven discovery of web resources in the Life Sciences

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