Data integration gets 'Sloppy'

Almeida, Jonas S.; Chen, Chuming; Gorlitsky, Robert; Stanislaus, Romesh; Aires-de-Sousa, Marta; Eleutério, Pedro; Carriço, João André; Maretzek, António; Böhn, Andreas; Chang, Allen Y.; Zhang, Fan; Mitra, Rahul; Mills, Gordon B.; Wang, Xiaoshu; Deus, Helena F.

doi:10.1038/nbt0906-1070

Cited by 18 publications

(33 citation statements)

References 12 publications

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“…Consequently, the S3QL query represented above has a SPARQL equivalent: ?SampleCollectionCenter :R44596 ?Name ., which is formulated directly from the description of the S3DB Rule R44596 used in the predicate : [ SampleCollectionCenter hasName Name .]. Note that S3DB Rules are typically defined by the researchers producing the data through S3DB-associated interfaces and are not necessarily knowledgeable about Semantic Web technologies [29,32]. …”

Section: Resultsmentioning

confidence: 99%

“…Often some ‘eye-parsing’ of the data is required in order to formulate a query [26]. A key feature of the solution proposed here is the separation of the domain descriptors from their instantiation, provided by the assignment of data elements to the S3DB management model [28,29]. Asan illustration, a graphical RDF representation tool, Sentient Knowledge Explorer, was used to generate Fig.…”

Section: Discussionmentioning

confidence: 99%

“…An extreme example of rewiring an FTP directory would force only a small change in the automated assignment procedure; however, it would not affect query functionality. The description of S3DB Rules can also be freely edited, because the relationship between the domain descriptors and their data elements are established using alphanumeric identifiers rather than descriptive terms [29]. …”

Section: Discussionmentioning

confidence: 99%

“…TCGA experimental datasets were broken into their fundamental data elements and assigned to entities of the Simple Sloppy Semantic Database (S3DB) management model [28]. S3DB defines entities and relationships using an RDF schema (RDFS) core model that enables encapsulation of RDF triples as part of a domain description, also represented as RDF triples [29]. This solution allows both the data elements and the description of the domain to have a representation in RDF, thereby supporting SPARQL queries formulated using the domain descriptors while targeting the data elements.…”

Section: Introductionmentioning

confidence: 99%

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Exposing the cancer genome atlas as a SPARQL endpoint

Deus

Veiga

Freire

et al. 2010

Journal of Biomedical Informatics

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The Cancer Genome Atlas (TCGA) is a multidisciplinary, multi-institutional effort to characterize several types of cancer. Datasets from biomedical domains such as TCGA present a particularly challenging task for those interested in dynamically aggregating its results because the data sources are typically both heterogeneous and distributed. The Linked Data best practices offer a solution to integrate and discover data with those characteristics, namely through exposure of data as Web services supporting SPARQL, the Resource Description Framework query language. Most SPARQL endpoints, however, cannot easily be queried by data experts. Furthermore, exposing experimental data as SPARQL endpoints remains a challenging task because, in most cases, data must first be converted to Resource Description Framework triples. In line with those requirements, we have developed an infrastructure to expose clinical, demographic and molecular data elements generated by TCGA as a SPARQL endpoint by assigning elements to entities of the Simple Sloppy Semantic Database (S3DB) management model. All components of the infrastructure are available as independent Representational State Transfer (REST) Web services to encourage reusability, and a simple interface was developed to automatically assemble SPARQL queries by navigating a representation of the TCGA domain. A key feature of the proposed solution that greatly facilitates assembly of SPARQL queries is the distinction between the TCGA domain descriptors and data elements. Furthermore, the use of the S3DB management model as a mediator enables queries to both public and protected data without the need for prior submission to a single data source.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Exposing the cancer genome atlas as a SPARQL endpoint

Deus

Veiga

Freire

et al. 2010

Journal of Biomedical Informatics

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“…These concepts envision a datacentric approach with loosely standardised formats for information exchange, based on explicit data descriptions [64]. To achieve these goals, an ontology of terms in the field must be explicitly described.…”

Section: Bioinformatics For Molecular Epidemiology: the Way Forwardmentioning

confidence: 99%

Bioinformatics in bacterial molecular epidemiology and public health: databases, tools and the next-generation sequencing revolution

et al. 2013

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Advances in typing methodologies have been the driving force in the field of molecular epidemiology of pathogens. The development of molecular methodologies, and more recently of DNA sequencing methods to complement and improve phenotypic identification methods, was accompanied by the generation of large amounts of data and the need to develop ways of storing and analysing them. Simultaneously, advances in computing allowed the development of specialised algorithms for image analysis, data sharing and integration, and for mining the ever larger amounts of accumulated data. In this review, we will discuss how bioinformatics accompanied the changes in bacterial molecular epidemiology. We will discuss the benefits for public health of specialised online typing databases and algorithms allowing for real-time data analysis and visualisation. The impact of the new and disruptive next-generation sequencing methodologies will be evaluated, and we will look ahead into these novel challenges.

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