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OntoGene web services for biomedical text mining.

Rinaldi F, Clematide S, Marques H, Ellendorff T, Romacker M, Rodriguez-Esteban R - BMC Bioinformatics (2014)

Bottom Line: Traditional architectures, based on monolithic applications, do not offer sufficient flexibility for a wide range of use case scenarios, and therefore open architectures, as provided by web services, are attracting increased interest.We present an approach towards providing advanced text mining capabilities through web services, using a recently proposed standard for textual data interchange (BioC).The web services leverage a state-of-the-art platform for text mining (OntoGene) which has been tested in several community-organized evaluation challenges,with top ranked results in several of them.

View Article: PubMed Central - HTML - PubMed

ABSTRACT
Text mining services are rapidly becoming a crucial component of various knowledge management pipelines, for example in the process of database curation, or for exploration and enrichment of biomedical data within the pharmaceutical industry. Traditional architectures, based on monolithic applications, do not offer sufficient flexibility for a wide range of use case scenarios, and therefore open architectures, as provided by web services, are attracting increased interest. We present an approach towards providing advanced text mining capabilities through web services, using a recently proposed standard for textual data interchange (BioC). The web services leverage a state-of-the-art platform for text mining (OntoGene) which has been tested in several community-organized evaluation challenges,with top ranked results in several of them.

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ODIN screenshot. Example of visualization of text mining results using the ODIN interface. The panel on the left shows the document with annotations, the panel on the right the corresponding concepts. The two panels are interconnected by the interface logic: whenever an item is selected in the concept panel, the corresponding terms are highlighted in the document panel.
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Figure 4: ODIN screenshot. Example of visualization of text mining results using the ODIN interface. The panel on the left shows the document with annotations, the panel on the right the corresponding concepts. The two panels are interconnected by the interface logic: whenever an item is selected in the concept panel, the corresponding terms are highlighted in the document panel.

Mentions: The user can choose to either inspect the results, using the ODIN web interface (see Figure 4), or to have them delivered back via the RESTful web services in BioC XML format, for further local processing (see Figure 2). The set of sentences, individually enumerated, contained within those papers can then be viewed through ODIN (OntoGene Document Inspector), a flexible browser-based client application which interfaces with the OntoGene server. The curator can then use the features provided by ODIN to visualize selected annotations, together with the statements from which they were derived, and, if necessary, add, remove or modify them. Once the curator has validated a set of candidate annotations, they can be exported, using a standard format (e.g. CSV, RDF), for further processing by other tools, or for inclusion in a reference database, after a suitable format conversion.


OntoGene web services for biomedical text mining.

Rinaldi F, Clematide S, Marques H, Ellendorff T, Romacker M, Rodriguez-Esteban R - BMC Bioinformatics (2014)

ODIN screenshot. Example of visualization of text mining results using the ODIN interface. The panel on the left shows the document with annotations, the panel on the right the corresponding concepts. The two panels are interconnected by the interface logic: whenever an item is selected in the concept panel, the corresponding terms are highlighted in the document panel.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4255746&req=5

Figure 4: ODIN screenshot. Example of visualization of text mining results using the ODIN interface. The panel on the left shows the document with annotations, the panel on the right the corresponding concepts. The two panels are interconnected by the interface logic: whenever an item is selected in the concept panel, the corresponding terms are highlighted in the document panel.
Mentions: The user can choose to either inspect the results, using the ODIN web interface (see Figure 4), or to have them delivered back via the RESTful web services in BioC XML format, for further local processing (see Figure 2). The set of sentences, individually enumerated, contained within those papers can then be viewed through ODIN (OntoGene Document Inspector), a flexible browser-based client application which interfaces with the OntoGene server. The curator can then use the features provided by ODIN to visualize selected annotations, together with the statements from which they were derived, and, if necessary, add, remove or modify them. Once the curator has validated a set of candidate annotations, they can be exported, using a standard format (e.g. CSV, RDF), for further processing by other tools, or for inclusion in a reference database, after a suitable format conversion.

Bottom Line: Traditional architectures, based on monolithic applications, do not offer sufficient flexibility for a wide range of use case scenarios, and therefore open architectures, as provided by web services, are attracting increased interest.We present an approach towards providing advanced text mining capabilities through web services, using a recently proposed standard for textual data interchange (BioC).The web services leverage a state-of-the-art platform for text mining (OntoGene) which has been tested in several community-organized evaluation challenges,with top ranked results in several of them.

View Article: PubMed Central - HTML - PubMed

ABSTRACT
Text mining services are rapidly becoming a crucial component of various knowledge management pipelines, for example in the process of database curation, or for exploration and enrichment of biomedical data within the pharmaceutical industry. Traditional architectures, based on monolithic applications, do not offer sufficient flexibility for a wide range of use case scenarios, and therefore open architectures, as provided by web services, are attracting increased interest. We present an approach towards providing advanced text mining capabilities through web services, using a recently proposed standard for textual data interchange (BioC). The web services leverage a state-of-the-art platform for text mining (OntoGene) which has been tested in several community-organized evaluation challenges,with top ranked results in several of them.

Show MeSH