AGUIA: autonomous graphical user interface assembly for clinical trials semantic data services
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| Publicado en: | BMC Medical Informatics and Decision Making vol. 10 (2010), p. 65 |
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| Autor Principal: | |
| Outros autores: | , , , , , |
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Springer Nature B.V.
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| Acceso en liña: | Citation/Abstract Full Text Full Text - PDF |
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| 100 | 1 | |a Correa, Miria C | |
| 245 | 1 | |a AGUIA: autonomous graphical user interface assembly for clinical trials semantic data services | |
| 260 | |b Springer Nature B.V. |c 2010 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Abstract Background: AGUIA is a front-end web application originally developed to manage clinical, demographic and biomolecular patient data collected during clinical trials at MD Anderson Cancer Center. The diversity of methods involved in patient screening and sample processing generates a variety of data types that require a resource-oriented architecture to capture the associations between the heterogeneous data elements. AGUIA uses a semantic web formalism, resource description framework (RDF), and a bottom-up design of knowledge bases that employ the S3DB tool as the starting point for the client's interface assembly. Methods: The data web service, S3DB, meets the necessary requirements of generating the RDF and of explicitly distinguishing the description of the domain from its instantiation, while allowing for continuous editing of both. Furthermore, it uses an HTTP-REST protocol, has a SPARQL endpoint, and has open source availability in the public domain, which facilitates the development and dissemination of this application. However, S3DB alone does not address the issue of representing content in a form that makes sense for domain experts. Results: We identified an autonomous set of descriptors, the GBox, that provides user and domain specifications for the graphical user interface. This was achieved by identifying a formalism that makes use of an RDF schema to enable the automatic assembly of graphical user interfaces in a meaningful manner while using only resources native to the client web browser (JavaScript interpreter, document object model). We defined a generalized RDF model such that changes in the graphic descriptors are automatically and immediately (locally) reflected into the configuration of the client's interface application. Conclusions: The design patterns identified for the GBox benefit from and reflect the specific requirements of interacting with data generated by clinical trials, and they contain clues for a general purpose solution to the challenge of having interfaces automatically assembled for multiple and volatile views of a domain. By coding AGUIA in JavaScript, for which all browsers include a native interpreter, a solution was found that assembles interfaces that are meaningful to the particular user, and which are also ubiquitous and lightweight, allowing the computational load to be carried by the client's machine. AGUIA is a front-end web application originally developed to manage clinical, demographic and biomolecular patient data collected during clinical trials at MD Anderson Cancer Center. The diversity of methods involved in patient screening and sample processing generates a variety of data types that require a resource-oriented architecture to capture the associations between the heterogeneous data elements. AGUIA uses a semantic web formalism, resource description framework (RDF), and a bottom-up design of knowledge bases that employ the S3DB tool as the starting point for the client's interface assembly. The data web service, S3DB, meets the necessary requirements of generating the RDF and of explicitly distinguishing the description of the domain from its instantiation, while allowing for continuous editing of both. Furthermore, it uses an HTTP-REST protocol, has a SPARQL endpoint, and has open source availability in the public domain, which facilitates the development and dissemination of this application. However, S3DB alone does not address the issue of representing content in a form that makes sense for domain experts. We identified an autonomous set of descriptors, the GBox, that provides user and domain specifications for the graphical user interface. This was achieved by identifying a formalism that makes use of an RDF schema to enable the automatic assembly of graphical user interfaces in a meaningful manner while using only resources native to the client web browser (JavaScript interpreter, document object model). We defined a generalized RDF model such that changes in the graphic descriptors are automatically and immediately (locally) reflected into the configuration of the client's interface application. The design patterns identified for the GBox benefit from and reflect the specific requirements of interacting with data generated by clinical trials, and they contain clues for a general purpose solution to the challenge of having interfaces automatically assembled for multiple and volatile views of a domain. By coding AGUIA in JavaScript, for which all browsers include a native interpreter, a solution was found that assembles interfaces that are meaningful to the particular user, and which are also ubiquitous and lightweight, allowing the computational load to be carried by the client's machine. | |
| 610 | 4 | |a University of Texas University of Texas M D Anderson Cancer Center | |
| 650 | 1 | 2 | |a Clinical Trials as Topic |x statistics & numerical data |
| 650 | 1 | 2 | |a Computer Graphics |
| 650 | 2 | 2 | |a Databases, Factual |
| 650 | 2 | 2 | |a Humans |
| 650 | 2 | 2 | |a Information Storage & Retrieval |
| 650 | 1 | 2 | |a Internet |
| 650 | 2 | 2 | |a Natural Language Processing |
| 650 | 2 | 2 | |a Semantics |
| 650 | 2 | 2 | |a Software |
| 650 | 2 | 2 | |a Statistics as Topic |
| 650 | 2 | 2 | |a Systems Integration |
| 650 | 1 | 2 | |a User-Computer Interface |
| 651 | 4 | |a United States--US | |
| 651 | 4 | |a Brazil | |
| 651 | 4 | |a Rio de Janeiro Brazil | |
| 653 | |a Cancer | ||
| 653 | |a User interface | ||
| 653 | |a Interoperability | ||
| 653 | |a Bioinformatics | ||
| 653 | |a Ontology | ||
| 653 | |a Medical research | ||
| 653 | |a Clinical trials | ||
| 653 | |a Oncology | ||
| 653 | |a Semantic web | ||
| 653 | |a Automation | ||
| 653 | |a Resource Description Framework-RDF | ||
| 653 | |a Knowledge organization | ||
| 700 | 1 | |a Deus, Helena F | |
| 700 | 1 | |a Vasconcelos, Ana T | |
| 700 | 1 | |a Hayashi, Yuki | |
| 700 | 1 | |a Ajani, Jaffer A | |
| 700 | 1 | |a Patnana, Srikrishna V | |
| 700 | 1 | |a Almeida, Jonas S | |
| 773 | 0 | |t BMC Medical Informatics and Decision Making |g vol. 10 (2010), p. 65 | |
| 786 | 0 | |d ProQuest |t Healthcare Administration Database | |
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