TY - JOUR
T1 - The center for expanded data annotation and retrieval
AU - Musen, Mark A.
AU - Bean, Carol A.
AU - Cheung, Kei-Hoi
AU - Dumontier, Michel
AU - Durante, Kim A.
AU - Gevaert, Olivier
AU - Gonzalez-Beltran, Alejandra
AU - Khatri, Purvesh
AU - Kleinstein, Steven H.
AU - O'Connor, Martin J.
AU - Pouliot, Yannick
AU - Rocca-Serra, Philippe
AU - Sansone, Susanna-Assunta
AU - Wiser, Jeffrey A.
PY - 2015/11
Y1 - 2015/11
N2 - The Center for Expanded Data Annotation and Retrieval is studying the creation of comprehensive and expressive metadata for biomedical datasets to facilitate data discovery, data interpretation, and data reuse. We take advantage of emerging community-based standard templates for describing different kinds of biomedical datasets, and we investigate the use of computational techniques to help investigators to assemble templates and to fill in their values. We are creating a repository of metadata from which we plan to identify metadata patterns that will drive predictive data entry when filling in metadata templates. The metadata repository not only will capture annotations specified when experimental datasets are initially created, but also will incorporate links to the published literature, including secondary analyses and possible refinements or retractions of experimental interpretations. By working initially with the Human Immunology Project Consortium and the developers of the ImmPort data repository, we are developing and evaluating an end-to-end solution to the problems of metadata authoring and management that will generalize to other data-management environments. ? The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: [email protected].
AB - The Center for Expanded Data Annotation and Retrieval is studying the creation of comprehensive and expressive metadata for biomedical datasets to facilitate data discovery, data interpretation, and data reuse. We take advantage of emerging community-based standard templates for describing different kinds of biomedical datasets, and we investigate the use of computational techniques to help investigators to assemble templates and to fill in their values. We are creating a repository of metadata from which we plan to identify metadata patterns that will drive predictive data entry when filling in metadata templates. The metadata repository not only will capture annotations specified when experimental datasets are initially created, but also will incorporate links to the published literature, including secondary analyses and possible refinements or retractions of experimental interpretations. By working initially with the Human Immunology Project Consortium and the developers of the ImmPort data repository, we are developing and evaluating an end-to-end solution to the problems of metadata authoring and management that will generalize to other data-management environments. ? The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: [email protected].
KW - datasets as topic
KW - data curation
KW - data collection
KW - standards
KW - biological ontologies
U2 - 10.1093/jamia/ocv048
DO - 10.1093/jamia/ocv048
M3 - Article
C2 - 26112029
SN - 1067-5027
VL - 22
SP - 1148
EP - 1152
JO - Journal of the American Medical Informatics Association
JF - Journal of the American Medical Informatics Association
IS - 6
ER -