Automatic detection and resolution of measurement-unit conflicts in aggregated data. Samadian, S., McManus, B., & Wilkinson, M. BMC Medical Genomics, 7(Suppl 1):S12, 2014. ![Automatic detection and resolution of measurement-unit conflicts in aggregated data [link]](https://bibbase.org/img/filetypes/link.svg "link")
Website doi abstract bibtex Motivation: Measurement-unit conflicts are a perennial problem in integrative research domains such as clinical meta-analysis. As multi-national collaborations grow, as new measurement instruments appear, and as Linked Open Data infrastructures become increasingly pervasive, the number of such conflicts will similarly increase. We propose a generic approach to the problem of (a) encoding measurement units in datasets in a machine-readable manner, (b) detecting when a dataset contained mixtures of measurement units, and (c) automatically converting any conflicting units into a desired unit, as defined for a given study. Results: We utilized existing ontologies and standards for scientific data representation, measurement unit definition, and data manipulation to build a simple and flexible Semantic Web Service-based approach to measurement-unit harmonization. A cardiovascular patient cohort in which clinical measurements were recorded in a number of different units (e.g., mmHg and cmHg for blood pressure) was automatically classified into a number of clinical phenotypes, semantically defined using different measurement units. Conclusion: We demonstrate that through a combination of semantic standards and frameworks, unit integration problems can be automatically detected and resolved.
@article{
title = {Automatic detection and resolution of measurement-unit conflicts in aggregated data},
type = {article},
year = {2014},
keywords = {Clinical Research,Measurement-units,Ontologies,Semantic Web Services},
pages = {S12},
volume = {7},
websites = {http://www.biomedcentral.com/1755-8794/7/S1/S12},
id = {d6595cdd-d461-3d5b-826b-b438ee9c39cd},
created = {2014-07-02T09:11:39.000Z},
accessed = {2014-05-08},
file_attached = {false},
profile_id = {17c87d5d-2470-32d7-b273-0734a1d9195f},
last_modified = {2017-03-22T07:45:59.566Z},
read = {false},
starred = {false},
authored = {true},
confirmed = {true},
hidden = {false},
citation_key = {Samadian},
private_publication = {false},
abstract = {Motivation: Measurement-unit conflicts are a perennial problem in integrative research domains such as clinical meta-analysis. As multi-national collaborations grow, as new measurement instruments appear, and as Linked Open Data infrastructures become increasingly pervasive, the number of such conflicts will similarly increase. We propose a generic approach to the problem of (a) encoding measurement units in datasets in a machine-readable manner, (b) detecting when a dataset contained mixtures of measurement units, and (c) automatically converting any conflicting units into a desired unit, as defined for a given study. Results: We utilized existing ontologies and standards for scientific data representation, measurement unit definition, and data manipulation to build a simple and flexible Semantic Web Service-based approach to measurement-unit harmonization. A cardiovascular patient cohort in which clinical measurements were recorded in a number of different units (e.g., mmHg and cmHg for blood pressure) was automatically classified into a number of clinical phenotypes, semantically defined using different measurement units. Conclusion: We demonstrate that through a combination of semantic standards and frameworks, unit integration problems can be automatically detected and resolved.},
bibtype = {article},
author = {Samadian, Soroush and McManus, Bruce and Wilkinson, Mark},
doi = {10.1186/1755-8794-7-S1-S12},
journal = {BMC Medical Genomics},
number = {Suppl 1}
}
Downloads: 0
{"_id":"YACHHPL4FbMdokAju","bibbaseid":"samadian-mcmanus-wilkinson-automaticdetectionandresolutionofmeasurementunitconflictsinaggregateddata-2014","downloads":0,"creationDate":"2018-01-15T08:18:50.413Z","title":"Automatic detection and resolution of measurement-unit conflicts in aggregated data","author_short":["Samadian, S.","McManus, B.","Wilkinson, M."],"year":2014,"bibtype":"article","biburl":"https://bibbase.org/service/mendeley/17c87d5d-2470-32d7-b273-0734a1d9195f","bibdata":{"title":"Automatic detection and resolution of measurement-unit conflicts in aggregated data","type":"article","year":"2014","keywords":"Clinical Research,Measurement-units,Ontologies,Semantic Web Services","pages":"S12","volume":"7","websites":"http://www.biomedcentral.com/1755-8794/7/S1/S12","id":"d6595cdd-d461-3d5b-826b-b438ee9c39cd","created":"2014-07-02T09:11:39.000Z","accessed":"2014-05-08","file_attached":false,"profile_id":"17c87d5d-2470-32d7-b273-0734a1d9195f","last_modified":"2017-03-22T07:45:59.566Z","read":false,"starred":false,"authored":"true","confirmed":"true","hidden":false,"citation_key":"Samadian","private_publication":false,"abstract":"Motivation: Measurement-unit conflicts are a perennial problem in integrative research domains such as clinical meta-analysis. As multi-national collaborations grow, as new measurement instruments appear, and as Linked Open Data infrastructures become increasingly pervasive, the number of such conflicts will similarly increase. We propose a generic approach to the problem of (a) encoding measurement units in datasets in a machine-readable manner, (b) detecting when a dataset contained mixtures of measurement units, and (c) automatically converting any conflicting units into a desired unit, as defined for a given study. Results: We utilized existing ontologies and standards for scientific data representation, measurement unit definition, and data manipulation to build a simple and flexible Semantic Web Service-based approach to measurement-unit harmonization. A cardiovascular patient cohort in which clinical measurements were recorded in a number of different units (e.g., mmHg and cmHg for blood pressure) was automatically classified into a number of clinical phenotypes, semantically defined using different measurement units. Conclusion: We demonstrate that through a combination of semantic standards and frameworks, unit integration problems can be automatically detected and resolved.","bibtype":"article","author":"Samadian, Soroush and McManus, Bruce and Wilkinson, Mark","doi":"10.1186/1755-8794-7-S1-S12","journal":"BMC Medical Genomics","number":"Suppl 1","bibtex":"@article{\n title = {Automatic detection and resolution of measurement-unit conflicts in aggregated data},\n type = {article},\n year = {2014},\n keywords = {Clinical Research,Measurement-units,Ontologies,Semantic Web Services},\n pages = {S12},\n volume = {7},\n websites = {http://www.biomedcentral.com/1755-8794/7/S1/S12},\n id = {d6595cdd-d461-3d5b-826b-b438ee9c39cd},\n created = {2014-07-02T09:11:39.000Z},\n accessed = {2014-05-08},\n file_attached = {false},\n profile_id = {17c87d5d-2470-32d7-b273-0734a1d9195f},\n last_modified = {2017-03-22T07:45:59.566Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {true},\n hidden = {false},\n citation_key = {Samadian},\n private_publication = {false},\n abstract = {Motivation: Measurement-unit conflicts are a perennial problem in integrative research domains such as clinical meta-analysis. As multi-national collaborations grow, as new measurement instruments appear, and as Linked Open Data infrastructures become increasingly pervasive, the number of such conflicts will similarly increase. We propose a generic approach to the problem of (a) encoding measurement units in datasets in a machine-readable manner, (b) detecting when a dataset contained mixtures of measurement units, and (c) automatically converting any conflicting units into a desired unit, as defined for a given study. Results: We utilized existing ontologies and standards for scientific data representation, measurement unit definition, and data manipulation to build a simple and flexible Semantic Web Service-based approach to measurement-unit harmonization. A cardiovascular patient cohort in which clinical measurements were recorded in a number of different units (e.g., mmHg and cmHg for blood pressure) was automatically classified into a number of clinical phenotypes, semantically defined using different measurement units. Conclusion: We demonstrate that through a combination of semantic standards and frameworks, unit integration problems can be automatically detected and resolved.},\n bibtype = {article},\n author = {Samadian, Soroush and McManus, Bruce and Wilkinson, Mark},\n doi = {10.1186/1755-8794-7-S1-S12},\n journal = {BMC Medical Genomics},\n number = {Suppl 1}\n}","author_short":["Samadian, S.","McManus, B.","Wilkinson, M."],"urls":{"Website":"http://www.biomedcentral.com/1755-8794/7/S1/S12"},"biburl":"https://bibbase.org/service/mendeley/17c87d5d-2470-32d7-b273-0734a1d9195f","bibbaseid":"samadian-mcmanus-wilkinson-automaticdetectionandresolutionofmeasurementunitconflictsinaggregateddata-2014","role":"author","keyword":["Clinical Research","Measurement-units","Ontologies","Semantic Web Services"],"metadata":{"authorlinks":{"wilkinson, m":"https://bibbase.org/service/mendeley/17c87d5d-2470-32d7-b273-0734a1d9195f"}},"downloads":0},"search_terms":["automatic","detection","resolution","measurement","unit","conflicts","aggregated","data","samadian","mcmanus","wilkinson"],"keywords":["clinical research","measurement-units","ontologies","semantic web services"],"authorIDs":["36ekkCAkZyyxuKaK4","3D2gJyDWo9oBKnSCp","3zcaogicCAqHPNnok","5a5c63eacb7e5d482c000023","5ded40109d5885de0100015c","5df7a7cbf3cb28df0100015a","5df7f4f8b9bb17df010000b9","5df8f68c277e45de0100017e","5dfb80e5c2820bdf01000127","5e05204a709177de0100007c","5e094022934cacdf0100009b","5e10d7b60192c6df010000e6","5e138dfda212e1de01000100","5e13ba3c280ddede01000044","5e166b79505a61df010008a8","5e18d20ba382e2de01000053","5e1c606fe556c6de010001b7","5e20532edf3867de0100010c","5e20c6d65c2065de010001cf","5e21c798af8ac1df0100001c","5e25953dd31494de0100016f","5e272a3f557b88de0100003e","5e281234f860fcde01000087","5e294dfc1470eddf010000b4","5e2c73a3ce5606de0100002d","5e3147538cf138de01000043","5e395116fa3db5df01000084","5e3aaf194518d5df01000139","5e3c7845feacaede0100000d","5e3d7c8296e576de01000071","5e4aa56015f6c7df01000018","5e4d641508a8e5de01000019","5e4ef29f338acfde01000064","5e553f95ca58a8df01000154","5e56516c6f0b61df01000064","5e56640e6f0b61df0100014f","5e59b537103b4fde01000036","5e5bcb64b57681df01000028","5e5d20e6168391de01000093","5e600cc113e3aede010001f2","5e618fad1d4ccede010000da","5e6222b82df238de01000101","5e66b4864b4a62de010000ea","5e67723c10be53de0100004b","6zAznqPzD5cqJbMMH","8abJywnFZcDu24ShP","9QLGMa73yQx5SHJxy","Bz9ccd9GKz9LhoC6Y","CgK7kn4dGJFGruaSM","CuyexYcxnkCNd3D4c","DadrcuWgdY84cCawp","FDc8hRmDr2qPXWkgL","FzAF3293AkCjvDfnT","GjsLZLwaMtB2eRYxy","HWbpM4xvWnDgaxhfW","JEcbfHjFzf49RmyTf","KiEfPgBp42PweWJ2X","MEspTDBJBjhrEya5h","SDCtrmyrMaghAhukd","SLpnx3c4EduLxA6oW","TkGxAPLygo9mfqNet","WLg4QvcCNNZrruNSd","WmohrPZayq5nBEMDZ","XXoxZ2skr7TR9KJKd","XzdwCmhzy8kZPntGL","Zwns6q8yR6MrKr5pY","a6NmgLfcCX6rNmf9q","aFTFFY2MNyAFdTAi2","arHEh6SMP2kQJkfn2","ctxLLCdynZRhc25W8","dFWbvT76ZMdew8Duf","dFmwiSphYj3Nxzjb4","ey7CdDbYue8dJCo5c","fTZznnFfMbPGdQiYH","of5vNXMxa2LQgmFSo","uvyDTMXpGSQJz2HQY"],"dataSources":["u3DebWvhQaEque62E","ya2CyA73rpZseyrZ8"]}