Cargando…

Life sciences domain analysis model

OBJECTIVE: Meaningful exchange of information is a fundamental challenge in collaborative biomedical research. To help address this, the authors developed the Life Sciences Domain Analysis Model (LS DAM), an information model that provides a framework for communication among domain experts and techn...

Descripción completa

Detalles Bibliográficos
Autores principales: Freimuth, Robert R, Freund, Elaine T, Schick, Lisa, Sharma, Mukesh K, Stafford, Grace A, Suzek, Baris E, Hernandez, Joyce, Hipp, Jason, Kelley, Jenny M, Rokicki, Konrad, Pan, Sue, Buckler, Andrew, Stokes, Todd H, Fernandez, Anna, Fore, Ian, Buetow, Kenneth H, Klemm, Juli D
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Group 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3486731/
https://www.ncbi.nlm.nih.gov/pubmed/22744959
http://dx.doi.org/10.1136/amiajnl-2011-000763
_version_ 1782248384970620928
author Freimuth, Robert R
Freund, Elaine T
Schick, Lisa
Sharma, Mukesh K
Stafford, Grace A
Suzek, Baris E
Hernandez, Joyce
Hipp, Jason
Kelley, Jenny M
Rokicki, Konrad
Pan, Sue
Buckler, Andrew
Stokes, Todd H
Fernandez, Anna
Fore, Ian
Buetow, Kenneth H
Klemm, Juli D
author_facet Freimuth, Robert R
Freund, Elaine T
Schick, Lisa
Sharma, Mukesh K
Stafford, Grace A
Suzek, Baris E
Hernandez, Joyce
Hipp, Jason
Kelley, Jenny M
Rokicki, Konrad
Pan, Sue
Buckler, Andrew
Stokes, Todd H
Fernandez, Anna
Fore, Ian
Buetow, Kenneth H
Klemm, Juli D
author_sort Freimuth, Robert R
collection PubMed
description OBJECTIVE: Meaningful exchange of information is a fundamental challenge in collaborative biomedical research. To help address this, the authors developed the Life Sciences Domain Analysis Model (LS DAM), an information model that provides a framework for communication among domain experts and technical teams developing information systems to support biomedical research. The LS DAM is harmonized with the Biomedical Research Integrated Domain Group (BRIDG) model of protocol-driven clinical research. Together, these models can facilitate data exchange for translational research. MATERIALS AND METHODS: The content of the LS DAM was driven by analysis of life sciences and translational research scenarios and the concepts in the model are derived from existing information models, reference models and data exchange formats. The model is represented in the Unified Modeling Language and uses ISO 21090 data types. RESULTS: The LS DAM v2.2.1 is comprised of 130 classes and covers several core areas including Experiment, Molecular Biology, Molecular Databases and Specimen. Nearly half of these classes originate from the BRIDG model, emphasizing the semantic harmonization between these models. Validation of the LS DAM against independently derived information models, research scenarios and reference databases supports its general applicability to represent life sciences research. DISCUSSION: The LS DAM provides unambiguous definitions for concepts required to describe life sciences research. The processes established to achieve consensus among domain experts will be applied in future iterations and may be broadly applicable to other standardization efforts. CONCLUSIONS: The LS DAM provides common semantics for life sciences research. Through harmonization with BRIDG, it promotes interoperability in translational science.
format Online
Article
Text
id pubmed-3486731
institution National Center for Biotechnology Information
language English
publishDate 2012
publisher BMJ Group
record_format MEDLINE/PubMed
spelling pubmed-34867312013-11-08 Life sciences domain analysis model Freimuth, Robert R Freund, Elaine T Schick, Lisa Sharma, Mukesh K Stafford, Grace A Suzek, Baris E Hernandez, Joyce Hipp, Jason Kelley, Jenny M Rokicki, Konrad Pan, Sue Buckler, Andrew Stokes, Todd H Fernandez, Anna Fore, Ian Buetow, Kenneth H Klemm, Juli D J Am Med Inform Assoc Research and Applications OBJECTIVE: Meaningful exchange of information is a fundamental challenge in collaborative biomedical research. To help address this, the authors developed the Life Sciences Domain Analysis Model (LS DAM), an information model that provides a framework for communication among domain experts and technical teams developing information systems to support biomedical research. The LS DAM is harmonized with the Biomedical Research Integrated Domain Group (BRIDG) model of protocol-driven clinical research. Together, these models can facilitate data exchange for translational research. MATERIALS AND METHODS: The content of the LS DAM was driven by analysis of life sciences and translational research scenarios and the concepts in the model are derived from existing information models, reference models and data exchange formats. The model is represented in the Unified Modeling Language and uses ISO 21090 data types. RESULTS: The LS DAM v2.2.1 is comprised of 130 classes and covers several core areas including Experiment, Molecular Biology, Molecular Databases and Specimen. Nearly half of these classes originate from the BRIDG model, emphasizing the semantic harmonization between these models. Validation of the LS DAM against independently derived information models, research scenarios and reference databases supports its general applicability to represent life sciences research. DISCUSSION: The LS DAM provides unambiguous definitions for concepts required to describe life sciences research. The processes established to achieve consensus among domain experts will be applied in future iterations and may be broadly applicable to other standardization efforts. CONCLUSIONS: The LS DAM provides common semantics for life sciences research. Through harmonization with BRIDG, it promotes interoperability in translational science. BMJ Group 2012 /pmc/articles/PMC3486731/ /pubmed/22744959 http://dx.doi.org/10.1136/amiajnl-2011-000763 Text en Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/3.0/ and http://creativecommons.org/licenses/by-nc/3.0/legalcode
spellingShingle Research and Applications
Freimuth, Robert R
Freund, Elaine T
Schick, Lisa
Sharma, Mukesh K
Stafford, Grace A
Suzek, Baris E
Hernandez, Joyce
Hipp, Jason
Kelley, Jenny M
Rokicki, Konrad
Pan, Sue
Buckler, Andrew
Stokes, Todd H
Fernandez, Anna
Fore, Ian
Buetow, Kenneth H
Klemm, Juli D
Life sciences domain analysis model
title Life sciences domain analysis model
title_full Life sciences domain analysis model
title_fullStr Life sciences domain analysis model
title_full_unstemmed Life sciences domain analysis model
title_short Life sciences domain analysis model
title_sort life sciences domain analysis model
topic Research and Applications
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3486731/
https://www.ncbi.nlm.nih.gov/pubmed/22744959
http://dx.doi.org/10.1136/amiajnl-2011-000763
work_keys_str_mv AT freimuthrobertr lifesciencesdomainanalysismodel
AT freundelainet lifesciencesdomainanalysismodel
AT schicklisa lifesciencesdomainanalysismodel
AT sharmamukeshk lifesciencesdomainanalysismodel
AT staffordgracea lifesciencesdomainanalysismodel
AT suzekbarise lifesciencesdomainanalysismodel
AT hernandezjoyce lifesciencesdomainanalysismodel
AT hippjason lifesciencesdomainanalysismodel
AT kelleyjennym lifesciencesdomainanalysismodel
AT rokickikonrad lifesciencesdomainanalysismodel
AT pansue lifesciencesdomainanalysismodel
AT bucklerandrew lifesciencesdomainanalysismodel
AT stokestoddh lifesciencesdomainanalysismodel
AT fernandezanna lifesciencesdomainanalysismodel
AT foreian lifesciencesdomainanalysismodel
AT buetowkennethh lifesciencesdomainanalysismodel
AT klemmjulid lifesciencesdomainanalysismodel