Life sciences domain analysis model

Robert Freimuth, Elaine T. Freund, Lisa Schick, Mukesh K. Sharma, Grace A. Stafford, Baris E. Suzek, Joyce Hernandez, Jason Hipp, Jenny M. Kelley, Konrad Rokicki, Sue Pan, Andrew Buckler, Todd H. Stokes, Anna Fernandez, Ian Fore, Kenneth H. Buetow, Juli D. Klemm

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
Pages (from-to)1095-1102
Number of pages8
JournalJournal of the American Medical Informatics Association
Volume19
Issue number6
DOIs
StatePublished - Nov 2012

Fingerprint

Biological Science Disciplines
Biomedical Research
Translational Medical Research
Research
Semantics
Chemical Databases
Clinical Protocols
Information Systems
Molecular Biology
Consensus
Language
Communication
Databases

ASJC Scopus subject areas

  • Health Informatics

Cite this

Freimuth, R., Freund, E. T., Schick, L., Sharma, M. K., Stafford, G. A., Suzek, B. E., ... Klemm, J. D. (2012). Life sciences domain analysis model. Journal of the American Medical Informatics Association, 19(6), 1095-1102. https://doi.org/10.1136/amiajnl-2011-000763

Life sciences domain analysis model. / Freimuth, Robert; 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.

In: Journal of the American Medical Informatics Association, Vol. 19, No. 6, 11.2012, p. 1095-1102.

Research output: Contribution to journalArticle

Freimuth, R, Freund, ET, Schick, L, Sharma, MK, Stafford, GA, Suzek, BE, Hernandez, J, Hipp, J, Kelley, JM, Rokicki, K, Pan, S, Buckler, A, Stokes, TH, Fernandez, A, Fore, I, Buetow, KH & Klemm, JD 2012, 'Life sciences domain analysis model', Journal of the American Medical Informatics Association, vol. 19, no. 6, pp. 1095-1102. https://doi.org/10.1136/amiajnl-2011-000763
Freimuth, Robert ; 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. In: Journal of the American Medical Informatics Association. 2012 ; Vol. 19, No. 6. pp. 1095-1102.
@article{d1afe7dd3929494d9e1af86e8de69db8,
title = "Life sciences domain analysis model",
abstract = "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.",
author = "Robert Freimuth and Freund, {Elaine T.} and Lisa Schick and Sharma, {Mukesh K.} and Stafford, {Grace A.} and Suzek, {Baris E.} and Joyce Hernandez and Jason Hipp and Kelley, {Jenny M.} and Konrad Rokicki and Sue Pan and Andrew Buckler and Stokes, {Todd H.} and Anna Fernandez and Ian Fore and Buetow, {Kenneth H.} and Klemm, {Juli D.}",
year = "2012",
month = "11",
doi = "10.1136/amiajnl-2011-000763",
language = "English (US)",
volume = "19",
pages = "1095--1102",
journal = "Journal of the American Medical Informatics Association : JAMIA",
issn = "1067-5027",
publisher = "Oxford University Press",
number = "6",

}

TY - JOUR

T1 - Life sciences domain analysis model

AU - Freimuth, Robert

AU - Freund, Elaine T.

AU - Schick, Lisa

AU - Sharma, Mukesh K.

AU - Stafford, Grace A.

AU - Suzek, Baris E.

AU - Hernandez, Joyce

AU - Hipp, Jason

AU - Kelley, Jenny M.

AU - Rokicki, Konrad

AU - Pan, Sue

AU - Buckler, Andrew

AU - Stokes, Todd H.

AU - Fernandez, Anna

AU - Fore, Ian

AU - Buetow, Kenneth H.

AU - Klemm, Juli D.

PY - 2012/11

Y1 - 2012/11

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84867664499&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84867664499&partnerID=8YFLogxK

U2 - 10.1136/amiajnl-2011-000763

DO - 10.1136/amiajnl-2011-000763

M3 - Article

VL - 19

SP - 1095

EP - 1102

JO - Journal of the American Medical Informatics Association : JAMIA

JF - Journal of the American Medical Informatics Association : JAMIA

SN - 1067-5027

IS - 6

ER -