TY - JOUR
T1 - Resolving complex research data management issues in biomedical laboratories
T2 - Qualitative study of an industry-academia collaboration
AU - Myneni, Sahiti
AU - Patel, Vimla L.
AU - Bova, G. Steven
AU - Wang, Jian
AU - Ackerman, Christopher F.
AU - Berlinicke, Cynthia A.
AU - Chen, Steve H.
AU - Lindvall, Mikael
AU - Zack, Donald J.
N1 - Funding Information:
The study was supported in part by a grant (1R41CA105217-01A1-STTR) from National Institute of Health/National Cancer Institute (NIH/NCI). Support was also provided by generous gifts from the Guerrieri Family Foundation and from Mr. and Mrs. Clarice Smith. We thank all study participants for their valuable time and contributions.
Funding Information:
The study was supported in part by a grant ( 1R41CA105217-01A1-STTR ) from National Institute of Health/National Cancer Institute (NIH/NCI) . Support was also provided by generous gifts from the Guerrieri Family Foundation and from Mr. and Mrs. Clarice Smith. We thank all study participants for their valuable time and contributions.
Publisher Copyright:
© 2015 Elsevier Ireland Ltd.
PY - 2016/4/1
Y1 - 2016/4/1
N2 - This paper describes a distributed collaborative effort between industry and academia to systematize data management in an academic biomedical laboratory. Heterogeneous and voluminous nature of research data created in biomedical laboratories make information management difficult and research unproductive. One such collaborative effort was evaluated over a period of four years using data collection methods including ethnographic observations, semi-structured interviews, web-based surveys, progress reports, conference call summaries, and face-to-face group discussions. Data were analyzed using qualitative methods of data analysis to (1) characterize specific problems faced by biomedical researchers with traditional information management practices, (2) identify intervention areas to introduce a new research information management system called Labmatrix, and finally to (3) evaluate and delineate important general collaboration (intervention) characteristics that can optimize outcomes of an implementation process in biomedical laboratories. Results emphasize the importance of end user perseverance, human-centric interoperability evaluation, and demonstration of return on investment of effort and time of laboratory members and industry personnel for success of implementation process. In addition, there is an intrinsic learning component associated with the implementation process of an information management system. Technology transfer experience in a complex environment such as the biomedical laboratory can be eased with use of information systems that support human and cognitive interoperability. Such informatics features can also contribute to successful collaboration and hopefully to scientific productivity.
AB - This paper describes a distributed collaborative effort between industry and academia to systematize data management in an academic biomedical laboratory. Heterogeneous and voluminous nature of research data created in biomedical laboratories make information management difficult and research unproductive. One such collaborative effort was evaluated over a period of four years using data collection methods including ethnographic observations, semi-structured interviews, web-based surveys, progress reports, conference call summaries, and face-to-face group discussions. Data were analyzed using qualitative methods of data analysis to (1) characterize specific problems faced by biomedical researchers with traditional information management practices, (2) identify intervention areas to introduce a new research information management system called Labmatrix, and finally to (3) evaluate and delineate important general collaboration (intervention) characteristics that can optimize outcomes of an implementation process in biomedical laboratories. Results emphasize the importance of end user perseverance, human-centric interoperability evaluation, and demonstration of return on investment of effort and time of laboratory members and industry personnel for success of implementation process. In addition, there is an intrinsic learning component associated with the implementation process of an information management system. Technology transfer experience in a complex environment such as the biomedical laboratory can be eased with use of information systems that support human and cognitive interoperability. Such informatics features can also contribute to successful collaboration and hopefully to scientific productivity.
KW - Biomedical laboratory
KW - Cognition
KW - Industry-academia collaboration
KW - Informatics implementation
KW - Information management
KW - Virtual research environment
U2 - 10.1016/j.cmpb.2015.11.001
DO - 10.1016/j.cmpb.2015.11.001
M3 - Article
C2 - 26652980
AN - SCOPUS:84960130810
SN - 0169-2607
VL - 126
SP - 160
EP - 170
JO - Computer Methods and Programs in Biomedicine
JF - Computer Methods and Programs in Biomedicine
ER -