Organization of biomedical data for collaborative scientific research: A research information management system

Biomedical researchers often work with massive, detailed and heterogeneous datasets. These datasets raise new challenges of information organization and management for scientific interpretation, as they demand much of the researchers' time and attention. The current study investigated the nature of the problems that researchers face when dealing with such data. Four major problems identified with existing biomedical scientific information management methods were related to data organization, data sharing, collaboration, and publications. Therefore, there is a compelling need to develop an efficient and user-friendly information management system to handle the biomedical research data. This study evaluated the implementation of an information management system, which was introduced as part of the collaborative research to increase scientific productivity in a research laboratory. Laboratory members seemed to exhibit frustration during the implementation process. However, empirical findings revealed that they gained new knowledge and completed specified tasks while working together with the new system. Hence, researchers are urged to persist and persevere when dealing with any new technology, including an information management system in a research laboratory environment.

[1]  D. Silverman.  Doing Qualitative Research , 2009 .

[2]  Nicola Cooley,et al.  MiMiR: a comprehensive solution for storage, annotation and exchange of microarray data , 2005, BMC Bioinformatics.

[3]  B. Crabtree,et al.  Doing Qualitative Research , 1999 .

[4]  Hao Li,et al.  Model Driven Laboratory Information Management Systems , 2006, AMIA.

[5]  Joan S. Ash,et al.  Viewpoint Paper: People and Organizational Issues in Research Systems Implementation , 2008, J. Am. Medical Informatics Assoc..

[6]  Edgars Celms,et al.  PASSIM – an open source software system for managing information in biomedical studies , 2007, BMC Bioinformatics.

[7]  Douglas L. Brutlag,et al.  Viewpoint: Directions for Clinical Research and Genomic Research into the Next Decade: Implications for Informatics , 1998, J. Am. Medical Informatics Assoc..

[8]  Yvonne Rogers,et al.  Beyond Interaction Design: Beyond Human-Computer Interaction , 2001 .

[9]  Carina Dennis,et al.  Biology databases: Information overload , 2002, Nature.

[10]  Hubert Hackl,et al.  MARS: Microarray analysis, retrieval, and storage system , 2005, BMC Bioinformatics.

[11]  Subbarao Kambhampati,et al.  Integration of biological sources: current systems and challenges ahead , 2004, SGMD.

[12]  Golan Yona,et al.  BIOZON: a system for unification, management and analysis of heterogeneous biological data , 2006, BMC Bioinformatics.

[13]  Lokman I. Meho.  E-mail interviewing in qualitative research: A methodological discussion: Research Articles , 2006 .

[14]  Edward H. Shortliffe,et al.  Medical data: their acquisition, storage, and use , 1990 .

[15]  Corbett S Klein.  LIMS user acceptance testing. , 2003, Quality assurance.

[16]  D. Roos,et al.  Bioinformatics--Trying to Swim in a Sea of Data , 2001, Science.

[17]  Yvonne Rogers,et al.  Interaction Design: Beyond Human-Computer Interaction , 2002 .

[18]  E Pennisi,et al.  The Human Genome , 2001, Science.

[19]  Walter V. Sujansky,et al.  Heterogeneous Database Integration in Biomedicine , 2001, J. Biomed. Informatics.

[20]  H. V. Jagadish,et al.  Biological Data Management: Research, Practice and Opportunities , 2004, VLDB.

[21]  A. Kuper,et al.  The Social Science Encyclopedia , 1986 .

[22]  Austin Henderson,et al.  Interaction design: beyond human-computer interaction , 2002, UBIQ.

[23]  Arnaud Droit,et al.  PARPs database: A LIMS systems for protein-protein interaction data mining or laboratory information management system , 2007, BMC Bioinformatics.

[24]  E. Unger,et al.  All is not well in the world of translational research. , 2007, Journal of the American College of Cardiology.

[25]  G. Sermonti.  The human genome. , 1988, Rivista di biologia.

[26]  Lokman I. Meho.  E-mail interviewing in qualitative research: A methodological discussion , 2006, J. Assoc. Inf. Sci. Technol..

[27]  H. Bernard.  Research methods in anthropology : qualitative and quantitative methods , 2002 .

[28]  Alon Y. Halevy,et al.  Data integration and genomic medicine , 2007, J. Biomed. Informatics.

[29]  James F. Brinkley,et al.  Issues in biomedical research data management and analysis: needs and barriers. , 2007, Journal of the American Medical Informatics Association : JAMIA.

[30]  Joachim Dudeck,et al.  Linking clinical data using XML topic maps , 2003, Artif. Intell. Medicine.

[31]  Pascale Carayon,et al.  Handbook of human factors and ergonomics in health care and patient safety , 2006 .

[32]  Elena Baralis,et al.  Exploring Heterogeneous Biological Data Sources , 2008, 2008 19th International Workshop on Database and Expert Systems Applications.

[33]  Vimla L. Patel,et al.  Patients' and physicians' understanding of health and biomedical concepts: relationship to the design of EMR systems , 2002, J. Biomed. Informatics.

[34]  Jakob Nielsen,et al.  Usability engineering , 1997, The Computer Science and Engineering Handbook.

[35]  James Lyons-Weiler,et al.  Standards of Excellence and Open Questions in Cancer Biomarker Research: An Informatics Perspective , 2005, Cancer informatics.

[36]  Peter Tarczy-Hornoch,et al.  qualitative study of the implementation of a ioinformatics tool in a biological research laboratory , 2007 .

[37]  Nir Friedman,et al.  Practical approaches to analyzing results of microarray experiments. , 2002, American journal of respiratory cell and molecular biology.

[38]  Pascale Carayon,et al.  New Technology Implementation in Health Care , 2006 .