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Implementation and use of cloud-based electronic lab notebook in a bioprocess engineering teaching laboratory
BACKGROUND: Electronic lab notebooks (ELNs) are better equipped than paper lab notebooks (PLNs) to handle present-day life science and engineering experiments that generate large data sets and require high levels of data integrity. But limited training and a lack of workforce with ELN knowledge have...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5701295/ https://www.ncbi.nlm.nih.gov/pubmed/29201138 http://dx.doi.org/10.1186/s13036-017-0083-2 |
Sumario: | BACKGROUND: Electronic lab notebooks (ELNs) are better equipped than paper lab notebooks (PLNs) to handle present-day life science and engineering experiments that generate large data sets and require high levels of data integrity. But limited training and a lack of workforce with ELN knowledge have restricted the use of ELN in academic and industry research laboratories which still rely on cumbersome PLNs for recordkeeping. We used LabArchives, a cloud-based ELN in our bioprocess engineering lab course to train students in electronic record keeping, good documentation practices (GDPs), and data integrity. RESULTS: Implementation of ELN in the bioprocess engineering lab course, an analysis of user experiences, and our development actions to improve ELN training are presented here. ELN improved pedagogy and learning outcomes of the lab course through stream lined workflow, quick data recording and archiving, and enhanced data sharing and collaboration. It also enabled superior data integrity, simplified information exchange, and allowed real-time and remote monitoring of experiments. Several attributes related to positive user experiences of ELN improved between the two subsequent years in which ELN was offered. Student responses also indicate that ELN is better than PLN for compliance. CONCLUSIONS: We demonstrated that ELN can be successfully implemented in a lab course with significant benefits to pedagogy, GDP training, and data integrity. The methods and processes presented here for ELN implementation can be adapted to many types of laboratory experiments. |
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