Literature DB >> 35800459

A System to Easily Manage Metadata in Biomedical Research Labs Based on Open-source Software.

Manuel A Castro-Alamancos1.   

Abstract

In most biomedical labs, researchers gather metadata (i.e., all details about the experimental data) in paper notebooks, spreadsheets, or, sometimes, electronic notebooks. When data analyses occur, the related details usually go into other notebooks or spreadsheets, and more metadata are available. The whole thing rapidly becomes very complex and disjointed, and keeping track of all these things can be daunting. Organizing all the relevant data and related metadata for analysis, publication, sharing, or deposit into archives can be time-consuming, difficult, and prone to errors. By having metadata in a centralized system that contains all details from the start, the process is greatly simplified. While lab management software is available, it can be costly and inflexible. The system described here is based on a popular, freely available, and open-source wiki platform. It provides a simple but powerful way for biomedical research labs to set up a metadata management system linking the whole research process. The system enhances efficiency, transparency, reliability, and rigor, which are key factors to improving reproducibility. The flexibility afforded by the system simplifies implementation of specialized lab requirements and future needs. The protocol presented here describes how to create the system from scratch, how to use it for gathering basic metadata, and provides a fully functional version for perusal by the reader. Graphical abstract: Lab Metadata Management System.
Copyright © 2022 The Authors; exclusive licensee Bio-protocol LLC.

Entities:  

Keywords:  Data; Database; Lab management; Metadata; Reproducibility; Rigor

Year:  2022        PMID: 35800459      PMCID: PMC9090580          DOI: 10.21769/BioProtoc.4404

Source DB:  PubMed          Journal:  Bio Protoc        ISSN: 2331-8325


  3 in total

1.  Rigor and reproducibility in rodent behavioral research.

Authors:  Maria Gulinello; Heather A Mitchell; Qiang Chang; W Timothy O'Brien; Zhaolan Zhou; Ted Abel; Li Wang; Joshua G Corbin; Surabi Veeraragavan; Rodney C Samaco; Nick A Andrews; Michela Fagiolini; Toby B Cole; Thomas M Burbacher; Jacqueline N Crawley
Journal:  Neurobiol Learn Mem       Date:  2018-01-04       Impact factor: 2.877

Review 2.  RRIDs: A Simple Step toward Improving Reproducibility through Rigor and Transparency of Experimental Methods.

Authors:  Anita E Bandrowski; Maryann E Martone
Journal:  Neuron       Date:  2016-05-04       Impact factor: 17.173

3.  A call for transparent reporting to optimize the predictive value of preclinical research.

Authors:  Story C Landis; Susan G Amara; Khusru Asadullah; Chris P Austin; Robi Blumenstein; Eileen W Bradley; Ronald G Crystal; Robert B Darnell; Robert J Ferrante; Howard Fillit; Robert Finkelstein; Marc Fisher; Howard E Gendelman; Robert M Golub; John L Goudreau; Robert A Gross; Amelie K Gubitz; Sharon E Hesterlee; David W Howells; John Huguenard; Katrina Kelner; Walter Koroshetz; Dimitri Krainc; Stanley E Lazic; Michael S Levine; Malcolm R Macleod; John M McCall; Richard T Moxley; Kalyani Narasimhan; Linda J Noble; Steve Perrin; John D Porter; Oswald Steward; Ellis Unger; Ursula Utz; Shai D Silberberg
Journal:  Nature       Date:  2012-10-11       Impact factor: 49.962

  3 in total

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