Social support for collaboration and group awareness in life science research teams

Vittorio Scarano,Ilaria Manno,Luigi Serra,Alberto Negro,Delfina Malandrino,Concita Cantarella,Andrea Petta

doi:10.1186/s13029-019-0074-4

Abstract

BackgroundNext-generation sequencing (NGS) technologies have revolutionarily reshaped the landscape of ’-omics’ research areas. They produce a plethora of information requiring specific knowledge in sample preparation, analysis and characterization. Additionally, expertise and competencies are required when using bioinformatics tools and methods for efficient analysis, interpretation, and visualization of data. These skills are rarely covered in a single laboratory. More often the samples are isolated and purified in a first laboratory, sequencing is performed by a private company or a specialized lab, while the produced data are analyzed by a third group of researchers. In this scenario, the support, the communication, and the information sharing among researchers represent the key points to build a common knowledge and to meet the project objectives.ResultsWe present ElGalaxy, a system designed and developed to support collaboration and information sharing among researchers. Specifically, we integrated collaborative functionalities within an application usually adopted by Life Science researchers. ElGalaxy, therefore, is the result of the integration of Galaxy, i.e., a Workflow Management System, with Elgg, i.e., a Social Network Engine.ConclusionsElGalaxy enables scientists, that work on the same experiment, to collaborate and share information, to discuss about methods, and to evaluate results of the individual steps, as well as of entire activities, performed during their experiments. ElGalaxy also allows a greater team awareness, especially when experiments are carried out with researchers which belong to different and distributed research centers.

Highlights

Next-generation sequencing (NGS) technologies have revolutionarily reshaped the landscape of ’-omics’ research areas
The plethora of information that emerges from large-scale next-generation sequencing experiments
With regard to the size of researchers teams, as shown in Fig. 1b, more than a quarter of the labs (28%) has less than 5 people working there; more than half of the labs (53%) has between 5 and 10 people working there, while 19% has more than 10 people working there (6% has 10-20 people, 13% has more than 20 people)

Summary

Introduction

Next-generation sequencing (NGS) technologies have revolutionarily reshaped the landscape of ’-omics’ research areas They produce a plethora of information requiring specific knowledge in sample preparation, analysis and characterization. More often the samples are isolated and purified in a first laboratory, sequencing is performed by a private company or a specialized lab, while the produced data are analyzed by a third group of researchers In this scenario, the support, the communication, and the information sharing among researchers represent the key points to build a common knowledge and to meet the project objectives. The plethora of information that emerges from large-scale next-generation sequencing experiments In this scenario, supporting and enabling communication and information sharing among researchers is a key point to build a common knowledge and to reach the Malandrino et al Source Code for Biology and Medicine (2019) 14:4 project objective. CSCW aims to improve group awareness by providing a clear understanding of the current state of the project and of the required and expected steps that have to be performed at a later stage [2]

Objectives

Methods

Results