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

Abstract

Background: 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. 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.

Results: We 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.

Conclusions: ElGalaxy 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.

Keywords: Life science teams collaboration; Social interactions; Working group awareness.

Fig. 1

Online Survey results. a Users’ origin countries breakdown. b Size of teams: a wide majority has less than 10 people. c The Model of work phases for biological experiments that we defined and proposed to users. d Users’ agreement about the proposed model of work phases. e Team composition: small labs have the same people in all the steps, larger labs have different people in different steps. f The majority of labs has different people involved in different steps, with eventually one person in charge of supervise all the steps. g Information sharing happens mostly in periodical meetings and small talks in the aisle. h Information sharing tools: the majority of people collects his/her information, and eventually share it in common folders (public or private)

Fig. 2

ElGalaxy functionalities. a Organization of users in Elgg, each user can be member of more than one group. b In Galaxy, a user can share a workflow with one of the groups to which he/she belongs to. c In Elgg, each team member can visualize and comment live and active versions of shared workflows. d In Elgg, each team member can visualize and comment the histories associated with the execution of shared workflows. e Users can share useful documents with other team members. f Page of Groups Activities

Fig. 3

ElGalaxy architecture. Integration of Galaxy and Elgg into ElGalaxy: components and interactions