Category Archives: data life cycle

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Open Science, Open Data, Open Source: 21st century research skills for life scientists

Open Science, Open Data, Open Source is published by colleagues in the EU.

Its introduction offers: 

The goal of this resource is to give a bird’s eye view of the developments in open scientific research. That is, we cover both social developments (e.g. the culture in various communities) as well as technological ones. As such, no part of the contents are especially in-depth or geared towards advanced users of specific practices or tools. Nevertheless, certain sections are more relevant to some people than to others.

Audiences include:

  • Graduate students 
  • Lab technicians 
  • Data scientists
  • Principal investigators 
  • Scientific publishers 
  • Science funders and policy makers 
  • Science communicators.

 


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Best Practice Data Life Cycle Approaches for the Life Sciences, now on F1000Research

Category : data life cycle , news

Following our very successful data life cycle workshops held in Melbourne in October 2016, the feedback, findings and further reflections are now published online at bioRxiv: http://www.biorxiv.org/content/early/2017/07/24/167619.

The paper has since been accepted for publication at F1000Research and open to peer review.

From the Abstract:

Throughout history, the life sciences have been revolutionised by technological advances; in our era this is manifested by advances in instrumentation for data generation, and consequently researchers now routinely handle large amounts of heterogeneous data in digital formats. The simultaneous transitions towards biology as a data science and towards a ‘life cycle’ view of research data pose new challenges. Researchers face a bewildering landscape of data management requirements, recommendations and regulations, without necessarily being able to access data management training or possessing a clear understanding of practical approaches that can assist in data management in their particular research domain. Here we provide an overview of best practice data life cycle approaches for researchers in the life sciences/bioinformatics space with a particular focus on ‘omics’ datasets and computer-based data processing and analysis. We discuss the different stages of the data life cycle and provide practical suggestions for useful tools and resources to improve data management practices.

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The paper was led by Pip Griffin and Vicky Schneider with a number of co-authors including our Key Area Coordinators Group and Activity Leads and workshop faculty (local and international) and participants.

Go here for further details about these workshops.


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EMBL-ABR: an interview with Kate LeMay

Category : data life cycle

Kate LeMay works at the Australian National Data Service as a Senior Research Data Specialist, focusing on health and medical data. She was in Melbourne last month to attend our EMBL-ABR workshops. We asked her about bioinformatics in general and the data life-cycle in particular. Her message is clear: using a framework like the data life cycle ensures that Australian bioinformaticians are keeping up with best practice standards being used and developed internationally.

Full interview.