Data Management Plan

15 March 2018

Ioannis Xenarios

Dr Grégoire Rossier, SIB, Lausanne
Corinne Dentan, UNIL, Lausanne

Dr Cécile Lebrand, Open Science advocate and information specialist Bibliothèque Universitaire de Médecine, CHUV
Dr Anastasia Chasapi, Computational Biologist Vital-IT Competence Center, SIB Swiss Institute of Bioinformatics

Managing and sharing research data as openly as possible is one of the principles of good scientific practice. The aim of a Data Management Plan (DMP) is to plan the life cycle of data. It offers a long-term perspective by outlining how data will be generated, collected, documented, shared and preserved. The SNSF agrees with this principle and will introduce new requirements in its project funding scheme as of October 2017. Researchers will have to include a data management plan (DMP) in their funding application. The SNSF expects that researchers share at least the data underlying their publications, but only to the extent to make the published results reproducible. This course will provide the keys to everyone to be able to integrate a DMP in their funding application.

University of Lausanne, Génopode building, classroom 2020 (Metro M1 line, UNIL-Sorge station)

Map

Overview

Recent studies have shown that worldwide, between 51% and 89% of published life sciences research is not reproducible, with consequent losses estimated at around $100 billions/year in biomedical research (Chalmers et al., 2009; Freedman et al., 2015; Begley and Ioannidis, 2015). In particular, these studies have made clear that the research data associated with a publication are fundamental to validate the published analyses and results. Many causes contribute to this lack of reproducibility in life science studies such as a lack of rigor in data management and analysis. This extensive problem related to improper research management has urged scientists to consider developing efficient Data Management Plans (DMP) for their research projects, a need that is also reflected in the requirements of funding agencies, amongst which the Swiss National Fund (SNF) and Horizon 2020.

During the first part of this workshop, researchers and professionals involved in Big Data management at VitalIT/SIB as well as in Data Management Plan preparation at UNIL/CHUV will teach you best practices in data management and how to collect, describe, store, secure and archive research data. You will be introduced to the need for a Data Management Plan (DMP) preparation, an evolving document reporting how the research data will be managed during and after a research project.

The second half of the workshop will be dedicated to a practical session on Data management, where you will learn how to fill a DMP corresponding to your own research project. You will be initiated in version control systems, data deposit, Open Access issues, metadata standards for datasets, file formats for long term datasets storage and re-use, data copyright, licenses and self-archiving rules.

This workshop will provide you with effective support to produce high quality DMP complying with the guidelines established by funding agencies. Importantly, it will provide you with tools to generate robust data and excellent quality studies that are reproducible and reusable.

Sources of information

• Begley, C G, and Ioannidis, J. PA. "Reproducibility in science improving the standard for basic and preclinical research." Circulation research. 2015; 116.1: 116-126.
• Chalmers I, Glasziou P. Avoidable Waste in the Production and Reporting of Research Evidence. Lancet. 2009; 374(9683): 86–89.
• Freedman LP, Cockburn IM, Simcoe TS. The Economics of Reproducibility in Preclinical Research. PLoS Biol. 2015;13(6): e1002165.

Learning objectives

At the end of the course you should be able to put in place a DMP (data management plan), making it possible to:

• fulfil the requirements of the funding agencies such as the FNS and H2020, which require a DMP to be put in place
• manage in detail your research data, specifying how your data will be analysed, organised, stored, secured and shared
• specify the type of data that is going to be created and shared
• indicate the process to be followed in respect of the budget, intellectual property, and monitoring

You will also learn how to use the "VitalIT DMP Canvas Generator tool" to make your own DMP template.

Prerequisites

Knowledge / competencies

To be involved in Life Sciences research.

Technical

Please bring your personal laptop as we will use it for the practical part of the course.

Time

The course will start at 9:00 and end around 17:00. Precise information will be provided to the participants on due time.

Additional information

Coordination: CUSO/StarOmics, SIB Training Group

For more information, please contact [email protected].

This course is free to CUSO PhD students. The registration fees for academics are 50 CHF. Participants from non-academic institutions should contact us before application.

Deadline for registration and free-of-charge cancellation is set is set to 08/03/2018. Cancellation after this date will not be reimbursed. Please note that participation to SIB courses is subject to general conditions.

You will be informed by email of your registration confirmation.

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