Data Management

With the advent of the digital turn and the new requirements of Open Science, data management has become in recent years one of the major challenges facing the scientific community. At FORS, we follow an integrated, tailor-made approach based on concrete research practices. Our team is committed to developing tools to help researchers optimize the scientific quality of their research materials, which take into account both the specificities of their projects and current standards.

We aim to answer questions such as: How can I meet ethical and legal standards while respecting the epistemological and methodological codes of my discipline? How to respond to the growing demand for data openness without violating the new data protection rules? How do I store my data securely? Can I share everything? What will happen to my data after I retire?

You will find here useful resources that will help you to develop a strategy adapted to your needs, be it for data management planning or its implementation throughout a research project. Much more than an administrative procedure, data management is an opportunity to reflect on fundamental issues related to the production and processing of data, but also on the potential of data beyond the research projects for which they were initially collected.

What do we mean by data management?
Data management can be defined as a process by which data are obtained, validated, protected and transformed, and by which their accessibility, reliability and speed of transmission are ensured in order to meet the needs of data users (data management. BusinessDictionary.com. Retrieved January 19, 2020, from BusinessDictionary.com website).  This includes most of the operations performed on the data throughout its life cycle with  the exception of their use. As such, there are organizational, technical and ethical aspects to this. Some practices, such as documentation, data security or file organization, must be implemented on an ongoing basis, while others concern specific moments of the research project. In any event, everything must be planned in advance.

Data management practices throughout the data life cycle

A data management plan (DMP) is a planning document, often required by funding agencies or research institutions. It aims to describe at the beginning of a research project the actions that will be implemented in order to allow the data to be reusable, and as far as possible, shareable for the long-term. Thus, it is above all a declaration of good intentions that will have to be updated and implemented once the project begins. In order to be fully useful, a DMP must be considered as a dynamic document that will develop during the project. It provides a basis for a detailed strategy and the implementation of good research and data practices.
In which legal framework is my research embedded?
The processing of personal and sensitive data is generally subject to specific legal provisions. National legislation protects citizens against the misuse of their data by imposing a number of obligations on researchers. Good data management therefore requires a good knowledge of the legal framework.

In Switzerland

In Europe

Worldwide

How to manage my data in an ethical way?
Good data management is not just about classifying and storing your files efficiently and securely. Good management also requires the implementation of adequate protection measures for the persons whose personal data are processed. These measures relate to what is generally referred to as research ethics. These include, among others, obtaining informed consent, conducting a risk assessment (with respect to privacy breaches), proceeding to the anonymization of sensitive data, etc. While ethical and legal considerations overlap on many points, they are not equivalent. Far from being the application of fixed principles, research ethics is a reflexive process aimed at ensuring the well-being of research participants through the implementation of ad-hoc strategies. To learn more about these topics, you can consult our FORS Guides:

FORS Guide N°3: Ethics in the era of open research data: some points of reference

FORS Guide N°5: The informed consent as legal and ethical basis of research data production

We also draw your attention to the fact that more and more stakeholders are demanding an ethical compliance certificate from researchers: funders, publishers, research fields, and governments. At the Swiss level, research that falls within the scope of the Federal Act on Research involving Human Beings (HRA) must be submitted to the competent cantonal commission. For projects not subject to the HRA, some universities have specialized commissions.

How to write a data management plan?
Since October 2017, any researcher who submits a proposal to the Swiss National Science Foundation (SNSF) must also submit a data management plan (DMP). This document aims to ensure, from the design stage of a project, that good research practices, which will eventually allow data to be shared in a repository that meets FAIR standards, have been considered. The template presented by the SNSF is generic and applies to all disciplines. We have therefore designed a practical guide to provide assistance from the perspective of the social sciences. This tool will help you answer the questions addressed in the DMP by approaching them in a reflexive way and by offering some practical advice. A DMP must be adapted to the specificities of each project: there is therefore no single model. Far from being an administrative formality, the DMP is a first step towards ensuring data quality and potential for data reuse. Proper consideration of the questions will have a direct impact on project design, data collection and processing. Once the project is funded, it is necessary to further develop the strategy and implement good practices in line with the needs of your project.

FORS Guide N°7 : How to draft a DMP from the perspective of the social sciences, using the SNSF template

How to operationalize data management on a daily basis?
Once the grant has been approved and the project has started, the intentions formulated in the data management plan must be turned into practice. This usually involves the development of a detailed strategy, the distribution of responsibilities within the team and the implementation of practices according to the stage of the research and the specific needs of the project. We are currently developing new practical guides on key data management practicesthat will complement this page. We also invite you to consult the CESSDA Data Management Expert Guide, which results from an international collaboration.

Currently available FORS guides can be found here.

How do I share my data?
Non-personal and non-sensitive data can be shared without restrictions, unless otherwise agreed (e.g. copyright). However, personal and/or sensitive data can only be shared under certain conditions. One should distinguish three protection measures that can be applied individually or in combination with each other, depending on the sensitivity of the data.

Anonymization

Informed consent

User contracts

What are the services offered by FORS?
We offer services for the implementation of best practices in research data management. Our expertise covers the following fields:

• Implementation of DMPs (data management plans)
• Compliance to ethical and legal standards
• Documentation practices
• Informed consent
• Anonymisation methods
• Data security and storage
• File management
• Archiving and sharing

We offer workshops and can also support you with individual consulting on the management of your qualitative or quantitative data. If you need our support, contact us.