Open research Data

UNIL's research data strategy is defined within a binding international and national framework. It is also based on the needs and expectations of its community as identified in a survey conducted in 2015. In this context, UNIL advocates honest and responsible research that aims to manage research data in a transparent and open manner, within the limits of the law and scientific requirements in terms of ethics, deontology and compliance with standards for the protection of the individual and intellectual property.

Research data, derived from scholarly work, is a public good whose management - in the short, medium and long term - raises many scientific, ethical, deontological, legal, technical, economic and societal issues. This management is essential and crucial in many respects: it ensures compliance with the legal and regulatory framework as well as the requirements of scientific funders and publishers; it guarantees the authenticity, integrity, reliability and usability of data; it facilitates their reproducibility, sharing and reuse; and it makes research works and results more visible and contributes to their quality.

These challenges and their complexity require a high number of skills that must first be identified and then reinforced to assist researchers. In addition, there is the need to take into account disciplinary specificities, as well as a number of binding obligations that arise from today's research environment.

UNIL, together with the University of Zurich, is actively participating in the SWISSUBase project led by the Swiss Competence Centre for Social Sciences (FORS), which aims to provide a general, open and sustainable repository of general and disciplinary data to comply with the FAIR Data Principles, i.e. data that are Findable, Accessible, Interoperable and Reusable.

• Awareness and communication of this "new" scientific culture ;
• The support and training of its researchers in the face of this evolution ;
• The development of technical infrastructure ;
• The establishment of a participatory organization and governance capable of effectively meeting the needs of its community.

This multivariate approach must make it possible to respond to the challenges and issues of OrD so that the management of research data becomes a responsible management of data for research.