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CSC

Open science is on the science policy agenda globally. In order to advance it, it is important that the impacts and practices of open science can be monitored reliably. It is also clear that if researchers are expected to advance open science, it must beneficial for them. However, open science is currently a less-considered element in research(er) evaluation or monitoring. This is largely due to the lack of reliable and comprehensive information on open science related activities.

Responsible research assessment attempts to address also this challenge. The demand for a more responsible research assessment has grown in the scientific community over the past decade. Several principles and declarations have contributed to what is meant by responsible research assessment, and in all of these diversity plays a central role. In other words taking into account a diversity of research activities and outputs as well as researcher careers and disciplines in evaluation is considered as important.

CSC is participating in three EU-funded projects to advance open science, the development of a more diverse knowledge base and increased findability of research outputs. In addition, the aim is to create added value for users of Research.fi, a service maintained by CSC, advance the widespread adoption and application of FAIR principles, and take part in international discussion and development work around this important topic.

FAIRCORE4EOSC – services to support open science

The CSC-coordinated FAIRCORE4EOSC project develops services related to EOSC (European Open Science Cloud). The services improve the findability, accessibility, interoperability and reusability of research outputs and services. EOSC promotes openness not only in publications but also in data, source code, and research services, such as computing and digital analysis services. FAIRCORE4EOSC contributes to advancing open science by, among other things, building system integrations, improving machine interoperability of data, and developing persistent identifiers.

FAIR-IMPACT – practical support for implementing FAIR principles

FAIR-IMPACT supports, coordinates and synchronises the implementation of practices, tools and services that apply the FAIR principles. The main task of CSC in the project relates to persistent identifiers as integral part of FAIR-compliant data management. As more transparency and reproducibility is expected of research, persistent identifiers ease the organising of information and increase their findability. The aim is to make the use and integration of persistent identifiers as fluent as possible by making clear recommendations while at the same time taking into consideration the different stages of research and the needs of different disciplines.

GraspOS – more responsible research assessment

The overarching theme of GraspOS is responsible research assessment with a particular focus on a more diverse consideration of open science. In the project, CSC aims to enrich the publication data in Research.fi with citation information. In addition, CSC is testing the openness profile developed in the project in the context of the Researcher’s Profile Tool. This would enable researchers to highlight their open science outputs and activities in their own profile and thus emphasise the importance of openness in their research activities.

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Laura Himanen

Project Manager

Laura Himanen develops Research.fi service and advances responsible research assessment nationally and internationally.

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Josefine Nordling

Senior Open Science Specialist

Josefine Nordling advances and promotes open science and persistent identifier practices and policies, mainly on an international level.

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Tommi Suominen

Senior Information Architect

PhD Tommi Suominen coordinates the EU HE FAIRCORE4EOSC project. He designs information systems, especially focusing on their national and international interoperability.



FAIR principles

The FAIR principles are the cornerstone of open science, defining key requirements for research data and services:

  • Findable  – Data must be easily found and equipped with unique identifiers
  • Accessible  – Access to data should be clearly defined and, where possible, open.
  • Interoperable  – The data must be interoperable with other systems and data sources.
  • Reusable – The data must also be reusable in new research, and its origins and terms of use must be clearly defined.