Adaptation of FAIR Data Maturity Model indicators in Validator

OpenAIRE is working to adapt the FAIR RDA Data Maturity Model indicators in our OpenAIRE Validator. The Validator is available to every logged-in user via the PROVIDE dashboard and is intended to provide an impression of the FAIRness of their repository. The FAIR Maturity Model Indicators, as core criteria to assess the implementation level of the FAIR (Data) principles, implemented in the OpenAIRE Validator, aims to offer to the datasource managers, a way to assess the implementation of FAIR (D...

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Online Good Practice Exchange programme at DANS in the Netherlands

After being postponed twice, due to Covid-19, the online OpenAIRE Good Practice Exchange (GPE) programme organized by DANS (Data Archiving and Networked Services) took place on 18 January 2021. The goal of the programme is to provide a framework through which OpenAIRE NOADs can share their knowledge and expand their skills in Open Science. And because DANS is a national centre of expertise and repository for research data, the main topics on this day were best practices on Research Data Manageme...

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Data Reuse Stories. Some concrete cases involving several institutions and consortia in Europe

Data can be reused by others, for example, to ask different questions or to enrich them and build further applications or new products. Many Research Funding Organizations are demanding data sharing with the idea that data reuse can foster new research outcomes, innovation and economic opportunities. Open Science strives for transparency, and opening up research data may have many advantages for science, ranging from replicability of experiments to reusability of the data itself. The idea is tha...

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New educational website on FAIR research data released

On the 3rd of July 2020 a new website was released which takes a deep dive into the practicalities of making FAIR research data. The site is conceived as a blended learning resource targeted at researchers in all disciplines and the goal is to show how they can make their own research data more FAIR through real life examples from the Humanities, Social, Natural, and Health Sciences. The site is based on written explanations garnished with video testimonials from 9 different researchers and scie...

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The road to FAIR data

This blog post is authored by Elly Dijk and Marjan Grootveld (DANS),  Najla Rettberg (UGOE), Sara Pittonet (Trust-IT) Introduction In the old days, all roads led to Rome. Nowadays, they all seem to lead to FAIR data, at least in the world of research. Regardless of one's research domain, the observations, interviews, responses, measurements, statistics, software code, should be findable, accessible, interoperable and reusable (FAIR). The aim is to make and keep data FAIR for humans and...

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How to make your data Open and FAIR?

Ilona von Stein, project leader and policy officer at DANS, writes about the importance of Data Management Training. What would happen if your data is not trusted by your own research community? What if your research community generates 2 petabyte of raw data per day, and and needs to share it between institutions? What if reuse of your data takes place in computational workflows, but data archives do not provide formats and annotations to support this? And what if you cannot find...

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