Services for the European Open Science Cloud
Services for the European Open Science Cloud
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 for machines alike. A scholarly environment that produces and supports FAIR research outputs is a more equitable one. That is why OpenAIRE, EOSC-hub, RDA Europe and FAIRsFAIR are committed to the FAIR principles as a key building block of this landscape.
Just like these roads to Rome, the roads to FAIR data are many and varied, and in OpenAIRE, EOSC-hub, RDA Europe and FAIRsFAIR we know that the implementation of FAIR can be challenging for both researchers and research support staff. That's why we offer services and share expertise. This post is aimed at giving a glimpse into the activities being carried out by these initiatives to support a FAIR scholarly environment.
During the month of April OpenAIRE, EOSC-hub, RDA Europe and FAIRsFAIR will organise two workshops in Prague (during the EOSC-hub Week) and Vienna (during the workshop 'Linking Open Science in Austria). Here we will explore how existing infrastructures can work together and understand how to deliver services that support the creation of FAIR research outputs. The workshops will also focus on FAIR in the context of infrastructure services.
The OpenAIRE Task Force on Research Data Management is active in creating materials for supporting FAIR. The members of the task force are OpenAIRE's National Open Access Desks, NOADs, who are involved in transferring knowledge and expertise about Open Science on a regular basis. Together they have a broad overview of how to manage research data that has to be FAIR and Open, and they are currently working on a set of train the trainer materials about RDM. Watch this space for when it is finalised!
A blogpost by task force members made the case for electronic lab notebooks as an obvious tool for conducting Open Science. Electronic lab notebooks are great for sharing information about the research method, which is essential for interpreting the data. Sharing and preserving the lab notebook along with the data (if the data are not already part of the notebook) therefore really supports the reusability of data.
Speaking of preserving data, the online guide about finding a trustworthy repository for your datadescribes how good repositories help to make and to keep data FAIR:
We refer those who want to delve deeper into the field of persistent identifiers to the recordings and slides of a joint OpenAIRE-FREYA webinar.
Accessibility of research data may be limited when the data are sensitive. Data privacy and sensitive data services were discussed in a recorded webinar organised by OpenAIRE and EOSC-hub together. In addition, the online guide on sensitive data describes how various kinds of sensitive data can still meet the requirements of the FAIR data principles and be processed in a way that the required protection is guaranteed also in the future.
The newly kicked off FAIRsFAIR project (Fostering FAIR Data Practices in Europe) will work over the next three years to define guidelines towards a FAIRness approach to data and service management for data repositories of all disciplines by providing a platform for using and implementing the FAIR principles in the day-to-day work of research data providers and repositories all around Europe. FAIRsFAIR will play a key role in the development of global standards for FAIR certification of repositories and the data within them contributing to those policies and practices that will turn the EOSC programme into a functioning infrastructure. FAIRsFAIR will also deliver essential FAIR dimensions of the Rules of Participation (RoP) and regulatory compliance for participation in the EOSC. The EOSC governance structure will use these FAIR-aligned RoPs to establish whether components of the infrastructure function in a FAIR manner. Parallel to addressing repositories, other service providers and research funders, the project team also involves research communities, individual researchers and data stewards in a FAIR competence center and in trainings. In the end, it's people who will produce, assess and benefit from FAIR data.
Several RDA Working groups and Interest groups address the question how the FAIR principles are best embedded in the research data landscape (See the FAIR Agenda at RDA P13 below). The RDA Working Group "FAIR data maturity model", established in January 2019, aims primarily to develop as an RDA Recommendation a common set of core assessment criteria for FAIRness, which will be accompanied by a generic and expandable self-assessment model for measuring the implementation level of the FAIR data principles. The expected outcomes of this RDA Working Group will improve the interoperability of existing and emerging assessment methodologies for FAIR, allow the combination and comparison of their results and increase the homogeneity of the FAIR metric tools developed at global level.
The Group will have its first face-to-face meeting during RDA Plenary 13 in Philadelphia, on 3rd April 2019 during the breakout session n. 4 starting at 12:00 (see P13 programme here). The session aims to reach consensus on the key principles and phases of the design methodology that will lead to the definition of the common set of core assessment criteria for FAIRness.
The Group of European Data Experts in RDA (GEDE-RDA), which includes delegates from 47 European research infrastructures, is also working to promote, foster and drive the discussions and consensus forming on creating guidelines, core components and concrete data fabric configuration building based on a bottom-up process. The GEDE group organised a webinar on 22 March on Maturity Indicators for FAIRness and Certification of Repositories where they discussed, among others things, what machine-actionable FAIRness functionally means, how levels of FAIRness can be objectively and reproducibly assessed and what tools are required that measure FAIRness automatically.
This year the RDM task force of OpenAIRE Advance will develop and provide more support for turning FAIR into a reality. But first, in the next few weeks, the FAIR road leads to Prague and Vienna.
OpenAIRE also provides Support Guides on FAIR
The following webinars have been recorded for you to view training about FAIR
This blog post is authored by Elly Dijk and Marjan Grootveld (DANS), Sara Pittonet (Trust-IT), Najla Rettberg (UGOE).