“This symposium addresses the interfaces between the laboratory and the new infrastructures currently being set up. Open Science aims to make research and development more effective by better supporting collaboration. The advantages of making data open will be critically reviewed and the development of highly interconnected, collaborative research in data driven laboratories of the future will be discussed. Adoption of the FAIR data principles is an important step to support this.
In chemistry, biochemistry and neighbouring areas, funding agencies and national and supranational bodies are strongly advocating the sharing and depositing of data. To make this work the incentive structures for academics need to be realigned, investment in infrastructure and new technologies increased, and the awareness of the advantages of making data available for AI and similar technologies heightened….”
“This document presents an updated review of Open Data and Open Science policies in Europe as of July 2019. It does not include Open Access to publications policy. This analysis goes more into depth on the types of policy in place in Europe, their processes of creation, and some of their specifics. This updated version of the deeper analysis reflects changes that have been identified between November 2018 and July 2019. We concentrate on the twenty-eight EU member states, but we also consider relevant countries from the European Research Area, namely Iceland, Norway, Serbia and Switzerland.
This report is the the fourth version of a report which was originally published in 2017….”
“SPARC Europe and the DCC have collaborated since 2017 on reviewing Open Science Policies in Europe. Our report has to date been downloaded over 5000 times and we have had feedback from users who find this a useful resource to draw on in their work, whether for research purposes or policy making. Today we are publishing the fourth version of the report, which demonstrates a move towards a stronger focus on open research data, and open science more generally across European science policy landscape. We have also noted a few instances of FAIR data being mentioned in policy papers, for example in Ireland.
We welcome your input!
We have been planning to change the structure of this paper to allow for better analysis and comparison, and we would very much like the input of the user community to guide us in these changes. We have to this end set up a short web survey, which should only take around 5 minutes to complete. You can access the survey here, …”
Abstract: There is an increasing focus on the part of academic institutions, funding agencies, and publishers, if not researchers themselves, on preservation and sharing of research data. Motivations for sharing include research integrity, replicability, and reuse. One of the barriers to publishing data is the extra work involved in preparing data for publication once a journal article and its supporting information have been completed. In this work, a method is described to generate both human and machine-readable supporting information directly from the primary instrumental data files and to generate the metadata to ensure it is published in accordance with findable, accessible, interoperable, and reusable (FAIR) guidelines. Using this approach, both the human readable supporting information and the primary (raw) data can be submitted simultaneously with little extra effort. Although traditionally the data package would be sent to a journal publisher for publication alongside the article, the data package could also be published independently in an institutional FAIR data repository. Workflows are described that store the data packages and generate metadata appropriate for such a repository. The methods both to generate and to publish the data packages have been implemented for NMR data, but the concept is extensible to other types of spectroscopic data as well.
From Google’s English: “The open science policy initiated by the ANR in 2013 is fully in line with the National Open Science Plan launched by Minister Frédérique Vidal in July 2018, with the following three objectives:
Promote open access to publications (Open Access)
As part of the ANR’s contribution to the promotion and implementation of open science, and in connection with the National Open Science Plan, the coordinator and the partners and the partners commit themselves in the event of funding to deposit scientific publications (full text) from the research project in an open archive, either directly in HAL or through a local institutional archive, under the conditions of Article 30 of the Law “For a Digital Republic ” . Moreover, the ANR recommends favoring publication in journals or books natively open access.
Contribute to open data whenever possible (Open Data)
In order to implement the principle “as open as possible, as closed as necessary” and in accordance with FAIR principles (Easy to find, Accessible, Interoperable, Reusable), the NRA encourages coordinators to consider the issue of research from the editing and throughout the project. The Agency will request the development of a data management plan for all funded projects within 6 months of the start of the project starting from the 2019 edition. This document summarizes the description and evolution of the projects. datasets, it prepares the sharing, reuse and sustainability of data….
Coordinate actions at European and international level
ANR is also involved in several transnational initiatives in which it takes the French position in favor of open science and bibliodiversity. She is a member of the coalition S which brings together several funding agencies to accelerate the transition to a full and immediate access to scientific publications and supports the S Plan . The Agency is also a member of the GO FAIR office in France….”
“This special one day workshop for data and information professionals, information technologists, and for disciplinary scientists interested in effective data sharing is focused on the wave of activities related to making data “FAIR” (Findable, Accessible, Interoperable, and Reusable).
We will focus on the implementations and ultimate impacts and implications, especially as data is made FAIR for people and machines….”
“But probably the most urgent question for many people who read and publish in journals is where do these journals, especially journals that operate under the subscription model, fit into this future? Crucially, any ideal future system will need to encompass a diverse range of possible solutions, technically and financially. Journals of all types will have their place, as will pre?print servers, data repositories, registries of trials and other studies, and repository systems maintained by libraries and other organisations. Essentially, the entire set of current components can be fitted into a remodelled system, provided they are able to support specific principles — maybe the FAIR principles, but perhaps other community?agreed principles will arise. The onus at this time is for publishers to look carefully at each of their journals and to develop plans that will support open scholarship now and into the future. However, at the same time as journals and publishers respond to the changing world, there needs to be a concerted program of education and support for everyone involved in publishing, especially readers and authors, on the wholesale changes now occurring….”
“The scholarly record is evolving to incorporate a widening range of research outputs, with stakeholders, systems, practices, and norms both adapting to and shaping this evolution. Stewardship of research data has received particular attention, evidenced by an ever-thickening network of services, resources, and consensus- or standards-building activities dedicated to making data sets accessible and reusable. One prominent initiative is FAIR: a set of principles that describe how to make data sets Findable, Accessible, Interoperable, and Reusable. It is still early days for FAIR – the principles were introduced in a 2016 article in Scientific Data. The future of FAIR is therefore very much to be determined; however, publishers, funders, researchers, and other stakeholders can draw some helpful lessons from history….
Changing data management practices is just as much about changing mindset and culture as it is about technical solutions – perhaps more. FAIR is a valuable tool for advocacy, in the sense of communicating the high-level goals of open, reusable data. FAIR is a valuable resource for education, by providing a shared framework within which new perspectives on responsible data management can be formed – even if those perspectives are not uniform, or easily operationalized. And FAIR is a valuable marker for how seriously the community is taking up the issue of open data: even if repositories declare their data FAIR without formal compliance or certification protocols, at least they are gesturing to the importance of the issue, and maybe even doing something substantive about it.
So the experience of OAIS tells us we should not place all our emphasis on formal implementation of FAIR as the final yardstick of its value to the community. FAIR can be, and I expect will be, a powerful catalyst in moving the research data community as a whole in the right direction….”
“As professional data curators, research data librarians, academic library administrators, directors of international data repositories, disciplinary subject experts, and scholars we represent academic institutions and non-profit societies that make research data available to the public….
Data curators prepare and enrich research data to make them findable, accessible, interoperable and reusable (FAIR). Sharing our data curation staff across DCN partner institutions enables data repositories to collectively, and more effectively, curate a wider variety of data types (e.g., discipline, file format, etc.) that expands beyond what any single institution might offer alone….”