“The theme of this symposium is convergence around ideas and implementations of FAIR. Throughout the week we will explore a range of activities which seem to be gaining influence, agreement and traction. A number of these will be introduced in Plenary Sessions 3: FAIR Convergence (Mon 30 Nov at 12:00-13:00 UTC). Watch the prerecorded presentations from the whole panel here.
The panel will discuss the central importance of FAIR Digital Objects (Luiz Bonino, GO FAIR); the contribution that can be made by FAIR Implementation Profiles (Erik Schultes, GO FAIR, and Barbara Magagna, Austrian Environment Agency); the role of FAIR Vocabularies and how these can be technically presented, maintained, governed and sustained (Alejandra Gonzalez-Beltran, STFC, and Simon Cox, CSIRO); the contribution which may be made by the approach taken by DDI-CDI to describing individual variable and tracking provenance (Arofan Gregory, Standards Consultant); and the fundamental need for interoperable units of measure (Bob Hanisch, NIST)….”
Abstract: The importance of data sharing and biobanking are increasingly being recognised in global health research. Such practices are perceived to have the potential to promote science by maximising the utility of data and samples. However, they also raise ethical challenges which can be exacerbated by existing disparities in power, infrastructure and capacity. The Global Forum on Bioethics in Research (GFBR) convened in Stellenbosch, South Africa in November 2018, to explore the ethics of data sharing and biobanking in health research. Ninety-five participants from 35 countries drew on case studies and their experiences with sharing in their discussion of issues relating to respecting research participants and communities, promoting equitable sharing, and international and national approaches to governing data sharing and biobanking. In this editorial we will briefly review insights relating to each of these three themes.
“Open Context reviews, edits, annotates, publishes and archives research data and digital documentation. We publish your data and preserve it with leading digital libraries. We take steps beyond archiving to richly annotate and integrate your analyses, maps and media. This links your data to the wider world and broadens the impact of your ideas….”
Abstract: The lack of comprehensive and standardized taxonomic reference information is an impediment for robust plant research, e.g. in systematics, biogeography or macroecology. Here we provide an updated and much improved reference list of 1,315,562 scientific names for all described vascular plant species globally. The Leipzig Catalogue of Vascular Plants (LCVP; version 1.0.3) contains 351,180 accepted species names (plus 6,160 natural hybrids), within 13,460 genera, 564 families and 84 orders. The LCVP a) contains more information on the taxonomic status of global plant names than any other similar resource, and b) significantly improves the reliability of our knowledge by e.g. resolving the taxonomic status of ~181,000 names compared to The Plant List, the up to date most commonly used plant name resource. We used ~4,500 publications, existing relevant databases and available studies on molecular phylogenetics to construct a robust reference backbone. For easy access and integration into automated data processing pipelines, we provide an ‘R’-package (lcvplants) with the LCVP.
“Our Accelerate Open Science Project aims to give context to various developments in the area of Open Science, and to make information about topics such as FAIR data easier accessible. As a second slide deck in our Info Slides Series, we present you Answers to five questions about FAIR data.
The slide deck is licensed under a CC-BY license, which enables you to make use of it any way you want. You can find the slides here….”
“This report presents the results of an inventory of research data services offered by US colleges and universities using a systematic web searching process. Our results represent a holistic, quantitative picture of services that support data-driven research across organizational units and institutional types.
In addition to sharing these findings, we have also provided extensive methodological documentation in hopes of inspiring and enabling future research. Until now, there has been no effective methodology for capturing quantitative data about the provision and organization of research data services across diverse institutional structures. Although there are limitations to this type of web-based inventory, the advantages over other research methods, such as surveys, are significant for measuring what research data services are offered and where. We discuss the scope of our study below and provide additional methodological details in the Appendix….”
“There has been significant concern expressed in the repository community about the requirements contained in the Data Repository Selection: Criteria that Matter, which sets out a number of criteria for the identification and selection of data repositories that will be used by publishers to guide authors in terms of where they should deposit their data.
COAR agrees that it is important to encourage and support the adoption of best practices in repositories. And there are a number of initiatives looking at requirements for repositories, based on different objectives such as the FAIR Principles, CoreTrustSeal, the TRUST Principles, and the CARE Principles of Indigenous Data Governance. Recently COAR brought together many of these requirements – assessed and validated them with a range of repository types and across regions – resulting in the publication of the COAR Community Framework for Best Practices in Repositories.
However, there is a risk that if repository requirements are set very high or applied strictly, then only a few well-resourced repositories will be able to fully comply. The criteria set out in Data Repository Selection: Criteria that Matter are not currently supported by most domain or generalist data repositories, in particular the dataset-level requirements. If implemented by publishers, this will have a very detrimental effect on the open science ecosystem by concentrating repository services within a few organizations, further exacerbating inequalities in access to services. Additionally, it will introduce bias against some researchers, for example, researchers who prefer to share their data locally; researchers in the global south; or researchers who want to share their data in a relevant domain repository, so it can be visible to their peers and integrated with other similar datasets….”
Scholexplorer data can be used to identify reuse and citation of published datasets
More dataset and article links can be identified now with the Scholexplorer API
Many links result from former manual data curation instead of direct data citation
Author and dataset owner affiliation would help identify different data use cases….”