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The COVID-19 pandemic has highlighted the need for FAIR (Findable, Accessible, Interoperable, and Reusable) data more than any other scientific challenge to date. We developed a flexible, multi-level, domain-agnostic FAIRification framework, providing practical guidance to improve the FAIRness for both existing and future clinical and molecular datasets. We validated the framework in collaboration with several major public-private partnership projects, demonstrating and delivering improvements across all aspects of FAIR and across a variety of datasets and their contexts. We therefore managed to establish the reproducibility and far-reaching applicability of our approach to FAIRification tasks.

Objective To evaluate the diagnosis of myocardial infarction using a high sensitivity troponin I assay and sex specific diagnostic thresholds in men and women with suspected acute coronary syndrome.Design Prospective cohort study.Setting Regional cardiac centre, United Kingdom.Participants Consecutive patients with suspected acute coronary syndrome (n=1126, 46% women). Two cardiologists independently adjudicated the diagnosis of myocardial infarction by using a high sensitivity troponin I assay with sex specific diagnostic thresholds (men 34 ng/L, women 16 ng/L) and compared with current practice where a contemporary assay (50 ng/L, single threshold) was used to guide care.Main outcome measure Diagnosis of myocardial infarction.Results The high sensitivity troponin I assay noticeably increased the diagnosis of myocardial infarction in women (from 11% to 22%; P<0.001) but had a minimal effect in men (from 19% to 21%, P=0.002). Women were less likely than men to be referred to a cardiologist or undergo coronary revascularisation (P<0.05 for both). At 12 months, women with undisclosed increases in troponin concentration (17-49 ng/L) and those with myocardial infarction (≥50 ng/L) had the highest rate of death or reinfarction compared with women without (≤16 ng/L) myocardial infarction (25%, 24%, and 4%, respectively; P<0.001).Conclusions Although having little effect in men, a high sensitivity troponin assay with sex specific diagnostic thresholds may double the diagnosis of myocardial infarction in women and identify those at high risk of reinfarction and death. Whether use of sex specific diagnostic thresholds will improve outcomes and tackle inequalities in the treatment of women with suspected acute coronary syndrome requires urgent attention.

Data in the life sciences are extremely diverse and are stored in a broad spectrum of repositories ranging from those designed for particular data types (such as KEGG for pathway data or UniProt for protein data) to those that are general-purpose (such as FigShare, Zenodo, Dataverse or EUDAT). These data have widely different levels of sensitivity and security considerations. For example, clinical observations about genetic mutations in patients are highly sensitive, while observations of species diversity are generally not. The lack of uniformity in data models from one repository to another, and in the richness and availability of metadata descriptions, makes integration and analysis of these data a manual, time-consuming task with no scalability. Here we explore a set of resource-oriented Web design patterns for data discovery, accessibility, transformation, and integration that can be implemented by any general- or special-purpose repository as a means to assist users in finding and reusing their data holdings. We show that by using off-the-shelf technologies, interoperability can be achieved atthe level of an individual spreadsheet cell. We note that the behaviours of this architecture compare favourably to the desiderata defined by the FAIR Data Principles, and can therefore represent an exemplar implementation of those principles. The proposed interoperability design patterns may be used to improve discovery and integration of both new and legacy data, maximizing the utility of all scholarly outputs.

Background Delirium affects > 15% of hospitalised patients but is grossly underdetected, contributing to poor care. The 4 ‘A’s Test (4AT, www.the4AT.com ) is a short delirium assessment tool designed for routine use without special training. The primary objective was to assess the accuracy of the 4AT for delirium detection. The secondary objective was to compare the 4AT with another commonly used delirium assessment tool, the Confusion Assessment Method (CAM). Methods This was a prospective diagnostic test accuracy study set in emergency departments or acute medical wards involving acute medical patients aged ≥ 70. All those without acutely life-threatening illness or coma were eligible. Patients underwent (1) reference standard delirium assessment based on DSM-IV criteria and (2) were randomised to either the index test (4AT, scores 0–12; prespecified score of > 3 considered positive) or the comparator (CAM; scored positive or negative), in a random order, using computer-generated pseudo-random numbers, stratified by study site, with block allocation. Reference standard and 4AT or CAM assessments were performed by pairs of independent raters blinded to the results of the other assessment. Results Eight hundred forty-three individuals were randomised: 21 withdrew, 3 lost contact, 32 indeterminate diagnosis, 2 missing outcome, and 785 were included in the analysis. Mean age was 81.4 (SD 6.4) years. 12.1% (95/785) had delirium by reference standard assessment, 14.3% (56/392) by 4AT, and 4.7% (18/384) by CAM. The 4AT had an area under the receiver operating characteristic curve of 0.90 (95% CI 0.84–0.96). The 4AT had a sensitivity of 76% (95% CI 61–87%) and a specificity of 94% (95% CI 92–97%). The CAM had a sensitivity of 40% (95% CI 26–57%) and a specificity of 100% (95% CI 98–100%). Conclusions The 4AT is a short, pragmatic tool which can help improving detection rates of delirium in routine clinical care. Trial registration International standard randomised controlled trial number (ISRCTN) 53388093 . Date applied 30/05/2014; date assigned 02/06/2014.

Background Provenance is a critical ingredient for establishing trust of published scientific content. This is true whether we are considering a data set, a computational workflow, a peer-reviewed publication or a simple scientific claim with supportive evidence. Existing vocabularies such as Dublin Core Terms (DC Terms) and the W3C Provenance Ontology (PROV-O) are domain-independent and general-purpose and they allow and encourage for extensions to cover more specific needs. In particular, to track authoring and versioning information of web resources, PROV-O provides a basic methodology but not any specific classes and properties for identifying or distinguishing between the various roles assumed by agents manipulating digital artifacts, such as author, contributor and curator. Results We present the Provenance, Authoring and Versioning ontology (PAV, namespace http://purl.org/pav/ ): a lightweight ontology for capturing “just enough” descriptions essential for tracking the provenance, authoring and versioning of web resources. We argue that such descriptions are essential for digital scientific content. PAV distinguishes between contributors, authors and curators of content and creators of representations in addition to the provenance of originating resources that have been accessed, transformed and consumed. We explore five projects (and communities) that have adopted PAV illustrating their usage through concrete examples. Moreover, we present mappings that show how PAV extends the W3C PROV-O ontology to support broader interoperability. Method The initial design of the PAV ontology was driven by requirements from the AlzSWAN project with further requirements incorporated later from other projects detailed in this paper. The authors strived to keep PAV lightweight and compact by including only those terms that have demonstrated to be pragmatically useful in existing applications, and by recommending terms from existing ontologies when plausible. Discussion We analyze and compare PAV with related approaches, namely Provenance Vocabulary (PRV), DC Terms and BIBFRAME. We identify similarities and analyze differences between those vocabularies and PAV, outlining strengths and weaknesses of our proposed model. We specify SKOS mappings that align PAV with DC Terms. We conclude the paper with general remarks on the applicability of PAV.

The notion that data should be Findable, Accessible, Interoperable and Reusable, according to the FAIR Principles, has become a global norm for good data stewardship and a prerequisite for reproducibility. Nowadays, FAIR guides data policy actions and professional practices in the public and private sectors. Despite such global endorsements, however, the FAIR Principles are aspirational, remaining elusive at best, and intimidating at worst. To address the lack of practical guidance, and help with capability gaps, we developed the FAIR Cookbook, an open, online resource of hands-on recipes for “FAIR doers” in the Life Sciences. Created by researchers and data managers professionals in academia, (bio)pharmaceutical companies and information service industries, the FAIR Cookbook covers the key steps in a FAIRification journey, the levels and indicators of FAIRness, the maturity model, the technologies, the tools and the standards available, as well as the skills required, and the challenges to achieve and improve data FAIRness. Part of the ELIXIR ecosystem, and recommended by funders, the FAIR Cookbook is open to contributions of new recipes.