| 1. |
- Andersen, Casper W., et al.
(author)
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OPTIMADE, an API for exchanging materials data
- 2021
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In: Scientific Data. - : Nature Portfolio. - 2052-4463. ; 8:1
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Journal article (peer-reviewed)abstract
- The Open Databases Integration for Materials Design (OPTIMADE) consortium has designed a universal application programming interface (API) to make materials databases accessible and interoperable. We outline the first stable release of the specification, v1.0, which is already supported by many leading databases and several software packages. We illustrate the advantages of the OPTIMADE API through worked examples on each of the public materials databases that support the full API specification.
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| 2. |
- Bisaccia, Giandomenico, et al.
(author)
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Cardiovascular Morbidity and Mortality Related to Non-Alcoholic Fatty Liver Disease : a Systematic Review and Meta-Analysis
- 2023
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In: Current Problems in Cardiology. - : Elsevier BV. - 0146-2806 .- 1535-6280. ; 48:6
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Research review (peer-reviewed)abstract
- BACKGROUND AND AIMS: Whether non-alcoholic fatty liver disease (NAFLD) is a cardiovascular (CV) risk factor is debated. We performed a systematic review and meta-analysis to assess the CV morbidity and mortality related to NAFLD in the general population, and to determine whether CV risk is comparable between lean and non-lean NAFLD phenotypes.METHODS AND RESULTS: We searched multiple databases, including PubMed, Embase, and the Cochrane Library, for observational studies published through 2022 that reported the risk of CV events and mortality. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) for all-cause mortality, CV mortality, myocardial infarction (MI), stroke, atrial fibrillation (AF), and major adverse cardiovascular and cerebrovascular events (MACCE) were assessed through random-effect meta-analysis. We identified 33 studies and a total study population of 10,592,851 individuals (mean age 53±8; male sex 50%; NAFLD 2,9%). Mean follow-up was 10±6 years. Pooled ORs for all-cause and CV mortality were respectively 1.14 (95%CI 0.78-1.67) and 1.13 (95%CI 0.57-2.23), indicating no significant association between NAFLD and mortality. NAFLD was associated with increased risk of MI (OR 1.6; 95%CI 1.5-1.7), stroke (OR 1.6; 95%CI 1.2-2.1), atrial fibrillation (OR 1.7; 95%CI 1.2-2.3) and MACCE (OR 2.3; 95%CI 1.3-4.2). Compared with non-lean NAFLD, lean NAFLD was associated with increased CV mortality (OR 1.50; 95%CI 1.1-2.0), but similar all-cause mortality and risk of MACCE.CONCLUSIONS: While NAFLD may not be a risk factor for total and CV mortality, it is associated with excess risk of non-fatal CV events. Lean and non-lean NAFLD phenotypes exhibit distinct prognostic profiles and should receive equitable clinical care.
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| 3. |
- Castelli, Ivano E., et al.
(author)
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Data Management Plans : the Importance of Data Management in the BIG-MAP Project
- 2021
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In: Batteries & Supercaps. - : John Wiley & Sons. - 2566-6223. ; 4:12, s. 1803-1812
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Journal article (peer-reviewed)abstract
- Open access to research data is increasingly important for accelerating research. Grant authorities therefore request detailed plans for how data is managed in the projects they finance. We have recently developed such a plan for the EU H2020 BIG-MAP project-a cross-disciplinary project targeting disruptive battery-material discoveries. Essential for reaching the goal is extensive sharing of research data across scales, disciplines and stakeholders, not limited to BIG-MAP and the European BATTERY 2030+ initiative but within the entire battery community. The key challenges faced in developing the data management plan for such a large and complex project were to generate an overview of the enormous amount of data that will be produced, to build an understanding of the data flow within the project and to agree on a roadmap for making all data FAIR (findable, accessible, interoperable, reusable). This paper describes the process we followed and how we structured the plan.
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| 4. |
- Ghiringhelli, Luca M., et al.
(author)
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Shared metadata for data-centric materials science
- 2023
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In: Scientific Data. - : NATURE PORTFOLIO. - 2052-4463. ; 10
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Journal article (other academic/artistic)abstract
- The expansive production of data in materials science, their widespread sharing and repurposing requires educated support and stewardship. In order to ensure that this need helps rather than hinders scientific work, the implementation of the FAIR-data principles (Findable, Accessible, Interoperable, and Reusable) must not be too narrow. Besides, the wider materials-science community ought to agree on the strategies to tackle the challenges that are specific to its data, both from computations and experiments. In this paper, we present the result of the discussions held at the workshop on “Shared Metadata and Data Formats for Big-Data Driven Materials Science”. We start from an operative definition of metadata, and the features that a FAIR-compliant metadata schema should have. We will mainly focus on computational materials-science data and propose a constructive approach for the FAIRification of the (meta)data related to ground-state and excited-states calculations, potential-energy sampling, and generalized workflows. Finally, challenges with the FAIRification of experimental (meta)data and materials-science ontologies are presented together with an outlook of how to meet them.
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