Enhancing FAIR Compliance in Research Data Infrastructures: Insights from Applications of the RDA FAIR Data Maturity Model and the F-UJI Automated FAIR Data Assessment Tool

We share experiences assessing KonsortSWD using two approaches (manual and automated assessments). We used the FAIR Data Maturity Model (RDA-FDMM), which proposes 41 FAIR indicators organized into three classes (essential, important, useful) and five assessment levels. We applied RDA-FDMM to KonsortSWD's PID service, aiming to assign PIDs to data elements below the study level (such as survey variables). The indicators were manually assessed using the pass-or-fail method. We used the F-UJI Tool to automatically assess the GESIS Search as a relevant repository in the context of KonsortSWD. Tools like F-UJI offer valuable feedback on how to improve FAIR scores by automated means. Our experience highlights the importance of evaluating both machine-readable and non-machine-readable elements. As the research ecosystem evolves, providing easily machine-readable metadata becomes increasingly important. We recommend adopting a "FAIR by design" approach early in product or service development to ensure FAIR principles are embedded in project outcomes.KonsortSWD is funded by the German Research Foundation (DFG) within the framework of the NFDI – project number: 442494171

Enhancing FAIR Compliance in Research Data Infrastructures: Insights from Applications of the RDA FAIR Data Maturity Model and the F-UJI Automated FAIR Data Assessment Tool [Presentation]

We share experiences assessing KonsortSWD using two approaches (manual and automated assessments). We used the FAIR Data Maturity Model (RDA-FDMM), which proposes 41 FAIR indicators organized into three classes (essential, important, useful) and five assessment levels. We applied RDA-FDMM to KonsortSWD's PID service, aiming to assign PIDs to data elements below the study level (such as survey variables). The indicators were manually assessed using the pass-or-fail method. We used the F-UJI Tool to automatically assess the GESIS Search as a relevant repository in the context of KonsortSWD. Tools like F-UJI offer valuable feedback on how to improve FAIR scores by automated means. Our experience highlights the importance of evaluating both machine-readable and non-machine-readable elements. As the research ecosystem evolves, providing easily machine-readable metadata becomes increasingly important. We recommend adopting a "FAIR by design" approach early in product or service development to ensure FAIR principles are embedded in project outcomes.KonsortSWD is funded by the German Research Foundation (DFG) within the framework of the NFDI – project number: 442494171

Beyond biofuels: jatropha’s multiple uses for farmers in East Africa

The jatropha plant produces seeds containing 25–40% oil by weight. This oil can be made into biodiesel. During the recent global fuel crisis, the price of crude oil peaked at over USD 130 per barrel. Jatropha attracted huge interest – it was touted as a wonder crop that could generate biodiesel oil on “marginal lands” in semi-arid areas. Its promise appeared especially great in East Africa. Today, however, jatropha’s value in East Africa appears to lie primarily in its multipurpose use by small-scale farmers, not in large-scale biofuel production

Gene Regulatory Network Reconstruction Using Bayesian Networks, the Dantzig Selector, the Lasso and Their Meta-Analysis

Modern technologies and especially next generation sequencing facilities are giving a cheaper access to genotype and genomic data measured on the same sample at once. This creates an ideal situation for multifactorial experiments designed to infer gene regulatory networks. The fifth “Dialogue for Reverse Engineering Assessments and Methods” (DREAM5) challenges are aimed at assessing methods and associated algorithms devoted to the inference of biological networks. Challenge 3 on “Systems Genetics” proposed to infer causal gene regulatory networks from different genetical genomics data sets. We investigated a wide panel of methods ranging from Bayesian networks to penalised linear regressions to analyse such data, and proposed a simple yet very powerful meta-analysis, which combines these inference methods. We present results of the Challenge as well as more in-depth analysis of predicted networks in terms of structure and reliability. The developed meta-analysis was ranked first among the teams participating in Challenge 3A. It paves the way for future extensions of our inference method and more accurate gene network estimates in the context of genetical genomics

Forward-central two-particle correlations in p-Pb collisions at root s(NN)=5.02 TeV

Two-particle angular correlations between trigger particles in the forward pseudorapidity range (2.5 2GeV/c. (C) 2015 CERN for the benefit of the ALICE Collaboration. Published by Elsevier B. V.Peer reviewe

Event-shape engineering for inclusive spectra and elliptic flow in Pb-Pb collisions at root(NN)-N-S=2.76 TeV

Peer reviewe

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead