Find research datasets worth reusing

opencc-by-4.0Dec 2021View details →

HARVEST_200130_MOD_ANIS_4.2_APDL_UNIPD_CONSORTIUM_COUPLED+THERMAL+ELECTRIC.txt

Ansys APDL files for the electric, thermal and thermo-electric properties of two-ply laminates with periodic boundary conditions.

opencc-by-4.0Mar 2022View details →

GERONTE H2020 Project - GERDAT002 - Composition of the health care professional consortium

The present document is a dataset generated as part of Deliverable D1.1. of the GERONTE project, which has received funding from the European Union’s Horizon 2020 Programme under Grant Agreement N°945218. It aims to provide the geriatric oncology professional community with a dataset of core health care professionals that should be involvoed in the evaluation and treatment trajectories of older patients with cancer and multimorbidity. GERONTE is a 5-year research and innovation project (April 2021 to Mars 2026) funded by the European Union within the framework of the H2020 Research and Innovation programme, in response to the health societal challenge topic SC1-BHC-24-2020 “Healthcare interventions for the management of the elderly multimorbid patient”. The overall aim of GERONTE is to improve quality of life - defined as well-being on three levels: global health status, physical functioning and social functioning- for older multimorbid patients, while reducing overall costs of care. To this end, GERONTE will co-design, test, and prepare for deployment an innovative cost-effective patient-centred holistic health management system, hereafter referred to as the GERONTE intervention. GERONTE intervention will rely on an ICT based application for real-time collection and integration of standardised clinical and home patient-reported data. GERONTE intervention will be demonstrated in the context of care of multimorbid patients having cancer as a dominant morbidity, and be adaptable to any other combination of morbidities. An important component of the GerOnTe care pathway was to determine which health care professionals should be included in the health care professional consortium (HPC) providing care for the patient. Beforehand, we had considered the option of four core members and at least eight other participants depending on the patient’s specificities or profile. Based on clinical experience, we developed a list of 15 potential participants, including general practitioner, one or more oncology specialists (such as surgeons, medical oncologists, radiotherapists), geriatrician, oncology nurse, social worker, clinical pharmacist, physiotherapist, anaesthesiologist, home care nurse, dietician, occupational therapist, spiritual helpers/clerics, psychologist/psychiatrist, palliative care specialist, organ-specific physician(s) such as cardiologist, pulmonologist, nephrologist, rheumatologist etc. This list was presented to the expert panel, and they were asked to determine whether or not these participants should be involved in decision-making and/or the subsequent oncologic care trajectory; experts could specify if these participants should be involved for all patients, only in specific situations/profiles, or did not need to be involved. The results of this expert panel survey and the subsequent composition of the health care professional consortium forms the basis of this dataset.

opencc-by-4.0Aug 2022View details →

Control panel created from 30 Nanopore sequencing data from the Human Pangenome Reference Consortium

This is control panel for <a href="https://github.com/friend1ws/nanomonsv">nanomonsv</a> software, which is expected to exclude many false positives as well as improve computational cost. This is made by aligning 30 Nanopore sequencing data from Human Pangenome Reference Consortium to the GRCh38 reference genome (obtained from <a href="https://console.cloud.google.com/storage/browser/genomics-public-data/resources/broad/hg38/v0;tab=objects">here</a>) with <a href="https://github.com/lh3/minimap2">minimap2</a> version 2.24. When you use these control panels and publish, do not forget to credit to <a href="https://humanpangenome.org/data-use-protocol/">HPRC</a>!

opencc-by-4.0Mar 2024View details →

Supplementary material: Negative valence in Obsessive-Compulsive Disorder: A worldwide mega-analysis of task-based functional neuroimaging data of the ENIGMA-OCD consortium

The ridge plots attached here accompany the supplement to the manuscript Negative valence in Obsessive-Compulsive Disorder: A worldwide mega-analysis of task-based functional neuroimaging data of the ENIGMA-OCD consortium (Dzinalija et al., 2024). These are full results of Figures 1, 2C, and 3C of the manuscript and Figures S3, S5, S7 and S9 of the supplement depicting whole-brain Bayesian multilevel models run using the Regional Bayesian Analysis toolbox (RBA; Chen et al., 2019). Whole-brain analyses were parcelated into the Schaefer-Yeo 7-network 200-parcel cortical atlas (Schaefer et al., 2018) and the Melbourne 32-region subcortical atlas (Tian et al., 2020). Results are presented according to contrast of interests: [Negative > Neutral], [OCD > Neutral], [Threat > Neutral], and [OCD > Threat], and effects of interest: [Diagnosis = OCD or HC], [MED = medication], [AO = age of onset], [YBOCS = OCD severity], and [Intercept = task effect].  P+ values denote the probability that there is increased brain activation in a given region of the Schaefer 200-parcel 7-network cortical atlas and Melbourne 32-region subcortical atlas. We used the guidelines proposed by Chen et al. (2019) to infer credibility of evidence, namely taking a positive posterior probability (P+) of <0.10 or >0.90 as indication of moderate evidence and, <0.05 or >0.95 or <0.025 or >0.975 as strong or very strong evidence, respectively. To interpret the pairwise comparisons presented as Group1-vs-Group2, posterior distributions to the right of the green no-effect line represent regions in which individuals in Group 1 show credible evidence for higher activation than individuals in Group 2. Regions with posterior distributions to the left of this line show credible evidence for higher activity in Group 2 than in Group 1.  (Darker) red color represents regions in which individuals in Group 1 show moderate-to-very-strong evidence for higher activation than Group 2. (Darker) blue color represents regions in which Group 2 show moderate-to-very-strong evidence for higher activation than Group 1. Grey color represents regions in which there is no strong evidence of a difference between Group 1 and Group 2. Schaefer-Yeo 200-parcel atlas name abbreviations can be retrieved <a href="https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/brain_parcellation/Schaefer2018_LocalGlobal/Parcellations">via this link.</a>

opencc-by-4.0Sep 2017View details →

CATCH-EyoU Work Package 2 Dataset 2.1a - Full Consortium Collection of Literature Matrix

The dataset includes one master spreadsheet containing literatures searched, catalogued and summarised in the fields of Cultural Studies, Education, History, Media and Communication, Philosophy, Political Science, Psychology and Sociology, which contains 770 selected texts.   The aims of the data collected are to produce an integrated theory that builds on the findings of different disciplines (Cultural Studies, Education, History, Media and Communication, Philosophy, Political Science, Psychology and Sociology) focused on the understanding of factors and processes (from the macro social level to the social and psychological level), within the different life contexts, that promote or hinder youth active citizenship in EU.   It is possible that similar databases of literature around Europe, Young People and Active Citizenship across the fields of Cultural Studies, Education, History, Media and Communication, Philosophy, Political Science, Psychology and Sociology exist in other forms, perhaps collected for studies on one or more of the included disciplines, but we do not currently have access to a similar repository.   With that said, it is highly unlikely that an exact dataset corresponding to the specifics of this study exist in any form elsewhere, thus justifying the creation of new data for this study in the absence of suitable existing data. Data collected here will bridge the gap between global aggregated literatures on youth and citizenship separated by discipline on the one hand, and a new dataset offering an integrated literature analysis of different fields of study.   The data sources are available in bibliographic format and attached via csv document.   The dataset relies on the following information taken from the data sources: specific identifying information about the text itself (title/author/year/publisher); and abstract or summarizing information either taken directly from the text or summarized by the researcher.   Finally, the aggregated literature review spreadsheet constitutes raw data which can be reused by researchers who want to compare our data with similar data collected in different countries, or to perform textual analysis (content analysis and/or data mining) on our data.

opencc-by-4.0May 2024View details →

Design of a new model yeast consortium for ecological studies of enological fermentation

Dataset describing the characterization of a new 6-species yeast consortium representative of wine yeast diversity, as well as its application as proof-of-concept to explore the diversity-functionnality relationship in microbial community. It includes the data, scripts, figures, tables, and additional informations pertaining to the article "Design of a new model yeast consortium for ecological studies of enological fermentation" to be submitted.

opencc-by-4.0May 2022View details →

First release of PLATO consortium stellar limb-darkening coefficients

First official grid of stellar limb-darkening coefficients and intensity profiles computed by the consortium of the PLAnetary Transits and Oscillations of stars (PLATO) Working Package 122400. Linked to the paper "First release of PLATO consortium stellar limb-darkening coefficients", published on the Research Notes of the American Astronomical Society (RNAAS).

opencc-by-4.0Feb 2017View details →

PanDDA analysis of BRD1 screened against 3D-Fragment-Consortium Fragment Library (HTML Summary)

Interactive summary page for "PanDDA analysis of BRD1 screened against 3D-Fragment-Consortium Fragment Library". Please click on "0_index.html" in the "Files" section to open the interactive summary. All datasets are also available as combined zip files from https://zenodo.org/record/48769 .

opencc-by-4.0Aug 2023View details →

LICROX- Consortium General Assembly and Open Symposium_17-18 July 2023

Final video of the LICROX project, with images and interviews from the final Consortium Meeting and Open Symposiums held in Tarragona on 17 and 18 July 2023.

opencc-by-4.0Aug 2020View details →

Figure 12 in Сarbon fluxes intensity from substrates and phototrophic consortiums of the photic zones in Montenegro caves

Figure 12. GPP per unit weight of dry phytomass of consortiums of the photic zones in Montenegro caves.

opencc-by-4.0Jan 2023View details →

Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium

Dataset includes 2.5 hours real-world data, for one participant from each of the technical validation study cohorts: ongestive heart failure (CHF), chronic obstructive pulmonary disease (COPD), healthy adult (HA), multiple sclerosis (MS), Parkinson’s (PD) and proximal femoral facture (PFF) linked to the manuscript entitled ‘Assessing real-world gait with digital technology? Validation, insights, and recommendations from the Mobilise-D consortium’.  The attached documentation has 6 datasets and a README document. The MOBILISE-D project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No. 820820. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation program and the European Federation of Pharmaceutical Industries and Associations (EFPIA). Content on this publication reflects the author’s view and neither IMI nor the European Union, EFPIA, or any Associated Partners are responsible for any use that may be made of the information contained herein.

Fig. 17 in Consortium of European TaXonomic Facilities (CETAF) best practices in electronic publishing in taXonomy

Fig. 17. Open Access benefits, from Aston University Library Services (available from https://www.yearofopen.org/march-open-perspective-open-access/).

Fig. 15 in Consortium of European TaXonomic Facilities (CETAF) best practices in electronic publishing in taXonomy

Fig. 15. Different routes for disseminating scientific publications (Cabut & Larousserie 2013, redrawn by Laurence Bénichou from Infographie du Monde).

Fig. 14 in Consortium of European TaXonomic Facilities (CETAF) best practices in electronic publishing in taXonomy

Fig. 14. Scholar production costs. Four steps are needed to produce scholar papers, of which three are publicly-funded. In the first scenario, the library pays back the final product by subscription to the publisher while in the second, the publishing costs are supported by the publisher (commercial or institutional) and then the access is free for the reader.

Fig. 13 in Consortium of European TaXonomic Facilities (CETAF) best practices in electronic publishing in taXonomy

Fig. 13. The authorships highlighted in yellow are cited nowhere else in the article and yet they are listed in the references section (Schott & Evans 2016).

Fig. 12 in Consortium of European TaXonomic Facilities (CETAF) best practices in electronic publishing in taXonomy

Fig. 12. Here "Bleeker, 1857" is considered by the authors as a bibliographical reference and listed as such under the references section although it has not been cited elsewhere in the text (Tucker et al. 2016).

Fig. 6 in Consortium of European TaXonomic Facilities (CETAF) best practices in electronic publishing in taXonomy

Fig. 6. Authorships formally presented as references, those in yellow are listed in the references section whereas those in orange are not considered as bibliographic references. A. Musavu Moussavou (2017). B. Mendoza-Garfias et al. (2017).