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D1.4 - Consolidated OA data set for responsible research practices and trust in science: POIESIS National and Regional Database

Deliverable 1.4 of the POIESIS project is a consolidated open access data set for responsible research practices and trust in science. D1.4 consists of two databases: the POIESIS National Database and the POEISIS Regional Database. The method and rationale behind the construction of all indicators in both databases are laid out in Work Package 1’s previous deliverable, D1.3 (Bauer et al., 2024). The two database are accompanied by a Guidance Sheet which provides details and relevant notes regarding the structure of the two databases.

Data Set

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Example data sets to accompany SeismicUnixGui tutorial (>V87.1)

<h1>SeismicUnixGui example data set for use with SeismicUnixGui (>V87.x)</h1> The data set that is included was collected (2018) during a week-long summer orientation internship program hosted (RESESS-Research Experience in Solid Earth Science for Students ) operated by the Earthscope Consortium.  The data set accompanies a tutorial for use of SeismicUnixGui. SeismicUnixGui is a graphical user interface (GUI) to select parameters for Seismic Un*x (SU) modules.  Seismic Un*x (Stockwell, 1999) is a widely distributed free software package for processing seismic reflection and signal processing.  Perl/Tk is a mature, well-documented and free object-oriented graphical user interface for Perl.   In a classroom environment, shell scripting of SU modules engages students and helps focus on the theoretical limitations and strengths of signal processing.  However, complex interactive processing stages, e.g., selection of optimal  stacking velocities, killing bad data traces, or spectral analysis requires advanced flows beyond the scope of  introductory classes.  In a research setting, special functionality from other free seismic processing software  such as SioSeis (UCSD-NSF) can be incorporated readily via an object-oriented style to programming. An object oriented approach is a first step toward efficient extensible programming of multi-step processes,  and a simple GUI simplifies parameter selection and decision making.  Currently, in SeismicUnixGui, Perl 5 packages  wrap nearly 300 SU modules that are used in teaching undergraduate and first-year graduate student  classes (e.g., filtering, display, velocity analysis and stacking).  Perl packages (classes) can advantageously add new functionality around each module and clarify parameter names for easier usage.  For example, through  the use of methods, packages can isolate the user from repetitive control structures, as well as replace the  names of abbreviated parameters with self-describing names.  Moose, an extension of the Perl 5 object system,  greatly facilitates an object-oriented style.  Perl wrappers are self-documenting via Perl programming document  markup language.

"Toy Data Set" referenced in the article "A deep-learning based analysis framework for ultra-high throughput screening time-series data" (https://doi.org/10.1101/2024.08.22.609110)

This data set, referenced as "toy data set" in the article "A deep-learning based analysis framework for ultra-high throughput screening time-series data" (<a href="Lint-to-article">https://doi.org/10.1101/2024.08.22.609110</a>), mimics a high-throughput screening data set. To demonstrate the application of our analysis framework described in the main article this toy data set was generated. It contains in total 1536000 individual transient signals, splitted in 5 batches of each 200 plates in 1536-well plate format. Five distinct signal classes were used to resemble typical shapes encountered in biological experiments. Fequency of occurrences for each class is reported in the main article.

Data set for "Stabilization of nesquehonite for application in carbon capture utilization and storage"

The dataset contains all relavent raw data from the study titile, "Stabilization of nesquehonite for application in carbon capture utilization and storage".

set of exploration data and parameters for h24/5ad agent based model

Different set of data used for exploration, used for reproductibility, updated with HigherProp parameters

RISMEAU data set

The RISMEAU project (RISques liés aux résidus de Médicaments, biocides et antibiorésistance d’origine humaine et vétérinaire sur les ressources en EAU du bassin versant de l’Arve – Risks related to residues of pharmaceuticals and biocides, and antimicrobial resistance of human and veterinary origin on the water resources of the Arve catchment area) was implanted from 2018 to 2024 on the SIPIBEL observatory. It was devoted to the evaluation of (i) transfers of and processes related to pharmaceutical residues and biocides from both urban sludge and manure spread on fields as fertilisers, and (ii) the environmental impacts of land spreading,  in particular the ecotoxicological risks and antimicrobial resistance dissemination. The methodology was based on the physico-chemical, ecotoxicological and antimicrobial resistance (AMR) characterisation of the infiltrated water and soil matrices samples, and focused on organic waste products application at locally representative agronomic rates. This dataset can be reused by other researchers for comparison with their own investigations on this emerging topic under different contexts and conditions, and may contribute to international reviews. The database includes in total 26217 values, measured on 351 samples of organic waste products (OWP), soil, infiltrated water, earthworms, plants with 3136 usual physico-chemical values, 15469 values on pharmaceuticals and biocides concentrations, 6827 bioassay values (ecotoxicity and phytotoxicity) and 785 values of antimicrobial resistance indicators.

Data set from the 6G-SANDBOX platforms benchmarking and assessment for different documented trial networks - Oulu facility

This data set covers core network and end-to-end measurements at the Oulu facility, part of the 6G-SANDBOX infrastructure.

Data set from the 6G-SANDBOX platforms benchmarking and assessment for different documented trial networks - Malaga facility

This data set covers core network and end-to-end measurements at the Malaga facility, part of the 6G-SANDBOX infrastructure.

Data set from the 6G-SANDBOX platforms benchmarking and assessment for different documented trial networks - Berlin facility

This data set covers core network and end-to-end measurements at the Berlin facility, part of the 6G-SANDBOX infrastructure.

Data set from the 6G-SANDBOX platforms benchmarking and assessment for different documented trial networks - Athens facility

This data set covers core network and end-to-end measurements at the Athens facility, part of the 6G-SANDBOX infrastructure.

Data set for "Multi-frequency SuperDARN HF radar observations of the ionospheric response to the October 2023 annular solar eclipse"

This data set contains rawACF and sounding mode data files from the Christmas Valley East (CVE) SuperDARN radar and manually scaled ionogram parameters from the Boulder (BC840) Digisonde used in the paper "Multi-frequency SuperDARN HF radar observations of the ionospheric response to the October 2023 annular solar eclipse" submitted to Geophysical Research Letters.

opencc-by-4.0Jul 2024View details →

data_set for "Time-resolved sensing of electromagnetic fields with single-electron interferometry"

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Data set: Evidence for the validity of the Attitudes toward Sexual Behaviours Scale (ASBS) with Canadian young people

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Data set "Correlation of in vitro biofilm formation capacity with persistence of antibiotic-resistant Escherichia coli on fresh leafy produce"

This repository contains the metadata and raw data for the analysis of an in vitro screening of 174 antibiotic-resistance E. coli strains isolated from various sources to evaluate their ability and strength to form biofilms. This repository contains the raw data to characterise a subset of eleven E. coli strains in their population dynamics and persistance on lamb's lettuce (Valerianella locusta) leaves. Raw images (czi format) of live/dead stain of selected strains in V. locusta leaves are provided. Data analysis and image processing scripts can be found in the GitHub repository associated to the manuscript.

Data Set available for Liquid Biopsy of CML Diagnosis

Chronic Myeloid Leukemia, CML, is caused in patients with myeloproliferative disorders by the presence of BCR::ABL1.  The research discussed the integration of microfluidic chips with biosensors for the purpose of detecting biomarkers in peripheral blood thereby showing the raw experimental data set avaialble, liquid bipsy sample set available and Calculation for methods and data Simulation along with graphs, which could obviate the need for painful biopsies, thereby improving diagnostic accuracy and accessibility.

Time-Motion Data Set of Construction Work

This open-access dataset, provides a detailed time-motion study of construction work, specifically focusing on MEP (Mechanical, Electrical, and Plumbing) activities. The dataset is intended to facilitate research and analysis to improve operational efficiency and safety within the construction industry. It includes anonymized and pseudonymized data, ensuring privacy while still offering valuable insights into worker activities. Contents: (1)Time-motion study dataset: Captures categorized work activities by MEP workers at a second-to-second level. (2) Description of work activities: Provides detailed classifications of the tasks performed, allowing for in-depth analysis. This dataset has been made publicly available under the CC-BY-SA license, encouraging reuse and redistribution with proper attribution and share-alike terms. By downloading the dataset, users acknowledge and agree to comply with the terms outlined above. Funding and Support: This work has been supported by the “Hukka LVI- ja sähkötöissä” (Waste in Plumbing and Electrical Work) project, funded by STUL (Electrical Contractor Association), LVI-TU (HVAC Contractor Association), and STTA (Electrical Employers Union) from Finland. This comprehensive dataset offers valuable resources for research and analysis purposes. For further information or collaboration inquiries, feel free to reach out to discuss data collection methods and potential research partnerships: olli.seppanen@aalto.fi & christopher.gorsch@vtt.fi.

Data set for "EghiFit: Smartphone based Behaviour Monitoring and Health Recommendation in a Weight Loss Intervention Study"

Dataset has been created for "EghiFit: Smartphone based Behaviour Monitoring and Health Recommendation in a Weight Loss Intervention Study" paper. We have created a smartphone based behaviour monitoring and recommendation system to aid patients recruited in a weight loss intervention programme. The main interaction element for the patients is EghiFit application which was used in context of this dataset for data acquisition and secure transmission to our servers. The data consists of application usage per patient, steps achieved, nutritional information of meals logged, heart rate data, interaction data and more. For more information about the dataset, please take a look at readme.md file and our paper.

opencc-by-4.0Oct 2024View details →

Consistency Bias Data Sets

This is the data set correspond to the calculation of Consistency Bias. This has been submitted for publication to a journal and will be linked directly to the manuscript when published.