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39 results for “Data Management System”
University Learning Management System xAPI data for the ILEDA project
<p>Anonymized data in xAPI format collected from learning management systems (Moodle and LAMS) for the ILEDA (2021-1-BG01-KA220-HED-000031121) project https://ileda.eu/ileda-project. The dataset contains 306,741 records of 829 individuals participating in eight different blended learning courses following either a flipped classroom methodology or a project-based learning methodology from four universities: University of Eastern Finland (Finland), University of León (Spain), Belgrade Metropolitan University (Serbia) and Sofia University (Bulgaria).</p>
Data and Code from: On-farm land management strategies and production challenges in United States Organic Agricultural Systems.
<p>This repository contains data and code used in:</p> <p>Isaac Mpanga, Russel Trondstad, Jessica Guo, David LeBauer, and John Omololu, 2021. On-farm land management strategies and production challenges in United States Organic Agricultural Systems. Current Research in Environmental Sustainability.</p> <p>It provides USDA Surveys of Agricultural Production from 2008-2019 to investigate state and national trends by state in organic farm area, number, and sales, as well to evaluate national trends in on-farm land-use practices and challenges facing US organic production.</p> <p>It also includes code used to transform, visualize, and analyze the data, and derived data products - notably organic farm area and sales with values imputed to correct for redacted state level measures.</p>
Data set on soil physicochemical parameters, biomass accumulation and carbon credit generation in different management systems in Rio Verde, GO, Brazil
<h1>Description</h1> <p>This repository contains a comprehensive dataset focused on soil organic carbon and its role in mitigating climate change through carbon sequestration on agricultural lands in Rio Verde, GO, Brazil. With the global imperative to reduce anthropogenic CO2 emissions, our data highlights the effectiveness of no-till agricultural practices in both improving soil quality and enhancing carbon storage. This collection represents extensive soil and biomass sampling from five distinct areas within the Cerrado region, utilizing three priority management systems:</p> <p>No-till with soybean and maize in sequence under rainfed conditions. No-till with soybean and maize in sequence with central pivot irrigation. First and second cuts of sugarcane. The samples were meticulously collected post-harvest and used to estimate both soil biomass accumulation and carbon stock indices. A thorough analysis of the soil's physicochemical parameters was conducted for the 0-20 cm soil profile in each area. This dataset not only provides a valuable resource for studying the impact of different no-till practices on carbon sequestration but also serves as a critical input for modeling future contributions of conservation management systems to carbon trading markets.</p> <div> <div> </div> <div> <h2>Data Contents</h2> </div> <p>Soil organic carbon measurements for various no-till systems. Biomass accumulation data post-harvest. Carbon stock indices derived from biomass samples. Detailed physicochemical profiles of soil samples.</p> <div> <h2>Significance</h2> </div> <p>This dataset is pivotal for researchers and policymakers focusing on the potentials of agricultural carbon sequestration and its implications for carbon trading schemes. It offers insights into the current contributions of no-till conservation management systems and aids in the development of future strategies to enhance carbon</p> <h1>Metadata Description and Script</h1> </div> <p>This repository contains two key data files that encapsulate diverse aspects of soil physicochemical parameters, biomass accumulation, and carbon credit generation across different management systems in Rio Verde, GO, Brazil. Below are descriptions of each file's contents and structure.</p> <div> <h2>all.txt</h2> </div> <p>This text file presents aggregated data from various sites under different agricultural management systems. Each row in the dataset represents measurements from distinct sample plots, with the following fields:</p> <ul> <li><code>Sites</code> - Identifier for the plot location.</li> <li><code>SB</code> - Soil bulk density (g/cm³).</li> <li><code>SOC</code> - Soil organic carbon (%).</li> <li><code>Stock</code> - Carbon stock (ton/ha).</li> <li><code>Biomass</code> - Biomass accumulation (ton/ha).</li> <li><code>Credits</code> - Estimated carbon credits (ton CO2 equivalent/ha).</li> </ul> <div> <h2>Quimica.xlsx</h2> </div> <p>This Excel file provides detailed physicochemical analyses of soil samples from different management zones in the study area. The data is structured to support in-depth analysis of soil characteristics influencing carbon sequestration capabilities. Each sheet in the workbook corresponds to a specific area, with columns typically representing:</p> <ul> <li><code>pH</code> - Soil pH, indicating the acidity or alkalinity.</li> <li><code>EC</code> - Electrical conductivity (dS/m).</li> <li><code>Cation Exchange Capacity (CEC):</code> - (meq/100g).</li> <li><code>Organipont c Matter:</code> - (%).</li> <li><code>NPK levels</code> - Concentrations of Nitrogen (N), Phosphorus (P), and Potassium (K).</li> </ul>
Illustrative Darwin core archive to input data on a citizen science platform from a collection management system
<p>Illustrative DwC archive to send data from a collection management system to a citizen sciences platform. This illustrative archive displays the specimens used for the trans-institutional and trans-platform pilot project held in the frame of ICEDIG.</p> <p>Further description of its content in the milestone28 document, worpackage 5.2 of the ICEDIG project.</p>
Example structure of data sent from a citizen science platformback to a collection management system, multi-determined case
<p>Illustrative example of data format following Darwin Core sent back from a citizen science platform to the relevant collection management system. Multi-determined herbarium sheet case : http://coldb.mnhn.fr/catalognumber/mnhn/p/p01978557</p> <p>Illustration of the milestone28 document, worpackage 5.2 of the ICEDIG project.</p>
Example structure of data sent from a citizen science platformback to a collection management system, simple case
<p>Illustrative example of data format following Darwin Core sent back from a citizen science platform to the relevant collection management system. Simple case : http://coldb.mnhn.fr/catalognumber/mnhn/p/p03558024</p> <p>Illustration of the milestone28 document, worpackage 5.2 of the ICEDIG project.</p>
Example structure of data sent from a collection management system to a citizen science platform, multi-imaged case
<p>Illustrative example of data format following Darwin Core to send from a collection management system to a citizen science platform. Multi-imaged vertebrate specimen case : http://coldb.mnhn.fr/catalognumber/mnhn/zo/2013-152</p> <p>Illustration of the milestone28 document, worpackage 5.2 of the ICEDIG project.</p>
Example structure of data sent from a collection management system to a citizen science platform, simple case
<p>Illustrative example of data format following Darwin Core to send from a collection management system to a citizen science platform. Simple case : http://coldb.mnhn.fr/catalognumber/mnhn/p/p03558024</p> <p>Illustration of the milestone28 document, worpackage 5.2 of the ICEDIG project.</p>
Experimental Data of Edge Energy Management System (EEMS)
<p>Readme>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>><br> This data repository contains the experimental data of low-voltage and <br> industrial settings. Separate folders are provided for both data artefacts.</p> <p>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>></p> <p>Low Voltage Residential Settings >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>><br> Different sub-Folders are provided with respect to the different <br> combination of electrical load</p> <p>Each folder contains .txt file</p> <p>This File Contains Timestamp such that date and time are separated by "!".<br> After parsing time, Voltage and Current are separated by the "Current".<br> Then each voltage and current waveforms can be further parsed by "@@@"<br> because non-consecutive waveform signals are separated using this symbol in <br> project. Furthermore, the variable slab during data acquisition is provided <br> at the end of .txt file and can be parsed using the term "Const"</p> <p>This data parsing process is also provided in all phase calculation files.</p> <p>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>></p> <p>Industrial Islanded Power System >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>><br> This Folder contains the data acquired from 15 diesel gensets. Their <br> operational parameters are logged in MySQL database and are presented using<br> LAMP server. This MySQL data is provided as CSV file in this folder.</p> <p>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>></p> <p> </p>
Data from: Hurry Up and Wait: Managing the Inherent Mismatches in Timescales in Natural and Artificial Photosynthetic Systems
<p>Houle, Frances A.; Yano, Junko; Ager, Joel W.;<br> Hurry Up and Wait: Managing the Inherent Mismatches in Timescales in<br> Natural and Artificial Photosynthetic Systems</p> <p><strong>Files</strong><br> Supplementary data coupled reaction-transport and cascades.xlxs<br> Input parameters for Kinetiscope calculations and associated figure data</p> <p>CO2R microkinetic model-DRC.ipynb<br> CO2R microkinetic model-DRC.pdf<br> Jupyter notebook and pdf for degree of rate control in CO2 reduction<br> Packages used:<br> Python: 3.7.7<br> Numpy: 1.21.5<br> SciPy: 1.7.3<br> Matplotlib: 3.5.1</p> <p>Wang 2018 Pathway 1 only DRC.ipynb<br> Wang 2018 Pathway 1 only DRC.pdf<br> Jupyter notebook and pdf for degree of rate control photoelectrocatalytic water oxidation<br> Python: 3.7.7<br> Numpy: 1.21.5<br> SciPy: 1.7.3<br> mpmath: 1.2.1<br> Matplotlib: 3.5.1</p>
Data from: A natural gene drive system influences bovine tuberculosis susceptibility in African buffalo: possible implications for disease management
Bovine tuberculosis (BTB) is endemic to the African buffalo (Syncerus caffer) of Hluhluwe-iMfolozi Park (HiP) and Kruger National Park, South Africa. In HiP, the disease has been actively managed since 1999 through a test-and-cull procedure targeting BTB-positive buffalo. Prior studies in Kruger showed associations between microsatellite alleles, BTB and body condition. A sex chromosomal meiotic drive, a form of natural gene drive, was hypothesized to be ultimately responsible. These associations indicate high-frequency occurrence of two types of male-deleterious alleles (or multiple-allele haplotypes). One type negatively affects body condition and BTB resistance in both sexes. The other type has sexually antagonistic effects: negative in males but positive in females. Here, we investigate whether a similar gene drive system is present in HiP buffalo, using 17 autosomal microsatellites and microsatellite-derived Y-chromosomal haplotypes from 401 individuals, culled in 2002-2004. We show that the association between autosomal microsatellite alleles and BTB susceptibility detected in Kruger, is also present in HiP. Further, Y-haplotype frequency dynamics indicated that a sex chromosomal meiotic drive also occurred in HiP. BTB was associated with negative selection of male-deleterious alleles in HiP, unlike positive selection in Kruger. Birth sex ratios were female-biased. We attribute negative selection and female-biased sex ratios in HiP to the absence of a Y-chromosomal sex-ratio distorter. This distorter has been hypothesized to contribute to positive selection of male-deleterious alleles and male-biased birth sex ratios in Kruger. As previously shown in Kruger, microsatellite alleles were only associated with male-deleterious effects in individuals born after wet pre-birth years; a phenomenon attributed to epigenetic modification. We identified two additional allele types: male-specific deleterious and beneficial alleles, with no discernible effect on females. Finally, we discuss how our findings may be used for breeding disease-free buffalo and implementing BTB test-and-cull programs.
A formative usability study of workflow management systems in label-free digital pathology - Data and Code
<p>This repository holds the necessary data and code as well as a descriptive Readme file that was used for our publication "A formative usability study of workflow management systems in label-free digital pathology" by Markus Jelonek et al. (2022), submitted to F1000Research.</p> <p> </p> <p>Abstract:</p> <p>We present a formative usability study that investigates the usability of different<br> workflow management systems in the field of biomedical data analysis. Specifically, we study a task in the field of so-called label-free digital pathology and investigate one graphical user interface based workflow and one script-based workflow to solve the task. Our main intention is to gain first insights into the systematic study of usability in the context of biomedical image analysis, and formulate experiences and guidelines for future usability studies dealing with workflow management systems. Embedded in a specific setup dealing with label-free digital pathology, the core question behind our contribution is how usability studies for scientific workflow management can be conducted, and how they can be used systematically to improve such tools. Further, we address specific questions about the resource utilisation and management of usability studies, including the recruitment of participants as well as the design of specific workflows to be investigated.</p>
Data and R scripts for: Identifying existing management practices in the control of Striga asiatica within rice–maize systems in mid-west Madagascar
<p>Infestations by the parasitic weed genus <i>Striga</i> result in significant losses to cereal crop yields across sub-Saharan Africa. The problem disproportionately affects subsistence farmers who frequently lack access to novel technologies. Effective <i>Striga </i>management therefore requires the development of strategies utilising existing cultural management practices. We report a multi-year, landscape-scale monitoring project for <i>Striga</i> asiatica in the mid-west of Madagascar, undertaken over 2019-2020 with the aims of examining cultural, climatic and edaphic factors currently driving abundance and distribution. Long-distance transects were established across the middle-west region of Madagascar, over which <i>Striga asiatica</i> abundance in fields was estimated. Analysis of the data highlights the importance of crop variety and legumes in driving <i>Striga </i>density. Moreover, the dataset revealed significant effect of precipitation seasonality, mean temperature and altitude in determining abundance. A composite management index indicated the effect of a range of cultural practices on changes in <i>Striga </i>abundance<i>. </i>The findings support the assertion that single measures are not sufficient for the effective, long-term management of <i>Striga</i>. Furthermore, the composite score has potential as a significant guide of integrated <i>Striga </i>management beyond the geographic range of this study. </p>
eELib: Open-Source Model Library for Prosumer Power Systems and Energy Management Strategies (data)
<p>Dataset and results used for the simulations in following publication:</p> <p>Carsten Wegkamp, Henrik Wagner, Eike Niehs, Julien Essers, Marcel Lüdecke, Mattias Hadlak, Bernd Engel:<br>"<strong>eELib: Open-Source Model Library for Prosumer Power Systems and Energy Management Strategies</strong>",<br>Open Source Modelling and Simulation of Energy Systems (OSMSES) 2024, Vienna, Austria, 2024</p> <p> </p> <p>This contains the input (scenario) files for the building & grid scenario and the results of the two simulations.<br>It uses the elenia Energy Library (eELib) with release version 1.0.0: https://gitlab.com/elenia1/elenia-energy-library</p>
Illustrative Darwin core archive to output data from a citizen science platform to a collection management system
<p>Illustrative DwC archive to send data back to a collection management system from a citizen sciences platform. This illustrative archive displays the specimens used for the trans-institutional and trans-platform pilot project held in the frame of ICEDIG.</p> <p>Further description of its content in the milestone28 document, worpackage 5.2 of the ICEDIG project.</p>
Demo-Dataset for publication "FAIR workflows in Earth system modelling: a use case with semantic data management"
<p>This demodataset is intended to be used to test the workflow described in the publication by Lennartz & Schlemmer "FAIR workflows in Earth System modelling: a use case with semantic data management". It contains example model output for an arbitrary biogeochemical model tracer (here: dissolved organic carbon, DOC) from an ocean model as a 4-dimensional dataset (latitude, longitude, depth, time), the corresponding grid point locations as well as a textfile specifying parameter inputs for the model. The file structure is adapted for seamless integration into the workflow described in Lennartz & Schlemmer, which builds on the open source semantic research data management system LinkAhead. The dataset contains the following structure: The folder DataAnalysis stores data required for data analysis, such as the grid point locations in the file TMM_grid_v2018a.mat. The folder SimulationData stores model output in the folder 2022_TMM, containing the parameter input file nl_in.txt and the model output TR_monthly.mat. Related instructions can be accessed here: https://gitlab.com/salexan/fairworkflows-demodataset .</p>
A Scalable Data Management System Data Model facilitating the integration of any inspection system and the automated data digitalization process.
<p>In the context of the EU-funded project PILOTING (No. 871542), a scalable Data Management System (DMS) was deployed and facilitated the easy integration of nine different robotic systems and various payloads and the storing of all the data observations produced during the inspections. In particular, a three-phase methodology was adopted for the creation of the DMS Data Model (DMS-DM) in order to define the architectural design of the DMS. <br> The first phase was to semantically define the entities of the PILOTING ecosystem, identifying assets and activities that were important to the data providers, and including them in the data model design. The second phase was to identify relationships between the entities, focusing on information that must pre-exist for entities to be semantically accurate, hierarchies between entities, especially physical assets, and the data needed to form the inspection plan. For the third phase, the information collected by the previous two stages of the data model construction was used to create the overall data model, taking into consideration the possible integration with third parties and the needs of the I&M Visualization portal. <br> The constructed document is attempted to present the designed Entity-Relationship-Diagram (ERD) of the DMS-DM. Additional definitions of the existing entities and the relations between them are also depicted. </p>
A Versatile and Secure Data Management System API facilitating the Interconnection of any software component and Easy Data Access.
<p>In the context of the EU-funded project PILOTING (No. 871542), a versatile Data Management System (DMS) was deployed and facilitated the easy integration of nine different robotic systems and various payloads and the storing of all the data observations produced during the inspections. The DMS is designed under the DMS-Data Model (DMS-DM) and operates on top of a representational state transfer (REST) application programming interface (API) that provides a simplified way to exchange data through HTTP(S) requests from a client to the server. One of its key advantages is that it provides a great deal of flexibility so the model could accommodate extensions if needed. Data is not tied to resources or methods, so REST can handle multiple types of calls, return different data formats and even change structurally with the correct implementation of hypermedia. <br> It supports CRUD operations via GET, POST, PUT, PATCH, and DELETE HTTP methods and stores the data on a PostgreSQL object-relational database system. The REST API has been created with Python's Django (web framework) and Django REST Framework, a powerful and flexible toolkit for building Web APIs. <br> The constructed document presents the communication endpoints (DMS API’s Uniform Resource Identifiers (URIs)) under which an authorized user can have access to the DMS API and subsequently to the collected data. </p>
Data from: Pest management science often disregards farming system complexities
<p><span>Since the 1940s, pesticide-intensive crop protection has sustained food security but also caused pervasive impacts on biodiversity, environmental integrity and human health. Here, we employ a systematic literature review to structurally analyze pest management science in 65 developing countries. Within a corpus of 3,407 publications, we find that taxonomic coverage is skewed towards a subset of 48 herbivores. Simplified contexts are commonplace: 48% of studies are performed within laboratory confines. 80% treat management tactics in an isolated rather than integrated fashion. 83% consider no more than two out of 15 farming system variables. Limited attention is devoted to pest-pathogen or pest-pollinator interplay, trophic interactions across ecosystem compartments or natural pest regulation. By overlooking social strata, the sizable scientific progress on agroecological management translates into slow farm-level uptake. We argue that the scientific enterprise should integrate system complexity to chart sustainable trajectories for global agriculture and achieve transformative change on the ground.</span></p>
Development of a Dietary Intervention Model Based on Genetic Data as an Implementation of a Healthy Lifestyle in the Management of Systemic Lupus Erythematosus Patients
ClinicalTrials.gov study NCT07183007. IPD Sharing: NO. Countries: 1. Publications: 1.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.