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1,069 results for “Data managment”
Figure 1 from: Irawan D, Rachmi C (2018) Promoting data sharing among Indonesian scientists: A proposal of generic university-level Research Data Management Plan (RDMP). Research Ideas and Outcomes 4: e28163. https://doi.org/10.3897/rio.4.e28163
Figure 1 Current situation of data lifecycle (Irawan 2018).
Data for "Response of global forest management to changes in future wood demand"
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Figure 2 from: Kress W, Knapp S, Stoev P, Penev L (2012) On the front line of modern data-management and Open Access publishing: Two years of PhytoKeys – the fastest growing journal in plant systematics. PhytoKeys 19: 1-8. https://doi.org/10.3897/phytokeys.19.4501
Figure 2 - Taxonomic distribution by family of the published nomenclatural novelties in PhytoKeys.
Data from: Rapid CRISPR-Cas13a genetic identification enables new opportunities for listed Chinook salmon management
<p>Figures and intermediate data files for https://github.com/MacCampbell/chinook-sherlock</p>
Data from: Subalpine vegetation changes in the Eastern Sudetes (1973–2021): Effects of abandonment, conservation management and avalanches
<p>This dataset contains the original data used in the article:</p> <p>Klinkovská K., Kučerová A., Pustková Š., Rohel J., Slachová K., Sobotka V., Szokala D., Danihelka J., Kočí M., Šmerdová E. & Chytrý M. (2023) Subalpine vegetation changes in the Eastern Sudetes (1973–2021): effects of abandonment, conservation management and avalanches. <em>Applied Vegetation Science</em>, 26, e12711. <a href="https://doi.org/10.1111/avsc.12711">https://doi.org/10.1111/avsc.12711</a></p> <p>The data contain plant species composition from vegetation plots repeatedly surveyed in the Hrubý Jeseník Mountains (Eastern Sudetes, Czech Republic). Vegetation plots surveyed by Leoš Bureš and Zuzana Burešová in 1973–1978 were resurveyed in 2004–2010 by Martin Kočí and Leo Bureš and resurveyed again in 2021 by the authors of this dataset. Several new plots were also surveyed in 2004–2010 and resurveyed in 2021. In the 1970s, plot locations were related to patches of a detailed vegetation map. In the 2000s, plot locations were measured using GPS with an uncertainty of less than 10 m. In 2021, plots were localized using differential GPS with ~5 cm accuracy (Topcon HiPer SR with Getac PS336 Data Collector) in each corner of the plot. These coordinates are stored in the fields Longitude, Longitude2, Longitude3, Longitude4, Latitude, Latitude2, Latitude3 and Latitude4 in the dataset.</p> <p>The dataset contains records of 148 vegetation plots, of which 66 were sampled three times (1970s, 2000s, 2021) and 82 were sampled twice (2000s, 2021), i.e. 362 vegetation-plot records in total. Their locations are shown at <a href="https://arcg.is/0uSrz9">https://arcg.is/0uSrz9</a>.</p> <p>Plot size and shape varied by vegetation type. Repeated sampling always used the same plot size as the previous sampling. Most plots were squares of 100 m<sup>2</sup> in woodlands and 16 m<sup>2</sup> in grasslands or rectangles of 10 m<sup>2</sup> in springs. All species of vascular plants were recorded in each plot, and their cover was estimated using the nine-grade Braun-Blanquet scale (Westhoff & van der Maarel, 1978). Bryophytes and lichens were recorded in only some plots, focusing on the dominant species.</p> <p>In 2021, soil samples were collected from the mineral soil horizon at 5–10 cm depth from four places within each plot. We mixed these samples for each plot and measured the soil pH and electrical conductivity of a mixed sample in a soil-water suspension (weight ratio 1:2.5) using the HQ40D digital multimeter. These data are found in the fields Soil_ph and Conduct.</p> <p>Plots were divided into managed and unmanaged based on the overlay of plot coordinates with GIS layers indicating the areas managed for conservation purposes in the last ten years provided by the Administration of the Landscape Protected Area Jeseníky (field Mown). In addition, plots were divided into affected and unaffected by the 2019 avalanche based on the positions of damaged trees observed in the field (field Avalanch).</p> <p>The structure of header data follows the structure of the ReSurveyEurope Database (<a href="http://euroveg.org/eva-database-re-survey-europe">http://euroveg.org/eva-database-re-survey-europe</a>). In addition, the vegetation type of each plot record in the 1970s, 2000s and 2021 is given in the fields Class_2021, Class_2000 and Class_1970, respectively</p> <p>The data on species composition and environmental variables are provided in two formats:</p> <ul> <li>Turboveg 2 database (see <a href="https://www.synbiosys.alterra.nl/turboveg/">https://www.synbiosys.alterra.nl/turboveg/</a>) – file <strong>TurbovegDbBackup_Jeseniky_resurvey.zip</strong>. To use this dataset in Turboveg, the database dictionary (TurbovegDdBackup_Default dictionary.zip) and species list (TurbovegSlBackup_Czechia_slovakia_2015.zip) have to be installed.</li> <li>Two TXT files with columns separated by tabs: <ul> <li><strong>Jeseniky_resurvey_species.txt</strong> contains the percentage covers of plant species in plots. Plant nomenclature harmonized according to Kaplan et al. (2019). Bryophytes, vernal species <em>Anemone nemorosa </em>and <em>Cardamine pratensis</em>, hybrids and species that could not be accurately identified were excluded. Woody species occurring in different layers were merged within each plot.</li> <li><strong>Jeseniky_resurvey_head.txt</strong> includes information about the number of species in each plot (spe.nr), the number and proportion of threatened species (IUCN categories CR, EN, VU, columns end.nr and perc.end) and unweighted means of Ellenberg-type indicator values for light (Light_IV), temperature (Temp_IV), moisture (Moist_IV), soil reaction (React_IV) and nutrients (Nutr_IV) used to test changes in these variables through time.</li> </ul> </li> </ul> <p>These data are also stored in the Czech National Phytosociological Database (Chytrý & Rafajová 2003; <a href="https://botzool.cz/vegsci/phytosociologicalDb">https://botzool.cz/vegsci/phytosociologicalDb</a>) and the ReSurveyEurope database (<a href="http://euroveg.org/eva-database-re-survey-europe">http://euroveg.org/eva-database-re-survey-europe</a>).</p>
Assessment of Awake Surgery With Electrocorticographic Recordings in the Management of Gliomas and Correlation With Imaging Data (ECoG)
ClinicalTrials.gov study NCT05875935. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Reflux Disease Therapy in the Management of Childhood Asthma-data Entry and Analysis Only
ClinicalTrials.gov study NCT01536457. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Johns Hopkins Weight Management Center Patient Data
ClinicalTrials.gov study NCT03321565. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Real-World Data of Clinicopathological Characteristics and Management of Breast Cancer Patients According to HER2 Status
ClinicalTrials.gov study NCT05217381. IPD Sharing: Not stated. Countries: 1. Publications: 0.
This Study Will Collect Clinical and Patient Reported Satisfaction Data From Males Requiring Urine Output Management Overnight in the Home Setting.
ClinicalTrials.gov study NCT06850259. IPD Sharing: NO. Countries: 1. Publications: 0.
Role of Ablative Radiotherapy in the Management of Metastatic Disease: A Patient Data Registry
ClinicalTrials.gov study NCT04085029. IPD Sharing: NO. Countries: 1. Publications: 0.
A Study Collecting Remote Data in People With an Overweight Condition or Obesity on a Weight Management Program
ClinicalTrials.gov study NCT06805539. IPD Sharing: YES. Countries: 1. Publications: 0.
Coordinating and Data Management Center for the Consortium for the Study of Chronic Pancreatitis, Diabetes, and Pancreatic Cancer
ClinicalTrials.gov study NCT03058926. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Retrospective Data Analysis of VitalCare Targeted Population Management on Scott and White Chronically Ill Beneficiaries
ClinicalTrials.gov study NCT01912430. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Use of Digital Tomosynthesis for Detection and Case Management of Scaphoid and Distal Radius Fractures: A VolumeRAD Data Collection Study
ClinicalTrials.gov study NCT03856450. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Remote Management of Diabetic Patients Via Data Transmission by Accu-Chek 360 Software
ClinicalTrials.gov study NCT00956800. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Development of Clinical Evidence for Optimal Management of Adrenal Diseases Based on Real-World Data
ClinicalTrials.gov study NCT06229405. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Prognosis and Management of Infective Endocarditis Using the Clinical Data Warehouse From AP-HP
ClinicalTrials.gov study NCT06957119. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Data from: An individual-based model of seed and rhizome propagated perennial plant species and sustainable management of Sorghum halepense in soybean production systems in Argentina
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Data from: Data management, archiving and sharing for biologists and the role of research institutions in the technology-oriented age
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.