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1,069 results for “Data Management”
Data from: Identifying priority areas for spatial management of mixed fisheries using ensemble of multi-species distribution models. Panzeri D. et al., 2023, Fish and Fisheries
<p>Panzeri D.<sup>1</sup>, Russo T., Arneri E., Carlucci R., Cossarini G., Isajlović I., Krstulović Šifner S., Manfredi C., Masnadi F., Reale M., Scarcella G., Solidoro C., Spedicato M.T., Vrgoč N., W. Zupa, Libralato S<sup>2</sup>.</p> <p><sup>1 </sup>dpanzeri@ogs.it<br> <sup>2 </sup>slibralato@ogs.it</p> <p>Spatial fisheries management is widely used to reduce overfishing, rebuild stocks, and protect biodiversity. However, the effectiveness and optimization of spatial measures depend on accurately identifying ecologically meaningful areas, which can be difficult in mixed fisheries. To apply a method generally to a range of target species, we developed an ensemble of species distribution models (e-SDM) that combines general additive models, generalized linear mixed models, random forest, and gradient-boosting machine methods in a training and testing protocol. The e-SDM was used to integrate density indices from two scientific bottom trawl surveys with the geopositional data, relevant oceanographic variables from the three-dimensional physical-biogeochemical operational model, and fishing effort from the vessel monitoring system. The determined best distributions for juveniles and adults are used to determine hot spots of aggregation based on single or multiple target species. We applied e-SDM to juvenile and adult stages of 10 marine demersal species representing 60% of the total demersal landings in the central areas of the Mediterranean Sea. Using the e-SDM results, hot spots of aggregation and grounds potentially more selective were identified for each species and for the target species group of otter trawl and beam trawl fisheries. The results confirm the ecological appropriateness of existing fishery restriction areas and support the identification of locations for new spatial management measures.</p> <p>Data (csv) for Panzeri et al. 2023</p> <p>1. <a href="https://zenodo.org/api/files/0b1b7af4-6a3b-481d-8d5f-57cf02d20eaa/Ensemble_density_F%26F_D.Panzeri_et_al_2023.csv">Ensemble_density_F&F_D.Panzeri_et_al_2023.csv: CSV file with density values (column pred) in terms of number of individuals (log N/km2) for each species (column sp) and life stage (column age) for each grid cell (X = longitude and Y = latitude).</a> </p> <p>2. <a href="https://zenodo.org/api/files/0b1b7af4-6a3b-481d-8d5f-57cf02d20eaa/Ensemble_density_F%26F_D.Panzeri_et_al_2023.csv">Getis_hotspot_F&F_D.Panzeri_et_al_2023.csv: CSV file with Getis ord Gi* values (column Gi) derived from the previous file 1, developed for each species and life stage for each grid cell (X = longitude and Y = latitude).</a></p> <p>3. <a href="https://zenodo.org/api/files/0b1b7af4-6a3b-481d-8d5f-57cf02d20eaa/Ensemble_density_F%26F_D.Panzeri_et_al_2023.csv">Multispecies_HotSpot_F&F_D.Panzeri_et_al_2023.csv: Frequency map expressed as the number of species for each grid cell (column freq) that has the hotspot (previous file 2) above the third quartile.</a></p> <p> </p> <p> </p>
Data from: Species delimitation in endangered groundwater salamanders: implications for aquifer management and biodiversity conservation
Open the record for dataset details and reuse information.
Data and R code for “Individual-level variation in reproductive effort in chestnut oak (Quercus montana Willd.) and black oak (Q. velutina Lam.)”, Forest Ecology and Management, 2022
Masting is a population-level reproductive strategy, where individuals synchronize large but intermittent seed production. Despite the high degree of synchrony at the population level, there can be considerable variation in reproduction among individuals (intraspecific variation). Here, we use 18 years of acorn production data from individual chestnut oak and black oak from control and thinned stands, to understand what factors influence individual differences in reproductive effort and variability. We included a variety of tree-level measurements, environmental characteristics, and measurements from tree cores to determine if certain characteristics were associated variations in reproduction. We considered both mean annual acorn production per m2 crown and interannual variation in acorn production (CV) as response variables. We also classified individuals as super producers (i.e., those that consistently produce more acorns than others), good, fair and poor producers (i.e., those that consistently produce less or have a higher number of failure years). In chestnut oak, 14% of the individuals were classified as super producers and contributed 34% of the total acorns, while poor producers made up 35% of the trees and contributed only 16% to total acorn production. In black oak, super producers (14% of the individuals) contributed 31% of total acorns and poor producers (24% of the individuals) contributed only 9% of the acorns. Diameter at breast height (DBH) was the most consistent variable for explaining intraspecific variation in reproductive effort and variability (i.e., larger individuals had higher mean acorn production for both chestnut oak and black oak, and lower CV for black oak). Other variables that influenced reproduction and variation included elevation and clay content for chestnut oak, and slope for black oak. We found no significant effect from the thinning treatment on acorn production. Our results illustrate how tree-level and environmental characte
Data from "Grassland woody plant management rapidly changes woody vegetation persistence and abiotic habitat conditions but not herbaceous community composition"
These files contain microhabitat, soil, vegetation structure, and woody plant species data used in the paper "Grassland woody plant management rapidly changes woody vegetation persistence and abiotic habitat conditions but not herbaceous community composition". The project was conducted at seven publicly accessible remnant (i.e., unplowed or old-growth) tallgrass prairie within 100 miles of Madison, Wisconsin, United States starting in the 2020 growing season and commencing following the 2022 growing season. The goal was to assess the initial effects of different management interventions on woody vegetation persistence, abiotic habitat conditions, and herbaceous community composition, including physical and chemical management interventions and their combination.
Why, what and how do European healthcare managers use performance data? Results of a survey and workshop among members of the European Hospital and Healthcare Federation (Data set; anonymised)
<p>The dataset presents results of a descriptive cross-sectional study based on a survey, delivered through an online self-reported questionnaire. The questionnaire was distributed to managers of hospitals and other health care organisations in a purposive sample of participants to the Exchange Programmes of the European Hospital and Health Care Federation (HOPE) eliciting information on the actual use of performance data in hospitals and other healthcare organisations in Europe in 2019.<br> Data collected through the online questionnaire was analysed using univariate descriptive statistics. Analyses were conducted using the R statistical program version 3.6.1. Respondents were, for certain parts of the analysis, sub-grouped by their reported managerial position and experience, as well as the type of organisation they work for. Analysis was done on a full sample of respondents, including the primary, 2019 HOPE Exchange Programme participants, and the secondary study population, 2015-2018 Exchange Programme alumni and local hosts.</p>
Livorno, Highway pilot, data management connected car
<p><strong>Scenario description</strong>: Dynamic speed adaptation due to puddle on the road</p> <p>Precondition:</p> <p>A vehicle is driving in the first lane of a “smart highway" at 90 km/h with all the devices working correctly and connected to all services needed.</p> <p>Actions or events:</p> <p>1 The puddle monitoring system of the highway trigger a puddle hazard warning for a specific extended zone.</p> <p>2 The AD car receives the information by IoT based services and sets a speed limitation according to the area interested by hazard conditions: it smoothly decelerates in order to enter in the area at the proper speed.</p> <p>3 At the end of dangerous area, as notified by the «smart road», the vehicle will recover the legally allowed cruise speed.</p> <p>Relevant situations: How the AD function interacts with different IoT input: from oneM2M platform (advisory speed limit due to puddles); from I2V (DENM, puddle hazard warning); from V2V (CAM with info from other vehicles).</p> <p><strong>Session description</strong>:</p> <p>pre-test session with only connected cars, lap of 12,3 km on the highway. Goal is to check all the system and data management.</p> <p><strong>Datasets description</strong>:</p> <p><strong>AUTOPILOT_Livorno_HighwayPilot_Vehicle_all</strong>: Data generated from the vehicle sensors</p> <p>This dataset refers to the vehicle datasets generated from the vehicle sensors during Highway Piloting in Livorno. This includes the data coming from the CAN bus and GPS. It includes following kind of dataset: Vehicle: general data (speed, battery); PositioningSystem: data from GPS; VehicleDynamics: data about dynamic (acceleration...); LateralControl: steering and lane control data</p> <p><strong>AUTOPILOT_Livorno_HighwayPilot_V2X_all</strong>: V2V messages during the Highway Pilot sessions</p> <p>This dataset refers to the V2V messages exchanged between ITS stations (vehicles and RSUs) during the Highway Piloting in Livorno.</p> <p><strong>AUTOPILOT_Livorno_HighwayPilot_IoT_all</strong>: Data extracted from IoT oneM2M platform</p> <p>This dataset refers to messages exchanged by HighwayPilot devices, applications and services across the oneM2M platform.</p>
Geriatric CO-mAnagement for Cardiology patients in the Hospital (G-COACH): outcome data
<p>The datasets reports baseline and outcome data from the 'Geriatric CO-mAnagement for Cardiology patients in the Hospital (G-COACH)' experimental study. The study evaluated the effectiveness of a geriatric co-management programme on the cardiac care units of the University Hospitals Leuven. Sample included patients aged 75 years or older. Measurements included: demographic, functional status, cognitive status, depressive symptoms, anxiety symptoms, quality of life, physical performance, readmission rates, survival.</p> <p>Please see Word document for more information.</p> <p>Please see protocols for more information:</p> <p><a href="https://clinicaltrials.gov/ct2/show/NCT02890927">https://clinicaltrials.gov/ct2/show/NCT02890927</a></p> <p><a href="https://bmjopen.bmj.com/content/8/10/e023593">https://bmjopen.bmj.com/content/8/10/e023593</a></p> <p>The evaluation study is available at https://agsjournals.onlinelibrary.wiley.com/doi/full/10.1111/jgs.17093 </p>
Data from: Deer-mediated ecosystem service vs. disservice depends on forest management intensity
MANUSCRIPT ABSTRACT <p>As global terrestrial biodiversity declines via land-use intensification, society has placed increasing value on non-commercial species as providers of ecosystem services. Yet, many deer species and non-crop plants are perceived negatively when they decrease crop productivity, leading to reduced economic gains and human-wildlife conflict. We hypothesized that deer provide an ecosystem service in forest plantations by controlling competition and promoting crop-tree growth, although the effects of herbivory may depend on forest management intensity. If management negatively affects foraging habitat at local and landscape scales, then we expected browsing to shift to less-palatable crop trees. To test these hypotheses, we established a 5-year experiment that manipulated early forest management intensity via herbicide treatments and access of two deer species to vegetation via exclosures. Contrary to our hypothesis, deer provided an ecosystem service at high management intensities and a disservice occurred with low-intensity management. Crop-tree growth and survival was greatest when herbivory and herbicides suppressed broadleaf regeneration. In contrast, crop-tree growth was lowest when broadleaf vegetation was retained and crop-trees were subject to both browse damage and competition. We found a positive, yet variable, association between deer detections and stand- and landscape-scale broadleaf habitat, and despite initial reductions in forage, herbivory pressure was similar among management intensities. When broadleaf vegetation was suppressed by herbicides and herbivory, selection of herbaceous forage by deer intensified, likely aiding in the service. Overall, our findings indicate that the effects of vegetation management for promoting timber production are highly dependent on the presence of large herbivores.</p> <p>Synthesis and applications: Although deer are thought to reduce crop productivity in many systems, we found that herbivory switched from reducing crop tree growth where non-crop vegetation was retained, to promoting crop tree growth when both herbivory and herbicides suppressed competing vegetation. However, the provision of this ecosystem service is likely contingent on the amount of forage available in the landscape and subsequent foraging pressure. We conclude that nature's capacity to provide ecosystem services depends on the intensity of management at local and landscape scales.</p>
Data management planning - Training for trainers, part I-III: answers to per-assignments
<p>The data have been collected as part of data management planning training for trainers. Data consists participants answers to pre-assignments.</p> <p>Consent for data sharing</p> <ul> <li>First session: Consent for datat sharing was asked afterwards by email</li> <li>Second and third session: Consent was asked when collecting answers on the e-form.</li> </ul> <p>The slides of the DMP training fro trainers is available on SlideShare:</p> <ul> <li>Session I: <a href="https://www2.slideshare.net/MariKuusniemi/part-i-data-management-planning-training-for-trainers">https://www2.slideshare.net/MariKuusniemi/part-i-data-management-planning-training-for-trainers</a></li> <li>Session II: <a href="https://www2.slideshare.net/MariKuusniemi/data-management-planning-training-for-trainers-part-ii">https://www2.slideshare.net/MariKuusniemi/data-management-planning-training-for-trainers-part-ii</a></li> <li>Session III: <a href="https://www2.slideshare.net/MariKuusniemi/data-management-planning-training-for-trainers-part-iii">https://www2.slideshare.net/MariKuusniemi/data-management-planning-training-for-trainers-part-iii</a></li> </ul> <p>The training was organised by Tuuli Office.</p>
Next Steps: How the FDNext Project is Tackling Research Data Management … and Farewell to Emma
<p>In this episode we talk to Kerstin Helbig about the research data management (RDM)project FDNext, which is also where our co-host Emma Harris' new role will be based. We discussed what the approach of FDNext is, the challenges of implementing effective RDM, and how it fits into the wider framework of Open and FAIR Data initiatives. </p> <p><strong>Episode Links</strong></p> <p><a href="https://www.forschungsdaten.org/index.php/FDNext">FDNext (German language)</a></p> <p><a href="https://zenodo.org/record/4071471#.X791NmhKhPY">FDMentor RDM Train-the-Trainer Concept</a></p> <p><a href="https://www.researchgate.net/profile/Kerstin_Helbig">Kerstin Helbig</a></p> <p><a href="https://www.linkedin.com/in/emma-a-harris-6bb865123/">Emma Harris</a></p>
Data for "Water (or the Lack Thereof), Management, and Conservation of an Endangered Desert Wetland Obligate, Lilaeopsis schaffneriana var. recurva"
<p>Raw and RData forms of data for "Water (or the Lack Thereof), Management, and Conservation of an Endangered Desert Wetland Obligate, <em>Lilaeopsis schaffneriana </em>var. <em>recurva". </em>Consists of six Excel files, with names corresponding to the type of data.</p> <ol> <li>field_ecology_data.xlsx </li> <li>experiment_randomization.xlsx </li> <li>experiment_entered_data.xlsx </li> <li>resilience_days_to_critical.xlsx </li> <li>resilience_experiment_data.xlsx </li> <li>resilience_leaf_density_data.xlsx </li> </ol> <p>Four RData files of the loaded Excel data, and one text file to explain the coding of the drought experiment data.</p>
Dataset for: Research data management in academic institutions: a scoping review
<p><strong>Overview</strong></p> <p>This dataset contains the raw data for the manuscript: <br> Perrier L, Blondal E, Ayala AP, Dearborn D, Kenny T, Lightfoot D, Reka R, Thuna M, Trimble L, MacDonald H. Research data management in academic institutions: A scoping review. PLOS One. 2017 May 23;12(5):e0178261. doi: 10.1371/journal.pone.0178261.</p> <p>Full-text available at: <a href="http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0178261 ">http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0178261 </a></p> <p><strong>Data and Documentation Files</strong> </p> <p>Five files make up the dataset: </p> <ol> <li>Data Dictionary: RDMScopingReview_DataDictionary.pdf</li> <li>Data Abstraction Sheet: RDMScopingReview_StudyCharacteristics.csv</li> <li>Data Abstraction Sheet: RDMScopingReview_Setting.csv</li> <li>Data Abstraction Sheet: RDMScopingReview_DataCollectionTools.csv</li> <li>Data Abstraction Sheet: RDMScopingReview_Outcomes.csv</li> </ol> <p>Contact: Laure Perrier: <a href="https://orcid.org/0000-0001-9941-7129">orcid.org/0000-0001-9941-7129</a></p>
Research Data Management in Selected Health Research Institutions in Uganda
<p>This data set was collected from Researchers in three purposively selected health reseach Institutions in Uganda. The purpose of the study was to explore compliance to FAIR data princiles and Open science initiative given the increasing dependence on donor funding and need to fulfill the requirement for good research practices. </p>
Research Data Management Aspects - A Mindmap
<p>Just my personal mind-map of research data management aspects. No guarantee to be complete, feel free to use it and give me feedback.</p>
US National Native Bee Monitoring RCN Data Management Workshop: CC BY NC Videos
<p>The US National Native Bee Monitoring Research Coordination Network (RCN) held a two-day workshop on data management best practices for native bee inventory, survey, and monitoring data on March 28 and 30, 2023. Videos in this data set were played at the workshop. These videos are released with a CC BY-NC license. These videos are for non-commercial use only. Please cite the presenter(s) of the video(s) you use. This data set includes the following videos: </p><ul><li>APHIS National Honey Bee Pests and Diseases Survey by Anne LeBrun</li><li>Importance of FAIR in Biodiversity Science and Research by Elizabeth R. Ellwood</li><li>Bugflow: A Community Driven Repository for Entomology Digitization Resources by Crystal Maier</li><li>A Primer on iNaturalist Bee Data by Keng-Lou James Hung, Paige Chesshire, Michael Orr, Alice Hughes, Jess Mullins, Katherine Parys, Patricia Simpson, Lindsie McCabe, Neil Cobb, and John Ascher</li></ul>
Software and data underlying the article 'A serious game approach for lake modeling and management: the EscapeBLOOM'
<p>Here we share the player version of the EscapeBLOOM, a dummy version showcasing the techniques to create a similar digital escape room, and the anonymized data of the quantitative survey as presented in the publication 'A serious game approach for lake modeling and management: the EscapeBLOOM'.</p> <p>Anyone is free to play or adjust the game for their own educational purposes. The dummy and supplementary material of the publication 'A serious game approach for lake modeling and management: The EscapeBLOOM' <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.envsoft.2024.105941" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.envsoft.2024.105941</a> together provide guides on how to create a new game from the start and may help to adjust the existing game.</p> <p>The data of the survey was used for the analysis of perceived learning in the publication 'A serious game approach for lake modeling and management: the EscapeBLOOM'.</p>
Data from: Seasonal bee communities vary in their responses to resources at local and landscape scales: Implication for land managers
<p><strong>Context</strong>:<em> </em>There is great interest in land management practices for pollinators; however, a quantitative comparison of landscape and local effects on bee communities is necessary to determine if adding small habitat patches can increase bee abundance or species richness. The value of increasing floral abundance at a site is undoubtedly influenced by the phenology and magnitude of floral resources in the landscape, but due to the complexity of measuring landscape-scale resources, these factors have been understudied.</p> <p><strong>Objectives</strong>: To address this knowledge gap, we quantified the relative importance of local versus landscape scale resources for bee communities, identified the most important metrics of local and landscape quality, and evaluated how these relationships vary with season.</p> <p><strong>Methods</strong>: We studied season-specific relationships between local and landscape quality and wild-bee communities at 33 sites in the Finger Lakes region of New York, USA. We paired site surveys of wild bees, plants, and soil characteristics with a multi-dimensional assessment of landscape composition, configuration, insecticide toxic load, and a spatio-temporal evaluation of floral resources at local and landscape scales.</p> <p><strong>Results</strong>:<em> </em>We found that the most relevant spatial scale and landscape factor varied by season. Early-season bee communities responded primarily to landscape resources, including the presence of flowering trees and wetland habitats. In contrast, mid to late-season bee communities were more influenced by local conditions, though bee diversity was negatively impacted when sites were embedded in highly agricultural landscapes. Soil composition had complex impacts on bee communities, and likely reflects effects on plant community flowering. </p> <p><strong>Conclusions</strong>:<em> </em>Early-season bees can be supported by adding flowering trees and wetlands, while mid to late-season bees can be supported by local addition of summer and fall flowering plants. Sites embedded in landscapes with a greater proportion of natural areas will host a greater bee species diversity.</p>
Investigating the Utility of Potato (Solanum tuberosum L.) Canopy Temperature and Leaf Greenness Responses to Water-Restriction for the Improvement of Irrigation Management Data
<p><span>Traits that rapidly respond to stress in important agricultural crops have the potential to provide growers with actionable feedback. E.g., traits that respond to water-restriction could inform irrigation systems by identifying crop water status and requirements in real-time. This would be particularly useful for potato, which is extremely susceptible to drought. We conducted two pot experiments and one field experiment to evaluate the utility of two traits, canopy temperature and leaf greenness, for informing irrigation management in potatoes. We also evaluated the efficacy of Phenospex PlantEye F500 sensors for the remote sensing of leaf greenness. We found that canopy temperatures of the cvs. Maris Piper (Spring Pot Experiment, +0.8°C; Autumn Pot Experiment, +5.3°C) and Désirée (Autumn Pot Experiment, +2.5°C) increased with water-restriction and that the canopy temperatures of Maris Piper return to baseline within three days after the resumption of well-watered conditions. We also found that these responses varied between cultivars, with predictable outcomes based on reported and corroborated drought tolerance ratings. We found inconclusive evidence of leaf greenness increasing due to water-restriction (Spring Pot Experiment, +0.8°C; Autumn Pot Experiment, +5.3°C) and found no evidence that post-drought recovery periods return this trait to baseline. However, leaf greenness measurements from the Phenospex PlantEye F500 were moderately to strongly correlated with SPAD values, suggesting this tool might be useful in the screening of drought-tolerant cultivars in the future.</span></p>
Supporting data for managing fire-prone forests in a time of decreasing carbon carrying capacity
<p>These data and code include surface fuels and prescribed fire emissions data from the Teakettle Experimental Forest in the Sierra Nevada, California, USA. These data include transect data of surface fuels and the emissions from a 2017 prescribed burn. Emissions from the prescribed burn were calculated using a stock change approach by subtracting pre-burn surface fuels from post-burn surface fuels. We used these data and a Monte Carlo simulation approach to estimate the frequency of prescribed burning required to reduce surface fuels following a widespread overstory tree mortality event.</p>
Data: Managing European Alpine forests with close-to-nature forestry to improve climate change mitigation and multifunctionality
<p><strong>The repository contains the data supporting the findings of the study: <em>Managing European Alpine forests with close-to-nature forestry to improve climate change mitigation and multifunctionality</em></strong></p> <p><strong>Abstract:</strong></p> <p>Close-to-nature forestry (CNF) has a long tradition in European Alpine forest management, playing a crucial role in ensuring the continuous provision of biodiversity and forest ecosystem services, including protection against natural hazards. However, climate change is causing huge uncertainties about the future applicability of CNF in the Alpine region. The question arises as to whether current CNF practices are still suitable for adapting forests to climate change impacts while also meeting the increasing societal demands regarding Alpine forests, including their potential contribution to climate change mitigation.</p> <p>To answer this question, we simulated forest development using the ForClim forest model at two Alpine study sites, together representing a large biogeographic gradient from high-elevation inner Alpine forests (Switzerland) to lower-elevation south-eastern Alpine forests (Slovenia). The simulations considered three climate scenarios (historical climate, SSP2‑4.5 and SSP5-8.5) and six alternative management strategies, including both current CNF management practices and climate-adapted versions. Using a multi-criteria decision analysis framework, we assessed the joint impacts of climate and management on biodiversity and key ecosystem services of the investigated regions, including carbon sequestration (CS) inside and outside the forest ecosystem boundary. </p> <p>The joint effects of climate change and CNF varied, both among and within the study sites along the biogeographical gradient. While CS was more resistant to climate change under current CNF at the south-eastern Alpine site, it was more sensitive at the inner Alpine site, where CS potentials decreased at lower elevations. This adverse effect could be partly mitigated by fostering the use of climate-adapted tree species. However, current CNF and adaptations of it did not meet multiple management objectives equally well: while protection from gravitation hazards and timber production also benefited from this silvicultural practice, biodiversity benefited from CNF variants with low-intensity or no management. </p> <p>In conclusion, CNF has a high potential to continue fulfilling its crucial role in European Alpine forests. A differentiated approach will be needed in the future, however, to identify forest stands where adaptive measures are required, especially at sites particularly vulnerable to climate change. In combination with less intensively managed or unmanaged areas, CNF provides a management portfolio that will help European Alpine forests to meet the demands of future society.</p> <p><strong>Data:</strong></p> <p>There is one folder for each case study, including: </p> <ul> <li>simulated biodiverstiy and ecosystem service indicators</li> <li>forest stand metadata</li> <li>normlized utility values for indicators</li> <li>partial utility values for biodiversity and ecosystem service groups</li> </ul> <p>This study was conducted as part of the <strong>ONEforest project</strong>, which received funding from the <strong>European Union's Horizon 2020</strong> research and innovation programme under the <strong>grant agreement Nº 101000406</strong>.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.