Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
226
datasets available to search
ShareScore release 0.7.1
Dataset results
226 results for “long term monitoring”
Supporting Documents for "The DESC Catchments: Long-term Monitoring of Inland Precambrian Shield Catchment Streamflow and Water Chemistry in Central Ontario, Canada"
<p>Supporting documents for "<strong>The DESC Catchments: Long-term Monitoring of Inland Precambrian Shield Catchment Streamflow and Water Chemistry in Central Ontario, Canada" </strong> that are otherwise not readily accessible. These include historical government reports and relevant laboratory method descriptions from the Ontario Ministry of Environment (Canada). Reports List includes a listing of the 14 documents.</p>
Improving citizen science data for long-term monitoring of plant species
<p>In 2012, a new volunteer-based recording scheme for vascular plants was launched in the Netherlands. Its purpose is to track the changes in the number of occupied 1-km grid cells for as many native plant species as possible between survey rounds of 8 years. We did not prescribe a strict field protocol to minimize variation in observer effort, but instead chose to statistically correct for this variation with occupancy models. These models require replicated visits to a grid cell per season, which was implemented by having two independent observers survey grid cells and record all plant species observed. Now that a first survey round has ended (2012–2019), we evaluate our approach, i.e. we tested whether the scheme has the potential to produce proper trend estimates. The number of occupied grid cells in the first round was estimated per species, using an occupancy model with day of year, visit duration and observer experience as covariates for detection. The detection probability, which was 0.43 on average, strongly depended on visit duration and day of year. It was possible to estimate the number of occupied grid cells quite precisely for several hundreds of species, such that the statistical power is expected to be high enough to detect changes of 10% between survey rounds. For rare species, however, the power to detect changes is expected to be quite low. We conclude that the approach works well, but further improvements are suggested.</p>
Long-term wastewater monitoring of SARS-CoV-2 viral loads and variants at the major international passenger hub Amsterdam Schiphol Airport: a valuable addition to COVID-19 surveillance
<p>Datasets used for the manuscript: <em>Long-term wastewater monitoring of SARS-CoV-2 viral loads and variants at the major international passenger hub Amsterdam Schiphol Airport: a valuable addition to COVID-19 surveillance</em></p> <p><em>pandemic_daily_passenger_counts.tsv</em>: An overview of daily passenger arrival counts at Amsterdam Schiphol Airport per continent of origin during the study period 16-02-2020 - 04-09-2022</p> <p><em>pre-pandemic_daily_passenger_averages.tsv: </em>An overview of mean daily passenger arrival counts at Amsterdam Schiphol Airport in the pre-pandemic period 2017-2019.</p> <p><em>viral_load_data.tsv: </em>Sample metadata (sample identifier, sampling date, flow, average # particles per ml, and flow-corrected viral-load) for samples taken at the wastewater treatment plant of Amsterdam Schiphol Airport.</p> <p><em>wastewater_variant_frequencies.tsv: </em>SARS-CoV-2 lineage estimates in samples taken at the wastewater treatment plant of Amsterdam Schiphol Airport, analyzed using whole-genome tiled amplicon sequencing.</p> <p> </p> <p> </p> <p> </p>
Assessment of the Effectiveness of Coarse Resolution Fire Products in Monitoring Long-term Changes in Fire Regime within Protected Areas in South Africa
<p>The dataset includes fire histrory (shapefiles with data perimeters for 2003-2020) within 3 protected areas in South Africa, Blyde, Manyeleti, and Songimvelo.</p>
NDVI-based monitoring of long-term vegetation dynamics and responses to multi-time scales droughts in Inner Mongolia
<p>The characteristics of vegetation and drought for different seasons between 1982 and 2015 in Inner Mongolia were studied based on the Normalized Difference Vegetation Index (NDVI) and the Standardized Precipitation Evapotranspiration Index (SPEI). The response of vegetation to drought over various time scales for different seasons and vegetation types was investigated using the maximum Pearson correlation, allowing a discussion about the possible causes of any changes. The results indicate that the vegetation NDVI in Inner Mongolia showed an increasing trend in different seasons, with spring vegetation NDVI (April to May) having the largest significant increasing rate, followed by the growing season (April to October), autumn (September to October), and summer (June to August). Accordingly, the proportion of stations with decreasing SPEI was, in descending order, summer, growing season, autumn, and spring. Additionally, the magnitude of the SPEI decrease was greater in eastern Inner Mongolia. NDVI and SPEI were positively correlated in most regions of Inner Mongolia, indicating that changes in vegetation in most parts of this region were affected by the spatial and temporal characteristics of drought, the correlation being them being strongest in the growing season, followed by summer, then spring and autumn. Considering the different types of vegetation, forests were less affected by drought, with broadleaf forests more affected than coniferous forests. The meadow steppes and typical steppes were more affected by 12-month droughts in the growing season and summer, 6-month droughts in spring, and 3-month droughts in autumn, with desert steppes mainly affected by 3-month droughts. The shrubs, sandy vegetation, and cropland were mostly affected by droughts in summer, and show a greater response to 3-month droughts in autumn. Finally, the water balance was found to be the most important factor affecting the response of vegetation to drought in Inner Mongolia.</p>
Trinity College Botanic Garden long-term monitoring program
<p><span>Botanic gardens hold large, documented, and accessible collections of living plants. These represent </span><span>unique subsets of taxa from different biogeographical regions growing under common environmental conditions, connecting people to global plant research and conservation efforts while offering a place beneficial for human health and wellbeing. Despite Botanic Gardens being an ideal setting for climate change research, their potential for comparative, long-term studies and outreach in the field is still underutilised. As part of its ten-year strategy, Trinity College Botanic Garden (TCBG) aims to tap this potential and establish a programme for long-term (>30 years) monitoring of key physiological performances in its living woody plant collection. The programme will also assess particulate pollution (PM10 and PM2.5) interception by the same trees, pairing climate change and urban green research. Importantly, the project will include the design of a transferable protocol, produce vouchered herbarium specimens as a future historical archive and as a pedagogical tool, and support the garden outreach strategy, so as to nurture its link with both Trinity College Dublin and local communities, ensuring the garden's legacy into the future.</span></p>
Long-term soil erosion monitoring in China using the RUSLE model based on Google Earth Engine
<p>This dataset contains soil erosion maps in China at 500m resolution from 2010 to 2020. The dataset is stored in GeoTif format with the unit of t/(km<sup>2 </sup>· a).</p>
A Study To Monitor Long-Term Treatment With PF-00547659
ClinicalTrials.gov study NCT01298492. IPD Sharing: Not stated. Countries: 15. Publications: 1.
Data from: The role of exotic ladybeetles in the decline of native ladybeetle populations: evidence from long-term monitoring
Open the record for dataset details and reuse information.
Data from: Long-term monitoring of seed dispersal by Asian elephants in a Sundaland rainforest
Open the record for dataset details and reuse information.
Trinity College Botanic Garden long-term monitoring program
Open the record for dataset details and reuse information.
Stakeholders engagement as an important step for the long-term monitoring of wild ungulate populations
Open the record for dataset details and reuse information.
Satellite-based habitat monitoring reveals long-term dynamics of deer habitat in response to forest disturbances
Open the record for dataset details and reuse information.
Data and code for: Leveraging long-term data to improve biodiversity monitoring with species distribution models
Open the record for dataset details and reuse information.
Final eddy covariance dataset to support lessons from long-term monitoring of carbon gains and losses in cropping systems
Open the record for dataset details and reuse information.
NDVI-based monitoring of long-term vegetation dynamics and responses to multi-time scales droughts in Inner Mongolia
Open the record for dataset details and reuse information.
Data for: Understanding post-fire vegetation recovery in Southern California ecosystems with the aid of pre-fire observations from long term monitoring
Open the record for dataset details and reuse information.
Monitoring long-term vegetation dynamics over the Yangtze River Basin, China, using multi-temporal remote sensing data
Open the record for dataset details and reuse information.
Improving citizen science data for long-term monitoring of plant species
Open the record for dataset details and reuse information.
Long-term monitoring reveals forest tree community change driven by atmospheric sulfate pollution and contemporary climate change
Open the record for dataset details and reuse information.
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.