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.
8,460
datasets available to search
ShareScore release 0.9.0
Dataset results
8,460 results for “MONITORING”
FIGURE 2 in Novel analysis of locality data can inform better inventory and monitoring practices for paleontological resources at John Day Fossil Beds National Monument Oregon, USA
FIGURE 2. Map of Oregon showing the three park units (purple) and the extent of the majority of non-NPS sites worked by JODA paleontologists (green). There are museum collections at JODA from many sites in area highlighted in green. However, many of these sites have not been visited recently. Many of the sites with paleontological resources in the green area are found on lands administered or owned by partners and are scattered across the full area.
FIGURE 3 in Novel analysis of locality data can inform better inventory and monitoring practices for paleontological resources at John Day Fossil Beds National Monument Oregon, USA
FIGURE 3. Map of locality data for cataloged specimens by year collected in one of the five main collection areas. Years correspond to cyclic prospecting schedule outlined in Table 1. Note the overlap between 1993 and 1994 and 1997 and 1998 contrary to the schedule shown in Table 1. Precise locality information is available to qualified researchers upon request from JODA's museum program.
FIGURE 1 in Novel analysis of locality data can inform better inventory and monitoring practices for paleontological resources at John Day Fossil Beds National Monument Oregon, USA
FIGURE 1. Composite stratigraphic column of the John Day Formation with the Columbia River Basalt Group capping the section. Stratigraphic relationships and radiometric dates are based on Hunt and Stepleton (2004), Albright et al. (2008), and Fremd (2010). The black box encompasses the subunits that are considered lower Turtle Cove for the purposes of this study. Figure provided by the National Park Service.
Figure 1 in Satellite Monitoring of the Black Sea Ecological Risk Areas
Figure 1. The pollution of the sea surface revealed by ASAR Envisat image from 17.03.2010 as a result of ship discharges: 1 - fresh oil spill, length- 19.5 km; 2 - weathered oil spill, length - 20 km, area 4 km2; 3 - fresh oil spill, length- 12.5 km; 4- weathered oil spill, total length - 21 km, area - 3 km2.
Figure 4 in Satellite Monitoring of the Black Sea Ecological Risk Areas
Figure 4. Summary map of oil-containing ship discharges in the Black Sea, detected as a result of satellite radar data analysis in 2009-2012.
Figure 1 in Evaluation of automated monitoring calving prediction in dairy buffaloes a new tool for calving management
Figure 1. Behavioral differences expressed as mean ± SE in 24-h periods before calving for (a) Feeding time (measured by the Nedap neck Tag); (b) rumination time (measured by the Nedap neck Tag); (c) Laying bouts (measured by the Nedap leg tag); (d) Laying time (measured by the Nedap leg tag); (e) Number of steps (measured by the Nedap leg tag); and (f) Total motion (measured by the Nedap leg tag). Differences were calculated as each buffaloes -24, -12, -6 and -2 days before calving. *P <0.01 and **P <0.001.
Development of public dynamic spatio-temporal monitoring and analysis tool of supply chain vulnerability, resilience, and sustainability
<p>Supply chains play a pivotal role in driving economic growth and societal well-being, facilitating the efficient movement of goods from producers to consumers. However, the increasing frequency of disruptions caused by geopolitical events, pandemics, natural disasters, and shifts in commerce poses significant challenges to supply chain resilience. This draft update report discusses the development of a dynamic spatio-temporal monitoring and analysis tool to assess supply chain vulnerability, resilience, and sustainability. Leveraging news data, macroeconomic metrics, inbound cargo data (for sectors in California), and operational conditions of California's highways, the tool employs Natural Language Processing (NLP) and empirical regression analyses to identify emerging trends and extract valuable information about disruptions to inform decision-making. Key features of the tool include sentiment analysis of news articles, topic classification, visualization of geographic locations, and tracking of macroeconomic indicators. By integrating diverse and dynamic data sources (e.g., news articles) and using empirical and analytical techniques, the tool offers a comprehensive framework to enhance our understanding of supply chain vulnerabilities and resilience, ultimately contributing to more effective strategies for decision-making in supply chain management. The dynamic nature of this tool enables continuous monitoring and adaptation to evolving conditions, thereby enhancing the analysis of resilience and sustainability in global supply chains.</p>
Accompanying dataset for: "A Bayesian method for predicting background radiation at environmental monitoring stations"
<h3>Physical parameters included</h3> <ul> <li>Ten-minute-averaged ambient dose equivalent rates (nSv/h) observed by the Immission Monitors for Ring area (IMR stations) at the sites of the SCK CEN and the Doel NPP for selected periods in time</li> </ul> <h3>Geographic locations</h3> <ul> <li>Belgian Nuclear Research Centre (SCK CEN) in Mol, Belgium: 18 IMR stations</li> <li>Nuclear Power Plant in Doel, Belgium: 16 IMR stations</li> </ul> <h3>Periods</h3> <ul> <li>6 through 13 August 2022</li> <li>30 August through 1 September 2022</li> <li>10 through 12 September 2022</li> </ul> <h3>Description of data</h3> <p>The zipped folder contains three sub folders for the different periods of interest. Each sub folder contains 34 files. Files are either named IMR-D##.txt to indicate Doel-based or IMR-M##.txt to indicate SCK CEN-based stations. Exact locations (WGS84) are included in the headers. Time stamps (referred to as 'local_time' in the files) are given in Central European Summer Time (UTC+2), and the ambient dose equivalent rates (referred to as 'value' in the files) in nanosievert per hour (nSv/h).</p> <h3>Acknowledgements</h3> <p>The authors thank François Menneson from FANC-ACFN for providing access to the Telerad data.</p>
Accompanying software for: "A Bayesian method for predicting background radiation at environmental monitoring stations"
<h3>Introduction</h3> <p>This software accompanies: "A Bayesian Method for predicting background radiation at environmental monitoring stations". The software is written in Python and depends (besides on standard packages like numpy) on the PyMC package for Bayesian inference. A brief user manual is provided that will allow to install the necessary prerequisites in a conda environment, and describes how to perform the inferences that are described in the paper. This requires additionally downloading the dataset that we have also made available on this platform (<a href="https://doi.org/10.5281/zenodo.12581795" target="_blank" rel="noopener">10.5281/zenodo.12581795</a>). </p> <h3>Description of files</h3> <ul> <li><em>manual.pdf</em> describes how to install the necessary packages in conda, and how to perform inferences from the paper.</li> <li><em>main.py</em> is the main script, which contains the input parameters and calls the relevant functions.</li> <li><em>bayesian_inference.py</em> contains the beating heart of the software. Here, the Bayesian problems for calibration and predictions are set up and solved using the PyMC package.</li> <li><em>data_paper_interface.py </em>is only necessary when reproducing the data from the paper. It contains the different cases that were used in the paper, and can be used to parse data from the accompanying dataset.</li> </ul>
High-resolution continuum source graphite furnace molecular absorption spectrometry for the monitoring of Sr isotopes via SrF formation: a case study
<p>This dataset contains the raw data corresponding to the figures of the publication <a title="Link to landing page via DOI" href="https://doi.org/10.1039/D2JA00245K">https://doi.org/10.1039/D2JA00245K</a></p>
Flood Quality monitoring
Open the record for dataset details and reuse information.
Estimation of porosity and information of ground temperature monitoring wells
<p>Estimation of porosity and information of ground temperature monitoring wells</p>
Data for the paper: "A soundscape approach for a short-term acoustic monitoring of a Critically Endangered Cuban frog"
<p>This 4 excel sheets contain the data sets for the paper “A soundscape approach for a short-term acoustic monitoring of a Critically Endangered Cuban frog” . The data comprises the call rate informatione xtracted from te recordings and the Acoustical index data for descibing the soundscape of the area</p>
Supplementary material 10 from: Ushio M, Murakami H, Masuda R, Sado T, Miya M, Sakurai S, Yamanaka H, Minamoto T, Kondoh M (2018) Quantitative monitoring of multispecies fish environmental DNA using high-throughput sequencing. Metabarcoding and Metagenomics 2: e23297. https://doi.org/10.3897/mbmg.2.23297
Abundance of some common fish species obtained by the direct visual census
Supplementary material 2 from: Ushio M, Murakami H, Masuda R, Sado T, Miya M, Sakurai S, Yamanaka H, Minamoto T, Kondoh M (2018) Quantitative monitoring of multispecies fish environmental DNA using high-throughput sequencing. Metabarcoding and Metagenomics 2: e23297. https://doi.org/10.3897/mbmg.2.23297
Primer, index and probe sequences used in the study
Supplementary material 1 from: Ushio M, Murakami H, Masuda R, Sado T, Miya M, Sakurai S, Yamanaka H, Minamoto T, Kondoh M (2018) Quantitative monitoring of multispecies fish environmental DNA using high-throughput sequencing. Metabarcoding and Metagenomics 2: e23297. https://doi.org/10.3897/mbmg.2.23297
The numbers of sequence reads remaining (filtered) in data processing steps
Supplementary material 7 from: Ushio M, Murakami H, Masuda R, Sado T, Miya M, Sakurai S, Yamanaka H, Minamoto T, Kondoh M (2018) Quantitative monitoring of multispecies fish environmental DNA using high-throughput sequencing. Metabarcoding and Metagenomics 2: e23297. https://doi.org/10.3897/mbmg.2.23297
Results of quantitative PCR for total fish eDNA, Japanese anchovy and Japanese jack mackerel
Supplementary material 3 from: Ushio M, Murakami H, Masuda R, Sado T, Miya M, Sakurai S, Yamanaka H, Minamoto T, Kondoh M (2018) Quantitative monitoring of multispecies fish environmental DNA using high-throughput sequencing. Metabarcoding and Metagenomics 2: e23297. https://doi.org/10.3897/mbmg.2.23297
Descriptions of TaqMan probe specificity test and supplementary Table S1 and S2
Figure 1 from: Garzon-Lopez C, Hattab T, Skowronek S, Aerts R, Ewald M, Feilhauer H, Honnay O, Decocq G, Van De Kerchove R, Somers B, Schmidtlein S, Rocchini D, Lenoir J (2018) The DIARS toolbox: a spatially explicit approach to monitor alien plant invasions through remote sensing. Research Ideas and Outcomes 4: e25301. https://doi.org/10.3897/rio.4.e25301
Figure 1 DIARS toolbox workflow. The green gears correspond to the sections of the toolbox and are accompanied by boxes stating its main goal. The gray gears describe the advantages of the DIARS toolbox.
Figure 5 from: Garzon-Lopez C, Hattab T, Skowronek S, Aerts R, Ewald M, Feilhauer H, Honnay O, Decocq G, Van De Kerchove R, Somers B, Schmidtlein S, Rocchini D, Lenoir J (2018) The DIARS toolbox: a spatially explicit approach to monitor alien plant invasions through remote sensing. Research Ideas and Outcomes 4: e25301. https://doi.org/10.3897/rio.4.e25301
Figure 5 Some examples of reconstructed images: A. Sylt island reconstructed image and plot locations (wavelengths: 170R, 65G, 17B). B. Compiègne Forest reconstructed image and plot locations (wavelengths: 207R, 65G, 10B).
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.