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42 results for “network science”
Chimpanzee identification and social Network construction through an online citizen science platform
<p><span><span><span><span><span><span><span><span><span><span><span>Citizen science has grown rapidly in popularity in recent years due to its potential to educate and engage the public while providing a means to address a myriad of scientific questions. However, the rise in popularity of citizen science has also been accompanied by concerns about the quality of data emerging from citizen science research projects. We assessed data quality in the online citizen scientist platform Chimp&See, which hosts camera trap videos of chimpanzees (<i>Pan troglodytes</i>) and other species across Equatorial Africa. In particular, we compared detection and identification of individual chimpanzees by citizen scientists to that of experts with years of experience studying those chimpanzees. We found that citizen scientists typically detected the same number of individual chimpanzees as experts, but assigned far fewer identifications (IDs) to those individuals. Those IDs assigned, however, were nearly always in agreement with the IDs provided by experts. We applied the data sets of citizen scientists and experts by constructing social networks from each. We found that both social networks were relatively robust and shared a similar structure, as well as having positively correlated individual network positions. Our findings demonstrate that, although citizen scientists produced a smaller data set based on fewer confirmed IDs, the data strongly reflect expert classifications and can be used for meaningful assessments of group structure and dynamics. This approach expands opportunities for social research and conservation monitoring in great apes and many other individually identifiable species. </span></span></span></span></span></span></span></span></span></span></span></p>
Machine learning for Material Science 2022 - Neural Networks Assignment Dataset
<p>Data for the neural network assignment</p> <p> </p>
Data from: Using artificial neural networks and citizen science data to assess jellyfish presence along coastal areas
<p><strong><span>General Information</span></strong></p> <p><span>This dataset was used in the study titled "Using artificial neural networks and citizen science data to assess jellyfish presence along coastal areas". The study employs citizen science data collected from the Infomedusa application to assess the presence of jellyfish on beaches along the Andalusian coast, along with environmental data to analyze the factors influencing jellyfish distribution. The study aims to employ machine learning techniques, specifically a Multi-Layer Perceptron (MLP) neural network, to classify user comments on the presence or absence of jellyfish and analyze how environmental factors such as sea surface temperature, wind direction, and wind speed influence jellyfish distribution.</span></p> <p><strong><span>Dataset Columns</span></strong></p> <ul> <li><strong><span>Fecha</span></strong><span>: Timestamp of the comment made by the user in the Infomedusa application.</span></li> <li><strong><span>Municipio</span></strong><span>: Name of the municipality where the beach mentioned in the comment is located.</span></li> <li><strong><span>Jellyfish</span></strong><span>: Binary variable indicating the presence (1) or absence (0) of jellyfish according to the user’s comment.</span></li> <li><strong><span>Comunidad</span></strong><span>: Autonomous community to which the municipality belongs.</span></li> <li><strong><span>Provincia</span></strong><span>: Province to which the municipality belongs.</span></li> <li><strong><span>Latitud</span></strong><span>: Geographical latitude of the municipality where the comment was made.</span></li> <li><strong><span>Longitud</span></strong><span>: Geographical longitude of the municipality where the comment was made.</span></li> <li><strong><span>Set</span></strong><span>: Set of grouped beaches for geographical analysis. Each set includes beaches close to each other and the nearest weather station.</span></li> <li><strong><span>Month</span></strong><span>: Month when the comment was made.</span></li> <li><strong><span>Longitud_sea</span></strong><span>: Longitude of the nearest point in the sea for which environmental data was available.</span></li> <li><strong><span>Latitud_sea</span></strong><span>: Latitude of the nearest point in the sea for which environmental data was available.</span></li> <li><strong><span>SST</span></strong><span>: Sea Surface Temperature at the nearest point in the sea to the municipality, obtained from the Copernicus Marine Environment Monitoring Service.</span></li> <li><strong><span>Wind_dir</span></strong><span>: Wind direction measured at the weather station closest to the municipality, provided by the Spanish Meteorological Agency (AEMET).</span></li> <li><strong><span>Wind_speed</span></strong><span>: Wind speed measured at the weather station closest to the municipality, provided by the AEMET.</span></li> </ul> <p><strong><span>Data Sources</span></strong></p> <ul> <li><strong><span>Infomedusa APP</span></strong><span>: Application developed by the Provincial Council of Malaga and Aula del Mar of Malaga to monitor the presence of jellyfish through citizen participation.</span></li> <li><strong><span>Copernicus Marine Environment Monitoring Service (CMEMS)</span></strong><span>: Provides data on sea surface temperature with an hourly temporal resolution and a spatial resolution of 0.0625° x 0.0625°.</span></li> <li><strong><span>Agencia Estatal de Meteorología (AEMET)</span></strong><span>: Provides daily data on wind direction and speed.</span></li> </ul>
Fig. 2. A–G, Aphaena discolor. A–B in Updating lanternflies biodiversity knowledge in Cambodia (Hemiptera: Fulgoromorpha: Fulgoridae) by optimizing field work surveys with citizen science involvement through Facebook networking and data access in FLOW website
Fig. 2. A–G, Aphaena discolor. A–B, specimen on his host-tree, Kirirom, 9.V.2015 (J. Constant). C, habitat in Kirirom, 9.V.2015 (J. Constant). D, Pursat, Cardamom, 2.I.2009 (J. Holden). E, Koh Kong, Tatai, 5.III.2012 (G. Chartier). F–G, Dichoptera sp. Chambok, 5.V.2015 (J. Constant). H, Kalidasa nigromaculata, Siem Reap, Angkor, 10.VIII.2014 (S. De Greef). I, Penthicodes atomaria tended by a cockroach, Cardamom Mts, 4.VIII.2013 (A. Anker). J, P. pulchella, Siem Reap, 18.IX.2013 (S. De Greef). K, P. variegata, Mondulkiri, O Reang District, 19.V.2015 (B. Barca). L–M, Polydictya tricolor, Siem Reap, Angkor, 1.VIII.2013 (S. De Greef). N–O, Polydictya sp., 8 km NNW Angkor, 6.XI.2013 (E. Smith).
Fig. 1 in Updating lanternflies biodiversity knowledge in Cambodia (Hemiptera: Fulgoromorpha: Fulgoridae) by optimizing field work surveys with citizen science involvement through Facebook networking and data access in FLOW website
Fig. 1. Call to collaboration to the study of Fulgoridae of Cambodia posted on Facebook on May 18th, 2015.
Fig. 3. A–B, Pyrops candelaria. A in Updating lanternflies biodiversity knowledge in Cambodia (Hemiptera: Fulgoromorpha: Fulgoridae) by optimizing field work surveys with citizen science involvement through Facebook networking and data access in FLOW website
Fig. 3. A–B, Pyrops candelaria. A, Chambok, 1.IX.2014 (S. Phauk). B, Kampong Tralach, 21.IX.2013 (O. Rodriguez). C–D, P. coelestinus, Chambok, 1.IX.2014 (S. Phauk). E, P. condorinus, Koh Kong, Tatai, 24.V.2015 (G. Chartier). F, P. ducalis, Mondulkiri, Seima Forest, 13.V.2015 (B. Barca). G–I, P. peguensis. G, Tumpor, Cardamom, 12.VIII.2009 (J. Holden). H, Chambok, 5.V.2015 (J. Constant). I, idem, biotope. J, P. spinolae, Ratanakiri, Veun Sai Siem Pang, 23.II.2015 (Marduk). K, P. viridirostris, Chambok, 7.V.2015 (J. Constant). L–N, Saiva gemmata. L, nymph, Chambok, 7 May 2015 (J. Constant). M, adult tended by a cockroach, Chambok, 7.V.2015 (J. Constant). N, Mondulkiri, Seima Forest, 13.V.2015 (B. Barca). O–Q, Zanna sp. O–P, Koh Kong, Tatai, 1.XI.2012 (G. Chartier). Q, Kampot, 21.XII.2013 (K.W. Meier-Doernberg).
BIOFRUITNET - Boosting Innovation in Organic FRUIT production through knowledge NETworks - WP2 - Bibliographic search in Web of Science
<p>In the project BIOFRUITNET (Boosting Innovation in Organic FRUIT production through knowledge NETworks, HORIZON 2020 Grant Agreement No. 862850), nine search strings covering <strong>stone fruits, pome fruits and citrus fruits</strong>, within the selected main topics: <strong>pests, plant diseases and plant nutrition </strong>were developed, to target the most relevant scientific literature within the topics. The bibliographic searches were conducted on October 19, 2020 in Web of Science. The databases presented are the complete lists of references included from the WoS search. These lists will be processed to select the most relevant materials ready for practice in a following project work package. Project homepage: <a href="https://biofruitnet.eu/">https://biofruitnet.eu/</a></p>
Chimpanzee identification and social Network construction through an online citizen science platform
Open the record for dataset details and reuse information.
Datasets for Age, Gender, and International Author Networks in the Earth and Space Sciences: Implications for Addressing Implicit Bias
<p>These files provide supplemental information and tabular data for figures in Hanson, Wooden, Lerback: Age, Gender, and International Author Networks in the Earth and Space Sciences: Implications for Addressing Implicit Bias, Submitted to Earth and Space Science.</p>
Supplementary material 1 from: Vohland K, Häuser C, Regan E, Hoffmann A, Wetzel F (2016) 2nd EU BON Stakeholder Roundtable (Berlin, Germany): How can a European biodiversity network support citizen science? Research Ideas and Outcomes 2: e8616. https://doi.org/10.3897/rio.2.e8616
2nd EU BON Stakeholder Roundtable – Acronyms
Figure 3 from: Vohland K, Häuser C, Regan E, Hoffmann A, Wetzel F (2016) 2nd EU BON Stakeholder Roundtable (Berlin, Germany): How can a European biodiversity network support citizen science? Research Ideas and Outcomes 2: e8616. https://doi.org/10.3897/rio.2.e8616
Figure 3 - Examples of citizen science projects and initiatives/tools from the EU BON consortium (Christoph Häuser and Florian Wetzel, MfN, 2014)
Figure 1 from: Vohland K, Häuser C, Regan E, Hoffmann A, Wetzel F (2016) 2nd EU BON Stakeholder Roundtable (Berlin, Germany): How can a European biodiversity network support citizen science? Research Ideas and Outcomes 2: e8616. https://doi.org/10.3897/rio.2.e8616
Figure 1 - EU BON Work Packages (WP) with the three sections (a) Data Sources and Infrastructure, (b) Science and Application and (c) Policy and Dialogue. The Stakeholder Roundtables are a specific task in the WP 6 that targets the stakeholder engagement and science-policy dialogue (credits: Pensoft).
Figure 4 from: Vohland K, Häuser C, Regan E, Hoffmann A, Wetzel F (2016) 2nd EU BON Stakeholder Roundtable (Berlin, Germany): How can a European biodiversity network support citizen science? Research Ideas and Outcomes 2: e8616. https://doi.org/10.3897/rio.2.e8616
Figure 4 - Species occurrence data records (in millions, x-axis) from CS sources, counted and freely available in Europe (Nils Valland, NBIC, updated in March 2016).
Dataset about sharks in French Polynesia extracted from the ORP citizen science network
<p><span>Observers of the Polynesian Shark Observatory (ORP), a citizen science network organized mainly through the Polynesian dive centers, collected an unprecedented amount of data in 43% of the islands of French Polynesia between July 8, 2011, and April 11, 2018, during 13,916 dives. The objective of such a data collection, not accessible to standard research resources, was to provide a unique dataset, offering the opportunity to explore the specific diversity, distribution, seasonality and abundance of many elasmobranch species spread out throughout the overall French Polynesia territory. Indeed, since the data are based on random citizen observation, the spatial distribution was biased toward the most frequented sites and islands where the scuba diving activity is mostly developed. Overall, the increase in observed abundance of rays and sharks observed in French Polynesia and the three most sampled islands, as well as the high specific diversity recorded for the region, provide the first evidence of the effectiveness of the Shark Sanctuary established in 2006. These data, collected randomly by the volunteers, also give insights about potential movement patterns and site fidelity of some species more often seen. While not leading to final conclusion, the network of volunteers filling with information to the Polynesian Shark Observatory is essential in giving preliminary results and research perspectives and directions for future projects on sharks and rays in French Polynesia.</span></p>
Data from: How new concepts become universal scientific approaches – insights from citation network analysis of agent-based complex systems science
Open the record for dataset details and reuse information.
Dataset about sharks in French Polynesia extracted from the ORP citizen science network
Open the record for dataset details and reuse information.
Figure 6 from: Vohland K, Häuser C, Regan E, Hoffmann A, Wetzel F (2016) 2nd EU BON Stakeholder Roundtable (Berlin, Germany): How can a European biodiversity network support citizen science? Research Ideas and Outcomes 2: e8616. https://doi.org/10.3897/rio.2.e8616
Figure 6 - Participants at the 2nd EU BON Stakeholder Roundtable (credits: Carola Radtke, MfN)
Figure 5 from: Vohland K, Häuser C, Regan E, Hoffmann A, Wetzel F (2016) 2nd EU BON Stakeholder Roundtable (Berlin, Germany): How can a European biodiversity network support citizen science? Research Ideas and Outcomes 2: e8616. https://doi.org/10.3897/rio.2.e8616
Figure 5 - Key success factors for citizen science projects (Nils Valland, NBIC, 2014).
Figure 2 from: Vohland K, Häuser C, Regan E, Hoffmann A, Wetzel F (2016) 2nd EU BON Stakeholder Roundtable (Berlin, Germany): How can a European biodiversity network support citizen science? Research Ideas and Outcomes 2: e8616. https://doi.org/10.3897/rio.2.e8616
Figure 2 - Setting the scene for the roundtable on Citizen Science (credits: Carola Radtke).
National Translational Science Network of Precision-based Immunotherapy for Primary Liver Cancer
ClinicalTrials.gov study NCT04145141. IPD Sharing: YES. Countries: 1. Publications: 0.
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
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.