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.
359
datasets available to search
ShareScore release 0.7.1
Dataset results
359 results for “social behavior”
Learning to embed lifetime social behavior from interaction dynamics - Data
<p><strong>Interaction matrices and metadata used in "Learning to embed lifetime social behavior from interaction dynamics"</strong></p> <p>The following files are included:</p> <ul> <li>interactions_bn16_sparse.npz and interactions_bn19_sparse.npz: These are the interaction affinity matrices for the BN16 and BN19 datasets as described in the publication. The data is stored as compressed sparse tensors with time on the first, and the individuals on the second and third dimensions. The data was stored using the <a href="http://sparse.pydata.org">pydata/sparse</a> library 0.9.1</li> <li> <p>alive_bn16.csv and alive_bn19.csv: These files contain the dates of emergence (also corresponding to the dates they were introduced into the colonies) and heuristically determined number days alive for all individuals in the interaction matrices. Death dates were determined using a bayesian changepoint model and the number of daily detections of each individual</p> </li> <li> <p>rhythmicity_bn16.csv and rhythmicity_bn19.csv: These files contain the circadian rhythmicity values used in the evaluation of the method. The circadian rhythmicity is the <span class="math-tex">\(R^2\)</span> value of a sine with a 24 hour period fitted to the individuals' movement velocities over a three day window</p> </li> <li> <p>indices_bn16.csv and indices_bn19.csv: These files contain the mapping between the original marker IDs used during the recording of the data (which has gaps, because not all markers were used) and the sequential indices used in the interaction matrices. These files can therefore be used to look up the original ID of an individual based on it's index in the interaction matrix and vice versa</p> </li> <li> <p>time_spent_on_substrates.csv: This data was used for the mapping from factors to the proportion of time spent on various cell substrates (Figure 5). The positions of the individuals were accumulated by minute, and the column "location_descriptor_count" contains the total number of minutes on the respective day that the individual was detected</p> </li> </ul> <p>See <a href="https://doi.org/10.1101/2020.05.06.076943">10.1101/2020.05.06.076943</a> for more details about the bayesian changepoint model, circadian rhythmicity calculation, and location mapping.</p>
Neurons for infant social behaviors in the mouse zona incerta
<p><strong>Neurons for infant social behaviors in the mouse zona incerta</strong></p> <p>Repository containing datasets supporting the study.</p> <p>Github link to related analysis code: https://github.com/yxl95/zona_incerta_infant_social_behavior</p>
Knowledge of Social Networks for Health is Associated with COVID-19 Health Protective Behaviors
<p>This is the dataset and stata code for the paper "Knowledge of Social Networks for Health is Associated with COVID-19 Health Protective Behaviors” submitted to Plos One May 1st, 2024.</p>
Social networks and transformative behaviors in a grassland social-ecological system
<p>Dataframe for analysis presented in Nesbitt et al.'s <span>Social networks and transformative behaviors in a grassland social-ecological system published in People and Nature. Dataframe includes responses from an ego network survey administered to Nebraska (USA) ranchers in 2021. </span></p> <p><span>Metadata describes each variable in further detail including the question number from the survey.</span></p> <p> </p>
Data of Chinese treatment group for the research work "Disentangling material, social, and cognitive determinants of human behavior and belief".
<p>This repository contains data files of Chinese treatment group for the research work "Disentangling material, social, and cognitive determinants of human behavior and belief".</p>
Spatial and Social Behavior of Acanthurus triostegus on Moorea (French Polynesia) and Palmyra Atoll (USA), 2017-2018
These data describe the schooling behavior of coral reef fish on Moorea (French Polynesia) and Palmyra Atoll (USA) in 2017 and 2018. Data are grouped into two sets of observations: 1) surveys measuring the abundance of reef fish and the proportion of those fish occurring in schools, and 2) behavioral observations including time spent grazing and GPS tracks of schooling and solitary Acanthurus triostegus.
Twice weekly monitoring of a Microtus ochrogaster population and social behavior in alfalfa in eastern Illinois, 1982-1987.
These data were obtained as part of a field study on social behavior of the prairie vole, Microtus ochrogaster in alfalfa. The study was conducted in two adjacent 1-ha alfalfa (Medicago sativa) fields within the University of Illinois Biological Research Area (Phillips Tract). Social groups were monitored over a 63-month period, from March 1982 through July 1984 in field 1 and from October 1983 to May 1987 in field 2, by locating underground and surface nests and subsequent trapping, twice weekly. 4-5 live traps were set around the entrances to underground nests and runways leading to a surface nest of social groups. Each month the study sites were also trapped at a 10-m grid interval as a part of an ongoing 25-year trapping study (Getz, L.L. 2024. Environmental Data Initiative. https://doi.org/10.6073/pasta/2dae8f08578ce31e7817c92a0f6acc87).
Zebra finches increase social behavior in traffic noise: implications for urban songbirds
<p>Statistical code & datasets for "Zebra finches increase social behavior in traffic noise: implications for urban songbirds" manuscript submitted to <em>Acta ethologica. </em>Also includes audio file for traffic noise playback in described experiment. </p>
Social behavior among nocturnally migrating birds revealed by automated moonwatching
<p>Migrating birds often fly in group formations during the daytime; whereas at night, it is generally presumed that they fly singly. However, it is difficult to quantify group behavior during nocturnal migration as there are few means of directly observing interactions among individuals. We employed an automated form of moonwatching to estimate percentages of birds that appear to migrate in groups during the night within the Central Flyway of North America. We compared percentages of birds in groups across the spring and fall and examined overnight temporal patterns of group behavior. We found groups were rare in both seasons, never exceeding 10% of birds observed, and were almost nonexistent during the fall. We also observed an overnight pattern of group behavior in the spring wherein groups were more commonly detected early in the night and again just before migration activity ceased. This finding may be related to changes in species composition of migrants throughout the night, or alternatively it suggests that group formation may be associated with flocking activity on the ground as groups are most prevalent when birds begin and end a night of migration.</p>
Fig. 2 in Social Behavior and Communication in the Neotropical Cicada Fidicina mannifera (Fabricius) (Homoptera: Cicadidae)
Fig. 2. Waveforms of two signals of Fidicina mannifera. (A) One complete call; (B) Twelve pulses from a calling song. Total X axis length is 280 ms in (A) and 18 ms in (B).
Fig. 1 in Social Behavior and Communication in the Neotropical Cicada Fidicina mannifera (Fabricius) (Homoptera: Cicadidae)
Fig. 1. Audiospectrograms of four acoustic displays in the repertoire of Fidicina mannifera. (A) Song; (B) Calls, given in alternation by two males (numbers below the calls identify the caller); (C) Low-amplitude song; (D) Disturbance sound.
Fig. 3 in Social Behavior and Communication in the Neotropical Cicada Fidicina mannifera (Fabricius) (Homoptera: Cicadidae)
Fig. 3. Proportion of calls vs. songs given by male Fidicina mannifera in relation to nearestneighbor distance. Note that the relationship with distance is not linear (fitted curve is logarithmic).
Food and social cues modulate reproductive development but not migratory behavior in a nomadic songbird, the Pine Siskin (Pinus spinus)
<p>Many animals rely on photoperiodic and non-photoperiodic environmental cues to gather information and appropriately time life history stages across the annual cycle, such as reproduction, molt, and migration. Here, we experimentally demonstrate that the reproductive physiology, but not migratory behavior, of captive Pine Siskins responds to both food and social cues during the spring migratory-breeding period. Pine Siskins are a nomadic finch with a highly flexible breeding schedule and, in the spring, free-living Pine Siskins can wander large geographic areas and opportunistically breed. To understand the importance of non-photoperiodic cues to the migratory-breeding transition, we maintained individually housed birds on either a standard or enriched diet in the presence of group-housed heterospecifics or conspecifics experiencing either the standard or enriched diet type. We measured body condition and reproductive development of all Pine Siskins and, among individually housed Pine Siskins, quantified nocturnal migratory restlessness. In group-housed birds, the enriched diet caused increases in body condition and, among females, promoted reproductive development. Among individually housed birds, female reproductive development differed between treatment groups whereas male reproductive development did not. Specifically, individually housed females showed greater reproductive development when presented with conspecifics compared to heterospecifics. The highest rate of female reproductive development, however, was observed amongst individually housed females provided the enriched diet and maintained with group-housed conspecifics on an enriched diet. Changes in nocturnal migratory restlessness did not vary by treatment group or sex. By manipulating both the physical and social environment, this study demonstrates how multiple environmental cues can affect the timing of transitions between life history stages with differential responses between sexes and between migratory and reproductive systems.</p>
Fig. 2 in Feeding and social behavior of the piabanha, Brycon devillei (Castelnau, 1855) (Characidae: Bryconinae) in the wild, with a note on following behavior
Fig. 2. Mean values of proportion of time expressing different foraging tactics by Brycon devillei for each season in the RPSP, between July 2006 and April 2009.
Fig. 3 in Feeding and social behavior of the piabanha, Brycon devillei (Castelnau, 1855) (Characidae: Bryconinae) in the wild, with a note on following behavior
Fig. 3. Two individuals of Brycon devillei aligned sideways to the timburé, Leporinus garmani, on a sand bank in the rio Preto channel. Photo by P. G. Azevedo.
Data from: Behavioral adjustments in the social associations of a precocial shorebird mediate the costs and benefits of grouping decisions
<p>Animals weigh multiple costs and benefits when making grouping decisions. The cost-avoidance grouping framework proposes that group density, information quality, and risk affect an individual's preference for con- or heterospecific groups. However, this assumes the cost-benefit balance of a particular grouping is constant spatiotemporally, which may not always be true. Investigating how spatiotemporal context influences grouping choices is therefore key to understanding how animals contend with changing conditions. </p> <p>Changes in body size during development lead to variable conditions for individuals over short timescales that can influence their ecological interactions. Hudsonian godwits (Limosa haemastica), for instance, form a protective nesting association with a major predator of young godwit chicks, colonial short-billed gulls (<em>Larus brachyrhynchus</em>). Godwit broods may avoid areas of higher gull densities when chicks are susceptible to gull predation but likely experience higher risk from alternative predators as a result. Associating with conspecifics could allow godwits to buffer these costs but requires enough other broods with whom to group. </p> <p>To determine how age-dependent predation risk and conspecific density influence godwit grouping behaviors, we first quantified the time-dependent effects of con- and heterospecific interactions on the mortality risk for godwit chicks throughout development. We then determined how godwit density and chick age affected their associations with con- and heterospecifics. </p> <p>We found that younger godwit chicks' survival improved with closer association with conspecifics, earlier hatch dates, and lower gull densities, whereas older chicks survived better with earlier hatch dates, though this effect was less clear. Concomitantly, godwit broods avoided gulls early in development and when godwit densities were high but maintained loose associations with conspecifics throughout development. </p> <p>We identified how individuals can optimally shift with whom they group according to risks that vary spatially and temporally. Investigating the effects of a species' ecological interactions across spatiotemporal contexts in this way can shed light on how animals adjust their associations according to the costs and benefits of each association.</p>
Figure 2: Optimization in natural ants collective behavior: foraging and clustering (from [8])-Self-organization and social insects algorithms
<p>On figure 2, two examples of self-organization in natural ants are presented.<br> On the left side, the well-known Deneubourg experiment consists to highlight<br> with a very simple device the ant foraging problem. The ant objectives is<br> to find the optimal way from nest to food source, using pheromone trail deposition.<br> On the right side, cemetery clustering formation are shown at 4<br> successive times: ants form piles of corpses to clean their nests. Each of them<br> has elementary actions, unknowing the whole situation, but dealing only with<br> local information. There is no supervisor to lead the piles formation which<br> emerges from ant interactions.</p>
Plains zebra time budgets, social behavior, and communication during the 2021-2022 Laikipia-Samburu ecosystem drought
<p>Anthropogenically induced climate change has significantly increased the frequency of acute weather events, such as drought. As human activities amplify environmental stresses, animals may be forced to prioritize survival over behaviors less crucial to immediate fitness, such as socializing. Yet, social bonds may also buffer organisms from the deleterious effects of environmental conditions. We investigated how the highly social plains zebra (<em>Equus quagga</em>) modify their activity budgets, social networks, and multimodal communication during a drought. This dataset contains a) activity budget, b) steps per minute as a proxy for foraging effort, c) nearest neighbor association data, d) interaction rate, e) juvenile social interaction partner data, and f) multimodal communication data.</p>
Reverse social contagion as a mechanism for regulating mass behaviors in highly integrated social systems
<h1>Reverse social contagion as a mechanism for regulating mass behaviors in highly integrated social systems</h1> <p>This repository houses supporting data for “Reverse social contagion as a mechanism for regulating mass behaviors in highly integrated social systems”. It contains three archives consisting of multiple files storing inter-individual interactions, trajectory data for multiple colonies of desert harvester ants (Pogonomyrmex californicus), and the code necessary to reproduce the study results. The behavioral data sets were obtained from 30s videos filmed at 15fps. </p> <h2>Description of the data and file structure</h2> <h3>Supplementary_Archive_1.zip</h3> <p>This collection of CSV files contains the antennal contact interactions among individual workers from colonies. Each file name represents the colony code and the data contained in each file belongs to a single colony. Each file contains three columns: The first (1) column represents the tag of an individual observed, the second (2) column represents the tag of the individual it interacted with, and the third (3) column represents the frame of the video at which the interaction occurred.</p> <h3>Supplementary_Archive_2.zip</h3> <p>This group of mdf files contains the trajectory data for each individual of a harvester ant colony. The files were generated using the ImageJ plugin MTrackJ. Each file contains the data of one colony and the filename represents the code of said colony. The data contained in this file is organized in rows and columns. The first row indicates the MTrackJ software version used to generate the file. The second row indicates the displaying preferences for the MTrackJ software. The third and fourth rows indicate the number of assemblies and clusters, respectively. However, this can be safely ignored as the colony was treated as a whole. The rows starting with ‘Track’ indicate the tag of the individual observed followed by its identifying number “Track 1” belongs to individual 1, “Track 2” belongs to individual 2, “Track 3 to individual 3, and so forth. The lines that start with ‘Point’ after each ‘Track’ represent the point in space in the video for each individual in a given frame. The second column after ‘Point’ simply refers to the point ID in the frame “e.g. Point 1”. The third and fourth columns represent the ‘x’ and ‘y’ coordinates in the video frame. The fourth, fifth, and sixth columns represent the dimensions of an image stack. In this case, the fourth and sixth columns are fixed to 1 and the fifth column represents the frame at which the point is taken. Each point is captured in 5-frame increments.</p> <h2>Code/Software</h2> <h3>Supplementary_Archive_3.zip</h3> <p>This archive contains the code necessary to reproduce the results of the study in the form of a Mathematica notebook. It also contains a folder with the trajectory data for each individual of a harvester ant colony, in a simplified format from that available in Supplementary_Archive_2.zip. Each CSV file in this folder corresponds to a different colony. It has four columns, respectively representing the identifying number of the individual observed, the frame number at which the observation, and the ‘x’ and ‘y’ coordinates, in that order. Finally, a XLSX file contains the number of individuals in each colony (first column), the metabolic rate of the colony (second column), and the identifying number of the colony (third column; numbers followed by the letter 's' correspond to size-reduced colonies). </p>
Fig. 2. Maximum likelihood tree for Crematogaster rothneyi and C. yaharai inferred from 12S in Fig. 7 in Effect of Kleptoparasitic Ants on the Foraging Behavior of a Social Spider ( Karsch, 1891).
Fig. 2. Maximum likelihood tree for Crematogaster rothneyi and C. yaharai inferred from 12S rRNA sequences (12S, 387 bp). Numbers above nodes indicate the bootstrap values. Please note, only one sequence from each population was available.
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.