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.
4,028
datasets available to search
ShareScore release 0.7.1
Dataset results
4,028 results for “Behaviour”
Рис. 2. ПоΛигон набΛюΑения за инΑивиΑуаΛьным повеΑением гренΛанΑского Λемминга, о. ВрангеΛя, июнь-август 1987 г. Fig. 2. Observation site to monitor individual behavior of the Greenland lemming, Wrangel Island, June–August 1987 in Territorial behaviour of the greenlandic lemming (Dicrostonyx groenlandicus Trail, 1823) on Wrangel Island
Рис. 2. ПоΛигон набΛюΑения за инΑивиΑуаΛьным повеΑением гренΛанΑского Λемминга, о. ВрангеΛя, июнь-август 1987 г. Fig. 2. Observation site to monitor individual behavior of the Greenland lemming, Wrangel Island, June–August 1987
Fig. 8 in Territorial behaviour of the greenlandic lemming (Dicrostonyx groenlandicus Trail, 1823) on Wrangel Island
Fig. 8. The dynamics of the average length of the run, the maximum distance from the burrow during the activity phase and an increase in the area of habitat of the young Greenland lemmings during the first 23 days after leaving the burrow
Рис. 5. ПроΑоΛжитеΛьность фаз активности и покоя ♀ гренΛанΑского Λемминга в периоΑ набΛюΑения 12.07 и 13.07 1987 г., о. ВрангеΛя Fig. 5. Duration of rest-activity phases of the Greenland lemming ♀ during the observation period, 12–13 July, 1987, Wrangel Island in Territorial behaviour of the greenlandic lemming (Dicrostonyx groenlandicus Trail, 1823) on Wrangel Island
Рис. 5. ПроΑоΛжитеΛьность фаз активности и покоя ♀ гренΛанΑского Λемминга в периоΑ набΛюΑения 12.07 и 13.07 1987 г., о. ВрангеΛя Fig. 5. Duration of rest-activity phases of the Greenland lemming ♀ during the observation period, 12–13 July, 1987, Wrangel Island
Fig. 4 in Territorial behaviour of the greenlandic lemming (Dicrostonyx groenlandicus Trail, 1823) on Wrangel Island
Fig. 4. Trajectories of ♂ movement during the observation period: a) 7 July from 00:57 to 06:40 (5 hours 43 minutes); b) 5 August from 21:00 to 22:53 (1 hour 53 minutes). The trajectories of movement are indicated by a solid black line. For other designations see Fig. 2
Fig. 3 in Influence of Hepatozoon parasites on host-seeking and host-choice behaviour of the mosquitoes Culex territans and Culex pipiens
Fig. 3. Time of mosquito biting activity on infected or uninfected frogs. Mosquitoes that fed on infected frogs are represented by the solid line, and those that fed on uninfected frogs are represented by the dashed line. The top figure represents the time for each mosquito to land in trials where mosquitoes were allowed to feed to repletion (i.e., uninterrupted trials). A significantly higher proportion of mosquitoes that fed on infected frogs began to land later in the trial, compared to mosquitoes feeding on uninfected frogs. The bottom figure represents the time for each mosquito to land in trials where mosquitoes were allow to land but were removed before feeding (i.e., interrupted trials). A significant difference in the time for mosquitoes to land on infected or uninfected frogs was not observed in interrupted trials.
Fig. 4 in Influence of Hepatozoon parasites on host-seeking and host-choice behaviour of the mosquitoes Culex territans and Culex pipiens
Fig. 4. Time between mosquito bites on infected and uninfected frogs. Mosquitoes that were allowed to feed are represented by a solid line. Mosquitoes that were aspirated off the frog after landing are represented by the dashed line. A significantly longer amount of time passed between the bite of one mosquito and the bite of the following mosquito during trials in which mosquitoes were allowed to feed on a frog, compared to trials where mosquitoes were removed before feeding.
Fig. 1 in Influence of Hepatozoon parasites on host-seeking and host-choice behaviour of the mosquitoes Culex territans and Culex pipiens
Fig. 1. Number of mosquitoes that chose wild-caught frogs paired by different levels of infection. Each panel represents a pairing by infection level in green frogs. Each trial was repeated three times, and separate trials are shown by different shapes. Higher numbers of mosquitoes chose to land on wild-caught frogs with high infections of H. clamatae when paired with frogs with moderate infections or without infection. Infection level had a weakly significant effect on the number of mosquitoes that chose to land on a frog. UI = uninfected.
Fig. 2 in Influence of Hepatozoon parasites on host-seeking and host-choice behaviour of the mosquitoes Culex territans and Culex pipiens
Fig. 2. Number of mosquitoes that chose laboratory-raised frogs that were uninfected or experimentally infected. Each panel represents a pairing of infected or uninfected green frogs. Each pairing was repeated four times and each trial is represented by a different shape. Infection level did not have a significant effect on the number of mosquitoes choosing to land on a frog.
Review of Recent Trends in Measuring the Computing Systems Intelligence-igure 2. Intelligence of different living creature (accessed 01.11.2017). 2.1. A crow solving a complex task (https://www.disclose.tv/spooky-genius-crow-had-to-be-removed-from-scientific-experiment- 314886). 2.2. A group of dolphins with a social behaviour (http://www.sciencemag.org/news/2012/04/teamwork-builds-big-brains); 2.3. An orangutan that use a spear to fish (https://primatology.net/2008/04/29/orangutan-photographed-using-tool-as-spear-to-fish)
<p>Some species of birds have been shown capable of using different tools. Many studies consider the crows as very intelligent. Smirnova, Lazareva, and Zorina (2000) suggested that crows have some kind of numerical ability. Figure 2.1 presents a crow that uses a tool, a small stone in order to catch a worm from a glass of water.The dolphins in many studies are considered intelligent at the individual level. An advanced ability of dolphins is the self-awareness. Marten and Psarakos (1995) presented an interesting study based on self-view television to distinguish between self-examination and social behavior in the Bottlenose dolphin. The most well-known abilities of dolphins are to teach, learn and cooperate. Dolphins have a complex communication and social behaviour. Figure 2.2 presents the image of a common group of dolphins. Some studies prove that primates are one of the most intelligent in the class of animals (Reader, Hager, & Laland, 2011). Orangutans are one of the most intelligent primates. The ability of orangutans to use different types of tools in order to perform tasks is well-known. Figure 2.3 presents an orangutan that uses a spear to catch fish. The orangutans can be considered intelligent at individual level.</p>
Review of Recent Trends in Measuring the Computing Systems Intelligence-Figure 1. Intelligence of different simple living creature (accessed 01.11.2017). 1.1. A carnivorous plants catching an insect (https://phys.org/news/2016-05-colombia-peace-reveal-jungle-species.html); 1.2. A colony of ants solving a very complex task (https://mappingignorance.org/2016/05/27/rafting-ants); 1.3. The collective behaviour of a school of fish (https://simple.wikipedia.org/wiki/Shoaling_and_schooling)
<p>The biological intelligence of different life forms, ranging from very simple (such as plants) to very complex (such as humans) is the subject of many studies and a large amount of research. Frequent studies related to different kind of biological intelligence include: the intelligence of horses (Krueger, & Heinze, 2008; Krueger, Farmer, & Heinze, 2014; Schuetz, Farmer, & Krueger, 2016), intelligence of pigs (Broom, Sena, & Moynihan, 2009), intelligence of dogs (Coren, 1995), intelligence of primates (Reader, Hager, & Laland, 2011) and so one. Figures 1, 2, and 3 present some biological life forms that are frequently considered intelligent. Trewavas (2002; 2005) considered that plants intelligence should be based on principles such as their ability to adjust their morphology, and phenotype accordingly to ensure self- preservation and reproduction. Figure 1.1 presents an intelligent plant (carnivorous) that uses a strategy for catching very fast flying insects. In order to eat the insect, it makes a movement. Figure 1.1 presents the catching of an insect by a carnivorous plant. The intelligence of colonies of ants, termites and other insects that live in large colonies is considered at the colony level (Brady, Fisher, Schultz, & Ward, 2014; Johnson, Borowiec, Chiu, Lee, Atallah, & Ward, 2013). Figure 1.2 presents the coherent intelligent surviving behaviour of a colony of a species of ants. The ants make a structural reorganization in order to move on the surface of the water. Figure 1.3 presents a very large school of fish with an intelligent coherent collective feeding and self-protecting behaviour. Each individual fish has a very simple behavior. Based on this it cannot be considered intelligent. The intelligence in large schools of fish emerges at the collective level (Shaw, 1978; Parrish, Viscedo, & Grunbaum, 2002).</p>
Dataset of the publication "Cross-sectional study of prevalence of dementia, behavioural symptoms, mobility, pain and other health parameters in nursing homes in Austria and the Czech Republic: results from the DEMDATA project"
<p>Dataset of the publication Stefanie R. Auer , Margit Höfler, Elisabeth Linsmayer, Anna Beránková, Doris Prieschl, Paulina Ratajczak,<br> Michal Šteffl and Iva Holmerová (2018) "Cross-sectional study of prevalence of dementia, behavioural symptoms, mobility, pain and other health parameters in nursing homes in Austria and the Czech Republic: results from the DEMDATA project"</p>
Data supplement to: "Refractory depression - Mechanisms & Efficacy of Radically Open Dialectical Behaviour Therapy (RefraMED): findings of randomised trial on benefits and harms"
<p>Data and code to support primary analyses reported in "Refractory depression – mechanisms and efficacy of radically open dialectical behaviour therapy (RefraMED): findings of a randomised trial on benefits and harms". British Journal of Psychiatry. doi: 10.1192/bjp.2019.53</p>
Adult-level learning and behavioural flexibility in T. scincoides
<p>Raw data files and R code</p> <p> </p>
The behaviour of copper at the nano-scale in an Al-Zn-Mg-Cu alloy, AA7010
<p>Data plots and images accompanying figures to paper.</p>
KPIs for the validation of the GreenSoul behavioural models
<p>This document presents both the methodology followed to select the Key Performance Indicators (KPI) and the final KPIs selected to measure the impact achieved by the actions carried on during the pilots. To select the KPIs we first have prepared a comprehensive list of KPIs to consider, then we follow a Delphi Method to reach a consensus among a panel of experts about the how to score every KPI in several aspects and finally we perform a descriptive statistical analysis to select the best set of KPIs.</p>
Figure 6 in A comparative study of the diurnal behaviour of the Northern Shoveller (Anas clypeata) during the wintering season at Garaet Hadj-Tahar (North-East Algeria) and Garaet Timerganine (Algerian highlands)
Figure 6. Balance of the rhythms of daytime activities of the Shovellers in Garaet Hadj-Tahar during the 2 wintering seasons of 2007 and 2009.
Figure 4 in A comparative study of the diurnal behaviour of the Northern Shoveller (Anas clypeata) during the wintering season at Garaet Hadj-Tahar (North-East Algeria) and Garaet Timerganine (Algerian highlands)
Figure 4. Percentage of time allocated by the Shoveller for diurnal activities at (A) Garaet Hadj-Tahar and (B) Garaet Timerganine.
Figure 2 in Breeding behaviour of Purple Sunbird, Cinnyris asiaticus (Latham, 1790) in semiurban area of Punjab
Figure 2. Egg laying and hatching in purple sunbird. a. A Clutch in Nest, b. Egg Size & Shape, c. Female PSB Incubating the Eggs, d. Hatching of Chick-1 (Day-1), e. Hatching of Chick-2 (Day-1), f. Hatching of Chick-3 (Day-3).
Figure 3 in Breeding behaviour of Purple Sunbird, Cinnyris asiaticus (Latham, 1790) in semiurban area of Punjab
Figure 3. Growth and fledging of chicks in purple sunbird. a. Chick-1 (Day-4), b. Chick-1 (Day-8), c. Chick-1 (Day-10), d. Chick-1 (Day-15), e. Use of Repaired Nest, f. Removal of Unhatched Egg by Female PSB.
Figure 1 in Araneophagic behaviour of the elusive snake Liopeltis calamaria (Günther, 1858) (Reptilia: Squamata: Colubridae)
Figure 1. Feeding habit and prey capture in Liopeltis calamaria (Günther, 1858). A-E: the snake feeding on spiders, F: the snake feeding on grasshopper.
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.