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.
6,025
datasets available to search
ShareScore release 0.9.0
Dataset results
6,025 results for “Science of science”
Database of parameters related to intensive fattening of lambs of sheep breeds raised in Latvia in 2022 within the framework of project of the Latvian Council of Science LZP-2021/1-0489 project
<p>Project of The Latvian Council of Science (LCS) - LZP-2021/1-0489 project: “<strong>Development of an innovative approach to identify biological determinants involved in the between-animal variation in feed efficiency in sheep farming</strong>”</p> <p>The <strong>aim of the project</strong> is to determine whether the feed efficiency status of Latvian meat sheep breeds could be predicted using a panel of genetic and molecular markers previously found to be associated with divergent Feed efficiency status in a training population of lambs when fed the same diet.</p> <p><strong>Novelty</strong>: to determine the parameters predicting the most productive result of lamb rearing, we set out to develop the cheapest and most effective method for determining markers of feed efficiency - based on molecular and genetic markers obtained from the blood of live lambs.</p> <p><strong>About the project:</strong></p> <p>The costs associated with lambing (buying or keeping sheep) and preparing or purchasing feed are the two largest components of variable costs in sheep raising. Feed costs are high due to poor grain growing conditions in major producing countries, the use of feed grains in ethanol production, and increased competition for land in crop production compared to urban development. Feed efficiency in growing lambs (i.e., the animal's ability to reach a market or adult body weight (BW) with the least amount of feed intake) is a key factor in the sheep industry. Improving Feed efficiency reduces production costs. Improving Feed efficiency by 5% can bring economic benefits that are up to four times higher than a 5% increase in average daily gain (ADG).</p> <p>Traditionally, meat breeding programs have focused on outputs due mainly to the routine availability of phenotypic data on outputs or correlated traits. Currently, no marker has successfully explained enough of the variability in feed efficiency that they were used as part of a routine improvement program, as well as according to our data, no genetic parameters for performance and feed efficiency traits are available for sheep. The physiological determinants of feed efficiency or putative biomarkers used to analyze animal-to-animal variation in live lambs could be used as a cost-effective and rapid tool for genetic selection or management decisions.</p> <p><strong>About the data of the project:</strong></p> <p>LZP-2021/1-0489 project data on lamb samples of the year 2022, or A22 group, which consists of 76 intensively fattened lambs from six breeds and nine samples from the LT breed, which were raised in the meadow and are semi-sibi lambs within the scope of the study.</p> <p>Based on the requirements of the breeding program of the breeds, every year, the offspring of the sire ram, certified for breeding activity, are selected and analyzed to estimate the sire rams. All lambs were born as twins, triplets or quadruplets from different ewes and health status was assessed before inclusion in the study so that there were at least two lambs per sire ram from the breed. This study was carried out in cooperation with Latvian Sheep Breeders' Association at the ram breeding control station.</p> <p>The database contains data on ultrasonography measurements of lambs during the beginning and end of fattening, intensive fattening data - real and calculated on the 90th and 150th day, the amount of feed used and slaughter data. Ultrasonography data were used to calculate muscle and/or fat depth changes at the 13th rib during the fattening period.</p> <p> </p> <p>The data is the<strong> joint property</strong> of the participants of the LCS project: the University of Latvia and the Latvian University of Life Sciences and Technologies.</p> <p> </p>
Database of average values of parameters of sire rams of Latvian dark-head breed calculated from values of intensive fattening lambs within the framework of the project of the Latvian Council of Science LZP-2021/1-0489 project
<p>Project of The Latvian Council of Science (LCS) - LZP-2021/1-0489 project: “<strong>Development of an innovative approach to identify biological determinants involved in the between-animal variation in feed efficiency in sheep farming</strong>.”</p> <p><strong>The aim of the project</strong> is to determine whether the feed efficiency status of Latvian meat sheep breeds could be predicted using a panel of genetic and molecular markers previously found to be associated with divergent Feed efficiency status in a training population of lambs when fed the same diet.</p> <p><strong>Novelty</strong>: to determine the parameters predicting the most productive result of lamb rearing, we set out to develop the cheapest and most effective method for determining markers of feed efficiency - based on molecular and genetic markers obtained from the blood of live lambs.</p> <p><strong>About the project:</strong></p> <p>The costs associated with lambing (buying or keeping sheep) and preparing or purchasing feed are the two largest components of variable costs in sheep raising. Feed costs are high due to poor grain growing conditions in major producing countries, the use of feed grains in ethanol production, and increased competition for land in crop production compared to urban development. Feed efficiency in growing lambs (i.e., the animal's ability to reach a market or adult body weight (BW) with the least amount of feed intake), is a key factor in the sheep industry. Improving Feed efficiency reduces production costs. Improving Feed efficiency by 5% can bring economic benefits that are up to four times higher than a 5% increase in average daily gain (ADG).</p> <p>Traditionally, meat breeding programs have focused on outputs due mainly to the routine availability of phenotypic data on outputs or correlated traits. Currently, no marker has successfully explained enough of the variability in feed efficiency that they were used as part of a routine improvement program, as well as according to our data, no genetic parameters for performance and feed efficiency traits are available for sheep. The physiological determinants of feed efficiency or putative biomarkers used to analyze animal-to-animal variation in live lambs could be used as a cost-effective and rapid tool for genetic selection or management decisions.</p> <p>As of 2018, there were 49.5 thousand ewes and 73 sire rams in Latvia from a flock of 134.29K sheep. In 2018, Latvian Dark-Head (Latvijas tumšgalve; LT) sheep were bred to implement the sheep breeding program in 35 farms, which had a total of 3,752 ewes, while 13 farms had 43 breeding rams. According to the EUROSTAT data, the number of sheep in Latvia in 2018 was 107.29K, but in December 2021 was 90.34K.</p> <p>The Latvian Dark-Head sheep breed was created by crossing local Latvian sheep with Shropshire and Oxfordshire rams imported from Sweden and England. The first pedigree or breeder's book for LT rams was issued in 1939. Currently, the live weight of ewes of the Latvian Dark-Head breed is about 55 – 65 kg, rams - 95 – 120 kg, wool cut 3.5 – 4.5 and 5.0 – 6.0 kg, respectively. The average prolificacy of ewes is 150 - 160%.</p> <p>Breeding of Latvian Dark-Head sheep in Latvia is carried out according to phenotypic and bloodline data, without information about values of feed efficiency indicators or carrying out genetic breeding. Therefore, this study aimed to analyze the Latvian Dark-Head breeds rams according to lambs' feed efficiency values.</p> <p><strong>About the data of the project:</strong></p> <p>LZP-2021/1-0489 project data on Latvian dark-head (LT; Latvijas tumšgalve) of the year 2022 lamb samples, or A22_LT group. In the group were 48 lambs from 13 sire rams.</p> <p>Based on the requirements of the breeding program of the breeds, every year, the offspring of the sire ram, certified for breeding activity, are selected and analyzed to estimate the sire rams. All lambs were born as twins, triplets or quadruplets from different ewes and health status was assessed prior to inclusion in the study so that there were at least two lambs per sire ram from the breed. This study was carried out in cooperation with Latvian Sheep Breeders' Association at the ram breeding control station.</p> <p>The dataset includes average data of each sire ram: (1) ultrasonography measurements of lambs during the beginning and end of fattening, (2) intensive fattening data - real and calculated on the 90th and 150th day, (3) the amount of feed used, (4) slaughter data, (5) biochemical indicators: Insulin-like growth factor 1, Insulin, Total thyroxine, Adrenocorticotropic hormone, Haematocrit, Hemoglobin, Glucose, (6) feed efficiency indicators: Feed efficiency (FE), Feed conversion ratio (FCR), Relative growth rate (RGR), Kleiber’s ratio (KR), Residual feed intake (RFI), Residual weight gain (RWG) and Residual intake and body weight gain (RIG).</p> <p> </p> <p>The data is the joint property of the participants of the LCS project: the University of Latvia and the Latvian University of Life Sciences and Technologies.</p>
FIGURE 3. Thismia paradisiaca. A. Habit. B in A flower in paradise: citizen science helps to discover Thismia paradisiaca (Thismiaceae), a new species from the Chocó Biogeographic region in Colombia
FIGURE 3. Thismia paradisiaca. A. Habit. B. Flower (top view). C1. Longitudinal dissection of flower. C2. Outer surface of the hypanthium. C3. Inner surface of hypanthium, showing papillae. C4. Glandular-like surface of the dorsal veins of the hypanthium. D1. Upper outer tepal (adaxial view). D2. Lateral outer tepal (abaxial view). E1. Dorsal stamens (inner=abaxial view). E2. Dorsal stamen (outer=adaxial view). E3. Papillae of the dorsal stamen apical lobe. F1. Ventral stamens (inner=abaxial view). F2. Ventral stamen (outer=adaxial view). F3. Papillae of the ventral stamen lateral lobe. G. Style and stigma. B.C. Corrales Restrepo, S. Guzmán-Guzmán & E. Restrepo 001. Illustration by Maria José Rodriguez.
Dataset of Effect of science outreach activities on chemophobic conceptions at the high school level
<p>Dataset corresponding to the article "Effect of science outreach activities on chemophobic conceptions at the high school level"</p>
DEEPICE Infographics about ice core science [French]
Open the record for dataset details and reuse information.
STATEMENT OF SCIENCE IN "TAQVIMUL ADILLA" BY ABU ZAYD DABUSI
Open the record for dataset details and reuse information.
FIGURE 3 in Remarkable fly (Diptera) diversity in a patch of Costa Rican cloud forest: Why inventory is a vital science
FIGURE 3. Venn diagrams indicating number of species shared by samples from Zurquí with species in a single Malaise trap at each of Tapantí and Las Alturas. Jaccard Index of similarity (JI) values are shown as percentages for each paired comparison. (A) Malaise trap # 1 at Zurquí. (B) Malaise trap # 2 at Zurquí. (C) All methods at Zurquí. Total number for a given site is underlined. Families studied at all three sites are shown in bold in Table 1.
Shanghai Meiji Health Science and Technology Co., Ltd
ClinicalTrials.gov study NCT04651023. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Shadow for All, a Citizenship Science Study to Promote the Prevention of Skin Cancer
ClinicalTrials.gov study NCT06145464. IPD Sharing: NO. Countries: 0. Publications: 0.
Proof-of-Science, Prospective, Interventional, Three-arm, Double-Blind, Randomized, Safety and Efficacy Real World Evidence Study.
ClinicalTrials.gov study NCT06552039. IPD Sharing: NO. Countries: 0. Publications: 0.
ABC Science Collaborative Registry Study
ClinicalTrials.gov study NCT04781218. IPD Sharing: NO. Countries: 0. Publications: 0.
Clinical Assessment of Next Science Wound Gels in Healing Below the Knee Amputation Surgical Wound Compared to SOC
ClinicalTrials.gov study NCT04053946. IPD Sharing: NO. Countries: 0. Publications: 0.
Evaluation of Interventions Based on Behavioral Sciences to Reduce Episiotomy Use
ClinicalTrials.gov study NCT06625866. IPD Sharing: NO. Countries: 0. Publications: 0.
Decreasing the Stigma of Mental Illness Among Health Science Students Through a Mentoring Program
ClinicalTrials.gov study NCT06593171. IPD Sharing: Not stated. Countries: 0. Publications: 0.
PSP Integrated Science Investigation of the Sun, Energetic Particle Instrument-Hi (ISOIS EPI-Hi) Low Energy Telescope 2 (LET2) Rates, Level 2 (L2), 5 min Data
Parker Solar Probe, PSP, Integrated Science Investigation of the Sun, IS☉IS, Energetic Particle Instrument, EPI-Hi, Low Energy Telescope 2, LET2, Rates: The Epoch time tags indicate midpoint of integration. For information concerning use of the IS☉IS data please refer to the Energetic Particle Data User Guide available from the PSP IS☉IS Science Operations Center, SOC, web site hosted by the University of New Hampshire. The energetic particle pitch angle calculations are made possible via use of magnetic field data provided by the PSP FIELDS team.The public data reflect current instrument calibration as determined by the IS☉IS science team. Calibration efforts are ongoing and the public data will be updated over the course of the mission based on improved understanding of instrument response to the near-Sun energetic particle environment. IS☉IS visualization tools are provided as a quicklook utility for the community to better access the IS☉IS data and are also under continual development. While we make every effort to ensure their accuracy, the IS☉IS team cannot guarantee that they are error-free. For questions regarding the use of IS☉IS data, please contact Colin Joyce (cjjoyce@princeton.edu).Refer to the following web site concerning the Rules of use for the IS☉IS energetic particle data: https://spp-isois.sr.unh.edu/ISOIS_Terms_of_Use.html.The PSP IS☉IS effort is funded as part of the NASA Parker Solar Probe mission under contract NNN06AA01C. Use of any PSP IS☉IS data in publications or presentations should include the following text for acknowledgement and also cite the PSP IS☉IS instrument suite publication:Acknowledgement: Thanks to the Integrated Science Investigation of the Sun (IS☉IS) Science Team (PI: D. J. McComas, Princeton University).Citation: McComas, D. J. (2020). PSP Integrated Science Investigation of the Sun, Energetic Particle Instrument-Hi (ISOIS EPI-Hi) Low Energy Telescope 2 (LET2) Rates, Level 2 (L2), 5 min Data [Data set]. NASA Space Physics Data Facility.
Van Allen Probe A Electric and Magnetic Field Instrument Suite and Integrated Science (EMFISIS) Density and other Parameters derived by digitizing Traces on Spectrograms, Level 4 (L4), 0.5 s Data
Van Allen Probe A, Electric and Magnetic Field Instrument Suite and Integrated Science, EMFISIS, derived Density and other Parameters inferred by digitizing Traces on Spectrograms. The EMFISIS Waves Instrument provides a Measure of the Frequency of the Upper Hybrid Resonance Band thereby providing an accurate Determination of the Electron Density. The Electron Density is most easily and accurately measured by Means of Resonances and Cutoffs in the Wave Spectrum rather than Particle Detector Measurements which are subject to Spacecraft Charging and other complicating Factors.
DAWN CERES GRAVITY SCIENCE DERIVED SCIENCE DATA V3.0
This data set contains archival results from gravity investigations conducted during the Dawn mission while the spacecraft was in orbit around the asteroid Ceres. Radio measurements were made using the Dawn spacecraft and Earth-based stations of the NASA Deep Space Network (DSN). The data set includes a spherical harmonic model of Ceres's gravity field generated by the Jet Propulsion Laboratory and gravity maps; these results were derived from raw radio tracking data.
MESSENGER V/H RADIO SCIENCE SUBSYSTEM 1 EDR V1.0
This data set contains archival raw, partially processed, and ancillary/supporting radio science data acquired during the MESSENGER mission. The radio observations were carried out using the MESSENGER spacecraft and Earth-based receiving stations of the NASA Deep Space Network (DSN). The observations were designed to be part of a data set that is of sufficient quality and quantity to generate high-resolution gravity field models of Mercury. Of most interest are likely to be the Orbit Data Files in the ODF directory. The data range from 2006 to 2014; there are gaps in the data.
Space Life and Physical Sciences Research and Applications Program
Space Life and Physical Sciences Research and Applications Program
Virginia Institute of Marine Science 2005 optical measurements
Measurements made along the York River by the Virginia Institute of Marine Science.
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.