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.
316
datasets available to search
ShareScore release 0.9.0
Dataset results
316 results for “lessons”
Figure 1 in Lessons from the WBF2020: extrinsic and intrinsic value of soil organisms
Figure 1. (A) The World Biodiversity Forum was held high up in the snowy Alps in Davos. Credit: Marianne Darbi. (B) Participants of the House of Commons style debate. Participants discussed whether they thought biodiversity was declining. Credit: Marten Winter
Supplementary Data for ZeroPM D2.3 - Lessons learnt from previous applications of the essential-use concept
<p>This dataset contains the data collected for all the studies which are mentioned in the ZeroPM deliverable D2.3 titled "Lessons learnt from previous applications of the essential-use concept".</p>
Dataset for article "W18O49 Nanowhiskers Decorating SiO2 Nanofibers: Lessons from In Situ SEM/TEM Growth to Large Scale Synthesis and Fundamental Structural Understanding" in Crystal Growth & Design, Des. 2024, 24, 1, 378–390
<p>Supported dataset for publication "W18O49 Nanowhiskers Decorating SiO2 Nanofibers: Lessons from In Situ SEM/TEM Growth to Large Scale Synthesis and Fundamental Structural Understanding" in Crystal Growth & Design Des. 2024, 24, 1, 378–390, https://doi.org/10.1021/acs.cgd.3c01094.</p> <p>The directory Data contains the figures (png, jpg), and vido (AVI) source data files for the manuscript.</p>
Training sessions for innovation procurers: methods lessons learned, best practices
<p>These webinars explore practical methods and key lessons learned from implementing innovation procurement, featuring insights from the BUILD project. Using real-world case studies from municipalities across Europe, they highlight effective strategies for overcoming procurement challenges and fostering collaboration between public buyers and the market. The sessions are ideal for public procurement professionals, policymakers, and stakeholders seeking actionable guidance on leveraging procurement as a tool for innovation and sustainability.<br><br>They are available here:<br><br><a href="https://www.youtube.com/watch?v=v-9blcYpK_g">Public procurers’ exchange of best practices - Innovation Procurement Task Force webinar insights</a></p> <p><a href="https://www.youtube.com/watch?v=EY759zLpmdU">Innovation Procurement Webinar: Methods and lessons learned by real cases - the BUILD Project</a></p>
Genome Mining for Data Carpentry lesson
<p>Data for Software Carpentry Genome Mining lesson. These data are part of the study<em> "Genome analysis of multiple pathogenic isolates of Streptococcus agalactiae: Implications for the microbial pan-genome" </em>(Hervé Tettelin et al 2005)</p>
Dataset: An Experience Report on Technical Debt in Pull Requests: Challenges and Lessons Learned
<p>This dataset contains the related data for the paper titled: "An Experience Report on Technical Debt in Pull Requests: Challenges and Lessons Learned". </p>
Figure 1 in A 19th Century New Ireland Dog, Canis familiaris novaehiberniae Lesson, 1827 and the Status of Canis hallstromi Troughton, 1957
Figure 1. Map of New Guinea region showing colonial territories in the late 1800s and type localities of: (1) Canis familiaris novaehiberniae Lesson, 1827a, New Ireland; (2) C. f. papuensis Ramsay, 1879, unspecified, southeastern New Guinea; and (3) C. hallstromi Troughton, 1957, Lavani Valley, Southern Highlands District.
From population connectivity to the art of striping Russian dolls: the lessons from Pocillopora corals
<p>Here, we examined the genetic variability in the coral genus <em>Pocillopora</em>, in particular within the Primary Species Hypothesis PSH09, identified by Gélin, Postaire, Fauvelot and Magalon (2017b) using species delimitation methods [also named <em>Pocillopora eydouxi/meandrina</em> complex <em>sensu</em> Schmidt-Roach, Miller, Lundgren, & Andreakis (2014)] and which was found to split into three Secondary Species Hypotheses (SSH09a, SSH09b and SSH09c) according to assignment tests using multi-locus genotypes (13 microsatellites). From a large sampling (2,507 colonies) achieved in three marine provinces [Western Indian Ocean (WIO), Tropical Southwestern Pacific (TSP) and Southeast Polynesia (SEP)], genetic structuring analysis conducted with two clustering analyses (Structure and DAPC) using 13 microsatellites revealed that SSH09a was restricted to the WIO while SSH09b and SSH09c were almost exclusively in the TSP and SEP. More surprisingly, each SSH split into two to three genetically differentiated clusters, found in sympatry at the reef scale, leading to a pattern of nested hierarchical levels (PSH > SSH > cluster), each level hiding highly differentiated genetic groups. Thus, rather than structured populations within a single species, these three SSHs, and even the eight clusters, likely represent distinct genetic lineages engaged in a speciation process or real species. The issue is now to understand which hierarchical level (SSH, cluster or even below) corresponds to the species one. Several hypotheses are discussed on the processes leading to this pattern of mixed clusters in sympatry, evoking formation of reproductive barriers, either by allopatric speciation or habitat selection.</p> <p>This submission contains the genotypes of 2507 individuals from PSH09 for 13 microsatellites.</p>
Table 1: The Number of Words and Lessons in Book Three
<p>Three hundred and thirty three lexical items included in the English textbook, namely,<br> Birjandy, P. & Norouzi, M. & Mahmoody, G. (2004). English Book Three, which is routinely<br> assigned by the Ministry of Education for EFL teaching in Iranian public high schools in Grade<br> three were taught to the participants in the present study. The book typically includes sections of<br> reading comprehension, grammar, pronunciation practice, dialogues, and a list of new words (with<br> no explanation of meaning or synonyms) in the ending part of each lesson. These wordlists (See<br> Appendix 1) were used for vocabulary instruction and subsequent vocabulary testing in the study.<br> To save space, the number of the new words in each lesson is presented in Table 1</p>
Extended Files for "Lessons from Hubble & Spitzer: 1D Self-Consistent Model Grids for 19 Hot Jupiter Emission Spectra"
<p>This directory includes extended files for Wiser et al. 2024, "Lessons from Hubble & Spitzer: 1D Self-Consistent Model Grids for 19 Hot Jupiter Emission Spectra." </p> <p>Files:</p> <ul> <li><strong>Extended Planet Figures:</strong> For each of the 20 planets discussed in the manuscript, <em>[PlanetName].pdf </em>includes figures showing the secondary eclipse spectra and parameter estimations for each model scenario. A file for Kepler-13Ab illustrates our grid models' inability to explain the WFC3 and Spitzer observations simultaneously. </li> <li><strong>Internal Temperature Tests:</strong><em> InternalTemperatureTests.pdf</em> includes figures illustrating our inability to constrain an atmosphere's internal temperature with these model grids and the WFC3 and Spitzer observations.</li> <li><strong>Parameter Estimates .csv Tables:</strong> <ul> <li>Both .csv files include planet and star parameters (temperatures, radii, mass, logg, semimajor axis) and parameter ranges for each planet grid. They also include parameter estimations for each model scenario. Listed are the medians of each parameter's posterior probability distribution and pos/neg values encompassing the one-sigma confidence region. This information is shown visually in the extended planet figures. </li> <li><em>fiducial_stats.csv</em> includes parameter estimations for the fiducial model scenario. For planets with multiple solutions (as described in Wiser et al. 2024), multiple rows detail each solution. There is also a "limit" flag for parameters with an upper limit, lower limit, or unconstrained (UL, LL, or UC, respectively).</li> <li><em>nonfiducial_stats.csv </em>includes parameter estimates for all other model scenarios. This table does not account for multiple solutions or "limit" flags. </li> </ul> </li> <li>For complete model grids, please contact the authors. </li> </ul>
Figure 3 in Lessons learnt from large-scale eradication of Australian swamp stonecrop Crassula helmsii in a protected Natura 2000 site
Figure 3. Photo impressions of the large scale eradication of Crassula helmsii on the Island of Terschelling. A. The dominant infestation of C. helmsii in an artificial lake (location 5). B. Installing a mitigation fence in order to prevent entry by amphibians and reptiles (2.75 linear km). C. Drainage installation and steel road plates tracks. D. Excavation of 40 cm topsoil (Step 4 of the described eradication approach). E. Recolonization of characteristic native plant species in excavated area 2.5 years after the eradication of C. helmsii (March 2021). F. Guided tours in the study area to inform those concerned.
Figure 1 in Lessons learnt from large-scale eradication of Australian swamp stonecrop Crassula helmsii in a protected Natura 2000 site
Figure 1. Locations of the dune slacks (1–5) where measures for eradication of Crassula helmsii were taken.
Figure 2 in Lessons learnt from large-scale eradication of Australian swamp stonecrop Crassula helmsii in a protected Natura 2000 site
Figure 2. Flow chart of the process for large scale eradication of Crassula helmsii on the Island of Terschelling.
FIGURE 2 in First record of a breeding colony of Masked Booby (Sula dactylatra Lesson, 1831; Sulidae) in the main island of the archipelago of Fernando de Noronha (Pernambuco, Brazil)
FIGURE 2: Map of Fernando de Noronha Archipelago, highlighting the location of the breeding colony of Sula dactylatra, located at the end of the Capim-açu trail (03°52'49.38"S; 32°27'29.47"W). Unscaled. Source: © 2016 google maps.
FIGURE 1 in First record of a breeding colony of Masked Booby (Sula dactylatra Lesson, 1831; Sulidae) in the main island of the archipelago of Fernando de Noronha (Pernambuco, Brazil)
FIGURE 1: Breeding colony of Sula dactylatra located at the end of the Capim-açu trail, main island of Fernando de Noronha archipelago, September 2015. Photo: Deborah Gutierrez, 2015.
2018-02-20_RNA-Seq_lesson
<p>Files for the RNA-Seq lesson on February 20, 2018.</p> <p>You have two compressed folder:</p> <ul> <li>The "RNAseq_lesson_only_start_files.zip" contains the necessary files to start. It does not contain the expected results.</li> <li>The "RNAseq_lesson_all_files.zip" contains all files necessary for the lesson + the expected results from Kallisto and Sleuth.</li> </ul>
LEARNING FROM INNOVATION FAILURE IN TOURISM: ADVICE AND LESSONS
<p>Through in-depth interviews the EU INNOVATE research project has highlighted multiple types of risks that innovative entrepreneurs in tourism could not overcome, and critical events and factors at different stages. The aim of this video is to review some of the key lessons reported by real-life entrepreneurs participating in the research who failed to succeed. Failing to succeed with an innovative entrepreneurial venture is a painful but valuable learning opportunity. Some lessons might seem obvious but they are real-life examples which illustrate how easy it is to overlook them in practice. With the video the researchers aim to translate the research findings into a language and format that can reach potential entrepreneurs to remind them about the importance of a proactive and active management of common potential risks. The video also brings teaching opportunities to academics lecturing entrepreneurship and innovation in tourism in order to attract their students’ interest and shape their future careers as potential entrepreneurs.</p> <p> </p>
Video abstract for "Communicating climate change in a 'post-factual' society: Lessons learned from the Pole to Paris campaign"
<p>MPEG-4 video containing the video abstract for the publication "Communicating climate change in a 'post-factual' society: Lessons learned from the Pole to Paris campaign" in Geoscience Communication by Erlend Moster Knudsen and Oria Jamar de Bolsée, published in 2019.</p>
Fig. 1 in The effect of reproductive system on invasiveness: lessons from South American weevils
Fig. 1. Worldwide spatial distribution of mitochondrial and nuclear genetic variation of Naupactus cervinus and Naupactus leucoloma. The lef and right side of the pie chart depicts the mitochondrial and nuclear variants, respectively. Circles are multi-locus genotypes of Naupactus cervinus and squares are multi-locus genotypes of Naupactus leucoloma. Distribution in Argentina of the colonizer genotypes also is indicated in smaller size.
Fig. 2 in The effect of reproductive system on invasiveness: lessons from South American weevils
Fig. 2. Multi-locus genotypes of N. cervinus in locations surrounding the port of Buenos Aires (indicated by ship's wheel (helm) symbol).
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.