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.
18,658
datasets available to search
ShareScore release 0.9.0
Dataset results
18,658 results for “impacts”
Replication Data for: ``Impact of Parameterized Isopycnal Diffusivity on Shelf-Ocean Exchanges under Upwelling-Favorable Winds: Offline Tracer Simulations Augmented by Artificial Neural Network''
<p>This dataset contains the modified MAMEBUS source code, configuration files for the MITgcm and MAMEBUS simulations, model diagnostics used in the paper, and scripts to train the Artificial Neural Networks.</p>
Dataset of relationship of collaboration and scientific impact
<p>This dataset was used as part of results of an scientific article whom abstract is:</p> <p>The relationship between international collaboration and scientific impact is studied in the context of South American universities. This study aims to comprehensively analyze the strength of this relationship using nonparametric statistical methods. The records are the 244300 papers published in journals indexed in Scopus (2011-2020) by researchers affiliated to 10 South American public universities and extracted with Scival support. There is a marked trend of collaborative work, since 93% of publications were collaborative at institutional, national or international level, with a higher percentage of international collaboration. A refined analysis of the geographic collaboration of publications in Q1 journals further evidences the frequency of international collaboration. In the top 4 collaborating partner institutions for each university, the presence of the Centre National de la Recherche Scientifique of France<br> (CNRS) is observed, followed by the National Council for Scientific and Technical Research of Argentina (Conicet). It is proven that there is a statistically significant relationship (p < .01) in each of the 10 universities between collaboration (number of<br> countries) and normalized impact (FWCI). The results confirmed the hypothesis of this study and the authors provide practical recommendations for science policy makers and researchers, including the promotion of strategic collaboration between different<br> institutional sectors of society to increase the impact of publications.</p>
Population genomics of a predatory mammal reveals patterns of decline and impacts of exposure to toxic toads
<p>Mammal declines across northern Australia are one of the major biodiversity loss events occurring globally. There has been no regional assessment of the implications of these species declines for genomic diversity. To address this, we conducted a species-wide assessment of genomic diversity in the northern quoll (<em>Dasyurus hallucatus</em>), an Endangered marsupial carnivore. We used next-generation sequencing methods to genotype 10,191 SNPs in 352 individuals from across a 3220 km length of the continent, investigating patterns of population genomic structure and diversity, and identifying loci showing signals of putative selection. We found strong heterogeneity in the distribution of genomic diversity across the continent, characterised by (1) biogeographic barriers driving hierarchical population structure through long-term isolation, and (2) severe reductions in diversity resulting from population declines, exacerbated by the spread of introduced toxic cane toads (<em>Rhinella marina</em>). These results warn of a large ongoing loss of genomic diversity and associated adaptive capacity as mammals decline across northern Australia. Encouragingly, populations of the northern quoll established on toad-free islands by translocations appear to have maintained most of the initial genomic diversity after 16 years. By mapping patterns of genomic diversity within and among populations, and investigating these patterns in the context of population declines, we can provide conservation managers with data critical to informed decision-making. This includes the identification of populations that are candidates for genetic management, the importance of remnant island and insurance/translocated populations for the conservation of genetic diversity, and the characterisation of putative evolutionarily significant units.</p>
Data from: Choice of prioritization method impacts recommendations for climate-informed bird conservation in the United States
<p class="MsoNormal">Climate-informed spatial planning is urgently needed to guide initiatives aimed at both conserving biodiversity as a whole (e.g., protection of 30% of lands and waters by 2030) and recovering North American avifauna in particular. Various methods for prioritizing conservation areas exist, yet alternative methods may direct managers to different lands for protection and thus varying recommendations for meeting area-based targets. Here, we used bird species distribution models and landcover projections to systematically evaluate two widely-used methods for prioritizing areas most likely to facilitate the persistence of multiple species under climate change: (1) <em>in situ </em>macrorefugia, identified as areas of high predicted species retention; and (2) complementarity-based optimizations, identified using the Zonation conservation planning software. For 17 biogeographical groups in the continental United States, we compared priority areas for bird conservation derived from these two alternatives with respect to their spatial distributions and consensus (i.e., overlap), expected conservation outcomes (e.g., species and functional diversity), predicted climate change exposure, habitat characteristics, landscape configurations, and degree of formal protection. Spatial distributions of priority areas differed by biogeographical group and method, with 40.5% consensus on average across groups. Consensus was extensive within mountainous and coastal regions and limited at high latitudes (e.g., Alaska) and in flat, interior regions (e.g., grasslands). As expected, complementarity-based optimizations more efficiently represented species than retention-based <em>in situ </em>macrorefugia, especially for forest groups, and had greater overall biodiversity value and better habitat condition. Conversely, <em>in situ </em>macrorefugia encompassed higher elevations and larger contiguous patches and were expected to experience less winter-season warming. Formal protection averaged <50% across biogeographical groups, regardless of prioritization method. Our findings illustrate the value of complementarity-based optimizations for bird conservation under climate change. More broadly, comparing approaches for prioritizing areas for long-term species persistence can reveal critical tradeoffs in recommendations for climate-informed protected area planning.</p>
anonymized author dataset from the publication "Impact of the COVID-19 pandemic on publishing in astronomy in the initial two years"
<p>We provide the anonymized author dataset that was prepared for the research presented in <a href="https://arxiv.org/pdf/2203.15621.pdf">https://arxiv.org/pdf/2203.15621.pdf</a> . The data is provided as two pickled pandas data frames. The first data frame contains the number of publications each author has written in each year per author position (as 1st author etc.) and their assigned gender. The second file contains the corresponding country of affiliation for each author and year. The two data frames can be matched by author_id.</p> <p>Columns in "matched_author_dataset_publication_counts_zenodo.pkl":</p> <pre>['author_id', 'gender', 'P(gender)', 'pub1_tot', 'first_auth_pub_year', 'pub2_tot', 'auth_2_pub_year', 'pub3_tot', 'auth_3_pub_year', 'pub4_tot', 'auth_4_pub_year', 'pub5_tot', 'auth_5_pub_year', 'pub6_tot', 'auth_6_pub_year', 'pub7_tot', 'auth_7_pub_year', 'pub8_tot', 'auth_8_pub_year', 'pub9_tot', 'auth_9_pub_year', 'pub10_tot', 'auth_10_pub_year', 'pub11_tot', 'auth_11_pub_year', 'pub12_tot', 'auth_12_pub_year', 'pub13_tot', 'auth_13_pub_year', 'pub14_tot', 'auth_14_pub_year', 'pub15_tot', 'auth_15_pub_year', 'pub16_tot', 'auth_16_pub_year', 'tot_pub', 'tot_pub_year', 'last_pub', 'first_pub']</pre> <p>'author_id' is a unique id assigned to the author. 'gender' contains the author's most likely gender and 'P('gender')' the likelihood of correct assignment. 'pubX_tot' contains the total number of publications the author has written as Xth author, 'auth_X_pub_year' contains a list with one entry per year from 1950 to 2022 counting the number of papers the author has published as Xth author in that year. 'tot_pub' counts the total number of publications (summed over all years) and 'tot_pub_year' for each year/ 'last_pub' and 'first pub' contain the list indices of the years when the author last/first published.</p> <p>Columns in author_dataframe_country.pkl:</p> <pre>['author_id', 'aff_year', 'aff_country_author']</pre> <p>'aff_year' is a list of years for which country information could be inferred for this author. 'aff_country_author' is a list of countries for each entry in 'aff_year'.</p> <p> </p>
The impact of COVID-19 on the everyday life of blind and sighted individuals
<p>The datasets contain: </p> <p>- raw data of the open-ended question with the percentage of participants declaring a specific difficulty for COVID-19.</p> <p>- raw data of Questionnaire 1 divided by: Daily routine, Social life and Sleep habits. In each file the question number is reported in the header of each column. </p> <p>- raw data of Questionnaire 2 with the individual sum of responses for each personality category.</p>
Dataset for "Definition and rationale for placebo composition: Cross-sectional analysis of randomized trials and protocols published in high-impact medical journals"
<p>Contains our data extraction sheets</p>
Data for: Concurrent impacts with harvesting on NTFP plants
<p>Investigating the concurrent impacts of harvesting wild vegetables can guide their sustainable management while contributing to the understanding of such impacts on NTFP species. This study investigated leaf production, morphological and growth responses to the concurrent impacts of drought and leaf harvesting between two wild vegetables. A randomized greenhouse experiment was implemented with 1,334 plants of <em>Amaranthus</em> sp. and 391 of <em>Bidens</em> <em>pilosa</em>. A drought treatment was first implemented through six levels of drought stress and a control treatment. The harvesting treatment consisted of four harvesting levels and was implemented twice. Measurements were recorded before the first and second harvests and at the end of the experiment. Data were separated into two periods (after first and second harvests) and analyzed using Multivariate Analysis of Variance and log-linear analysis. The results showed significant effects of drought on both species. However, <em>Amaranthus</em> sp. appeared more resilient to reduction in the daily amount of water than reduction in the frequency, while <em>B</em>. <em>pilosa</em> was resilient under both facets of drought stress. For <em>Amaranthus</em> sp., basal diameter, its growth, leaf production and survival increased with increase in the harvesting level (with some exceptions) after first harvest. After second harvest, there was a decrease in plant height and leaf production. In <em>B</em>. <em>pilosa</em>, the impact was only significant on survival and leaf production (after first harvest). The effect of the interaction of the two drivers was significant for <em>Amaranthus</em> sp. but not for <em>B</em>. <em>pilosa</em>. The results also highlighted the possible negative impact of a prolonged high rate of harvesting on the species' performance, especially under severe drought. Basal diameter, its growth, survival and leaf production appeared more resilient to reduced amounts of watering in <em>Amaranthus</em> sp. and under both types of drought stress for <em>B</em>. <em>pilosa</em>. This suggests that both species could be sustained under medium drought stress.</p>
Figure 3 in Impact of brood parasitoids and oophagy on survival of Asemonea tenuipes (Araneae: Salticidae: Asemoneinae) broods in Karnataka
Figure 3 (continued from previous page). 27-30, Views of Idris sp. parasitoids emerging from the third brood and, as adult wasps, moving over to the fourth brood, still attended by the female Asemonea. It is likely that this brood will also be infected. 31, View of cocoon (remnant of first brood) and exuviae remaining in second brood, the only successful brood of the four, under the first leaf. Note the presence of a Myrmarachne sp. (arrow) in this Asemonea nest. 32, Five days later the female Asemonea was gone, leaving only scattered eggs from her third and fourth broods on the underside of the second Ficus leaf.
Figure 3 in Impact of brood parasitoids and oophagy on survival of Asemonea tenuipes (Araneae: Salticidae: Asemoneinae) broods in Karnataka
Figure 3 (continued from previous page, continued on next page). 15-16, The mantispid emerged from its cocoon (apparently remnant of first brood) and molted. 17, Detail of empty mantispid cocoon. 18, Mantispid near spiderlings of the second brood. 19, Female Asemonea tending her third brood. 20, View of mantispid and second brood beneath lower leaf, and female attending third brood beneath upper Ficus microcarpa leaf.
Figure 3 in Impact of brood parasitoids and oophagy on survival of Asemonea tenuipes (Araneae: Salticidae: Asemoneinae) broods in Karnataka
Figure 3 (continued from previous page, continued on next page). 21, Mantispid near its empty cocoon and exuvium, also near the developing second brood. 22, About one week later the female Asemonea was gone but the third brood was developing normally. The emergent (instar II) spiderlings shown here most likely came from the second brood. 23, A female Asemonea, perhaps the original female, moved into the nest near the third brood. 24, Same female Asemonea feeding on a chironomid midge in her nest near the second brood. 25, Gravid female Asemonea near the third brood, now clearly infected with Idris sp. parasitoids. 26, Same female after depositing a fourth brood of 18 eggs near the infected third brood.
Figure 3 in Impact of brood parasitoids and oophagy on survival of Asemonea tenuipes (Araneae: Salticidae: Asemoneinae) broods in Karnataka
Figure 3 (continued from previous page, continued on next page). 7, Developing second brood (instar I) under the first leaf. 8, Female Asemonea with third brood under the second leaf (upper left) with cocoon that replaced the first brood and the developing second brood under the first leaf. 9-11,14, Cocoon and developing second brood. 12, Detail of small insect (Heteroptera) near the mantispid cocoon, from (10). 13, Female Asemonea attending her third brood of 10 eggs on the second leaf.
Figure 1 in Impact of brood parasitoids and oophagy on survival of Asemonea tenuipes (Araneae: Salticidae: Asemoneinae) broods in Karnataka
Figure 1 (continued from previous page). 8-9, The 9 instar I spiderlings continued to develop as the female returned to her original colour. 10-12, Still attended by the female, 7 remaining spiderlings molted to the emergent instar (instar II). 13, The female and all of her spiderlings were gone.
Figure 3 in Impact of brood parasitoids and oophagy on survival of Asemonea tenuipes (Araneae: Salticidae: Asemoneinae) broods in Karnataka
Figure 3 (continued on next page). 1-2, Female Asemonea tenuipes attending her nest including a mantispid cocoon and a normal brood of 19 eggs on the underside of a Ficus microcarpa leaf. 3-8, Eggs of the second brood of 19 eggs were hatching (3) as the female Asemonea tenuipes moved to a nearby leaf and deposited a new brood of 10 eggs (6).
Figure 2 in Impact of brood parasitoids and oophagy on survival of Asemonea tenuipes (Araneae: Salticidae: Asemoneinae) broods in Karnataka
Figure 2 (continued from previous page, continued on next page). 5-6, Neuropteran larva (possibly mantispid) feeding on eggs in the more recent or second brood. 7-10, The female Asemonea continued to attend to her nest, now inhabited by the cocooning neuropteran and 7 eggs that may have been damaged or infested by Idris.
Figure 1 in Impact of brood parasitoids and oophagy on survival of Asemonea tenuipes (Araneae: Salticidae: Asemoneinae) broods in Karnataka
Figure 1 (continued on next page). 1, Light green Female A. tenuipes tending her clutch of 9 eggs beneath a leaf of Ficus microcarpa. 2, 9 newly hatched spiderlings (instar I) with short legs. Note that the female was now darker. 3-7, The 9 instar I spiderlings continued to develop.
Dataset of "System-level Impacts of 24/7 Carbon-free Electricity Procurement"
<p>This dataset includes three zip files and several other files to replicate the runs. It also includes the load time-series of commercial and industrial electricity usage of each zone of the manuscript. It also includes the full 8760hour time-series of the gross load.</p> <p>1. The file "2030.zip" includes the inputs and outputs from each case run by GenX.</p> <p>2. The file "CompiledResult_upload.zip" includes the compiled results of all cases; in the unzipped folder, there are nine (9) ".csv" files. There are four common columns in these nine files:</p> <ul> <li>case: this is the long case name, can be represented by Scenario, and TechSensitivity</li> <li>year: this is 2030 because of the target year is 2030</li> <li>Scenario: this is the name of each scenario modeled in the study. There are nine scenarios. <ul> <li>10% CI Part, Curt. Tech. = 10% C&I Participation Rate, Current Technology Scenario</li> <li>10% CI Part, Curt. Tech., No Ex. Limit = 10% C&I Participation Rate, Current Technology Scenario, No Excess Limit</li> <li>25% CI Part, Curt. Tech. = 25% C&I Participation Rate, Current Technology Scenario</li> <li>10% CI Part, Adv. Tech. no Comb. = 10% C&I Participation Rate, Advanced Technology no Combustion Scenario</li> <li>10% CI Part, Adv. Tech. no Comb., no Ex. Limit = 10% C&I Participation Rate, Advanced Technology no Combustion Scenario, No Excess Limit</li> <li>25% CI Part, Adv. Tech. no Comb. = 25% C&I Participation Rate, Advanced Technology no Combustion Scenario</li> <li>10% CI Part, Adv. Tech. Full = 10% C&I Participation Rate, Advanced Technology, Full Portfolio</li> <li>10% CI Part, Adv. Tech. Full, no Ex. Limit = 10% C&I Participation Rate, Advanced Technology, Full Portfolio, No Excess Limit</li> <li>25% CI Part, Adv. Tech. Full = 25% C&I Participation Rate, Advanced Technology, Full Portfolio</li> </ul> </li> <li>TechSensitivity: There are eleven cases <ul> <li>Hourly 80%-100%, these are the 24/7 CFE procurement cases with different CFE Score Target</li> <li>Annual 100%: this is the 100% annual matching case</li> <li>No 24x7 Purchase: this is the reference case</li> </ul> </li> </ul> <p>For the rest of the files, see description below</p> <ul> <li>Gen_Output_California.csv: this file includes the annual generation output of California generators. The unit is "MWh"</li> <li>NetImport_California.csv: this file include the annual net imports of California (negative number stands for net exports. The unit is "MWh"</li> <li>tfs_cfe_table.csv: this file includes a table with the following columns: <ul> <li>Policy: this column is all 1 because there is only one 24/7 CFE buyers</li> <li>Shortfall: this column includes the annual grid supply that is not clean. Unit is MWh</li> <li>Excess: this column includes the annual excess. Unit is MWh</li> <li>Shortfall price: this column includes the shadow prices of the CFE target constraint. Unit is $/MWh</li> <li>Excess Price: this column includes the shadow prices of the CFE excess limit constraint. Unit is $/MWh</li> <li>Load: this column includes the annual load of 24/7 participants. Unit is MWh.</li> <li>Storage loss: this column includes the annual storage loss of the 24/7 participating storage. Unit is MWh.</li> <li>Post-Grid CFE Score Local_n_Import: this column includes the final CFE score of the model. Unitless</li> </ul> </li> <li>tfs_gen_capacity_California.csv: this documents the capacity procured by the 24/7 or 100% annual matching participants. Unit is MW</li> <li>tfs_gen_output_California.csv: this documents the energy procured by the 24/7 or 100% annual matching participants. Unit is MWh</li> <li>tfs_gents_table.csv: this documents the time-series of the 24/7 CFE procurement. Unit is MW.</li> <li>tfs_lse_cost.csv: this documents the cost of 24/7 CFE participants in each case. Unit is 2020USD</li> <li>tfs_modified_load.csv: this documents the modified load time-series of the 24/7 CFE participants. Unit is MW</li> <li>tfs_system_emissions.csv: this documents the carbon footprint of the 24/7 CFE participants and the rest of the California load. <ul> <li>participating_load_emission: this is the carbon footprint of the 24/7 CFE participants. Unit is metric tons</li> <li>emission_rest_of_local_w_import: this is the carbon footprint of the rest of the California load. Unit is metric tons</li> <li>emission_local_n_import: this is the carbon footprint of the California load, i.e., the sum of the "participating_load_emission" and "emission_rest_of_local_w_import". Unit is metric tons</li> </ul> </li> </ul> <p>3. GenX_upload.zip: this includes a workable version of GenX that, if installed correctly, can be run with provided inputs to replicate the runs. Please check GenX's github website https://github.com/GenXProject/GenX for the installation guide. However, because GenX (the uploaded one) has been updated since the results were generated, there are a few changes to be made so that GenX can run those slightly outdated files. Use Run_247.jl (uploaded) to run the cases; this 'jl' file will also calculate several other files that are needed for 24/7 analysis; furthermore, this jl file includes the iteration algorithm used for finding grid supply clean share. </p> <p> The necessary changes to the case files include</p> <ul> <li>in Generators_data.csv, add a column of "CapRes_duration_requirement" with entries being 1 for all generators; further, change the Min_Duration and Max_Duration of pumped hydro generators to 1 and 20;</li> <li>Add Capacity_reserve_margin_slack.csv (provided in this zenodo repo) to the case to be run.</li> <li>Add RPSH_MER (uploaded) to the case to be run</li> <li>in RPSH.csv, add three columns <ul> <li>MWhExtraBudget = 0</li> <li>Carbon_Offset_Target = 0</li> <li>Carbon_Offset_Penalty = 0</li> </ul> </li> <li>Add Energy_share_requirement_slack.csv to the cases to be run; if this case is an annual matching case, i.e., the name ends with "cipannual100", copy and paste Energy_share_requirement_slack_annualmatching.csv but rename it to Energy_share_requirement_slack.csv before running.</li> <li>Add a new column in any Maximum_capacity_limit.csv called "PriceCap" with all entries being 1000000 (1 million).</li> <li>in Settings/genx_settings.yml; add three rows <ul> <li> <p>CO2Capture: 1</p> </li> <li> <p>ref_case_id: if a case name begins with p[x]_, put <em>p[x]_ncp</em> in this row; for example, if a case name begins with p1, then put p1_ncp.</p> </li> <li> <p>ref_case_name:</p> <ul> <li> <p>if a case name begins with p2, use <em>currentpolicy_10ci_nocip</em></p> </li> <li> <p>if a case name begins with p3, use currentpolicy_25ci_nocip</p> </li> <li> <p>if a case name begins with p7, use currentpolicy_10ci_adv_nocip</p> </li> <li> <p>if a case name begins with p8, use currentpolicy_25ci_adv_nocip</p> </li> <li> <p>if a case name begins with p12, use currentpolicy_10ci_adv_nocip_noccszcf</p> </li> <li> <p>if a case name begins with p13, use currentpolicy_25ci_adv_nocip_noccszcf</p> </li> <li> <p>if a case name begins with p19, use currentpolicy_10ci_adv_nocip_noccszcf_noexcess</p> </li> <li> <p>if a case name begins with p30, use currentpolicy_10ci_nocip_noexcess</p> </li> <li> <p>if a case name begins with p31, use currentpolicy_10ci_adv_nocip_noexcess</p> </li> </ul> </li> </ul> </li> </ul> <p>4. CI_Load_Formatted_google.csv included the Commercial and Industrial load for each zone; This study uses columns with "current_policy," year = 2030</p> <p>5. Total_Load_Formatted_google.csv included the gross load of each zone; This study uses columns with "current_policy," year = 2030</p>
Impact of a pulmonary rehabilitation program on social disadvantage and physical activity data of postCOVID19 patients: A North-African pilot study
<p><strong>WHAT IS ALREADY KNOWN</strong></p> <ul> <li>In post-acute COVID19, many patients still manifest symptoms for weeks and months.</li> <li>Psychological manifestations are prevalent and persisting in recovered COVID19 patients.</li> <li>Indeed, COVID19 was reported to possibly lead to symptoms of depression and anxiety, and to alter health-related quality of life (HRQoL).</li> <li>Physical activity has been proven to be effective in improving both mental and physical health.</li> <li>Thus, COVID19 patients could benefit from pulmonary rehabilitation program (PRP).</li> <li>Many studies related the effects of a standard PRP on physical activity and HRQoL in post COVID19 patients. However, to the best of the authors’ knowledge, no study evaluated the physical activity and social disadvantage of patients who were hospitalized for COVID19 in a low income country.</li> <li>This paper is the second part of a cross sectional study that aimed to evaluate the impact of a PRP on social disadvantage (physical activity, hospital anxiety and depression (HAD), HRQoL) data of Tunisian patients with postCOVID19.</li> </ul> <p><strong>WHAT THIS PAPER ADDS</strong></p> <ul> <li>The present North African study demonstrated that a PRP improved HRQoL, HAD, and physical activity data of Tunisian COVID19 patients.</li> <li>For instance, the means of the functional, psychological and relation dimensions, and the VQ11 total score (ie; main outcome) decreased significantly by 1.79, 2.00, 1.57, and 5.36 points. In addition, the means of the HAD anxiety and depression scores decreased significantly by 2.07, and 2.57 points, respectively, and the means of the physical activity and total scores improved significantly by 1.75 and 1.78 points, respectively.</li> <li>To the best of the authors’ knowledge, this is the first African and Arab study investigating the impact of a PRP on postcovid19 patients in terms of social disadvantages and physical activity.</li> <li> </li> </ul> <ul> <li>This study confirms that an outpatient PRP program improves physical activity, psychological status and HRQoL in the management of postCOVID19 patients.</li> </ul>
Understanding the Impact of Digital Technology: a Case Study in Rural Areas [Supplementary Material]
<p>This package contains supplementary material associated to the paper "Understanding the Impact of Digital Technology: a Case Study in Rural Areas". </p> <p><em>Abstract:</em> Designing systems that account for sustainability concerns demands for a better understanding of the impact that digital technology interventions can have on a certain socio-technical context. However, limited studies are available about the elicitation of impact-related information from stakeholders. This paper reports the experience of the authors in identifying the impact of digitalisation in remote mountain areas, in the context of a system for ordinary land management and hydro-geological risk control. Based on a set of interviews and a workshop, we reconstructed the current socio-technical system. Furthermore, we elicited information about the impact of digital technologies that were introduced in the specific context in recent years (GIS software, instant messaging apps, sensors, drones, etc.). Positive impacts are mostly economic and organisational. Negative ones are higher stress due to the excess of connectivity, and partial reduction of decision-making abilities. Our study contributes to the literature with a set of impacts specific to the case, and a list of lessons learned from the experience.</p> <p>The package contains the following files:</p> <p>1. Socio-technical System.pdf: a graphical representation of the socio-technical system that has been reconstructed by the authors of the paper.</p> <p>2. Description of System Entities.pdf: detailed description of the entities represented in the socio-technical system.</p> <p>3. Incremental Data Analysis.pdf: graphs depicted during data analysis, to represent relations between entities, towards the representation of the socio-technical system. </p> <p>4. Impacts and quotes - selected examples (EN).pdf: sample quotes (translated from Italian) associated to the impacts identified. </p>
Datasets for "High-resolution, basin-scale simulations reveal the impact of intermediate zonal jets on the Atlantic oxygen minimum zones".
<p>This repository contains the 7-year averaged files from runs TATL10 and TATL3 used in the manuscript "High-resolution, basin-scale simulations reveal the impact of intermediate zonal jets on the Atlantic oxygen minimum zones".</p> <p>Additional files include the CARS oxygen climatology and the CMEMS model output used in the study.</p> <p> </p>
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.