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647 results for “historical_data”
Historical contingency shapes adaptive radiation in Antarctic fishes [Data set]
<p>Assembled reference contigs for protein-coding exons and conserved non-coding regions from targeted sequence enrichment of notothenioid fishes and outgroups. </p> <p>Published in : Daane, JM, Dornburg, A, Smits, P, MacGuigan, D, Hawkins, B, Near, TJ, Detrich, HW III*, Harris MP*. (2019). Historical contingency shapes adaptive radiation in Antarctic fishes. <em>Nature Ecology & Evolution.</em></p> <p> </p> <p>-contigs.zip contains the assembled contigs for each species. Each contig represents a targeted region with the addition of flanking DNA sequence</p> <p>-cnes.zip contains the targeted conserved non-coding regions isolated from the larger contigs in contigs.zip</p> <p>-exons.zip contains the targeted protein coding exons isolated from the larger contigs in contigs.zip</p> <p>-protein.zip contains the translated protein coding exons from exons.zip</p>
Temperature and Relative Humidity Data in Rooms of Historical Museum (Cabildo) in Salta, Argentina.
<p><strong>Temperature and Relative Humidity Data in Rooms of Historical Museum (Cabildo) in Salta, Argentina.</strong></p> <p>Data was monitored over 15 consecutive days, with readings taken at 15-minute intervals during two periods: the cold season and the warm season. HOBO data loggers (model U12-12) were used, featuring a temperature accuracy of ±0.35°C and a resolution of 0.03°C at 25°C, as well as a humidity accuracy of ±2.5% and a resolution of 0.03%. The sensors were specifically calibrated for the expected temperature range, with a calibration age of less than one year and a calibration error within ±0.5°C. Additionally, a sensor was installed in the building's galleries in all cases to record outdoor temperature and relative humidity data, allowing for a comparative analysis between indoor and outdoor conditions.</p>
Supplementary material for 'Station to Station: Linking and Enriching Historical British Railway Data'
<p>Supplementary material for the <a href="https://github.com/Living-with-machines/station-to-station">station-to-station</a> Github repository, containing the underlying code and materials for the paper 'Station to Station: Linking and Enriching Historical British Railway Data', accepted to CHR2021 (Computational Humanities Research).</p> <p>Mariona Coll Ardanuy, Kaspar Beelen, Jon Lawrence, Katherine McDonough, Federico Nanni, Joshua Rhodes, Giorgia Tolfo, and Daniel C.S. Wilson. "Station to Station: Linking and Enriching Historical British Railway Data." In Computational Humanities Research (CHR2021). 2021.</p>
High frequency (tick data) of historical FOREX prices
<p>Price tick data for the most liquid Forex assets (AUDUSD, EURCAD, EURCHF, EURUSD, GBPUSD, USDJPY). The period covered 09 March 2020 to 07, September 2022. </p>
Historical (1979 - 2020) data for anthropogenic inputs to a catchment and riverine mainstem exports for carbon, nitrogen, and phosphorus
<p>We estimated the difference in Net Anthropogenic Nitrogen and Phosphorus Inputs (NANI-NAPI) at the finest scale possible (the municipality) in the <em>Rivière du Nord</em> watershed (Québec, Canada) between 1981 and 2016. The dataset here reports the delta between those two years for each municipality in the watershed.</p> <p>Three sites along the mainstem of <em>Rivière du Nord </em>have been sampled ~bi-monthly from ~1979 - 2020 for dissolved organic carbon (DOC), total nitrogen (TN), and total phosphorus (TP), from which we estimated annual riverine export at each site. We also include annual precipitation (as the sum of rain and snow), and NANI-NAPI interpolated for each sub-watershed for 1981, 1986, 1991, 1996, 2001, 2006, 2011, and 2016.</p> <p> </p> <p> </p>
Regional Revised River Runoff Reanalysis (R5): historical and projected river runoff data set for the northwest of the European part of Russia
<p>This data set presents a uniform spatio-temporal assessment of projected river runoff for the northwest of the European part of Russia, which is based on two hydrological models (GR4J-REG and LSTM-REG), four General Circulation models (GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A, and MIROC5), and three Representative Concentration Pathways (RCP2.6, RCP6.0, and RCP8.5). Each of the 24 gridded runoff data sets has daily temporal and 0.5° spatial resolution. They cover the geographical domain of 25–57° East and 55–70° North, and the temporal period from 2006 (2007 for LSTM-REG) to 2099.</p>
Plant life history data as evidence of an historical mixed-severity fire regime in Banksia woodlands
<p><i><strong>Context:</strong></i> The concept of the fire regime serves as an agreed upon template by which to inform understanding and management of fire-prone ecosystems globally. While observations from satellite imagery or palaeoecological proxy data can provide direct evidence of past fire regimes, they may be limited in temporal and/or spatial scale and are not available for all ecosystems. However, fire-related plant trait and demographic data offers an alternative approach to understand species-fire regime associations at the ecosystem scale. </p><p><i><strong>Aims:</strong></i> We aimed to quantify the life history strategies and associated fire regimes for six co-occurring shrub and tree species from fire-prone, Mediterranean climate Banksia woodlands in southwestern Australia. </p><p><i><strong>Methods:</strong></i> We collected static demographic data on size structure, seedling recruitment, and plant mortality across sites of varying time since last fire. We combined demographic data with key fire-related species traits to define plant life history strategies. We then compared observed life histories with <i>a priori</i> expectations for surface, stand-replacing, and mixed-severity fire regime types to infer historical fire regime associations.</p><p><i><strong>Key results:</strong></i> Fire-killed shrubs and weakly serotinous trees had abundant post-fire seedling recruitment, but also developed multi-cohort populations during fire-free periods via inter-fire seedling recruitment. Resprouting shrubs had little seedling recruitment at any time, even following fire, and showed no signs of decline in the long absence of fire likely due to their very long lifespans. </p><p><i><strong>Conclusions:</strong></i> The variation in life history strategies for these six co-occurring species is consistent with known ecological strategies to cope with high variation in fire intervals in a mixed-severity fire regime. While resprouting and strong post-fire seedling recruitment indicate a tolerance of frequent fire, inter-fire recruitment and weak serotiny is interpreted as a bet-hedging strategy to cope with occasional long fire-free periods that may otherwise exceed adult and seed bank lifespans. </p><p><i><strong>Implications:</strong></i> Our findings suggest that Banksia woodlands have evolved with highly variable fire intervals in a mixed-severity fire regime. Further investigations of species adaptations to varying fire size and patchiness can help extend our understanding of fire regime tolerances.</p>
Transport Starter Data Kit: Historical socio-transport data for selected countries in Africa, Asia, and South America
<p>This Transport Starter Data Kit contains historical annual data (1990–2021) on passenger activity, freight activity, vehicle stock, energy intensity, and load factor segregated by mode and fuel, where available. Additionally, historical data on population (total, urban, rural, growth) and GDP (total, agriculture, construction, mining, manufacturing, service, energy, growth) are included in the kit, within the 'Data' tab. The historical data can be used as a foundation for transport-energy modelling and/or to identify areas of improvement. This data was verified through consultation with relevant stakeholders before publishing. The definition used for each vehicle mode is found in the 'Definitions' tab, and the description of each data observation status is found in the 'Notes' tab. All data sources are linked where possible.</p><p>Countries included: Angola, Burundi, Benin, Burkina Faso, Brazil, Botswana, Central African Republic, Côte d'Ivoire, Cameroon, Democratic Republic of the Congo, Congo, Colombia, Djibouti, Algeria, Egypt, Eritrea, Ethiopia, Gabon, Ghana, Guinea, Gambia, Guinea-Bissau, Equatorial Guinea, Indonesia, Kenya, Cambodia, Republic of Korea, Lao People's Democratic Republic, Liberia, Libya, Lesotho, Morocco, Mali, Myanmar, Mozambique, Mauritania, Malawi, Malaysia, Namibia, Niger, Nigeria, Philippines, Rwanda, Sudan, Senegal, Sierra Leone, Somalia, South Sudan, Eswatini, Chad, Togo, Thailand, Tunisia, Taiwan Province of China, United Republic of Tanzania, Uganda, Viet Nam, South Africa, Zambia, Zimbabwe.</p>
Transport Starter Data Kit: Historical socio-transport data for Egypt
<p>This Transport Starter Data Kit contains historical annual data (1990–2021) on passenger and freight activity, segregated by mode and fuel. Additionally, historical data on energy intensities, load factors, vehicle stock, population (total, urban, rural, growth), and GDP (total, agriculture, construction, mining, manufacturing, service, energy, growth) are included in the kit, within the 'Data' tab. The historical data can be used as a foundation for transport-energy modelling and/or to identify areas of improvement. This data was verified through consultation with relevant stakeholders before publishing. The definition used for each vehicle mode is found in the 'Definitions' tab, and the description of each data observation status is found in the 'Notes' tab. All data sources are linked where possible.</p>
Transport Starter Data Kit: Historical socio-transport data for Djibouti
<p>This Transport Starter Data Kit contains historical annual data (1990–2021) on passenger and freight activity, segregated by mode and fuel. Additionally, historical data on energy intensities, load factors, vehicle stock, population (total, urban, rural, growth), and GDP (total, agriculture, construction, mining, manufacturing, service, energy, growth) are included in the kit, within the 'Data' tab. The historical data can be used as a foundation for transport-energy modelling and/or to identify areas of improvement. This data was verified through consultation with relevant stakeholders before publishing. The definition used for each vehicle mode is found in the 'Definitions' tab, and the description of each data observation status is found in the 'Notes' tab. All data sources are linked where possible.</p>
Transport Starter Data Kit: Historical socio-transport data for Equatorial Guinea
<p>This Transport Starter Data Kit contains historical annual data (1990–2021) on passenger and freight activity, segregated by mode and fuel. Additionally, historical data on energy intensities, load factors, vehicle stock, population (total, urban, rural, growth), and GDP (total, agriculture, construction, mining, manufacturing, service, energy, growth) are included in the kit, within the 'Data' tab. The historical data can be used as a foundation for transport-energy modelling and/or to identify areas of improvement. This data was verified through consultation with relevant stakeholders before publishing. The definition used for each vehicle mode is found in the 'Definitions' tab, and the description of each data observation status is found in the 'Notes' tab. All data sources are linked where possible.</p>
Transport Starter Data Kit: Historical socio-transport data for Sierra Leone
<p>This Transport Starter Data Kit contains historical annual data (1990–2021) on passenger and freight activity, segregated by mode and fuel. Additionally, historical data on energy intensities, load factors, vehicle stock, population (total, urban, rural, growth), and GDP (total, agriculture, construction, mining, manufacturing, service, energy, growth) are included in the kit, within the 'Data' tab. The historical data can be used as a foundation for transport-energy modelling and/or to identify areas of improvement. This data was verified through consultation with relevant stakeholders before publishing. The definition used for each vehicle mode is found in the 'Definitions' tab, and the description of each data observation status is found in the 'Notes' tab. All data sources are linked where possible.</p>
Transport Starter Data Kit: Historical socio-transport data for Niger
<p>This Transport Starter Data Kit contains historical annual data (1990–2021) on passenger and freight activity, segregated by mode and fuel. Additionally, historical data on energy intensities, load factors, vehicle stock, population (total, urban, rural, growth), and GDP (total, agriculture, construction, mining, manufacturing, service, energy, growth) are included in the kit, within the 'Data' tab. The historical data can be used as a foundation for transport-energy modelling and/or to identify areas of improvement. This data was verified through consultation with relevant stakeholders before publishing. The definition used for each vehicle mode is found in the 'Definitions' tab, and the description of each data observation status is found in the 'Notes' tab. All data sources are linked where possible.</p>
Transport Starter Data Kit: Historical socio-transport data for Rwanda
<p>This Transport Starter Data Kit contains historical annual data (1990–2021) on passenger and freight activity, segregated by mode and fuel. Additionally, historical data on energy intensities, load factors, vehicle stock, population (total, urban, rural, growth), and GDP (total, agriculture, construction, mining, manufacturing, service, energy, growth) are included in the kit, within the 'Data' tab. The historical data can be used as a foundation for transport-energy modelling and/or to identify areas of improvement. This data was verified through consultation with relevant stakeholders before publishing. The definition used for each vehicle mode is found in the 'Definitions' tab, and the description of each data observation status is found in the 'Notes' tab. All data sources are linked where possible.</p>
Transport Starter Data Kit: Historical socio-transport data for Somalia
<p>This Transport Starter Data Kit contains historical annual data (1990–2021) on passenger and freight activity, segregated by mode and fuel. Additionally, historical data on energy intensities, load factors, vehicle stock, population (total, urban, rural, growth), and GDP (total, agriculture, construction, mining, manufacturing, service, energy, growth) are included in the kit, within the 'Data' tab. The historical data can be used as a foundation for transport-energy modelling and/or to identify areas of improvement. This data was verified through consultation with relevant stakeholders before publishing. The definition used for each vehicle mode is found in the 'Definitions' tab, and the description of each data observation status is found in the 'Notes' tab. All data sources are linked where possible.</p>
Transport Starter Data Kit: Historical socio-transport data for Congo
<p>This Transport Starter Data Kit contains historical annual data (1990–2021) on passenger and freight activity, segregated by mode and fuel. Additionally, historical data on energy intensities, load factors, vehicle stock, population (total, urban, rural, growth), and GDP (total, agriculture, construction, mining, manufacturing, service, energy, growth) are included in the kit, within the 'Data' tab. The historical data can be used as a foundation for transport-energy modelling and/or to identify areas of improvement. This data was verified through consultation with relevant stakeholders before publishing. The definition used for each vehicle mode is found in the 'Definitions' tab, and the description of each data observation status is found in the 'Notes' tab. All data sources are linked where possible.</p>
Transport Starter Data Kit: Historical socio-transport data for Namibia
<p>This Transport Starter Data Kit contains historical annual data (1990–2021) on passenger and freight activity, segregated by mode and fuel. Additionally, historical data on energy intensities, load factors, vehicle stock, population (total, urban, rural, growth), and GDP (total, agriculture, construction, mining, manufacturing, service, energy, growth) are included in the kit, within the 'Data' tab. The historical data can be used as a foundation for transport-energy modelling and/or to identify areas of improvement. This data was verified through consultation with relevant stakeholders before publishing. The definition used for each vehicle mode is found in the 'Definitions' tab, and the description of each data observation status is found in the 'Notes' tab. All data sources are linked where possible.</p>
Transport Starter Data Kit: Historical socio-transport data for Togo
<p>This Transport Starter Data Kit contains historical annual data (1990–2021) on passenger and freight activity, segregated by mode and fuel. Additionally, historical data on energy intensities, load factors, vehicle stock, population (total, urban, rural, growth), and GDP (total, agriculture, construction, mining, manufacturing, service, energy, growth) are included in the kit, within the 'Data' tab. The historical data can be used as a foundation for transport-energy modelling and/or to identify areas of improvement. This data was verified through consultation with relevant stakeholders before publishing. The definition used for each vehicle mode is found in the 'Definitions' tab, and the description of each data observation status is found in the 'Notes' tab. All data sources are linked where possible.</p>
Transport Starter Data Kit: Historical socio-transport data for South Sudan
<p>This Transport Starter Data Kit contains historical annual data (1990–2021) on passenger and freight activity, segregated by mode and fuel. Additionally, historical data on energy intensities, load factors, vehicle stock, population (total, urban, rural, growth), and GDP (total, agriculture, construction, mining, manufacturing, service, energy, growth) are included in the kit, within the 'Data' tab. The historical data can be used as a foundation for transport-energy modelling and/or to identify areas of improvement. This data was verified through consultation with relevant stakeholders before publishing. The definition used for each vehicle mode is found in the 'Definitions' tab, and the description of each data observation status is found in the 'Notes' tab. All data sources are linked where possible.</p>
Transport Starter Data Kit: Historical socio-transport data for Burkina Faso
<p>This Transport Starter Data Kit contains historical annual data (1990–2021) on passenger and freight activity, segregated by mode and fuel. Additionally, historical data on energy intensities, load factors, vehicle stock, population (total, urban, rural, growth), and GDP (total, agriculture, construction, mining, manufacturing, service, energy, growth) are included in the kit, within the 'Data' tab. The historical data can be used as a foundation for transport-energy modelling and/or to identify areas of improvement. This data was verified through consultation with relevant stakeholders before publishing. The definition used for each vehicle mode is found in the 'Definitions' tab, and the description of each data observation status is found in the 'Notes' tab. All data sources are linked where possible.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
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