Find research datasets worth reusing

opencc-by-4.0Feb 2017View details →

Supplementary material 1: Reviewer Comments from: Widening the circle of care: An arts-based, participatory dialogue with stakeholders on cancer care for First Nations, Inuit, and Métis peoples in Ontario, Canada - Research Ideas and Outcomes 2: e9115 (25 May 2016) https://doi.org/10.3897/rio.2.e9115

The attached file includes the evaluation of the postdoctoral fellowship application from three reviewers. Guidelines for reviewers are available online for more inforamtion (http://www.cihr-irsc.gc.ca/e/33043.html), including the rating scale that is used to score each section of the evaluation.

opencc-zeroJun 2024View details →

Dataset: First National Corporation (FXNC) Stock Performance

This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.

opencc-zeroJun 2024View details →

Dataset: Simmons First National Corporation (SFNC) Stock Performance

Figure 3. A & B in A rapid biodiversity assessment of Lesotho's first proposed Biosphere Reserve: a case study of Bokong Nature Reserve and Tšehlanyane National Park

Figure 3. A & B, the spectacular scenery of mountaineous landscapes forming part of the proposed BR; C, the endemic spiral aloe; D, the near-endemic Lesotho lily; E, the Lesotho red-hot poker; F, locally uncommon fern – bracken; G, endemic Maloti minnow; H, common eland; and I, its presence on rock paintings; J, some of the wetlands in the BNR; K, some of them damaged by diggings of Sloggett's ice rat (Source: K. Kobisi).

Figure 1. A & B in A rapid biodiversity assessment of Lesotho's first proposed Biosphere Reserve: a case study of Bokong Nature Reserve and Tšehlanyane National Park

Figure 1. A & B, Lesotho's first proposed Biosphere Reserve, showing the core (Tšehlanyane National Park and Bokong Nature Reserve), buffer and transition zones (Source: T. Leballo).

Figure 2 in A rapid biodiversity assessment of Lesotho's first proposed Biosphere Reserve: a case study of Bokong Nature Reserve and Tšehlanyane National Park

Figure 2. Transect walks covered during the different phases of the biodiversity survey (data collection) in the proposed Biosphere Reserve (Source: T. Leballo).

opencc-by-4.0Dec 2023View details →

Рис. 4. Карта-схема мест встреч пятнистого оΛеня в Нижнем Приамурье в 1979–2021 гг. КваΑраты — места фоторегистрации: 1 — верховья рр. Обор и Àурмин; 2, 3 — Анюйский национаΛьный парк; круги — места встреч по Λитературным и опросным Αанным: 1 — окрестности с. Кутузовка (место первой регистрации в 1979 г.); 2 — верховья р. СиΑима; 3 — устье р. Нижняя Буге; 4 — бассейн р. Мухен; 5–8 — Анюйский национаΛьный парк (соответственно, р. Пихца, урочище Сира, окрестности с. Арсеньево, устье р. СоΛоми); 9 — среΑнее течение р. СоΛоми; 10 — 76 км трассы ΔиΑога — Ванино; 11 — бассейн р. Кия; 12 — бассейн р. ХойΑур; 13 — бассейн р. Нюра Fig. 4. A schematic map of sika deer sightings in the Lower Amur Region in 1979-2021. Squares designate sites of photo recording: 1 — upper reaches of the rivers Obor and Durmin; 2, 3 — Anyui National Park; circles designate sightings sites according to the literature and the survey data: 1 — vicinity of the village Kutuzovka (the place of the first registration in 1979); 2 — upper reaches of the river Sidima; 3 — the mouth of the river Lower Buge; 4 — the Mukhen River basin; 5-8 —Anyui National Park (respectively, the Pikhtsa River, the Sira tract, the vicinity of the village Arsenyevo, the mouth of the Solomi River); 9 — the middle course of the Solomi River; 10 — 76 km of the Lidoga-Vanino Highway; 11 — the Kiya River basin; 12 — the Khoydur River basin; 13 — the Nyura River basin in New data on the distribution of sika deer Cervus nippon Temminck, 1838 in the Lower Amur Region

Рис. 4. Карта-схема мест встреч пятнистого оΛеня в Нижнем Приамурье в 1979–2021 гг. КваΑраты — места фоторегистрации: 1 — верховья рр. Обор и Àурмин; 2, 3 — Анюйский национаΛьный парк; круги — места встреч по Λитературным и опросным Αанным: 1 — окрестности с. Кутузовка (место первой регистрации в 1979 г.); 2 — верховья р. СиΑима; 3 — устье р. Нижняя Буге; 4 — бассейн р. Мухен; 5–8 — Анюйский национаΛьный парк (соответственно, р. Пихца, урочище Сира, окрестности с. Арсеньево, устье р. СоΛоми); 9 — среΑнее течение р. СоΛоми; 10 — 76 км трассы ΔиΑога — Ванино; 11 — бассейн р. Кия; 12 — бассейн р. ХойΑур; 13 — бассейн р. Нюра Fig. 4. A schematic map of sika deer sightings in the Lower Amur Region in 1979-2021. Squares designate sites of photo recording: 1 — upper reaches of the rivers Obor and Durmin; 2, 3 — Anyui National Park; circles designate sightings sites according to the literature and the survey data: 1 — vicinity of the village Kutuzovka (the place of the first registration in 1979); 2 — upper reaches of the river Sidima; 3 — the mouth of the river Lower Buge; 4 — the Mukhen River basin; 5-8 —Anyui National Park (respectively, the Pikhtsa River, the Sira tract, the vicinity of the village Arsenyevo, the mouth of the Solomi River); 9 — the middle course of the Solomi River; 10 — 76 km of the Lidoga-Vanino Highway; 11 — the Kiya River basin; 12 — the Khoydur River basin; 13 — the Nyura River basin

opencc-by-4.0Dec 2019View details →

Fig. 1 in Epizootic ulcerative syndrome - First report of evidence from South Africa's largest and premier conservation area, the Kruger National Park

Fig. 1. Sampling location from which evidence of genomic material of Aphanomyces invadans was obtained in Clarias gariepinus from Nhlangaluwe Pan on the Limpopo River in the Kruger National Park, South Africa.

opencc-by-4.0Jun 2018View details →

Figure 2 in First photographic evidence of Asian Golden Cat Catopuma temminckii (Vigors and Horsfield, 1827) from Neora valley National Park, Central Himalayas, India

Figure 2. Camera Trap photograph of Asian golden cat (Catopuma temminckii Vigors & Horsfield, 1827) captured in Neora Valley National Park, West Bengal, India.

opencc-by-4.0Jun 2018View details →

Figure 1 in First photographic evidence of Asian Golden Cat Catopuma temminckii (Vigors and Horsfield, 1827) from Neora valley National Park, Central Himalayas, India

Figure 1. The distribution of Asian Golden Cat according to the IUCN Redlist database and the photo-capture site of the species from the present study at Neora Valley National Park, West Bengal, India.

opencc-by-4.0Nov 2024View details →

The first 10-m China's national-scale sandy beach map in 2022 derived from Sentinel-2 imagery

This is the first 10-meter national scale beach map dataset of China. Based on the cloudless Sentinel-2 images for the whole year of 2022, we use the image classification method to draw a 10-meter beach map of China. The projection coordinate system of this data is WGS_1984_UTM_Zone_51N and the geographic coordinate system is GCS_WGS_1984. The "Shape_Leng" field in the data set represents the circumference of the beach, the "Shape_Area" field represents the area of the beach, and the "Province" field represents the province of each independent beach.

First Adoption for National Renewable Energy Targets in 187 Countries (1975-2017)

This dataset was used in the publication of "All Roads Lead to Paris: The Eight Pathways to Renewable Energy Target Adoption" in the journal of Energy Research & Social Science. The objective was to compile data on the first national adoption of a renewable energy target in each country to analyze its mechanisms of diffusion (learning, economic competition, emulation, and coercion). The data were compiled for 187 countries for the period ranging from 1975 to 2017. The list of countries was gathered from the Annex I of IRENA's "Renewable Energy Target Setting" report. We used primarily the IEA policies database (<a href="https://www.iea.org/policies">https://www.iea.org/policies</a>) to identify the first adoption of a renewable energy target in each country. Other sources were used when data was unavailable in such repository for specific countries. Additionally, we include the data gathered from various sources, as they were used in our paper for measuring variables. The variables in this dataset include: target adoption (or “Target”, from various sources listed in the dataset); year of adoption (or “Year”, from various sources listed in the dataset); cumulative membership to energy-related international environmental agreements (or “IEA”, with data from Mitchell’s International Environmental Agreements Database Project); net energy imports as a percentage of energy use (or “Energy”, with data from the World Bank); a similarity index (or “Similarity”, created with data from the Polity Index, population and GDP per capita from the World Bank, and revenue from the World Bank); official development assistance as a percentage of gross national income (or “ODAGNI”, with data from the World Bank and OECD); income level (“Income”, with data from the World bank); and the international price for oil (“Oil”, with data from the Federal Reserve Bank of St. Louis). For more details, refer to the manuscript. Note that in 2018 the “IEA’s policy database” was actually the “IEA/IRENA RE Policies and Measures database”. The links for the sources for renewable energy target adoption for Norway and Albania were lost in the transition from one to the other; all other sources could be retrieved by the authors.

opencc-by-4.0Nov 2019View details →

Text-fig. 1. Sampling areas in Çankırı province: the village of Sakarcaören near to the town of Orta (green circle) in the east of GVP, and the other sites (yellow circles), volcanic centers (red circles) and the border of GVP. The sites marked as yellow circles: ELM, Elmali village; SOG, Soguksu National Park; BUG, Bugralar village; INO, Inozu Valley South Side; INL, Inozu Valley North Side; KAR, Karasar village; MEN, Menceler Plateau; KIR, Kiraluc Site near Nuhhoca village; AGU, Asagiguney village; KUZ, Kuzca village (Bayam et al. 2018); PEL, Pelitcik village (Akkemik et al. 2009); GUD, Gudul (Akkemik et al. 2017); HOC, Hoçaş village and KOZ, Kozyaka village (Akkemik et al. 2016). The sites located in the western part (INO, INL, KAR, MEN, KIR, AGU, KUZ, HOC and KUZ) are from early – middle Burdigalian and Hancili Formation (Altun et al. 2002, Akbaş et al. 2002). The sites in the central part (GUD, BUG, ELM, PEL and SOG) are from middle – late Burdigalian, Pazar Formation (Kazancı 2012, Sen et al. 2017), and finally the fossil site in the east part of GVP is the late Miocene, Hüyükköy Formation (Sengüler 2007). in The First Glyptostroboxylon And Taxodioxylon Descriptions From The Late Miocene Of Turkey And Palaeoclimatological Evaluation

Text-fig. 1. Sampling areas in Çankırı province: the village of Sakarcaören near to the town of Orta (green circle) in the east of GVP, and the other sites (yellow circles), volcanic centers (red circles) and the border of GVP. The sites marked as yellow circles: ELM, Elmali village; SOG, Soguksu National Park; BUG, Bugralar village; INO, Inozu Valley South Side; INL, Inozu Valley North Side; KAR, Karasar village; MEN, Menceler Plateau; KIR, Kiraluc Site near Nuhhoca village; AGU, Asagiguney village; KUZ, Kuzca village (Bayam et al. 2018); PEL, Pelitcik village (Akkemik et al. 2009); GUD, Gudul (Akkemik et al. 2017); HOC, Hoçaş village and KOZ, Kozyaka village (Akkemik et al. 2016). The sites located in the western part (INO, INL, KAR, MEN, KIR, AGU, KUZ, HOC and KUZ) are from early – middle Burdigalian and Hancili Formation (Altun et al. 2002, Akbaş et al. 2002). The sites in the central part (GUD, BUG, ELM, PEL and SOG) are from middle – late Burdigalian, Pazar Formation (Kazancı 2012, Sen et al. 2017), and finally the fossil site in the east part of GVP is the late Miocene, Hüyükköy Formation (Sengüler 2007).

opencc-by-4.0Aug 2023View details →

SinoLC-1: the first 1-meter resolution national-scale land-cover map of China created with the deep learning framework and open-access data (User guide V2.4)

The User Guide V2.4 of the SinoLC-1 land-cover product. The SinoLC-1 was created by the Low-to-High Network (L2HNet), which can be found at: <a href="https://doi.org/10.1016/j.isprsjprs.2022.08.008">L2HNet</a>. A more detailed description of the data can be found in the <a href="https://doi.org/10.5194/essd-15-4749-2023">paper</a>. More related work can be found at my <a href="https://lizhuohong.github.io/lzh/">homepage</a>. <a href="https://zenodo.org/search?q=parent.id%3A7707461&f=allversions%3Atrue&l=list&p=1&s=10&sort=version">Click to check all the data versions and download the data (点击查看/下载所有数据版本)</a> NOTE: If you have any data needs, questions, or technical issues, contact us at <a href="http://ashelee@whu.edu.cn">ashelee@whu.edu.cn</a> (Zhuohong Li, 李卓鸿). The land-cover mapping method with Python code is open-access at <a href="https://github.com/LiZhuoHong/Paraformer/">Code link</a>. You can now update the high-resolution land-cover map by yourself with the code! The updated method is accepted by CVPR 2024 (<a href="https://arxiv.org/abs/2403.02746">Paper link</a>). 我们的最新制图算法被计算机视觉顶会CVPR2024接收(<a href="https://arxiv.org/abs/2403.02746">Paper link</a>),代码开源在:<a href="https://github.com/LiZhuoHong/Paraformer/">Code link</a>,您可以利用该代码高效地更新自己数据集的高分土地覆盖图。 Citation format of the paper: Li, Z., He, W., Cheng, M., Hu, J., Yang, G., and Zhang, H.: SinoLC-1: the first 1 m resolution national-scale land-cover map of China created with a deep learning framework and open-access data, Earth Syst. Sci. Data, 15, 4749–4780, 2023.  Li, Z., Zhang, H., Lu, F., Xue, R., Yang, G. and Zhang, L.: Breaking the resolution barrier: A low-to-high network for large-scale high-resolution land-cover mapping using low-resolution labels, ISPRS Journal of Photogrammetry and Remote Sensing. 192, pp.244-267, 2022. BibTex format of the paper: <blockquote> <pre>@article{li2023sinolc, title={SinoLC-1: the first 1 m resolution national-scale land-cover map of China created with a deep learning framework and open-access data}, author={Li, Zhuohong and He, Wei and Cheng, Mofan and Hu, Jingxin and Yang, Guangyi and Zhang, Hongyan}, journal={Earth System Science Data}, volume={15}, number={11}, pages={4749--4780}, year={2023}, publisher={Copernicus Publications G{\"o}ttingen, Germany} }</pre> <pre>@article{li2022breaking, title={Breaking the resolution barrier: A low-to-high network for large-scale high-resolution land-cover mapping using low-resolution labels}, author={Li, Zhuohong and Zhang, Hongyan and Lu, Fangxiao and Xue, Ruoyao and Yang, Guangyi and Zhang, Liangpei}, journal={ISPRS Journal of Photogrammetry and Remote Sensing}, volume={192}, pages={244--267}, year={2022}, publisher={Elsevier} }</pre> </blockquote>

opencc-by-4.0Feb 2022View details →

Drivers of extreme wildfire years in the 1965–2019 fire regime of the Tłı̨chǫ First Nation territory, Canada

Datasets, metadata and Rscript used to describe 1965-2019 wildfire regime and extreme wildfire years in central NWT.

opencc-by-4.0Jun 2020View details →

First Street Foundation's National Flood Adaptation Database

In order to create a national model with complete coverage of the contiguous United States, the First Street Foundation Flood Model relies on nationally available data that consistently represents the hydrologic conditions of the United States. However, most of this data represents the natural environment better than the modifications made by human activity that impact hydrology and therefore flooding. To make this model as accurate a representation of actual flood risk as possible, First Street has spent considerable time and effort to build a database of “grey” and “green” infrastructure and adaptation projects that affect the flow of water and therefore flooding. Grey Flood control projects include a variety of traditional infrastructure solutions like levees, pump stations, and flood control channels. Many green infrastructure projects also contribute to flood reduction, such as wetland restoration, floodable open space, retention basins, and creek rehabilitation projects. The First Street Foundation Flood Model also records and accounts for climate adaptation projects such as beach renourishment projects that are designed to counteract the effects of rising seas. This data is collected from state, county, and city agencies across the United States. It is digitized by drawing the area for which a structure is providing flood protection and assigned a level of protection provided. These service areas can range in size from a few residential blocks to a small city. Each feature is associated with one or more sources of flooding for which it provides protection. Estimates of the level of protection are based on the return period to which it will continue to function. This data is accounted for in the hydraulic and hydrologic model in several different ways. In most places, water is blocked within the model from entering a service area. This is similar to how a levee operates in real life, blocking water from entering a given location and pushing it somewhere else. Importantly, water is not removed from the model. In other cases like various runoff reduction green infrastructure projects, the service area of the project represents a change in the underlying soil classification within the hydrologic model. This replicates the way green infrastructure projects reduce runoff from their service area. In still other projects such as pump stations, the service area represents an adjustment to the flow of water in an area. Just as a pump station has a certain flowrate at which it will continue to be effective, even in an event beyond its design standard, this is represented in the model by removing an amount of flooding from an area equivalent to the modeled flow in the project’s service area at the design standard. So a pump station designed for a 5 year event would always remove the equivalent of the 5 year event, even in a 100 year event. You can download a sample of the database through Zenodo. If you wish to acquire the adaptation database, you can do so by reaching out to First Street Foundation <a href="https://firststreet.dev/register">here</a>.

opencc-by-4.0Dec 2020View details →

Figure 3 in First photographic evidence of Panthera tigris from Neora Valley National Park, Central Himalayas, India

Figure 3. Recorded tiger left view at Kattus Dara, Neora Valley National Park.