Find research datasets worth reusing

opencc-by-4.0Dec 2023View details →

Star Trails of the Forbidden City

Honorable mention in the 2023 IAU OAE Astrophotography Contest, category Still images with smartphones-mobile devices: Star Trails of the Forbidden City, by Stephanie Ziyi Ye. Beneath the celestial ballet of star trails that weave their way across the night sky, the Beijing Forbidden City stands as a testament to ancient celestial connections in this image captured in March 2022. Designed with a cosmic alignment in mind, the palace echoes the orientation of the North Star, also known as Polaris, a celestial anchor that has long guided navigators and symbolised steadiness in the sky. It was believed that the Emperor embodied the earthly representation of this pole star, bridging the realms between heaven and earth. In this harmonious one-hour exposure captured with a smartphone, the streaks of stars trace their nightly journey across the firmament, converging toward the North Star, reflecting the precision of both architectural design and celestial paths. The image receives an honourable mention in the category of Still images taken exclusively with smartphones/mobile devices. Credit: Stephanie Ziyi Ye/IAU OAE (<a href="https://creativecommons.org/licenses/by/4.0/legalcode">CC BY 4.0</a>)

opencc-by-4.0Dec 2023View details →

Shared mobility provision in European cities

This dataset includes different types of shared mobility schemes (i.e. including service provider, type of modality, type of operational model and type of public/private involvement) across European cities (having a population of more than 100.000).

opencc-by-4.0Nov 2023View details →

YJMob100K: City-Scale and Longitudinal Dataset of Anonymized Human Mobility Trajectories

The YJMob100K human mobility datasets (YJMob100K_dataset1.csv.gz and YJMob100K_dataset1.csv.gz) contain the movement of a total of 100,000 individuals across a 75 day period, discretized into 30-minute intervals and 500 meter grid cells. The first dataset contains the movement of 80,000 individuals across a 75-day business-as-usual period, while the second dataset contains the movement of 20,000 individuals across a 75-day period (including the last 15 days during an emergency) with unusual behavior.  While the name or location of the city is not disclosed, the participants are provided with points-of-interest (POIs; e.g., restaurants, parks) data for each grid cell (~85 dimensional vector) as supplementary information (cell_POIcat.csv.gz). The list of 85 POI categories can be found in POI_datacategories.csv.  For details of the dataset, see Data Descriptor:  <ul> <li>Yabe, T., Tsubouchi, K., Shimizu, T., Sekimoto, Y., Sezaki, K., Moro, E., & Pentland, A. (2024). YJMob100K: City-scale and longitudinal dataset of anonymized human mobility trajectories. Scientific Data, 11(1), 397. <a href="https://www.nature.com/articles/s41597-024-03237-9" target="_blank" rel="noopener">https://www.nature.com/articles/s41597-024-03237-9</a>  </li> </ul>     --- Details about the Human Mobility Prediction Challenge 2023 (ended November 13, 2023) ---  The challenge takes place in a mid-sized and highly populated metropolitan area, somewhere in Japan. The area is divided into 500 meters x 500 meters grid cells, resulting in a 200 x 200 grid cell space. The human mobility datasets (task1_dataset.csv.gz and task2_dataset.csv.gz) contain the movement of a total of 100,000 individuals across a 90 day period, discretized into 30-minute intervals and 500 meter grid cells. The first dataset contains the movement of a 75 day business-as-usual period, while the second dataset contains the movement of a 75 day period during an emergency with unusual behavior. There are 2 tasks in the Human Mobility Prediction Challenge. In task 1, participants are provided with the full time series data (75 days) for 80,000 individuals, and partial (only 60 days) time series movement data for the remaining 20,000 individuals (task1_dataset.csv.gz). Given the provided data, Task 1 of the challenge is to predict the movement patterns of the individuals in the 20,000 individuals during days 60-74. Task 2 is similar task but uses a smaller dataset of 25,000 individuals in total, 2,500 of which have the locations during days 60-74 masked and need to be predicted (task2_dataset.csv.gz). While the name or location of the city is not disclosed, the participants are provided with points-of-interest (POIs; e.g., restaurants, parks) data for each grid cell (~85 dimensional vector) as supplementary information (which is optional for use in the challenge) (cell_POIcat.csv.gz). For more details, see https://connection.mit.edu/humob-challenge-2023

opencc-by-sa-4.0Mar 2024View details →

Dataset of Hotels from Major Cities in Spain - 2024

Trend Analysis of Accommodation Prices in the Major Cities of Spain: A Comparative Perspective.

opencc-by-4.0Dec 2021View details →

Fig. 1 in Species Diversity And Ecology Of Amphibians And Reptiles In Urbanized Landscapes Of The City Of Minsk

Fig. 1 Location of the largest habitats and stable populations of amphibians and reptiles in the urbanized areas of the Minsk city.

РИС. 4. Дистальные отделы половой системы Arion vulgaris иЗ г. Минска: А – атриум; E – Эпифаллус; PN – пневмостон; SP – семЯприемник; OV – Яйцевод; SPD – проток семЯприемника; VD – семЯпровод. FIG. 4. Distal parts of the reproductive system of Arion vulgaris from the Minsk city: А – atrium; E – epiphallus; PN – pneumostone; SP – spermatheca (bursa copulatrix); OV – free oviduct; SPD – spermatheca duct (duct of bursa copulatrix); VD – vas deferens. in Новые находки синантропных слиЗней Limacus maculatus и Arion vulgaris (Mollusca, Gastropoda, Stylommatophora) в Беларуси

РИС. 4. Дистальные отделы половой системы Arion vulgaris иЗ г. Минска: А – атриум; E – Эпифаллус; PN – пневмостон; SP – семЯприемник; OV – Яйцевод; SPD – проток семЯприемника; VD – семЯпровод. FIG. 4. Distal parts of the reproductive system of Arion vulgaris from the Minsk city: А – atrium; E – epiphallus; PN – pneumostone; SP – spermatheca (bursa copulatrix); OV – free oviduct; SPD – spermatheca duct (duct of bursa copulatrix); VD – vas deferens.

РИС. 3. Внешний вид Arion vulgaris иЗ г. Минска (фото И.Н. Субботиной). FIG. 3. Live specimen of Arion vulgaris from the Minsk city (photo by I.N. Subbotina). in Новые находки синантропных слиЗней Limacus maculatus и Arion vulgaris (Mollusca, Gastropoda, Stylommatophora) в Беларуси

РИС. 3. Внешний вид Arion vulgaris иЗ г. Минска (фото И.Н. Субботиной). FIG. 3. Live specimen of Arion vulgaris from the Minsk city (photo by I.N. Subbotina).

РИС. 1. Внешний вид Limacus maculatus иЗ окрестностей г. ГомелЯ. FIG. 1. Live specimen of Limacus maculatus from the vicinity of Gomel city. in Новые находки синантропных слиЗней Limacus maculatus и Arion vulgaris (Mollusca, Gastropoda, Stylommatophora) в Беларуси

РИС. 1. Внешний вид Limacus maculatus иЗ окрестностей г. ГомелЯ. FIG. 1. Live specimen of Limacus maculatus from the vicinity of Gomel city.

РИС. 2. Дистальные отделы половой системы Limacus maculatus иЗ окрестностей г. ГомелЯ: А – атриум; P – пенис; PR – простата; SP – семЯприемник; OV – Яйцевод; SPOV – спермовидукт; SPD – проток семЯприемника; VD – семЯпровод. FIG. 2. Distal parts of the reproductive system of Limacus maculatus from the vicinity of Gomel city: А – atrium; P – penis; PR – prostata; SP – spermatheca (bursa copulatrix); OV – free oviduct; SPOV – spermoviduct; SPD – spermatheca duct (duct of bursa copulatrix); VD – vas deferens. in Новые находки синантропных слиЗней Limacus maculatus и Arion vulgaris (Mollusca, Gastropoda, Stylommatophora) в Беларуси

РИС. 2. Дистальные отделы половой системы Limacus maculatus иЗ окрестностей г. ГомелЯ: А – атриум; P – пенис; PR – простата; SP – семЯприемник; OV – Яйцевод; SPOV – спермовидукт; SPD – проток семЯприемника; VD – семЯпровод. FIG. 2. Distal parts of the reproductive system of Limacus maculatus from the vicinity of Gomel city: А – atrium; P – penis; PR – prostata; SP – spermatheca (bursa copulatrix); OV – free oviduct; SPOV – spermoviduct; SPD – spermatheca duct (duct of bursa copulatrix); VD – vas deferens.

FIG. 5. Correlation between the spatial distribution index and population density. A in Demographic and spatial structure at the stage of expansion in the populations of some alien land snails in Belgorod city (Central Russian Upland)

FIG. 5. Correlation between the spatial distribution index and population density. A. For Brephulopsis cylindrica and Xeropicta derbentina at 160 plots for three years. B. For Harmozica ravergiensis in nine sites×20 plots for two years. РИС. 5. Корреляция меЖду индексом пространственного распределения и плотностью популяции. А. Для Brephulopsis cylindrica и Xeropicta derbentina на 160 плоЩадках За три года. В. Для Harmozica ravergiensis на девяти участках по 20 плоЩадок За два года.

FIG. 4 in Demographic and spatial structure at the stage of expansion in the populations of some alien land snails in Belgorod city (Central Russian Upland)

FIG. 4. Boxplots for estimating the density of different age classes in the Xeropicta derbentina population in warm months of 2017, 2019, and 2020 for 160 test plots. Adult snails are represented by red boxes; juvenile snails are represented by blue boxes. РИС. 4. Боксплоты для оценок плотности раЗличных воЗрастных классов в популяции Xeropicta derbentina в раЗные теплые месяцы 2017, 2019 и 2020 гг. для 160 пробных плоЩадок. ВЗрослые особи покаЗаны красным цветом, ювенильные особи покаЗаны голубым цветом.

FIG. 3 in Demographic and spatial structure at the stage of expansion in the populations of some alien land snails in Belgorod city (Central Russian Upland)

FIG. 3. Boxplots for estimating the density of different age classes in the Brephulopsis cylindrica population in warm months of 2017, 2019, and 2020 for 160 test plots. Adult snails are represented by red boxes; juvenile snails are represented by blue boxes. РИС. 3. Боксплоты для оценок плотности раЗличных воЗрастных классов в популяции Brephulopsis cylindrica в раЗные теплые месяцы 2017, 2019 и 2020 гг. для 160 пробных плоЩадок. ВЗрослые особи покаЗаны красным цветом, ювенильные особи покаЗаны голубым цветом.

FIG. 2 in Demographic and spatial structure at the stage of expansion in the populations of some alien land snails in Belgorod city (Central Russian Upland)

FIG. 2. Scheme of plots in a regular grid. A. Study site. B. Brephulopsis cylindrica and Xeropicta derbentina in the field. C. Scheme of plots in a regular grid. РИС. 2. Регулярная сетка плоЩадок. A. РасполоЖение исследуемого участка. B. Brephulopsis cylindrica и Xeropicta derbentina в месте обитания. C. Схема регулярной сетки плоЩадок.

opencc-byOct 2024View details →

Land surface temperature (heatmaps) derived from earth observation data to assess thermal behaviour of 3 European cities: Milano, Logroño and Athens.

Next tables present the detail description of the datasets developed in REACHOUT to characterize heat phenomena at city level by providing an assessment of the land surface temperature (heatmaps) of three European cities: Milan, Logroño and Athens. TECNALIA is the responsible partner for these datasets. There is a wide range of methods that can be used to characterise the thermal behaviour of a city, each of them with its advantages and disadvantages. One of these methods uses the land surface temperature that is obtained from remote sensing observations. Although thermal indices are considered more suitable when characterising thermal comfort, still the LST can provide a useful information about the behaviour of a citiy’s surfaces and materials. This has implications for several applications such as urban energy efficiency or urban environmental health.  The input data used by the current version of the dataset came from Landsat 8. All the images acquired since 2013 by this satellite for Milan, Logroño and Athens were downloaded and processed to characterise not only the current (2019-2023) thermal behaviour of the city, but also its evolution considering the last seven 5-year windows. -    2013-2017 -    2014-2018 -    2015-2019 -    2016-2020 -    2017-2021 -    2018-2022 -    2019-2023 The input data used in this dataset come from Landsat 8 downloaded from <a href="https://earthexplorer.usgs.gov/">Earth Explorer (usgs.gov)</a>. The format of this dataset is organized in two ZIP format files: -    LANDSAT_8_L2SP_000000-milan_LST_peak.zip -    LANDSAT_8_L2SP_000000-logrono_LST_peak.zip -    LANDSAT_8_L2SP_000000-athens_LST_peak.zip Each of these zip files contain seven TIF images that represent the peak LST map according to the images of the above mentioned seven periods. The peak LST is obtained after getting the Annual Cycle Parameters of each of the periods and selecting a 30-day window centred on the day that the city reaches the maximum LST. The values of the images are in degree Celsius and nodata value is -9999.

opencc-zeroAug 2024View details →

National Checklists: Vatican City Species List

Data from: GBIF.org (23 January 2025) GBIF Occurrence Download <a href="https://doi.org/10.15468/dl.vd2ajk" target="_blank" rel="noopener">https://doi.org/10.15468/dl.vd2ajk</a>

opencc-by-4.0Sep 2024View details →

Large Landslide Exposure in Metropolitan Cities

These datasets (.Rmd, .Rroj., .rds) are ready to use within the R software for statistical programming with the R Studio Graphical User Interface (https://posit.co/download/rstudio-desktop/). Please copy the folder structure into one single directory and follow the instructions given in the .Rmd file. Files and data are listed and described as follows: Main directory files: results_fpath <ul> <li>Code containing statisticla analysis and ploting: 20240927_code.Rmd </li> <li>1_melted_lan_df.rds: Landslide time series database covering 1,085 landslides intersected with settlement footprints from 1985-2015.</li> <li>4_cities_lan.df.rds: City and landslide data for these 1,085 landslides intersected with settlement footprints from 1985-2015.</li> <li>7_zoib_nested_pop_pressure_model: brms statistical model file.</li> <li>ghs_stat_fua_comb.gpkg: Urban center data from the GHSL - Global Human Settlement Layer.</li> </ul> Population estimation files: wpop_files  <ul> <li>2015_ls_pop.csv: Estimates of population on landslides using the 100x100 population density grid from the WorldPop dataset.</li> </ul> Steepness and elevation analysis derived from SRTM and processed in Google Earth Engine for landslides, mountain regions and urban centers in cities: gee_files <ul> <li>1_mr_met.csv: Elevation and mean slope for mountain region areas in cities</li> <li>2_uc_met.csv: Elevation and mean slope for urban centers (defined by in the GHSL data) in cities</li> </ul> Standard deviation analysis derived from SRTM and processed in Google Earth Engine for mean slope in mountain regions and urban centers in cities: gee_sd <ul> <li>gee_mr.csv: Mean slope and standard deviation for mountain region</li> <li>gee_uc.csv: Mean slope and standard deviation for urban centers (defined by in the GHSL data)</li> </ul> Summary overview of cities with large landslides used in this study: cities_summary.csv Variables in this file are: <ul> <li> <ul> <li>eFUA_name := City name</li> <li>cntry := Country name</li> <li>cntry_ISO := Country ISO code</li> <li>fua_area := Estimate of total metropolitan city area (km^2)</li> <li>ls_total_area := Total large landslide areas within city (m^2)</li> <li>ls_pct_fua_area := Mapped large landslides\n(% of the metropolitan city area)</li> <li>pop_FUA_2015 :=  Metropolitan population estimate (2015)</li> <li>pop_ls := Estimate of total number of people on large landslides</li> </ul> </li> </ul>

opencc-by-4.0Dec 2018View details →

Vehicular traffic count measurements at Tampere City, Finland, Updated version

Inductive loop vehicular traffic count measurements from Tampere City, Finland 15-minute resolution, 2 locations, 2011-2014 Data utilized in "Origin-destination matrix estimation with a conditionally binomial model" by P.Kuusela, I. Norros, J. Kilpi and T. Räty See VehicularTrafficCountMeasurements_TampereFinland_2011-2014.rtf

opencc-by-4.0Nov 2021View details →

Artaxata-Artashat (Armenia) magnetic data of the eastern lower city (south)

This data was collected during the 2021 campaign of the Armenian-German Artaxata Project (Armenian Academy of Science and University of Münster). Data is provided for UTM WGS84 Zone 38N, EPSG: 32638 Geophysical prospections were undertaken by cornelius meyer prospection, Berlin Funded by Deutsche Forschungsgemeinschaft

opencc-by-4.0Nov 2021View details →

Artaxata-Artashat (Armenia) magnetic data of the eastern lower city

This data was collected during the 2018 campaign of the Armenian-German Artaxata Project (Armenian Academy of Science and University of Münster). Data is provided for UTM WGS84 Zone 38N, EPSG: 32638 Geophysical prospections were undertaken by EasternAtlas, Berlin Publication: Lichtenberger A, Meyer C, Zardaryan M. 2019. ‘Report on the 2018 Magnetic Prospection at Artaxata/Artashat in Armenia.’ Archäologischer Anzeiger 2019: 70-89. doi: <a href="https://dx.doi.org/10.34780/aa.v0i2.1004">10.34780/aa.v0i2.1004 </a>.