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3,685 results for “indonesia”
Dataset on waste separation in Indonesia
<p>The dataset contains data on observed waste separation in a gated community in Bogor, Indonesia. <br>Get more information on the project: <a href="https://prevent-waste.net/projects/creating-value-in-plastics-through-digital-technology/" target="_blank" rel="noopener">Creating Value in Plastics through Digital Technology - Prevent Waste Alliance (prevent-waste.net)</a> </p> <p> </p> <p>The data is provided in the following formats:</p> <ul> <li> .csv file (105281-zenodo-10889452_anon-df_2024-04-15_V1) <br>[character set "West Europe / Windows-1252"]</li> </ul> <p>Additional files:</p> <ul> <li>.txt documentation of VBA code for data anonymising (documentation_makro_anonymisingHH_ID.txt)<br> </li> </ul>
Yield determinants of Kappaphycus alvarezii seaweed in South Sulawesi, Indonesia
<p>Experimental data for the paper "Yield determinants of Kappaphycus alvarezii seaweed in South Sulawesi, Indonesia" by van Oort et al.:</p> <ul> <li>seaweed biomasss monitored bi-weekly in 5 cycles of 6 weeks (42 days) in 2023 - 2024 in two locations in South Sulawesi, Indonesia</li> <li>era5 oceanographic data for the two locations in South Sulawesi, monthly, 2015 - 2024</li> <li>water quality data for the two locations in South Sulawesi, bi-weekly, cycles 4 & 5 in 2024</li> <li>temperature data for the two locations in South Sulawesi, hourly, cycles 4 & 5 in 2024</li> <li>location data (kml files)</li> </ul> <p>Plus r-scripts for visualisation and some metadata</p>
Field-lab data and analyses results West Kalimantan, Indonesia
<p>Field data included in this compressed folder were collected over an area of approximately 23,500 hectares in West Kalimantan, Indonesia. The folder includes Excel and txt files with the following contents: field measurements of the peat thickness at 63 coring sites, laboratory analyses results of the samples collected in the field, field and lab measurements of electrical conductivity. Moreover, there is a file containing all the measurements of peat thickness and soil elevation extracted from the figures contained in previous studies. Finally, the folder also includes the results obtained from the inversion of the Airborne Electromagntic (AEM) data collected with the SkyTEM instrument over the study site, and specifically the resistivity of the soil layers obtained from the inversion and the peat thickness corresponding to the 45 Ohmm threshold. The folder also includes the Python codes used for the statistical analyses explained in the paper.</p>
A Multi-Site Investigation into the Epidemiology of Chikungunya Virus in Neglected Regions of Indonesia
<p>Supporting datasets for phylogenetic analysis of Indonesian chikungunya virus sequences using BEAST v1.10.4.</p> <p> </p>
Orangutan habitat survey in Sebangau National Park, Central Kalimantan, Indonesia
<p>This dataset is used to initialise BORNEO (arBOReal aNimal movEment mOdel), as a part of publication entitled:</p> <p>Assessing the impact of forest structure disturbances on the arboreal movement oforangutans - an agent-based modelling approach.</p> <p>The article manuscript is being prepared to be submitted to Frontiers in Ecology and Evolution</p> <p><strong>Data collection</strong></p> <p>The data is collected in Sebangau, Central Kalimantan, Indonesia. Two 1-ha plots were established, each in unburned and burned forest. </p>
Suplemen: Perkembangan & Penerapan Sains Terbuka di Indonesia
<p>Material ini berisi tentang:</p> <ol> <li>Data jurnal Open Access dari DOAJ</li> <li>Data jumlah artikel Indonesia di Scopus</li> <li>Video demonstrasi Altmetric</li> </ol>
National Checklists 2017: Indonesia Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details<p></p>A list of species from Indonesia collected using effechecka and geonames polygons
National Checklists 2019: Indonesia Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details.<p></p>A list of species from Indonesia collected using effechecka and geonames polygons
Respondents' perspectives on the impact of digital data-based health services on disaster risk management in Indonesia.
<p>This data contains respondents' perspectives on the impact of digital data-based health services on disaster risk management. Digital health services are the implementation of digital, information, and communication technologies in the context of health services. Digital health services include: mHealth, Health Information Technology, Wearable Devices, Telehealth and Telemedicine, and Personalized Medicine. </p> <p>Data was collected and processed as part of the ODDEA (Overcoming Digital Divide Between Europe and Southeast Asia) EU research project (Project ID: HORIZON MSCA-SE 101086381) would be advisable.</p>
INCOME DISPARITIES AMONG MICRO AND SMALL ENTERPRISES: THE DIGITAL DIVIDE IN INDONESIA
<p>Data related to small scale enterprise in relations to the digital aspects by prinvince in Indonesia source from Badan Pusat Statistik, Republic of Indonesia</p> <p>Data was collected and processed as part of the ODDEA (Overcoming Digital Divide Between Europe and Southeast Asia) EU research project (Project ID: HORIZON MSCA-SE 101086381) </p>
Canopy top height and indicative high carbon stock maps for Indonesia, Malaysia, and Philippines
<p>Canopy top height and indicative high carbon stock maps for Indonesia, Malaysia, and Philippines. The provided land cover maps follow the high carbon stock approach (HCSA) stratifying vegetation based on the estimated carbon density (aboveground biomass). A deep convolutional neural network was trained to estimate canopy top height from Sentinel-2 optical satellite images using reference data derived from GEDI lidar waveforms. Carbon density and high carbon stock classes were derived from these dense canopy height maps using calibration data from an airborne lidar campaign in Sabah, Borneo. The resulting maps have a ground sampling distance (GSD) of 10 m and are based on images between 1st of September 2020 and 1st of March 2021.</p> <p>The style files (color_style_HCS.qml, color_style_canopy_top_height.qml) contain the color coding and can be loaded for visualization (e.g. in QGIS).</p> <p>The indicative HCS maps contain 9 land cover categories noted as "Label: name [colorcode]":</p> <p> 0: Open land (OL) [#440154]<br> 1: Scrub (S) [#404387]<br> 2: Young regenerating forest (YRF) [#29788e]<br> 3: Low density forest (LDF) [#22a884]<br> 4: Medium density forest (MDF) [#7ad251]<br> 5: High density forest (HDF) [#fde725]<br> 10: Oil palm [#fcffa4]<br> 11: Coconut [#a4feff]<br> 50: Urban [#fa0000]<br> 255: No data</p> <p><strong>Citation: </strong>Use of these data require citation of this dataset and the original research articles. These citations are as follows:</p> <p>Lang, N., Schindler, K., & Wegner, J. D. (2021). High carbon stock mapping at large scale with optical satellite imagery and spaceborne LIDAR. arXiv preprint arXiv:2107.07431.</p> <p>Rodríguez, A. C., D'Aronco, S., Schindler, K., & Wegner, J. D. (2021). Mapping oil palm density at country scale: An active learning approach. <em>Remote Sensing of Environment</em>, <em>261</em>, 112479.</p> <p>Lang, N., Rodríguez, A. C., Schindler, K., & Wegner, J. D. (2021). Canopy top height and indicative high carbon stock maps for Indonesia, Malaysia, and Philippines (Version 1.0) [Data set]. Zenodo. http://doi.org/10.5281/zenodo.5012448</p> <p> </p>
Morphotectonic indices and earthquake dataset of Batui Thrust Segment, Banggai, Indonesia
<p>To measure the tectonic activity of a region, morphotectonic, a quantitave measurement of landscapes are carried out. Combination between geological, geomorphology, and earthquake data approach are powerful source to determine process that make up mountainous landscape. The combined data are applied to Pagimana and adjacent area, Banggai, Indonesia by dividing into eight watersheds and aim the Batui Thurst as main objective. The data comprised of 8.5m vertical resolution Digital Elevation Model (DEM) and earthquakes catalog were downloaded from the open-source database and extracted using composited GIS software. We use seven morphometry indices consist of Mountain Front Sinousity (Smf), Drainage Basin: Asymmetry Factor (AF) and Transverse Topographic Symmetry (T), Hypsometric Integral (HI), Channel Sinuosity (S), Ratio of Valley Floor Width to Valley Height (Vf), Stream Length-Gradient Index (SL), and Basin Elongation Ratio (Re) and embed them on eight watersheds which taken by remote sensing. Weighing indices and watersheds matrix also calculated to define correlation between each watershed on each index. Fieldwork also carried out to ensure the presence of Batui Thrust and other related structural geology which have been developed on the Pagimana. This dataset is potentially can be used for geologist, geophysicist and geomorpher to get new insight on the forming of East Arm of Sulawesi landscape and the Banggai-Sula Microcontinent development. Beside, the urban planner and risk assessor can be easily analyze the dataset to avoid and minimize effect of the potential earthquake hazard in the future.</p>
Indonesia, monthly Standardized Precipitation-Evapotranspiration Index (SPEI) blend 1960 - 2021
<p>IDN_CLI_SPEI_blend_0p042_1961_2021 is currently the only comprehensive high resolution Indonesia gridded historical dataset of SPEI blend and available for public.</p> <p>The SPEI - https://spei.csic.es/ is an extension of the widely used SPI. The SPEI is designed to take into account both precipitation and potential evapotranspiration (PET) in determining drought. Thus, unlike the SPI, the SPEI captures the main impact of increased temperatures on water demand.</p> <p>The IDN_CLI_SPEI_blend_0p042_1960_2021 is derived using precipitation and potential evapotranspiration from TerraClimate data - https://www.climatologylab.org/terraclimate.html, it has 0.042 degree gridded resolution, a monthly and available from 1958 to 2021. The calibration period is January 1961 to December 2020. The starting date of the dataset is 1960 in order to provide common information across the different SPEI time-scales.</p> <p>The SPEI blend integrate several SPEI scales into a single product, combine 3-, 6-, 9-, 12- and 24-month SPEI to estimate the overall dry/wet condition. </p> <p>The SPEI processed using climate_indices, an open source Python library providing reference implementations of commonly used climate indices. https://pypi.org/project/climate-indices/</p>
New insights into crustal deformation of the Indonesia-Australia-New Guinea collision zone from a broad-scale kinematic model: Supplementary Model Files
<p>Supplementary kinematic model input for the JGR: Solid Earth publication "New insights into crustal deformation of the Indonesia-Australia-New Guinea collision zone from a broad-scale kinematic model".</p>
The GNSS time series along the northern coastline of Java, Indonesia
<p>This repository contains the GNSS time series along the northern coastline of Java, both in .rneu and the GAGE's .pos format (https://www.unavco.org/data/gps-gnss/derived-products/docs/NOTICE-TO-DATA-PRODUCT-USERS-GPS-2013-03-15.pdf). The repository also contains the stations' coordinates. </p> <p>Notes:<br> In the .rneu format of the GNSS time series:<br> 1. The outliers have been removed.<br> 2. The offsets due to instrument changes at CGON in mid-2016 and at CSIT in late 2015 have been corrected.</p> <p>Please refer to:<br> Susilo, S., Salman, R., Hermawan, W. <em>et al.</em> GNSS land subsidence observations along the northern coastline of Java, Indonesia. <em>Sci Data</em> <strong>10</strong>, 421 (2023). https://doi.org/10.1038/s41597-023-02274-0</p>
Fig. 1 in Platygobiopsis hadiatyae, a new species of deepwater gobiid from Indonesia (Teleostei, Gobiidae, Gobiinae)
Fig. 1. Platygobiopsis hadiatyae, new species, MZB 17230, holotype, 43.0 mm SL, photographed soon after collection; Indonesia, Panaitan Strait along the Sunda Strait. Photographs by Tan Heok Hui.
Fig. 2 in Platygobiopsis hadiatyae, a new species of deepwater gobiid from Indonesia (Teleostei, Gobiidae, Gobiinae)
Fig. 2. Platygobiopsis hadiatyae, new species, MZB 17230, holotype, 43.0 mm SL; fixed specimen, lateral view. Right pectoral fin dissected. Photographs by Tan Heok Hui.
Fig. 3 in Platygobiopsis hadiatyae, a new species of deepwater gobiid from Indonesia (Teleostei, Gobiidae, Gobiinae)
Fig. 3. Platygobiopsis hadiatyae, new species, MZB 17230, holotype, 43.0 mm SL; line drawing of head (lateral view) showing sensory papilla pattern. Scale bar equal to 8 mm. Drawing by Helen Larson.
Fig. 5 in Four new species and new records of Manota (Diptera: Mycetophilidae) from Sulawesi, Indonesia
Fig. 5. Manota paulula Hippa & Ševčík, 2013 (North Sulawesi). A – hypopygium, dorsal view; B – hypopygium, ventral view; C – hypoproct and aedeagus, ventral view. Scale 0.10 mm.
Fig. 4 in Four new species and new records of Manota (Diptera: Mycetophilidae) from Sulawesi, Indonesia
Fig. 4. Manota spathigera. sp. nov. (holotype). A – hypopygium, dorsal view; B – hypopygium, ventral view; C – hypoproct and aedeagus, ventral view. Scale 0.10 mm.
ScienceDex guides
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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.