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482 results for “Digital data”
Data for "The Heritage Digital Twin: a bicycle made for two."
<p>The file contains the data used in the case studies of the paper "The Heritage Digital Twin: a bicycle made for two. The integration of digital methodologies into cultural heritage research" published on ORE.</p>
Caribou Poker Creek Research Watershed GIS Data: Digital Elevation Model (DEM)
This file contains one of many raster grids of the Elevation Derivatives for National Applications (EDNA), a multi-layered database that provides systematic and consistent topographically-derived hydrologic derivatives. The filled DEM grid was created from the original elevation data by filling all of the depressions, or sinks, in the original DEM. To create this grid, an algorithm was used to loacted and fill all depressions or sinks where there was no flow from pixel to pixel. During this process, efforts were made to maintain natural sink features. Originator: U.S. Geological Survey. Publication_Date: 2006. Title: cpcrw_dem.tif. Edition: Stage I Data. Geospatial_Data_Presentation_Form: Remote-sensing image. Series_Information: Series_Name: Elevation Derivatives for National Applications (EDNA). Publication_Information: Publication_Place: USGS EROS, Sioux Falls, South Dakota. Publisher: U.S. Geological Survey.
Bonanza Creek Experimental Forest GIS Data: Digital Elevation Model (DEM)
This file contains one of many raster grids of the Elevation Derivatives for National Applications (EDNA), a multi-layered database that provides systematic and consistent topographically-derived hydrologic derivatives. The filled DEM grid was created from the original elevation data by filling all of the depressions, or sinks, in the original DEM. To create this grid, an algorithm was used to loacted and fill all depressions or sinks where there was no flow from pixel to pixel. During this process, efforts were made to maintain natural sink features. Originator: U.S. Geological Survey. Publication_Date: 2006. Title: bcef_dem.tif. Edition: Stage I Data. Geospatial_Data_Presentation_Form: Remote-sensing image. Series_Information: Series_Name: Elevation Derivatives for National Applications (EDNA). Publication_Information: Publication_Place: USGS EROS, Sioux Falls, South Dakota. Publisher: U.S. Geological Survey.
10 Women of Digital Humanities: An Analysis of Linked Open Data
<p>This is a spreadsheet of linked open data, including tweets of the 10 female scholars randomly chosen for this project. This is an experimental study, and was prepared for my own learning. Presentation prepared for a Masters seminar in Information Science at uOttawa in Winter 2020. </p> <p>Linked Open Data in the Humanities was taught by Prof. Constance Crompton.</p> <p>10 Women of Digital Humanities: An Analysis of Linked Open Data</p> <p>tags: dh, digital humanities, feminist dh, computational analysis, Voyant, word clouds, vizualization, digital identifiers, open scholarship</p>
Data and R code for the revised manuscript "Downscaling digital soil maps using electromagnetic induction and aerial imagery"
<p>Data and R code for the revised manuscript "Downscaling digital soil maps using electromagnetic induction and aerial imagery". This is the code for the revised version of the manuscript, after adressing comments from reviewers. The data and code for the preprint, before submission to peer review (Møller et al., 2020), is available at <a href="https://doi.org/10.5281/zenodo.3699130">https://doi.org/10.5281/zenodo.3699130</a>.</p> <p>The R code was written for R version 3.6.3.</p> <p>References<br> Møller, A.B., Koganti, T., Beucher, A., Iversen, B.V. and Greve, M.H., 2020. Downscaling digital soil maps using electromagnetic induction and aerial imagery. EarthArXiv. <a href="http://dx.doi.org/10.31223/osf.io/a7xz6">http://dx.doi.org/10.31223/osf.io/a7xz6</a>. [preprint]</p>
Data Lakes for Digital Humanities
<p>Traditional data in Digital Humanities projects bear various formats (structured, semi-structured, textual) and need substantial transformations (encoding and tagging, stemming, lemmatization, etc.) to be managed and analyzed. To fully master this process, we propose the use of data lakes as a solution to data siloing and big data variety problems. We describe data lake projects we currently run in close collaboration with researchers in humanities and social sciences and discuss the lessons learned running these projects.</p>
Data for the Paper "Digital color codes of stars"
<p>Data for the paper "Digital color codes of stars" by Jan-Vincent Harre and René Heller.</p> <p>Our code "spec2col.py" can be found at <a href="https://github.com/janvincentharre/spec2col">GitHub</a>.</p>
Digitized patient level time to event data of overall survival
<p>This dataset contains digitized patient level time to event data for overall survival of patients with locally advanced and metastatic (stage IIIB/IV) Non-small cell lung cancer (NSCLC). The data can be used to recreate the original Kaplan-Meier survival curves that were published in randomized controlled trials, in order to perform secondary analysis on the survival data. In order to recreate a survival curve, you need two csv.files per trial arm that are in this <br> database: (1) starting with 'surv_', containing the individual patient level time to event data, and (2) starting with 'natrisk_', containing the corresponding numbers at risk table. For the methodology and r-code that can be used for this purpose we refer to article that is linked to this dataset. </p>
Data availability. Multivariate data analysis. Validation of an instrument for the evaluation of teaching digital competence.
<p><strong>Data availability</strong>. Multivariate data analysis. Validation of an instrument for the evaluation of teaching digital competence. </p><ul><li>SPSS DATA. Multivariate data analysis. Validation of an instrument for the evaluation of teaching digital competence (spss data.sav). The data presented in this file contains the data imported wiyh the Software IBM SPSS Statistics, versión 28.0.1.1(15).</li><li>EXCEL DATA. Multivariate data analysis. Validation of an instrument for the evaluation of teaching digital competence (spss data.sav). The data presented in this file contains the data imported wiyh the Software IBM SPSS Statistics, versión 28.0.1.1(15).</li><li>Data of Project factorial.xlsx (The data presented in this file contains the results of the statistical analysis carried out with the Software Microsoft Excel).</li><li>Data Project reliability.xlsx (The data presented in this file contains the results of the statistical analysis carried out with the Software Microsoft Excel).</li><li>FIGURES. Multivariate data analysis. Validation of an instrument for the evaluation of teaching digital competence (Figure 1.jpeg, Figure 2.jpeg, Figure 3 and Figure 4.jpeg).</li></ul>
Data from: Artificial intelligence enabled multi-purpose smart detection in active-matrix digital microfluidics
<p>Active-matrix digital microfluidics (AM-DMF), integrated with hundreds of thousands of active electrodes, can simultaneously realize multiple on-chip bio-chemical reactions at the single-cell level. An intelligent detection system is critical for fully automating manipulations of thousands of digitalized bio-samples and programming the subsequent experiments in real time. In this work, we developed a series of deep learning algorithms based on an AM-DMF system for sample detections. We used the U-net model to quantitatively evaluate different splitting methods on sample droplet generation uniformity. The results revealed that droplets generated using the "one-to-two" strategy exhibits optimal uniformity. We used the YOLOv5 model to monitor the droplet splitting success rates over 18 different AM-DMF chips, and a 97.7% splitting success rate was observed. The results indicated that the model precision was 99.980% and the model recall was 99.976% through manual verification. In addition, we used an improved YOLOv8 model to detect single cells in nanoliter droplets effectively. In comparison with manual verification, the results showed that the model achieved a precision of 99.260% and a recall of 99.193%. By leveraging an artificial intelligence enabled smart detection system, AM-DMF has shown great potential as a ubiquitous platform for true lab-on-a-chip.</p>
Data on digital perfomance of public sector in South-East Asia
<p>Data on digital perfomance of public sector in South-East Asia includes variables affecting process of digitalization in public sector in South-East Asian countries. </p>
Digitization of Musu Rma data in Liu 1985
<p>This is a dataset that has been digitized from Liu 1985. The data are Liu's transcriptions of Rma/Qiang words in the Musu variety of Heishui County, SIchuan China. </p><p>This dataset includes the original transcription system which was not standard IPA due to type-setting. It also includes a version of the data in standardized IPA, as well as the Chinese glosses given by Liu. </p><p>Liu, Huiqiang. 1985. Musu Qiang Phonology [Qiangyu Musuhua Yinxi]. Qiang Studies 110– 118.</p><p> </p>
Data from: 3D printed digital pneumatic logic for the control of soft robotic actuators
<p>Soft robots are paving their way to catch up with the application range of metal-based machines and to occupy fields which are challenging for traditional machines. Pneumatic actuators play an important role in this development, allowing the construction of bioinspired motion systems. Pneumatic logic gates provide a powerful alternative for controlling pressure-activated soft robots, which are often controlled by metallic valves and electric circuits. Many existing approaches for fully compliant pneumatic control logic suffer from high manual effort and low pressure tolerance. In our work, we invented 3D printable, pneumatic logic gates that perform Boolean operations and imitate electric circuits. Within 7 hours, an FDM printer is able to produce a module that serves as either an OR, AND or NOT gate; the logic function is defined by the assigned input signals. The gate contains two alternately acting pneumatic valves, whose work principle is based on the interaction of pressurized chambers and a 3D printed 1 mm tube inside. The gate design does not require any kind of support material for its hollow parts, which makes the modules ready to use directly after printing. Depending on the chosen material, the modules can operate on a pressure supply between 80 and over 750 kPa. The capabilities of the invented gates were verified by implementing an electronics-free drink dispenser based on a pneumatic ring oscillator and a 1-bit memory. Their high compliance is demonstrated by driving a car over a fully flexible, 3D printed robotic walker controlled by an integrated circuit.</p>
Data and code from: SIDERITE: Unveiling Hidden Siderophore Diversity in the Chemical Space Through Digital Exploration
<h1>TMAP of COCONUT database</h1> <p>The script and data used in SIDERITE paper to generate TMAP picture (Figure S3 in supplementart material).</p> <p>Requirement: tmap</p> <p>You can install tmap by conda.</p> <blockquote> <p>conda create -n tmap python=3.7</p> <p>conda activate tmap</p> <p>conda install -c tmap tmap</p> <p>pip install faerun</p> <p>pip install matplotlib</p> <p>conda install scipy</p> <p>conda install -c rdkit rdkit</p> <p>conda install -c conda-forge mhfp</p> </blockquote> <p> </p> <p>Usage: python plot_COCONUT.py</p> <p>Then it will use COCONUT.csv to generate index.html and index.js. Open index.html to see result.</p> <h1>Other large input files</h1> <p>Tanimoto_COCONUT_SIDERITE.xlsx is the input file in <a href="https://github.com/RuolinHe/SIDERITE/blob/main/predicted_new/Clustering_coconut.m">SIDERITE/predicted_new/Clustering_coconut.m at main · RuolinHe/SIDERITE</a>.</p> <p> </p> <p>Sid_structure_output3.xlsx is used in <a href="https://github.com/RuolinHe/SIDERITE/blob/main/statistics/Figure1.m" target="_blank" rel="noopener">SIDERITE/statistics/Figure1.m at main · RuolinHe/SIDERITE</a>, <a href="https://github.com/RuolinHe/SIDERITE/blob/main/TAMP/tmap_code.m" target="_blank" rel="noopener">SIDERITE/TAMP/tmap_code.m at main · RuolinHe/SIDERITE</a> and <a href="https://github.com/RuolinHe/SIDERITE/blob/main/siderophore_process/Sid_process_code.m" target="_blank" rel="noopener">SIDERITE/siderophore_process/Sid_process_code.m at main · RuolinHe/SIDERITE</a>.</p> <p> </p> <p>COCONUT4MetFrag_Canonical.xlsx is the input file in <a href="https://github.com/RuolinHe/SIDERITE/blob/main/TAMP/tmap_code.m" target="_blank" rel="noopener">SIDERITE/TAMP/tmap_code.m at main · RuolinHe/SIDERITE</a>.</p> <p> </p> <p>COCONUT_r.txt is the output file in <a href="https://github.com/RuolinHe/SIDERITE/blob/main/TAMP/tmap_code.m" target="_blank" rel="noopener">SIDERITE/TAMP/tmap_code.m at main · RuolinHe/SIDERITE</a>. and the input file in <a href="https://github.com/RuolinHe/SIDERITE/blob/main/predicted_new/isSiderophore1.py" target="_blank" rel="noopener">SIDERITE/predicted_new/isSiderophore1.py at main · RuolinHe/SIDERITE.</a></p> <p> </p> <p>COCONUT4MetFrag.xlsx is the input file in <a href="https://github.com/RuolinHe/SIDERITE/blob/main/TAMP/CheckSMILES2.py" target="_blank" rel="noopener">SIDERITE/TAMP/CheckSMILES2.py at main · RuolinHe/SIDERITE</a>.</p> <p> </p>
PSM-AP Comparative document analysis data: Priorities and challenges in the policy and digital strategies of ten PSM
<p>The document consists of a list of 61 key policy and strategy documents analysed as part of the comparative work conducted in WP1 of the project Public Service Media in the Age of Platforms (PSM-AP). It also contains a series of selected quotes supporting the three key areas prioritised by the policies and PSM digital strategies: People (reaching audiences), Personalisation (developing the video-on-demand portal), and Prominence (of PSM services and content). The data was collected and analysed in 2023, from documents concerning 10 PSM organisations in seven media markets: Belgium-Flanders (VRT), Belgium-Wallonia Brussels (RTBF), Canada (CBC/Radio-Canada), Denmark (DR, TV 2) Italy (RAI), Poland (TVP), and the UK (BBC, Channel 4, ITV). All quotes were translated to English by the authors.</p>
Annotation dataset for the article titled "On the Emerging Supremacy of Structured Digital Data in Archaeology: A Preliminary Assessment of Information, Knowledge and Wisdom Left Behind"
<p>This is the resulting dataset from the text annotation exercise in the article titled "<strong>On the Emerging Supremacy of Structured Digital Data in Archaeology: A Preliminary Assessment of Information, Knowledge and Wisdom Left Behind</strong>" that will appear in the journal Open Archeology in a special issue titled Archaeological Practice on Shifting Grounds (edited by Åsa Berggren and Antonia Davidovic-Walther). The article is accepted for publication and the annotations are final. CIDOC CRM is used for text annotations.</p>
rmidura/emdigit: Early Modern Digital Itineraries: Itinerating Europe Article Appendix & Data
<p>This project combines history of the book with digital approaches to explore how a database of sixteenth- through eighteenth-century itineraries may reshape our understanding of historical travel and communication. Printed itinerary books provided early modern travelers with lists of cities along routes. Digital spatial approaches often rely upon modern mapmaking and its built-in assumptions of up-to-date accuracy, decentered viewpoint, stable place identifiers, and direct distances. The data provided has been hand-entered from over 80 multilingual, international itineraries published from the sixteenth through eighteenth centuries and formatted for relative ease of use with network and spatial analysis tools.</p> <p>The data provided here represents the stage of work at the time of publication of Rachel Midura, Itinerating Europe: Early Modern Spatial Networks in Printed Itineraries, 1545–1700, Journal of Social History, Volume 54, Issue 4, Summer 2021, Pages 1023–1063, <a href="https://doi.org/10.1093/jsh/shab011">https://doi.org/10.1093/jsh/shab011</a>. Drawing from the physical and digitized collections of European state libraries, the database includes more than three-quarters of identified itinerary authors (twenty-five of thirty-two) and nearly a third of identified surviving editions (84 of 299, see Appendix). The resulting database consists of 3,655 unique routes, connecting 1,587 cities, published and re-published over the course of two centuries.</p> <p>All titles featured in the appendix bibliography follow the format of a header ("Rome to Milan") followed by a list of intermediary cities. Narrative guidebooks are only included if they feature such route tables as a significant component.</p> <p>I distinguish between a "route," meaning an abstracted connection between an origin, a destination, and possible intermediaries ("Rome to Paris via Milan,") and an "edge," meaning a one-to-one relationship between locations ("Rome to Paris," "Rome to Milan," and "Milan to Paris."). Routes and edges both preserve the original directionality, distinguishing between "Rome to Paris," and "Paris to Rome," for example.</p> <p>This dataset consists solely of the route headers found across the included itineraries and not the intermediary stops within at the present time. Further detail can be found in the included data schema.</p>
Supplementary GIS data - Potential and implications of automated pre-processing of LiDAR-based digital elevation models for large-scale archaeological landscape analysis
<p>A supplementary dataset related to the paper discussing preparation of a digital elevation model derived from DMR 5G (LiDAR-based DEM of the Czech Republic) cleaned of modern artificial features. It includes data used as a clipping mask and data produced during the testing phase.</p> <p>Contents:</p> <ul> <li>..\clipping_buffers.gdb\ - Clipping buffers based on ZABAGED dataset used for masking the original data stored as ESRI geodatabase.</li> <li>..\drainages\ - Drainages with Strahler order higher than four (potential watercourses) for the original and filtered DEMs. <ul> <li>drainages_filtered - Drainges identified in the filtered DEM stored as GeoTIFF.</li> <li>drainages_original - Drainges identified in the original DEM stored as GeoTIFF. </li> </ul> </li> <li>..\LSC\ - Locations with significant land surface curvature for the original and filtered DEMs. <ul> <li>LSC_filtered - Significant LSC identified in the filtered DEM stored as GeoTIFF. </li> <li>LSC_original - Significant LSC identified in the original DEM stored as GeoTIFF. </li> </ul> </li> <li>..\visibility\ - Viewsheds computed over the original and filtered DEMs. <ul> <li>Libice\ - Sample viewsheds computed for the early medieval hillfort of Libice. <ul> <li>Libice_visibility_filtered - Viewshed based on the filtered DEM stored as GeoTIFF. </li> <li>Libice_visibility_original - Viewshed based on the original DEM stored as GeoTIFF. </li> <li>observer_points - Observer points used for calculating the viewsheds.</li> </ul> </li> <li>regular_grid\ - Cumulative viewsheds calculated for regularly spaced points in a 10 x 10 km grid with a visibility radius of 5 km and an observer height of 2 m; a total of 574 viewsheds. <ul> <li>visibility_filtered - Cumulative viewshed for the filtered DEM stored as GeoTIFF.</li> <li>visibility_original - Cumulative viewshed for the original DEM stored as GeoTIFF. </li> <li>visibility_test_buffers - Buffers used for the viewshed calculations stored as ESRI shapefile.</li> <li>visibility_test_observers - Observer points used for the viewshed calculations stored as ESRI shapefile.</li> </ul> </li> </ul> </li> </ul> <p> </p> <p>Preprint version of the related paper:</p> <p>Novák, David and Pružinec, Filip, Potential and Implications of Automated Pre-Processing of Lidar-Based Digital Elevation Models for Large-Scale Archaeological Landscape Analysis. Available at SSRN: <a href="https://ssrn.com/abstract=4063514">https://ssrn.com/abstract=4063514</a></p>
Full dataset of several mechanical tests on an S355 steel sheet as reference data for digital representations
<p>The dataset provided in this repository comprises data obtained from a series of characterization tests performed to a sheet of typical S355 (material number: 1.0577) structural steel (designation of steel according to DIN EN 10025-2:2019). The tests include methods for the determination of mechanical properties such as, e.g., tensile test, Charpy test and sonic resonance test. This dataset is intended to be extended by the inclusion of data obtained from further test methods. Therefore, the entire dataset (concept DOI) comprises several parts (versions), each of which is addressed by a unique version DOI.</p> <p>The data were generated in the frame of the digitization project Innovationplatform Material<em>Digital </em>(PMD) which, amongst other activities, aims to store data in a semantically and machine understandable way. Therefore, data structuring and data formats are focused in addition to aspects in the field of material science and engineering (MSE). Hence, this data is supposed to provide reference data as basis for experimental data inclusion, conversion and structuring (data management and processing) that leads to semantical expressivity as well as for MSE experts being generally interested in the material properties and knowledge.</p>
Supplementary data for Plutniak, S. 2022. "What makes the identity of a scientific method? A history of the 'Structural and analytical typology' in the growth of evolutionary and digital archaeology in southwestern Europe (1950s–2000s)", Journal of Paleolithic Archaeology, vol. 5, 10.
<p>Supplementary data for Plutniak, S. 2022. “What makes the Identity of a Scientific Method? A History of the ‘Structural and analytical typology’ in the Growth of Evolutionary and Digital Archaeology in Southwestern Europe (1950s–2000s)”, <em>Journal of Paleolithic Archaeology</em>. vol 5, 10. DOI: <a href="https://doi.org/10.1007/s41982-022-00119-7">10.1007/s41982-022-00119-7</a>.</p> <p> </p> <p> </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.