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482 results for “Digital data”
Freischütz Digital: data-music, The Academy 2017 Release
<p>This is a copy of the <a href="https://github.com/Freischuetz-Digital/data-music" target="_blank" rel="noopener">Freischütz Digital/data-music</a> repository, which is meant for long-term preservation. A description of the dataset can be found in the <em>readme.md</em> file. </p>
Data on the Digital Index (DiGiX), the E-Government Development Index (EGDI), and the Global Talent Competitiveness Index (GTCI)
<p>This dataset contains the measurement of the Digital Index (DiGiX), the E-Government Development Index (EGDI), and the Global Talent Competitiveness Index (GTCI) in 2022.</p> <p> </p> <p>References:</p> <p>The Global Talent Competitiveness Index 2023 report: https://www.insead.edu/system/files/2023-11/gtci-2023-report.pdf</p> <p>UN E-Government Knowledgebase: https://publicadministration.un.org/egovkb/Data-Center</p> <p>Camara, N., (2022), DiGiX 2022 Update: A Multidimensional Index of Digitization, https://www.bbvaresearch.com/wp-content/uploads/2022/06/DiGiX_2022_Update_A_Multidimensional_Index_of_Digitization.pdf</p>
Linked collectors and determiners for: Flora Sumatra: Digitizing and data basing specimens of the Sumatran Flora deposited at Herbarium Universitas Andalas (ANDA)-Part 2.
Natural history specimen data linked to collectors and determiners held within, "Flora Sumatra: Digitizing and data basing specimens of the Sumatran Flora deposited at Herbarium Universitas Andalas (ANDA)-Part 2". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/39e85504-1ebe-4671-be65-19ccdc1d7c7d">https://bionomia.net/dataset/39e85504-1ebe-4671-be65-19ccdc1d7c7d</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/39e85504-1ebe-4671-be65-19ccdc1d7c7d">https://gbif.org/dataset/39e85504-1ebe-4671-be65-19ccdc1d7c7d</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Digitization PEN: Digital Data from the Terrestrial Polyneoptera at American Museum of Natural History.
Natural history specimen data linked to collectors and determiners held within, "Digitization PEN: Digital Data from the Terrestrial Polyneoptera at American Museum of Natural History". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/d475b3b1-1e5a-4d56-a547-f7afb810c4c5">https://bionomia.net/dataset/d475b3b1-1e5a-4d56-a547-f7afb810c4c5</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/d475b3b1-1e5a-4d56-a547-f7afb810c4c5">https://gbif.org/dataset/d475b3b1-1e5a-4d56-a547-f7afb810c4c5</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Data from CRSN herbarium digitization initiative under BID-funded project.
Natural history specimen data linked to collectors and determiners held within, "Data from CRSN herbarium digitization initiative under BID-funded project". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/bcffbc19-b28c-42ae-995a-ff852e158ce5">https://bionomia.net/dataset/bcffbc19-b28c-42ae-995a-ff852e158ce5</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/bcffbc19-b28c-42ae-995a-ff852e158ce5">https://gbif.org/dataset/bcffbc19-b28c-42ae-995a-ff852e158ce5</a>. Formatted as a Frictionless Data package.
Digital Collections Data and Tracking Disease Workshop 2: Introduction and Museum Perspectives Talks
<p>Recordings of talks by speakers in the Museum Perspectives section of our Digital Collections Data and Tracking Disease Workshop 2 at the American Society of Mammalogists Meeting in Boulder, Colorado in June of 2024.</p> <ul> <li><strong>Topic -- A Museum Perspective</strong> <ul> <li><strong>Museums and Emerging Pathogens in the Americas</strong>, Joe Cook, University of New Mexico<strong><br></strong></li> <li><strong>Museums and pathogens: Challenges, potential, and management</strong>, <a href="https://orcid.org/0000-0002-6931-6420" target="_blank" rel="noopener">Adam Ferguson</a>, Field Museum of Natural History</li> <li><strong>The UX Side of Extended Specimen Databases</strong>, <a href="https://orcid.org/0000-0002-8775-7254" target="_blank" rel="noopener">Kelly Speer</a></li> <li><strong>Preventing the next viral pandemic via elucidation of mammalian reservoirs</strong>, Rick White, University of North Carolina-Charlotte</li> <li><strong>Scientific collections and public health surveillance: institutional weaknesses and perspectives from Uruguay,</strong> <a href="https://orcid.org/0000-0002-4055-9277" target="_blank" rel="noopener">Germán Botto Nuñez</a>, Universidad de la República <ul> <li>(note talk sound did not work for this presentation)</li> </ul> </li> <li><strong>Building integrated archives for parasite and pathogen discovery</strong><br><a href="https://orcid.org/0000-0002-8065-0833" target="_blank" rel="noopener">Kurt Galbreath</a>, Northern Michigan University</li> <li><strong>The Dark Side of the Light: Fireflies, Snails, and Viromes</strong>, <a href="https://orcid.org/0000-0001-5067-3316" target="_blank" rel="noopener">Oliver Keller</a>, University of Michigan</li> </ul> </li> </ul>
Digital Twins: A Systematic Literature Review Based on Data Analysis and Topic Modeling
<p>The digital twin has recently become a popular topic in research related to manufacturing, such as Industry 4.0, the industrial internet of things, and cyber-physical systems. In addition, digital twins are the focus of several research areas: construction, urban management, digital transformation of the economy, medicine, virtual reality, software testing, and others. The concept is not yet fully defined, its scope seems unlimited, and the topic is relatively new; all this can present a barrier to research. The main goal of this paper is to develop a proper methodology for visualizing the digital-twin science landscape using modern bibliometric tools, text-mining and topic-modelling, based on machine learning models—Latent Dirichlet Allocation (LDA) and BERTopic (Bidirectional Encoder Representations from Transformers). The scope of the study includes 8693 publications on the topic selected from the Scopus database, published between January 1993 and September 2022. Keyword co-occurrence analysis and topic-modelling indicate that studies on digital twins are still in the early stage of development. At the same time, the core of the topic is growing, and some topic clusters are emerging. More than 100 topics can be identified; the most popular and fastest-growing topic is ‘digital twins of industrial robots, production lines and objects.’ Further efforts are needed to verify the proposed methodology, which can be achieved by analyzing other research fields.</p>
Poses of People in Art: A Data Set for Human Pose Estimation in Digital Art History
<p>Throughout the history of art, the pose—as the holistic abstraction of the human body's expression—has proven to be a constant in numerous studies. However, due to the enormous amount of data that so far had to be processed by hand, its crucial role to the formulaic recapitulation of art-historical motifs since antiquity could only be highlighted selectively. This is true even for the now automated estimation of human poses, as domain-specific, sufficiently large data sets required for training computational models are either not publicly available or not indexed at a fine enough granularity. With the <em>Poses of People in Art</em> data set, we introduce the first openly licensed data set for estimating human poses in art and validating human pose estimators. It consists of 2,454 images from 22 art-historical depiction styles, including those that have increasingly turned away from lifelike representations of the body since the 19<sup>th</sup> century. A total of 10,749 human figures are precisely enclosed by rectangular bounding boxes, with a maximum of four per image labeled by up to 17 keypoints; among these are mainly joints such as elbows and knees. For machine learning purposes, the data set is divided into three subsets—training, validation, and testing—, that follow the established JSON-based Microsoft COCO format, respectively. Each image annotation, in addition to mandatory fields, provides metadata from the art-historical online encyclopedia WikiArt.</p>
Data for Demonstration of quantum-digital payments
<p>Timetags that lead to coincidence count events in a 3ns window for Client and TTP.<br> For linear (commitment to M0) and diagonal (M1) basis.</p> <p>Format:<br> <uint8 c>\t<double t></p> <p>c: channel on timetagger<br> t: photon arrival time in ns</p> <p><br> TTP Channels:<br> 2: H<br> 3: V<br> 4: +<br> 5: -</p> <p>Client Channels:<br> 2: H / +<br> 4: V / -</p> <p>--------------<br> The files in folder "tagfile_example" are intended as input to the analysis scripts provided under DOI 10.5281/zenodo.7997961</p> <p> </p>
Surface Survey and Legacy Data in the Upper Plain of the Heraion of Perachora: The Perachora Peninsula Archaeological Project 2020 [Digital Supplement with updated polygons from 2020]
<p><strong>The digital Supplement </strong>contains figures in original size (TIFF) & digital data (SHP, CSV). The data can be also found in the linked GitHub repository <a href="https://github.com/sdam-au/perachora-medit-arch/">https://github.com/sdam-au/perachora-medit-arch/</a>.</p> <p> </p> <p><strong>Abstract</strong></p> <p>The Perachora Peninsula Archaeological Project held its first season of intensive surface survey from 12 January to 2 February 2020, during which time we focused on the region called the Upper Plain, situated above the sanctuary of Hera, which was in use from the 8th to the 2nd century BC. The nature of this area has been disputed, with Humfry Payne seeing it as a substantial town, while Richard Tomlinson referred to it as “a sporadic scatter of structures.” In order to clarify the nature of the settlement we employed a two-pronged effort: first to verify and document the legacy data in Tomlinson’s plan of the area, and second to conduct intensive surface survey from the boundary of the sanctuary to Lake Vouliagmeni. Within three weeks, our teams measured, photographed, and took the coordinates of nearly all the structures on Tomlinson’s plan, which included domestic structures, a small temple, and an extensive waterworks system, and several that had not been previously recorded. Building A 1 and the Fountain House were cleared and recorded using photogrammetry. The survey’s finds informed our legacy data verification efforts. Densities across all land types were high: nearly 23,000 artefacts were counted, and all but nine survey units produced artefacts. A preliminary analysis of the ceramics indicates a consistent habitation from the Archaic through the Classical period. Concentrations of miniature votives and fine wares were also found on hillsides, possibly indicating open-air shrines. Our work also highlights the need to conserve the structures in the Upper Plain.</p>
Digitized geological and geophysical data from the Po Plain and the northern Adriatic Sea (north Italy) collected from public sources.
<p>The database is a supplementary material of:</p><p>Livani, M., Petracchini, L., Benetatos, C., Marzano, F., Billi, A., Carminati, E., Doglioni, C., Petricca, P., Maffucci, R., Codegone, G., Rocca, V., Antoncecchi, I. (2023). Subsurface geological and geophysical data from the Po Plain and the northern Adriatic Sea (north Italy). Earth System Science Data Discussions, 15, n. 9, 4261-4293, doi: 10.5194/essd-15-4261-2023</p><p> </p><p>This database comprises subsurface geological and geophysical data from the Po Plain and the northern Adriatic Sea (north Italy). We realized the database by collecting, revising, and digitizing data, originally in raster format, from public sources. These data have been then used to reconstruct the overall subsurface 3D architecture and to extract the physical properties of the subsurface geological units.</p><p>The data have a common geographical system: WGS 84/UTM zone 32N; EPSG: 32632.</p><p>The database contains borehole information from 160 deep wells (i.e., wellhead coordinates, rotary table elevation, measured depth, true depth, total depth and deviation survey) and digitized Spontaneous Potential, Gamma Ray, and Sonic logs. Five horizons were digitized from 61 geological cross-sections and from 10 isobath maps that roughly correspond to the boundaries of units showing different lithological properties and with different mechanical properties. The horizons are, from the oldest to the youngest: the top of the magnetic basement, the top of the carbonate succession, the base of the Pliocene, the base of the Calabrian and the base of recent continental deposits. In addition, the gridded surfaces of the 3D geological model are available.</p><p>We organized the database into two groups: "primitive data" and "derived data".</p><p>Primitive data are the result of the digitization of public data. The database of the primitive data is formed by the main horizons reported in the geological cross-sections, the isobaths of the main geological surfaces, the well locations, comprised their trajectory along depth, lithological and stratigraphical information, and geophysical logs from composite well logs. Well data include specific sets of well logs aimed to geological/mechanical characterization of the geological units (e.g., Spontaneous Potential log, Resistivity log, Gamma Ray log, and Sonic log).</p><p>Derived data consist of two datasets: i) the primitive isobaths maps and geological cross-sections data that have been filtered and verified after a data accuracy analysis performed to unravel discrepancies in the interpretation of the subsurface geological horizons; ii) a set of regional surfaces of the main geological units of the Po Plain subsurface. These surfaces were generated by interpolating the filtered primitive data and without considering the fault occurrence/displacements.</p><p>Primitive and derived data are provided in delimited text file format organized according to the data type (i.e., well, geological cross-section, map and gridded surface). The format and the organization of data are explained in the related "readme" file presents within each data folder.</p><p>Our database represents a collection of the main published works regarding the Po Plain. Detailed studies related to specific sectors of the Po Plain might not be present in our database.</p><p>Further details about the data processing and organization are given in the related manuscript.</p><p> </p>
Data from: Origins of mammalian vertebral function revealed through digital bending experiments
Open the record for dataset details and reuse information.
Data from: Integrating deep learning derived morphological traits and molecular data for total-evidence phylogenetics: lessons from digitized collections
Open the record for dataset details and reuse information.
Data from: Digital twin mathematical models suggest individualized hemorrhagic shock resuscitation strategies
Open the record for dataset details and reuse information.
Data from: Artificial intelligence enabled multi-purpose smart detection in active-matrix electrowetting-on-dielectric digital microfluidics
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Data from: 3D printed digital pneumatic logic for the control of soft robotic actuators
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Air Temperature for 4 LTTG sites, digitized from thermograph weather charts: Hourly Data; 1968-1989
Data is from weather stations. Pre- 5/89 data is all from thermographs of various makes (Bendix, Belfort, and Casella). Temperatures were digitized on a CalComp drawing board using software developed by Robert E. Schlentner (Forest Soils Lab, U. of Ak.). Program reads automatically at each hour's "distance" on the chart and allows for the specific curvature of the plot due to pen sweep. Post 5/89 data is from Omnidata easy logger data loggers replaced these thermographs in 1989. The data logger data is also available (see eloga.dfd, elogd.dfd and elogs.dfd).
Data for: Mechanisms of root-reinforcement in soils: an experimental methodology using four-dimensional X-ray computed tomography and digital volume correlation
<p>Collection of data files used in the paper titled: Mechanisms of root-reinforcement in soils: an experimental methodology using four-dimensional X-ray computed tomography and digital volume correlation.</p> <p>Additional dataset which covers the noise study CT scans and digital volume correlation noise studies can be found in DOI: <a href="http://www.doi.org/10.5281/zenodo.3352268">10.5281/zenodo.3361832</a></p> <p><strong>Data contains the following:</strong></p> <ul> <li>X-ray CT data for the interrupted direct shear tests of a soil sample containing a Willow plant. The first file is the specimen scanned unloaded, followed by seven incremental shear load steps to 20 mm shear displacement. Files are 8-bit unsigned and 1800x1800x1600px. Voxel resolution is 0.04642 mm. <ol> <li><strong>20180430_HUTCH_1839_DJB_willow_C_8-bit_1800x1800x1600.raw</strong></li> <li><strong>20180430_HUTCH_1839_DJB_willow_C_Load_A_8-bit_1800x1800x1600.raw</strong></li> <li><strong>20180430_HUTCH_1839_DJB_willow_C_Load_B_8-bit_1800x1800x1600.raw</strong></li> <li><strong>20180430_HUTCH_1839_DJB_willow_C_Load_C_8-bit_1800x1800x1600.raw</strong></li> <li><strong>20180430_HUTCH_1839_DJB_willow_C_Load_D_8-bit_1800x1800x1600.raw</strong></li> <li><strong>20180430_HUTCH_1839_DJB_willow_C_Load_E_8-bit_1800x1800x1600.raw</strong></li> <li><strong>20180430_HUTCH_1839_DJB_willow_C_Load_F_8-bit_1800x1800x1600.raw</strong></li> <li><strong>20180430_HUTCH_1839_DJB_willow_C_Load_G_8-bit_1800x1800x1600.raw</strong></li> </ol> </li> <li>Direct shear vs. displacement data is presented in an Excel spreadsheet: <ul> <li><strong>All_load_data_with_reducing_area.xlsx</strong></li> </ul> </li> <li>Normal and shear strain DVC data which has been averaged and plotted against specimen depth is presented in an Excel spreadsheet: <ul> <li><strong>Average_slice_vs_depth_data_all_samples_all_loads3.xlsx</strong></li> </ul> </li> <li>CT scan metadata giving information to the scan settings, voxel resolution, etc. is contained in a .zip file which consists of .xtekct and .XML files generated from the Nikon CT scanner. <ul> <li><strong>CT_Scan_Metadata.zip</strong></li> </ul> </li> <li>Drawings and Solidworks CAD files of the direct shear test rig are contained within the .zip file. There are a number of parts to the assembly. The file SSSB1003-5.SLDASM contains the complete assembly of the direct shear rig and will help identify the part names. The folder CAD_Drawings contains pdf documents of the part drawings. <ul> <li><strong>Direct_Shear_Drawings_Solidworks_Files.zip</strong></li> </ul> </li> <li>Tabulated DVC data taken at 32x32x32px subset size is contained inside a .zip file. These consist of tab separated .dat files from unloaded (data_1.dat) through incremental load steps Load A, Load B... Load G, (data_2.dat, data_3.dat... data_8.dat). The structure of the .dat file contains columns of data with each column number corresponding to the following: (1) x, (2) y (3) z, (4) vx, (5) vy, (6) vz, (7) exx, (8) eyy, (9) ezz, (10) exy, (11) exz, (12) eyz, (13) volumetric strain, (14) is valid. Columns 1-3 are subset positions in mm, 4-6 are displacements in mm, 7-9 are normal strains, 10-12 are shear strains, 13 is volumetric strain and 14 is a binary value indicating if the subset is valid. <ul> <li><strong>DVC_Load_Data_Willow_C.zip</strong></li> </ul> </li> <li>Tabulated DVC data applied to the load step CT data at 32, 48, 64, 96, 128 pixels is presented in the .zip files containing .dat tab separated files. The structure of the .dat files is described in the previous bullet point. These files were used to construct the noise study applied to incrementally loaded CT data by sampling regions away from the shear zone where the strain signals are close to zero. <ul> <li><strong>DVC_Noise_Study_Data_Load_Steps_Willow_C.zip</strong></li> </ul> </li> <li>Processed noise study data which compares the effects of DVC subset size is presented in the .xlsx file. This file contains both the controlled noise experiment data (stationary, magnification and rigid body motion) and noise study data applied to incrementally loaded data using sampled regions away from the shear zone where the strain signals are close to zero. <ul> <li><strong>Willow_C_Processed_Noise_study2.xlsx</strong></li> </ul> </li> <li>Tabulated data which compares the local x displacement vs depth profile from DVC and direct measurement of root position is contained in the following Excel spreadsheet file: <ul> <li><strong>X_Displacement_Root_and_DVC_Comparison_Willow C.xlsx</strong></li> </ul> </li> </ul>
SPECTRAL PROPERTIES OF QUASARS FROM SLOAN DIGITAL SKY SURVEY DATA RELEASE 14: THE CATALOG
<p>We present measurements of the spectral properties for a total of 526,265 quasars, out of which 63% have continuum S/N> 3 pixel<sup>−1</sup>, selected from the fourteenth data release of the Sloan Digital Sky Survey (SDSS-DR14) quasar catalog. We performed a careful and homogeneous analysis of the SDSS spectra of these sources, to estimate the continuum and line properties of several emission lines such as Hα, Hβ, Hγ, Mg ii, C iii], C iv and Lyα. From the derived emission line parameters, we estimated single-epoch virial black hole masses (M<sub>BH</sub>) for the sample using Hβ, Mg ii, and C iv emission lines. The sample covers a wide range in bolometric luminosity (log L<sub>bol;</sub> erg s<sup>−1</sup> ) between 44.4 and 47.3 and log M<sub>BH</sub> between 7.1 and 9.9 M. Using the ratio of L<sub>bol</sub> to the Eddington luminosity as a measure of the accretion rate, the logarithm of the accretion rate is found to be in the range between −2.06 and 0.43. We performed several correlation analyses between different emission line parameters and found them to match with that known earlier using smaller samples. We noticed that strong Fe ii sources with large Balmer line width, and highly accreting sources with large M<sub>BH</sub> are rare in our sample. We make available an extended and complete catalog that contains various spectral properties of 526,265 quasars derived in this work along with other properties culled from the SDSS-DR14 quasar catalog.</p> <p> </p> <p><strong>Here, you will find the entire spectral catalog in the FITS forma</strong>t.</p> <ul> <li>The main catalog (“ <strong>dr14q_spec_prop.fits</strong>”) is based on the spectral information from this study consisting of 274 columns, which are described in Table B4.</li> <li>An extended catalog (“ <strong>dr14q_spec_prop_ext.fits</strong>”) where all the columns of DR14Q (Paris et al. 2018) are appended after the main catalog (ie, after column # 274). The extended catalog has a total of 380 columns.</li> </ul> <p><strong>We also make available all the model components (in FITS format) for each quasar and the spectral decomposition plots (PDF format):</strong> <strong><a href="https://seafile.utu.fi/d/9866433c200743119e92/">HERE</a></strong></p> <ul> <li><em>Each model FITS file has the following 8 columns:</em></li> </ul> <blockquote> <ol> <li>wave : rest-frame wavelength</li> <li>flux : rest-frame spectral flux</li> <li>err : rest-frame spectral flux uncertainty</li> <li>model_host : decomposed host-Galaxy flux</li> <li>model_pl_bc : a sum of the model power law and Balmer continuum</li> <li>model_feii : a sum of the Fe II UV and Fe II optical</li> <li>model_line_bc : total broad line model</li> <li>model_line_nc : total narrow line model</li> </ol> </blockquote> <ul> <li><strong>A dedicated website has been created for Supplementary material:</strong> <strong><a href="http://www.utu.fi/sdssdr14">WEBSITE</a></strong></li> </ul>
La Digital Libray open data della Biblioteca del Comune di Mottola - Progetto "Terra delle Gravine"
<p><em>Terra delle Gravine tra sharing economy e turismo esperienziale</em><a href="#_ftn1">[1]</a> è un progetto finanziato dalla Regione Puglia a un consorzio di dodici comuni della provincia di Taranto, finalizzato alla formazione di studenti di scuola secondaria superiore nella descrizione di risorse digitali relative al patrimonio culturale in formato open data e alla creazione di una piattaforma, sempre in formato Open Data, di contenuti relativi ai beni culturali dei comuni coinvolti.</p> <p>Le attività sono state progettate e realizzate tra il 2017 e il 2018 dal Dipartimento di Studi Umanistici – DISUM dell’Università degli Studi di Bari e dalla spin off DABIMUS S.r.l. in collaborazione con l’Open Data Manager Pierfrancesco Paolicelli.</p> <p>I percorsi formativi e i tracciati in Open Data da utilizzare per indicizzare i beni considerati sono stati progettati in relazione alle diverse classi di beni culturali oggetto di interesse, che hanno incluso beni monumentali, beni storico artistici e demo-etnoantropologici e beni librari.</p> <p>Il DISUM, nella persona del prof. Nicola Barbuti, ha curato sia la progettazione e realizzazione del tracciato in open data utilizzato per indicizzare e pubblicare on line una selezione di volumi a stampa delle biblioteche comunali di Massafra, Mottola e Grottaglie, sia la formazione degli studenti delle scuole secondarie superiori dei tre comuni alla descrizione catalografica di risorse digitali librarie.</p> <p>I dataset sono stati strutturati conformemente alle regole definite dalla Regione Puglia nel suo catalogo <a href="http://www.dataset.puglia.it/">http://www.dataset.puglia.it/</a>, conformi all’ontologia dei luoghi della cultura e degli eventi culturali <em>Cultural ON</em> realizzata dal MiBACT nell’ambito del progetto nazionale <a href="http://dati.beniculturali.it">http://dati.beniculturali.it</a>, la piattaforma in cui il Ministero si propone di pubblicare il patrimonio culturale informativo secondo la logica dei Linked Open Data.</p> <p>Gli studenti degli istituti scolastici superiori dei tre comuni, impegnati in percorsi di Alternanza Scuola Lavoro, hanno prima seguito la formazione, quindi hanno indicizzato una selezione di volumi delle biblioteche comunali di riferimento utilizzando il tracciato in formato open data realizzato per il progetto<a href="#_ftn2">[2]</a>.</p> <p>Per facilitare la descrizione collaborativa e per la condivisione dei file con i tracciati è stata utilizzata la suite di Google Drive, di semplice utilizzo.</p> <p>Il monitoraggio degli stati di avanzamento di progetto e l’interazione con i team di studenti è stato realizzato attivando anche specifici gruppi tramite l’app Telegram, veloce, sicura, semplice e open.</p> <p>Le attività si sono svolte secondo le seguenti fasi:</p> <ul> <li>affiancamento degli studenti e formazione sui processi di indicizzazione secondo il formato di dati open CKAN;</li> <li>formazione sugli standard di descrizione digitale e indicizzazione di risorse librarie e sulla co-creazione assistita di dataset in open data;</li> <li>insegnamento sul riuso dei dati aperti per creare mappe, percorsi, infografiche, statistiche.</li> </ul> <p>Le tre digital library sono pubblicate sul sito dell’AgID <a href="http://dati.gov.it">http://dati.gov.it</a><a href="#_ftn3">[3]</a></p> <p> </p> <p><a href="#_ftnref1">[1]</a> https://terradellegravineprogettazioneperlacultura.wordpress.com/il-progetto/</p> <p><a href="#_ftnref2">[2]</a> http://www.terradellegravine.eu:3389/dataset</p> <p><a href="#_ftnref3">[3]</a> Massafra: <a href="https://dati.gov.it/dataset?id=69a7c931-b910-4acd-9f8f-47d0bd4f9dfb">https://dati.gov.it/dataset?id=69a7c931-b910-4acd-9f8f-47d0bd4f9dfb</a></p> <p>Grottaglie: <a href="https://dati.gov.it/dataset?id=644e8203-18f0-40a5-a46a-bd78cb2bd999">https://dati.gov.it/dataset?id=644e8203-18f0-40a5-a46a-bd78cb2bd999</a></p> <p>Mottola: <a href="https://dati.gov.it/dataset?id=5a99673e-2123-462e-a868-85b03c46c7fd">https://dati.gov.it/dataset?id=5a99673e-2123-462e-a868-85b03c46c7fd</a></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.