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3,101 results for “Historical”
Fig. 3. – Herbarium sheet with a in Caspar Bauhin's contribution to a historical herbarium stored in Bologna
Fig. 3. – Herbarium sheet with a specimen of Daphne mezereum L. (upper left) and the inscription: "Daphenoides Matth. / Camalea sive Melarada Tragi / Camelea germanica Dodonei / Mezereum germanicum Lobelli / Laurus pusilla eodem in iconibus".
Fig. 1. – Herbarium sheet with a in Caspar Bauhin's contribution to a historical herbarium stored in Bologna
Fig. 1. – Herbarium sheet with a specimen of Cerinthe major L. (in the middle) and the inscription: "Plumbago et Molibdena plini / Lepidium Antonius Petrisentis / Herba Santi Antoni / Romae Dentelaria / Rondoletii herba ad Dificultatem".
Dataset of historical prediction of ash dispersal of the Sakurajima Taisho eruption
<p>This dataset contains all outputs of the VATDM simulation of the Sakurajima Taisho eruption using the PUFF model with GSM-GPV as the wind fields from July 2018 to December 2022. The details of the simulation process and the model inputs follow Rahadianto et al. (2022). Each file describes the location (latitude and longitude) of the deposit with its depth in cm for each prediction lead time in descending order (24, 18, 12, 6, 0 hours ahead). Only CSV format is available, and each file named based on the date of the simulation, grouped within a yearly folder. Please extract the zip file to access each file.</p>
Data for: Phylogenomics and historical biogeography of Hydrangeeae (Hydrangeaceae) elucidate the effects of geologic and climatic dynamics on diversification
<p>Demonstrating the process of transregional biogeography and mechanisms underlying evolutionary radiations is crucial to understanding biological evolution. Here, we use Hydrangeeae (Hydrangeaceae), a tribe with a unique disjunct distribution and complex trait variations, using a solid phylogenetic framework, to investigate how geographical and climatic factors interact with functional traits to trigger plant evolutionary radiations. We constructed the first highly supported and dated phylogenetic framework using 79 protein-coding genes obtained from 81 plastomes, representing 63 species and all major clades, and found that most extant species originated from asynchronous diversification of two lineages undergoing repeated expansion and retraction, at middle and high latitudes of the Northern Hemisphere between East Asia and North America, during the Eocene to Pleistocene (driven by geologic and climatic dynamics). In accordance with these drivers, interactions of flora between central-eastern China and Japan occurred frequently after the Late Tertiary. We found that resource limitation and range fragmentation likely accelerated the diversification of Hydrangeeae, which supports the resource-use hypothesis. Our study sheds light on the evolutionary radiation and assembly of flora within East Asia, and the East Asian-North American disjunction, through integration of phylogenomic and biogeographic data with functional trait and ecological data.</p>
Historical Aerial Photografies of the Rio Grande do Sul
<p>This data paper discusses a collection of aerial photographs, which are scientific images obtained through cameras fixed on balloons, planes, drones, and other manned or crewless aerial vehicles. Initially, they were used to conducting studies on exploring space and landscape and territorial analysis. The images are a physical collection from a university in southern Brazil. The objective is to justify aerial photographs as research data in Geosciences.The study methodology is based on aerial photographs collected between 1960 and 2000. For 40 years, they were taken in road projects by the Autonomous Department of Highways (DAER RS), which had a Sector of Topography and Aerophotogrammetry. With its plane, the sector carried out around 240 aerial surveys between 1969 and 2001 (flight scales between 1: 2,000 to 1: 20,000), where around 60,000 photographs were generated and printed based on 170 rolls of film. The sample of pictures from this data paper is part of the raw data of the thesis entitled "Morphodynamic complexity and anthropogenic diachronic in the northern coastal plain of Rio Grande do Sul." (Rocha, 2023), which is in progress. The work consists of identifying and characterizing geological indicators of environmental changes since the 1940s in a stretch of the north coast of Rio Grande do Sul, Brazil. RMK-ZeISS was then scanned with an A3 scanner with a resolution of 1200 Dpi. The methods and conditions used to collect data from aerial photographs are the same as listed; flight conditions, camera quality, flight height, and the scale of the photo are directly related to the generation of aerial photography. When an aerial photograph is printed analog, it does not have information on geographic coordinates, geometric attributes, time, and spatial or topological relationships; they are not georeferenced. Thus, even after digitization, the image needs to be cataloged and transformed into a georeferenced image format, the so-called geodata, such as GeoTiff, for later availability in geographic databases and used by geographic information systems. The plane's camera parameters are essential information for this type of survey data. For example, what was the plane? What is the flight speed and height? Visibility, flight date, time, and flight time? What is the region, flight ranges, and specific purpose of aerial mapping? What type of camera, lens focus, type of film used, film thickness, and filters? Finally, what is the developer equipment, and the development date?</p> <p> </p>
Use of historical isoscapes to develop an estuarine nutrient baseline
<p class="MsoNormal"><span>Coastal eutrophication is a prevalent threat to the healthy functioning of ecosystems globally. While degraded water quality can be detected by monitoring oxygen, nutrient concentrations, and algal abundance, establishing regulatory guidelines is complicated by a lack of baseline data (e.g., pre-Anthropocene). We use historical carbon and nitrogen isoscapes from sediment cores to reconstruct spatial and temporal changes in nutrient dynamics for a central California estuary, where development and agriculture dramatically enhanced nutrient inputs over the past century. We found strong contrasts between current sediment stable isotopes and those from the recent past, demonstrating </span>shifts exceeding those in previously studied eutrophic estuaries and <span>substantial increases in nutrient inputs. Comparisons of contemporary with historical isoscapes also revealed that nitrogen sources shifted from a marine-terrestrial gradient to amplified denitrification at the head and mouth of the estuary. Geospatial analysis of historical data suggests that an increase in fertilizer application – rather than population growth or increases in the extent of cultivated land – is chiefly responsible for increasing nutrient loads during the 20<sup>th</sup> century. This study demonstrates the ability of isotopic and stoichiometric maps to provide important perspectives on long-term shifts and spatial patterns of nutrients that can be used to improve management of nutrient pollution.</span></p>
WILD RICE HISTORICAL ARCHIVES
<p>This is a collection of photos from searches at the Minnesota Historical Society, online newspaper databases and private collections. There is a TROPY database file. The original titles of the photos have not been changed so that the TROPY program can recognize them and the database file can be used. Search terms included 'wild rice' and 'manoomin'. </p> <p> </p> <p> </p>
Dataset and R script used in "Local knowledge reconstructs historical resource use" published in Frontiers in Ecology and the Environment
<p>Data and R code used in: L. Castello, E.G. Martins, M. Sorice, E. Smith, M. Almeida, G.C.C. Bastos, L.G. Cardoso, M. Clauzet, A.P. Dopona, B. Ferreira, M. Haimovici, M. Jorge, J. Mendonça, A.O. Ávila-da-Silva, A.P.O. Roman, M. Ramires, L.M. Villwock, P.F.M. Lopes. (Year) Local knowledge reconstructs historical resource use. Frontiers in Ecology and the Environment.</p>
Dataset and Models for Detection of News Agency Releases in Historical Newspapers
<p>This record contains the annotated datasets and models used and produced for the work reported in the Master Thesis "<em>Where Did the News come from? Detection of News Agency Releases in Historical Newspapers</em> " (<a href="https://infoscience.epfl.ch/record/305129?&ln=en">link</a>).</p> <p>Please cite this report if you are using the models/datasets or find it relevant to your research:</p> <pre><code>@article{Marxen:305129, title = {Where Did the News Come From? Detection of News Agency Releases in Historical Newspapers}, author = {Marxen, Lea}, pages = {114p}, year = {2023}, url = {http://infoscience.epfl.ch/record/305129}, }</code></pre> <p><br> <strong>1. DATA</strong></p> <p>The <strong>newsagency-dataset</strong> contains historical newspaper articles with annotations of news agency mentions. The articles are divided into French (fr) and German (de) subsets and a train, dev and test set respectively. The data is annotated at token-level in the CoNLL format with IOB tagging format.</p> <p>The distribution of articles in the different sets is as follows:</p> <table> <caption>Dataset Statistics</caption> <thead> <tr> <th scope="row"> </th> <th scope="col">Lg.</th> <th scope="col">Docs</th> <th scope="col">Agency Mentions</th> </tr> </thead> <tbody> <tr> <th scope="row">Train</th> <td>de</td> <td>333</td> <td>493</td> </tr> <tr> <th scope="row"> </th> <td>fr</td> <td>903</td> <td>1,122</td> </tr> <tr> <th scope="row">Dev</th> <td>de</td> <td>32</td> <td>26</td> </tr> <tr> <th scope="row"> </th> <td>fr</td> <td>110</td> <td>114</td> </tr> <tr> <th scope="row">Test</th> <td>de</td> <td>32</td> <td>58</td> </tr> <tr> <th scope="row"> </th> <td>fr</td> <td>120</td> <td>163</td> </tr> </tbody> </table> <p>Due to an error, there are seven duplicated articles in the French test set (<em>article IDs: courriergdl-1847-10-02-a-i0002, courriergdl-1852-02-14-a-i0002, courriergdl-1860-10-31-a-i0016, courriergdl-1864-12-15-a-i0005, lunion-1860-11-27-a-i0004, lunion-1865-02-05-a-i0012, lunion-1866-02-16-a-i0009</em>).</p> <p> </p> <p><strong>2. MODELS</strong></p> <p>The two agency detection and classification models used for the inference on the <em><a href="https://impresso-project.ch/">impresso</a> </em>Corpus are released as well:</p> <ul> <li><strong>newsagency-model-de</strong>: based on <a href="https://www.deepset.ai/german-bert">German BERT</a> (with maximum sequence length 128), fine-tuned with the German training set of the newsagency-dataset</li> <li><strong>newsagency-model-fr</strong>: based on <a href="https://huggingface.co/dbmdz/bert-base-french-europeana-cased">French Europeana BERT</a> (with maximum sequence length 128), fine-tuned with the French training set of the newsagency-dataset</li> </ul> <p>The models perform multitask classification with two prediction heads, one for token-level agency entity classification and one for sentence-level (<em>has_agency: yes/no</em>). They can be run with TorchServe, for details see the <a href="https://github.com/impresso/newsagency-classification/tree/main/lib/bert_classification">newsagency-classification</a> repository.</p> <p> </p> <p>Please refer to the report for further information or contact us.</p> <p> </p> <p><strong>3. CODE</strong></p> <p><a href="https://github.com/impresso/newsagency-classification">https://github.com/impresso/newsagency-classification</a></p> <p> </p> <p><strong>4. CONTACT</strong></p> <p>Maud Ehrmann (EPFL-DHLAB)<br> Emanuela Boros (EPFL-DHLAB)</p>
irish Historical Rail Stations
<p>Locations of irish rail stations to present day</p>
Data for: Greening the dike revetment with historic sod transplantation technique in a Living Lab.
<p>Data from an <em>in-situ</em> experiment on a dike in Living Lab Hedwige Prosperpolder. In the experiment we applied a historic sod transplantation technique. We tested the erosion resistance of the adapted vegetated dike revetment after one growth season. <br><br>Dataset contains measurements in sods plot S1, S2, S3, S4 and in reference plots R1-R4. In addition, two section were only milled (K1 and F). These sections are not described in the publication, however some data is available and thus included in this dataset. </p> <p>This dataset contains files from the following research steps: </p> <p>1. Visual observation (vegetation)<br>2. Soil moisture content & Soil penetration resistance <br>3. Root indication (doorwortelling)<br>4. Sod pulling method (grastrek proef)<br>5. Wave impact test (golfklap proef) & Overflow test (overloop proef)</p> <p>The data is described in the following publication:</p> <p>Kim van den Hoven, K., Grashof-Bokdam, C.J., Slim, P.A., Wentholt, L., Peeters, P., Depreiter, D., Koelewijn, A.R., Stoorvogel, M.M., van den Berg, M., Kroeze, C., van Loon-Steensma, J.M. (2024) Greening the dike revetment with historic sod transplantation technique in a Living Lab. Journal of Flood Risk Management. DOI:10.1111/jfr3.12968</p>
Digitisation of Weather Records of Seungjeongwon Ilgi: A Historical Weather Dynamics Dataset of the Korean Peninsula (1623-1910)
<p><strong>Introduction</strong></p> <p>This study has exploited the daily weather records of Seungjeongwon Ilgi from the NIKH database (http://sjw.history.go.kr/main.do). Seungjeongwon Ilgi is a daily record of the Seungjeongwon, the Royal Secretariat of the Joseon Dynasty of Korea. These diaries span from 1623 to 1910 and generally involve daily weather records in the entry header. Their observational site would be located in Seoul (N37°35′, E126°59′). We have exploited the weather records from the NIKH database and classified the daily weather using text mining method. We have also converted the report dates from the traditional lunisolar calendar to the Gregorian calendar, to better contextualise our data into the contemporary daily measurements.</p> <p><strong>Data</strong></p> <p>We provide different formats (csv, xlsx, json) to facilitate the usage of data. The main contents of data are listed as below.</p> <ul> <li><strong>ID</strong>: The unique identifier of a specific record in the metadata, which can also serve as the identifier to merge with external data in the NIKH digital database.</li> <li><strong>Traditional calendar</strong>: The original lunar dates in the NIKH digital database, which are listed in data format "YYYY-MM-DD". More specifically, "L0" implies the leap year and "L1" implies the common year.</li> <li><strong>Leap</strong>: The identifier of a leap year.</li> <li><strong>Gregorian calendar</strong>: The Gregorian calendar date that converted by the traditional calendar date.</li> <li><strong>Weather Text</strong>: The text that describe the weather conditions. Specifically, multiple weather descriptions of the same day have been put together.</li> <li><strong>Flag</strong>: The computed value that indicates different combinations of weather conditions.</li> <li><strong>Volume</strong>: The volume of text in the original record.</li> <li><strong>Herbal Volume</strong>: The volume of text in the herbal record.</li> <li><strong>Sunny</strong>: A dummy variable that represents whether the weather description contains the expression of sunny.</li> <li><strong>Cloudy</strong>: A dummy variable that represents whether the weather description contains the expression of cloudy.</li> <li><strong>Rainy</strong>: A dummy variable that represents whether the weather description contains the expression of rainy.</li> <li><strong>Snow</strong>: A dummy variable that represents whether the weather description contains the expression of snow.</li> <li><strong>Wind</strong>: A dummy variable that represents whether the weather description contains the expression of wind.</li> </ul> <p><strong>Import Data</strong></p> <pre><code class="language-python"># Python # CSV file import pandas as pd data=pd.read_csv('~/SJWilgi_Seoul_Weather_YR1623_1910.csv',encoding="utf-8") # JSON file data=pd.read_json('~/SJWilgi_Seoul_Weather_YR1623_1910.json',encoding="utf-8") # Excel file data=pd.read_excel('~/SJWilgi_Seoul_Weather_YR1623_1910.xlsx') # Excel file</code></pre> <pre><code class="language-bash"># R # CSV file library(readr) data<- read_csv("~/SJWilgi_Seoul_Weather_YR1623_1910.csv") # Excel file library(readxl) data <- read_excel("~/SJWilgi_Seoul_Weather_YR1623_1910.xlsx")</code></pre> <p> </p>
Greetings From! Historical Postcards Address Transcription Dataset
<p>This dataset provides both Ground Truth (GT) and Handwritten Text Recognition (HTR) transcriptions of historical postcard addresses, stemming from a project to extract address information from historical picture postcards from Belgium, France, Germany, Luxembourg, the Netherlands, and the UK. The dataset encapsulates the back of 500 historically significant postcards.</p><p>The research associated with this dataset will be presented at <strong>Computational Humanities Research Conference, December 6--8, 2023, Paris, France.</strong></p><p><strong>Scope and Content:</strong></p><ul><li><strong>HTR Material</strong>: Handwritten Text Recognition outputs for 500 postcards.</li><li><strong>GT Material</strong>: Ground Truth transcriptions created by human transcribers for the same set of 500 postcards.</li></ul><p><strong>File Structure and Formats:</strong></p><p><i>For both HTR and GT Material, the following files are provided:</i></p><ul><li><strong>JPEG Images</strong>: Scanned or digitized images of the postcards.</li><li><strong>.txt</strong>: Plain text transcriptions of the postcards.</li><li><strong>_tei.xml</strong>: Transcriptions rendered in the TEI XML format.</li><li><strong>.pdf</strong>: PDF presentation of the postcards along with their transcriptions.</li><li><strong>mets.xml</strong>: METS (Metadata Encoding and Transmission Standard) schema for the data.</li><li><strong>page</strong> folder: XML files for individual images, offering metadata and structural information.</li><li><strong>metadata.xml</strong>: metadata concerning the dataset.</li><li><strong>GT_addresses_GPT4.json & HTR_addresses_GPT4.json</strong>: JSON files detailing individual address data for each postcard in structured format.</li></ul><p><strong>Annotation and Transcription:</strong></p><ul><li><strong>GT</strong>: Ground Truth data was annotated by human transcribers who examined both the images of the postcards and the outputs of the HTR system. Transcribers made corrections according to predefined conventions: using <strong>#</strong> for illegible characters, <strong>*</strong> at the start of lines without address information (e.g., person's name), and starting a line with <strong>@</strong> for irrelevant lines.</li><li><strong>HTR</strong>: The HTR versions emerged from state-of-the-art HTR systems (<a href="https://readcoop.eu/introducing-transkribus-super-models-get-access-to-the-text-titan-i/">Transkribus Text Titan I</a>). The <strong>.json</strong> files hold precise address details derived from the main data, which were processed using OpenAI's GPT-4 Large Language Model.</li></ul>
2003 Piru Fire Historical Imagery
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A historic global ground-based monthly seasonal aerosol climatology based in AERONET data: a database 1993-2013
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Data from: Evolutionary responses to historic drought across the range of scarlet monkeyflower
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Data from: Gloger's rule or historical conjecture? Tests in mammals
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Code for: A century of wild bee sampling: historical data and neural network analysis reveal ecological traits associated with species loss
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Use of historical isoscapes to develop an estuarine nutrient baseline
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Data from: Feather corticosterone is lower in translocated and historical populations of the endangered Laysan duck (Anas laysanensis)
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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.