Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
6
datasets available to search
ShareScore release 0.9.0
Dataset results
6 results for “Offline dataset”
A Brazilian Portuguese Dataset for Offline Handwritten Text Recognition (BRESSAY)
<p>The BRESSAY dataset comprises images of handwritten essays in Brazilian Portuguese, which present a series of challenges to optical recognition models. These images were sourced from multiple online platforms, limiting our ability to standardize the capture process. Due to these varied sources and the lack of a uniform collection method, the dataset provides a realistic reflection of real-world conditions. Each essay is unique, contributed by different writers, and addresses a specific content topic. Furthermore, the constraints placed on the writers often lead to various handwriting scenarios, including hard-to-read words, connected words, noise, overwriting, and struck-through texts.</p> <h3><strong>Technical Details</strong></h3> <p>The BRESSAY dataset represents a comprehensive collection of handwritten essays in Brazilian Portuguese, offering detailed insights into various handwriting scenarios. It covers a total of 1,000 pages, each contributed by a unique writer, resulting in 1,000 distinct handwriting styles. This aspect of the dataset adds a layer of diversity, which is further emphasized by the total of 4,214 paragraphs, 30,090 lines, and 416,826 words. Regarding unique tokens, we have 41,318 unique words, and 107 unique characters.</p> <h3><strong>Data Structure</strong></h3> <p>The dataset is organized as follows:</p> <ul> <li>data/: Main folder containing segmented essay images <ul> <li>lines/: Images of individual lines <ul> <li> PNG files: Line images</li> <li> TXT files: Transcriptions of lines</li> </ul> </li> <li>pages/: Full page essay images <ul> <li> PNG files: Page images</li> <li> TXT files: Transcriptions of pages</li> </ul> </li> <li>paragraphs/: Images of paragraphs <ul> <li> PNG files: Paragraph images</li> <li> TXT files: Transcriptions of paragraphs</li> </ul> </li> <li>words/: Images of individual words <ul> <li> PNG files: Word images</li> <li> TXT files: Transcriptions of words</li> </ul> </li> </ul> </li> <li>sets/: Contains partition files <ul> <li>test.txt: Names of images in the test set</li> <li>validation.txt: Names of images in the validation set</li> <li>training.txt: Names of images in the training set</li> </ul> </li> </ul> <h3><strong>Dataset Usage and Annotations</strong></h3> <p>Each name in test.txt, validation.txt and training.txt represents the name of the page and all its content (words, lines, paragraphs) must be in the respective partition.</p> <p>Annotations used in the dataset:</p> <ul> <li> <code>##@@???@@##</code>: Superscript text that has become unidentifiable and unreadable.</li> <li> <code>$$@@???@@$$</code>: Subscript text that has become unidentifiable and unreadable.</li> <li> <code>@@???@@</code>: Text that cannot be read or identified due to its illegibility.</li> <li> <code>##--xxx--##</code>: Text that has been added as a superscript and subsequently crossed out, rendering it illegible.</li> <li> <code>$$--xxx--$$</code>: Text that has been added as a subscript and subsequently crossed out, rendering it illegible.</li> <li> <code>--xxx--</code>: Text that has been crossed out in a way that makes it unreadable.</li> <li> <code>##--text--##</code>: Text that has been added as a superscript and subsequently crossed out, but remains legible.</li> <li> <code>$$--text--$$</code>: Text that has been added as a subscript and subsequently crossed out, but remains legible.</li> <li> <code>##text##</code>: Text added as a superscript in the line, typically as a correction or additional note.</li> <li> <code>$$text$$</code>: Text added as a subscript in the line, typically as a correction or additional note.</li> <li> <code>--text--</code>: Text that has been crossed out but remains readable.</li> </ul>
BanglaWriting Words Dataset: A Collection of Isolated Word Images from the BanglaWriting multi-purpose Bangla offline-handwriting dataset (WoBW)
<p>The WoBW (Words from BanglaWriting) dataset is a curated collection of isolated word images, adapted from the original BanglaWriting dataset (url: https://data.mendeley.com/datasets/r43wkvdk4w/1).</p> <p>WoBW focuses on individual words extracted from handwritten Bangla text samples in the BanglaWriting corpus, making it a valuable resource for research in word-level Bangla handwriting recognition and related natural language processing tasks.</p> <p>Mridha, Dr. M. F.; Quwsar Ohi, Abu; Ali, M. Ameer; Emon, Mazedul Islam; Kabir, Md Mohsin (2020), “BanglaWriting: A multi-purpose offline Bangla handwriting dataset”, Mendeley Data, V1, doi: 10.17632/r43wkvdk4w.1</p>
Robotic manipulation datasets for offline compositional reinforcement learning
Open the record for dataset details and reuse information.
Dataset for Understanding Unemployment during COVID-19 from Online and Offline Behaviors
<table> <tbody> <tr> <td>variable</td> <td>data</td> <td>source</td> <td>file</td> </tr> <tr> <td><em>Insurance</em></td> <td>Health Insurance Coverage Uninsured, Percent</td> <td>U.S. Census Bureau, 2008 to 2019 American Community Surveys (ACS).</td> <td>Health Insurance Coverage Percent uninsured by State.csv</td> </tr> <tr> <td><em>Income</em></td> <td>household Income</td> <td>United States Census Bureau’s Annual ASEC survey 2019</td> <td>Median Household Income by State.csv</td> </tr> <tr> <td><em>Diploma</em></td> <td>Percent of adults with less than a high school diploma plus Percent of adults with a high school diploma only</td> <td>U.S. Census Bureau 2014-18 American Community Survey 4-yr average county-level estimates</td> <td>Education by State.xls</td> </tr> <tr> <td><em>Death, Case</em></td> <td>COVID-19 deaths and cases</td> <td> Centers for Disease Control and Prevention </td> <td>United_States_COVID-19_Cases_and_Deaths_by_State_over_Time.csv</td> </tr> <tr> <td><em>Test</em></td> <td>Test</td> <td>The COVID Tracking Project</td> <td>COVID-19 Tests by State.xlsx</td> </tr> <tr> <td><em>Density</em></td> <td>population density/population</td> <td>US Census Bureau</td> <td>population-density-data-table.xlsx</td> </tr> <tr> <td><em>Nonwhite</em></td> <td>Non-white%</td> <td>US Census Bureau</td> <td>Bridged-Race Population Estimates 2019_by State .xlsx</td> </tr> <tr> <td><em>Gini</em></td> <td>Gini</td> <td>U.S. Census Bureau, American Community Survey .</td> <td>US State Gini.csv</td> </tr> <tr> <td><em>Grant</em></td> <td>total grants</td> <td>U.S. Department of Education</td> <td>U.S. Department of Education appropriations for major programs, by state or jurisdiction Fiscal year 2018.xls</td> </tr> <tr> <td><em>Unemployment</em></td> <td>unemployment rate</td> <td>US Census Bureau</td> <td>Unemployment rate by State.csv</td> </tr> </tbody> </table> <p> </p>
Dataset for "Explainable Offline-Online Training of Neural Networks for Parameterizations: A 1D Gravity Wave-QBO Testbed in the Small-data Regime" by Pahlavan et al. (2023)
Open the record for dataset details and reuse information.
Dataset for offline training of a self-driving telescope with Reinforcement Learning
<p>Go to https://zenodo.org/doi/10.5281/zenodo.8388482 for the updated version!!</p> <p>The dataset was generated through simulation and used during the offline training and the comparison of algorithms while targeting the self-driving telescope implementation with Deep Reinforcement Learning (RL).<br> </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.