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.
3
datasets available to search
ShareScore release 0.9.0
Dataset results
3 results for “Spelling Variation”
Data Files for Tresoldi/Robinson article on spelling variation in Canterbury Tales manuscripts
<p>This data is at <a href="https://github.com/peterrobinson/CTSpellingArticle2024">https://github.com/peterrobinson/CTSpellingArticle2024</a>. It is contained in three folders, each folder corresponding to one of the three sets of data used in this analysis, as follows:</p> <p><strong> </strong></p> <ol> <li> <p>“sorted by regularization”. This folder contains spelling data and results derived from the regularization process, where (for example) spellings of forms regularized to “goode” are distinguished from spellings of forms regularized to “god”;</p> </li> <li> <p>“sorted by part of speech”. This folder contains spelling data and results derived from a lemmatization and part-of-speech identification process, where (for example) spellings of forms lemmatized to “goode” singular adjective are distinguished from spellings of forms regularized to “goode” plural adjective, and forms lemmatized to “gode” singular noun nominative case are distinguished from “gode” singular noun oblique case (as in “to gode”).</p> </li> <li> <p>“all spellings unsorted”. This folder contains spelling data as undifferentiated counts of “bags of words”: for each witness: so many occurrences of “good”, so many of “goode”, so many of “god”, so many of “gode”.</p> </li> </ol> <p><strong> </strong></p> <p>Each folder contains the following files (under various names):</p> <p><strong> </strong></p> <ol> <li> <p>A . json file holding all the data, structured according to its categorization. The “sorted by part of speech” folder contains two .json files, one with spellings organized by headword lemma, the other organized by part-of-speech;</p> </li> <li> <p>Two .nex Nexus files containing all the data. In the “sorted by regularization” and “sorted by part of speech” folders one Nexus file groups spellings by variant sites within each line, the other Nexus file groups spellings by words within each line. In the “all spellings unsorted” folder one Nexus file contains all the spellings organized by spelling; the second holds a Nexus distance matrix with distances created according to the Manhattan distance algorithm;</p> </li> <li> <p>A .dst distance matrix file, containing a distance matrix constructed with distacnes calculated by the Manhattan distance algorithm;</p> </li> <li> <p>A “features” file, containing a spreadsheet ranking each variant site according to its impact on the analysis </p> </li> <li> <p>Multiple .pdf files visualizing the results of our analysis, with the names reflecting the analysis each contains. Files with names including “Splits” were created using the SplitsTree algorithm and software <a href="https://www.zotero.org/google-docs/?peaEav">(Huson and Bryant 2006; “SplitsTree | Universität Tübingen,” n.d.)</a></p> </li> </ol> <p><strong> </strong></p> <p>The “sorted by regularization” folder also contains a single image file, “tiagoplot1.jpg”, visualizing the results of PCA analysis on the “sorted by regularization” data.</p> <p> </p>
Do Word Embeddings Capture Spelling Variation?
<p>When using the data, please cite:</p> <p><em>"Do Word Embeddings Capture Spelling Variation?". Dong Nguyen and Jack Grieve, COLING 2020.</em></p> <p>The data contains:</p> <ul> <li>the trained embeddings (embeddings-reddit.tgz and embeddings-twitter.tgz), 50-300 dimensions</li> <li>the analysis/output files (data.tgz).</li> </ul> <p>See also the Github repository: https://github.com/dongpng/coling2020.</p>
Tracking the spelling performance of disadvantaged primary- and middle-school students enrolled on an innovative cross-grade program: Variations according to the nature of spelling errors considered
<p>Data set about the number of spelling errors (phonological, orthographical and morphological) produced in both 2020-2021 and 2021-2020 by students who enrolled on an innovative cross-grade program in a disadvantaged neighborhood. The second year their spelling performance have been compared to those of control's students from the same disadvantaged neighborhood but who not enrolled on the innovative program.</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.