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483 results for “SEMANTICS”

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zenodo28/100

Figures 7-12 from: Mullins P, Kawada R, Balhoff J, Deans A (2012) A revision of Evaniscus (Hymenoptera, Evaniidae) using ontology-based semantic phenotype annotation. ZooKeys 223: 1-38. https://doi.org/10.3897/zookeys.223.3572

Figures 7-12 - Brightfield images of Evaniscus rafaeli Kawada sp. n. 7, 8 Lateral habitus 9, 10 Dorsal habitus 11 Anterior oblique 12 Anterior face.

opencc-by-4.0Sep 2012View details →
zenodo28/100

Figures 1-6 from: Mullins P, Kawada R, Balhoff J, Deans A (2012) A revision of Evaniscus (Hymenoptera, Evaniidae) using ontology-based semantic phenotype annotation. ZooKeys 223: 1-38. https://doi.org/10.3897/zookeys.223.3572

Figures 1-6 - Brightfield images of Evaniscus lansdownei Mullins sp. n. 1, 2 Lateral habitus 3, 4 Dorsal habitus 5 Anterior oblique 6 Anterior face.

opencc-by-4.0Sep 2012View details →
zenodo28/100

Figures 25-30 from: Mullins P, Kawada R, Balhoff J, Deans A (2012) A revision of Evaniscus (Hymenoptera, Evaniidae) using ontology-based semantic phenotype annotation. ZooKeys 223: 1-38. https://doi.org/10.3897/zookeys.223.3572

Figures 25-30 - Brightfield images of Evaniscus tibialis Szépligeti. 25, 26 Lateral habitus 27, 28 Dorsal habitus 29 Anterior oblique 30 Anterior face.

opencc-by-4.0Sep 2012View details →
zenodo28/100

Figures 32-33 from: Mullins P, Kawada R, Balhoff J, Deans A (2012) A revision of Evaniscus (Hymenoptera, Evaniidae) using ontology-based semantic phenotype annotation. ZooKeys 223: 1-38. https://doi.org/10.3897/zookeys.223.3572

Figures 32-33 - Brightfield images of Evaniscus rufithorax . 32 Male specimen; arrow points to visible lower tubular sclerite 33 Female specimen; arrow shows where lower tubular sclerite is not visible.

opencc-by-4.0Sep 2012View details →
zenodo28/100

Figures 19-24 from: Mullins P, Kawada R, Balhoff J, Deans A (2012) A revision of Evaniscus (Hymenoptera, Evaniidae) using ontology-based semantic phenotype annotation. ZooKeys 223: 1-38. https://doi.org/10.3897/zookeys.223.3572

Figures 19-24 - Brightfield images of Evaniscus marginatus Cameron. 19, 20 Lateral habitus 21, 22 Dorsal habitus 23 Anterior oblique 24 Anterior face.

opencc-by-4.0Sep 2012View details →
zenodo28/100

Semantic Clones Dataset for TrainTicket Microservices benchmark

<p>It contains Component Call Graphs pairs for the analysis of TrainTicket&nbsp;benchmark (release 0.1.0).</p> <p>It classifies the pairs into semantic clones and non-clones. It contains&nbsp;27,222 total CCGs pairs.</p> <p>This dataset is published as part of the paper titled as &quot;Detecting Semantic Clones In Microservices Using Components&quot;.</p> <p>&nbsp;</p> <p>This version contains correction for 6 pairs are classified as clones. (Highlighted in&nbsp;yellow)</p> <p>This correction is detected using our automatic approach. Check it out in the paper.</p> <p>&nbsp;</p>

opencc-by-4.0Feb 2023View details →
zenodo28/100

Dataset from the article, "False memory facilitation through semantic overlap"

<p>Dataset from the article, &quot;False memory facilitation through semantic overlap&quot;.</p>

opencc-by-4.0Apr 2023View details →
zenodo28/100

Artefact for PhD thesis "Dynamic Fault Trees: Semantics, Analysis and Applications"

<p>This artefact contains the example files, tools, and log files for the evaluation in Chapter 7 of the PhD thesis</p> <p><em>Matthias Volk - Dynamic Fault Trees: Semantics, Analysis and Applications</em></p> <p>&nbsp;</p> <p>The tools are licensed according to the license provided with each tool.</p>

openother-atApr 2023View details →
zenodo28/100

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

<p>The dataset for CodeSearchNet. See https://github.com/github/CodeSearchNet and https://arxiv.org/abs/1909.09436 for more.</p>

opencc-by-4.0Sep 2019View details →
zenodo28/100

Dataset from "Synthetic Training Data for Semantic Segmentation of the Environment from UAV Perspective"

<p>This dataset contains the images and ground truth label masks for semantic segmentation created and described in &quot;Hinniger, C.; R&uuml;ter, J. Synthetic Training Data for Semantic Segmentation of the Environment from UAV Perspective. Aerospace 2023, 10, 604. https://doi.org/10.3390/aerospace10070604&quot;.</p>

openJun 2023View details →
zenodo28/100

SEM Data Base Microvilli Semantic Segmentation in Microscopic Images Using a Visual Learning Pipeline

<p>SEM images raw data X1, X1, Y1, Y2,&nbsp; Z1 and Z2</p>

opencc-by-4.0Jun 2023View details →
zenodo28/100

Event Data and Semantic Header for OCED-PG

<p>Data sets and json files (describing the semantic header and dataset description) to build an Event Knowledge Graph (EKG) using OCED-PG as used in [1].&nbsp;</p> <p>Provides input data for 6 datasets (BPIC14,&nbsp;BPIC15,&nbsp;BPIC16,&nbsp;BPIC17,&nbsp;BPIC19 and a simulated libraray example).</p> <p>EKGs are built using OCED-PG, implemented in <a href="https://pypi.org/project/promg/0.1.25/">PromgG v0.1.25</a>.&nbsp;The source code can be found at <a href="https://github.com/PromG-dev/promg-core">Github</a>.</p> <p>To build EKGs using OCED-PG</p> <ul> <li>for one of the BPIC challenges, fork the query code from Github: <a href="https://github.com/Ava-S/ekg_bpi_challenges">ekg_bpi_challenges</a>.</li> <li>for the simulated library example, fork the query code from Github: <a href="https://github.com/Ava-S/ekg_library_example">ekg_library_example</a>.</li> </ul> <p>[1] Swevels, A., Fahland, D., Montali, M.:&nbsp;Implementing Object-Centric Event Data Models in Event Knowledge Graphs (2023)</p>

openlgpl-3.0-or-laterAug 2023View details →
zenodo28/100

Classical art semantics information extraction

<p>Abstract. The paper discusses the application of Natural Language Processing&nbsp;(NLP) techniques in the context of semantic annotation of classical art text via rule-based Information Extraction (IE) techniques combined with ontological&nbsp;and domain vocabulary input. The CASIE (Classical Art Semantics Information&nbsp;Extraction) was a pilot collaborative project between the Hypermedia Research<br> Unit (University of South Wales) and the Beazley Archive (Oxford University),&nbsp;which aims to automatically extract information about cultural objects from&nbsp;classical art scholarly texts and represent this information in terms of the ISO&nbsp;metadata standard for cultural heritage, the International Council of Museum&rsquo;s&nbsp;CIDOC Conceptual Reference Model (CRM). In total 12 documents (fascicules<br> &ndash; high quality catalogues) were processed, originating from the Corpus&nbsp;Vasorum Antiquorum (CVA) collection containing over 350 high quality&nbsp;catalogues of mostly ancient Greek painted pottery, illustrating more than&nbsp;100,000 vases. The extracted information was expressed in interoperable RDF&nbsp;graphs consistent with the CLAROS project format. The role of CIDOC-CRM&nbsp;is central for enabling semantic interoperability across the range of datasets that&nbsp;contribute to CLAROS. The CASIE pilot enabled a complementary exploitation&nbsp;of terminological and ontological resources via rule-based information&nbsp;extraction techniques, delivering semantic annotation with respect to the CRM&nbsp;in the broader field of digital humanities.</p>

opencc-ncJul 2013View details →
ClinicalTrials.gov28/100

Ketamine's Effect Changes the Cortical Electrophysiological Activity Related to Semantic Affective Dimension of Pain

ClinicalTrials.gov study NCT03915938. IPD Sharing: UNDECIDED. Countries: 0. Publications: 1.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov28/100

Semantic Learning Deficits in School Age Children With Developmental Language Disorder

ClinicalTrials.gov study NCT04508699. IPD Sharing: Not stated. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
dryad28/100

Data from: A revision of Evaniscus (Hymenoptera, Evaniidae) using ontology-based semantic phenotype annotation

Open the record for dataset details and reuse information.

publicSep 2012View details →
dryad28/100

Data from: The influence of evaluative right/wrong feedback on phonological and semantic processes in word learning

Open the record for dataset details and reuse information.

publicAug 2018View details →
dryad28/100

Data from: Evaluating active learning methods for annotating semantic predications

Open the record for dataset details and reuse information.

publicMay 2019View details →
zenodo24/100

Sundqvist et al. - The white matter module-hub network of semantics revealed by semantic dementia - Supplementary Figure

<p><strong>Supplementary Figure</strong> The correlation circle: correlations between the different MRI measures and semantic scores and the two first principal components via coordinates. The two first components sum up 68% of the total variance.</p> <p>Semantic composite (verbal, non-verbal) scores are measured in percentage. L indicates left hemisphere, R indicates right hemisphere. Mean Diffusivity (MD) for white matter tracts are: UNC-L, UNC-R, ILF-L, ILF-R, ATL-WVFA-L, ATL-FFA-R, ATL-LA-L, and ATL-LA-R. Mean cortical thickness of the regions of interests are: ATL-L, ATL-R, WVFA-L, FFA-R, LA-L, and LA-R.</p> <p>Link to publication:&nbsp;https://doi.org/10.1162/jocn_a_01549</p> <p>&nbsp;</p>

opencc-by-4.0Feb 2020View details →
zenodo24/100

Modeling Factual Claims with Semantic Frames

<p>We introduce an extension of the Berkeley FrameNet for the structured and semantic modeling of factual claims. Modeling is a robust tool that can be leveraged in many different tasks such as matching claims to existing fact-checks and translating claims to structured queries. Our work introduces 11 new manually crafted frames along with 9 existing FrameNet frames, all of which have been selected with fact-checking in mind. Along with these frames, we are also providing 2,540 fully annotated sentences, which can be used to understand how these frames are intended to work and to train machine learning models.&nbsp;</p>

opencc-by-4.0Mar 2020View details →

ScienceDex guides

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated 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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record