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 “semantic methods”
A decade of Semantic Web research through the lenses of a mixed methods approach (Resources)
<p>This work has been submitted to <a href="http://www.semantic-web-journal.net/content/decade-semantic-web-research-through-lenses-mixed-methods-approach">Semantic Web Journal</a>. We provide here resources to reproduce our approach.</p> <p>In this paper, we aim to provide a broader and more complete picture of Semantic Web topics and trends by adopting a mixed methods methodology, which allows a combined use of both qualitative and quantitative approaches. Concretely, we build on a qualitative analysis of the main seminal papers, which adopt a top-down approach, and on quantitative results derived with three bottom-up data-driven approaches (<a href="https://technologies.kmi.open.ac.uk/Rexplore/">Rexplore</a>, <a href="http://saffron.insight-centre.org/">Saffron</a>, <a href="https://www.poolparty.biz/">PoolParty</a>), on a corpus of Semantic Web papers published in the last decade. In this process, we both use the latter for “fact-checking” on the former and also to derive key findings in relation to the strengths and weaknesses of top-down and bottom-up approaches to research topic identification.</p> <p>Please access the full set of resources at: <a href="https://aic.ai.wu.ac.at/qadlod/SW/">https://aic.ai.wu.ac.at/qadlod/SW/</a></p>
Datasets of the paper "Retrieval-Mediated Directed Forgetting in the Item-Method Paradigm: The Effect of Semantic Cues"
<p>Data sets and analyses scripts of the paper "Retrieval-Mediated Directed Forgetting in the Item-Method Paradigm: The Effect of Semantic Cues".</p>
Towards Green Cartography & Visualization: An automated, semantically-enriched method of generating energy-aware color schemes for digital maps and visualizations
<p>Towards Green Cartography & Visualization: An automated, semantically-enriched method of generating energy-aware color schemes for digital maps and visualizations</p>
SeSaMe: A Data Set of Semantically Similar Java Methods
<p>This is the data set presented in the paper</p> <p>Kamp, M., Kreutzer P., Philippsen M.: SeSaMe: A Data Set of Semantically<br> Similar Java Methods. 16th International Conference on Mining Software<br> Repositories (MSR 2019), Montreal, QC, Canada. 2019</p>
Data from: Evaluating active learning methods for annotating semantic predications
Objectives: This study evaluated and compared a variety of active learning strategies, including a novel strategy we proposed, as applied to the task of filtering incorrect SemRep semantic predications. Materials and Methods: We evaluated three types of active learning strategies – uncertainty, representative, and combined– on two datasets of semantic predications from SemMedDB covering the domains of substance interactions and clinical medicine, respectively. We also designed a novel combined strategy with dynamic β without hand-tuned hyperparameters. Each strategy was assessed by the Area under the Learning Curve (ALC) and the number of training examples required to achieve a target Area Under the ROC curve (AUC). We also visualized and compared the query patterns of the query strategies. Results: Combined strategies outperformed all other methods in terms of ALC, outperforming the baseline by over 0.05 ALC for both datasets and reducing 58% annotation efforts in the best case. While representative strategies performed well, their performance was matched or outperformed by the combined methods. All the uncertainty sampling methods beat the baseline but they were the worst performing methods overall. Our proposed AL method with dynamic β shows promising ability to achieve near-optimal performance across two datasets. Discussion: Our visual analysis of query patterns indicates that strategies which efficiently obtain a representative subsample perform better on this task. Conclusion: Active learning is shown to be effective at reducing annotation costs for filtering incorrect semantic predications from SemRep. Our proposed AL method demonstrated promising performance.
Data from: Evaluating active learning methods for annotating semantic predications
Open the record for dataset details and reuse information.
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.