Exploring Scalability in Large-Scale Time Series in DeepVATS framework Article Swipe
Inmaculada Santamaria-Valenzuela
,
Víctor Rodríguez-Fernández
,
David Camacho
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2408.04692
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2408.04692
Visual analytics is essential for studying large time series due to its ability to reveal trends, anomalies, and insights. DeepVATS is a tool that merges Deep Learning (Deep) with Visual Analytics (VA) for the analysis of large time series data (TS). It has three interconnected modules. The Deep Learning module, developed in R, manages the load of datasets and Deep Learning models from and to the Storage module. This module also supports models training and the acquisition of the embeddings from the latent space of the trained model. The Storage module operates using the Weights and Biases system. Subsequently, these embeddings can be analyzed in the Visual Analytics module. This module, based on an R Shiny application, allows the adjustment of the parameters related to the projection and clustering of the embeddings space. Once these parameters are set, interactive plots representing both the embeddings, and the time series are shown. This paper introduces the tool and examines its scalability through log analytics. The execution time evolution is examined while the length of the time series is varied. This is achieved by resampling a large data series into smaller subsets and logging the main execution and rendering times for later analysis of scalability.
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- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2408.04692
- https://arxiv.org/pdf/2408.04692
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4402386120
All OpenAlex metadata
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- OpenAlex ID
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https://openalex.org/W4402386120Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2408.04692Digital Object Identifier
- Title
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Exploring Scalability in Large-Scale Time Series in DeepVATS frameworkWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-08-08Full publication date if available
- Authors
-
Inmaculada Santamaria-Valenzuela, Víctor Rodríguez-Fernández, David CamachoList of authors in order
- Landing page
-
https://arxiv.org/abs/2408.04692Publisher landing page
- PDF URL
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https://arxiv.org/pdf/2408.04692Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
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https://arxiv.org/pdf/2408.04692Direct OA link when available
- Concepts
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Series (stratigraphy), Scalability, Scale (ratio), Computer science, Time series, Geography, Geology, Cartography, Database, Machine learning, PaleontologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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