ECharts: A declarative framework for rapid construction of web-based visualization

Li, Deqing; Mei, Honghui; Shen, Yi; Su, Shuang; Zhang, Wenli; Wang, Junting; Zu, Ming; Chen, Wei

doi:10.1016/j.visinf.2018.04.011

Cited by 209 publications

(92 citation statements)

References 17 publications

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“…The platform uses Echarts [40], an advanced visualization component, to provide visualization of the data level cases. Users obtain different visualization results, such as optical scattering magnitude, optical scattering intensity, and optical scattering images, by selecting different data and parameters.…”

Section: Sooc Data Visualizationmentioning

confidence: 99%

SOOCP: A Platform for Data and Analysis of Space Object Optical Characteristic

Lan

2019

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With the advancement of various technologies, the research and application of space object optical characteristic (SOOC), one of the main characteristics of space objects, are faced with new challenges. Current diverse structures of massive SOOC data cannot be stored and retrieved effectively. Moreover, SOOC processing and application platforms are inconvenient to build and deploy, while researchers’ innovative algorithms cannot be applied effectively, thereby limiting the promotion of the research achievements. To provide a scaffolding platform for users with different needs, this paper proposes SOOCP, a SOOC data and analysis service platform based on microservice architecture. Using the hybrid Structured Query Language (SQL)/NoSQL service, the platform provides efficient data storage and retrieval services for users at different levels. For promoting research achievements and reusing existing online services, the proposed heterogeneous function integration service assists researchers and developers in independently integrating algorithmic modules, functional modules, and existing online services to meet high concurrency requests with a unified interface. To evaluate the platform, three research cases with different requirement levels were considered. The results showed that SOOCP performs well by providing various data and function integration services for different levels of demand.

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Section: Sooc Data Visualizationmentioning

confidence: 99%

SOOCP: A Platform for Data and Analysis of Space Object Optical Characteristic

Lan

2019

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“…The web interface is implemented with PHP programming, HTML, and JavaScript. All the graphs are generated through the plug-in ECharts [35]. All the tables are in the style of Layui (https://www.layui.com/).…”

Section: Web Implementationmentioning

confidence: 99%

CuAS: a database of annotated transcripts generated by alternative splicing in cucumbers

et al. 2020

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Background: Alternative splicing (AS) plays a critical regulatory role in modulating transcriptome and proteome diversity. In particular, it increases the functional diversity of proteins. Recent genome-wide analysis of AS using RNA-Seq has revealed that AS is highly pervasive in plants. Furthermore, it has been suggested that most AS events are subject to tissue-specific regulation.Description: To reveal the functional characteristics induced by AS and tissue-specific splicing events, a database for exploring these characteristics is needed, especially in plants. To address these goals, we constructed a database of annotated transcripts generated by alternative splicing in cucumbers (CuAS: http://cmb.bnu.edu.cn/alt_iso/index.php) that integrates genomic annotations, isoform-level functions, isoform-level features, and tissue-specific AS events among multiple tissues. CuAS supports a retrieval system that identifies unique IDs (gene ID, isoform ID, UniProt ID, and gene name), chromosomal positions, and gene families, and a browser for visualization of each gene. Conclusion:We believe that CuAS could be helpful for revealing the novel functional characteristics induced by AS and tissue-specific AS events in cucumbers. CuAS is freely available at

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“…Besides the smooth exploration experimence, flexible visual representation methods are also required [40,46,64]. For example, a simple equi-width binning cannot guarantee desired charts that can exhibit a particular pattern due to skewed data distribution.…”

Section: Scenariosmentioning

confidence: 99%

RSATree: Distribution-Aware Data Representation of Large-Scale Tabular Datasets for Flexible Visual Query

Mei

Chen

Wei

et al. 2020

IEEE Trans. Visual. Comput. Graphics

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Fig. 1. RSATree facilitates fast answering of aggregate queries in large-scale tabular datasets while allowing flexible binning strategies. (a) A case built on a social network check-in dataset with 4.5 million records. A brushing and linking operation is performed by brushing workdays (Monday -Friday) and 13 hours of each day (9am -9pm) for filtering. (b) Binned scatterplot created from an airline on-time performance dataset with 180 million records. The bin width can be freely modified and instant previews are shown. (c) Capability of RSATree to generate a histogram with varied bin widths by using the same dataset as (b). As shown on the left side of (c), the distribution of "LateAircraftDelay" is relatively unbalanced. Application of log-scale binning produces a recognizable histogram (right side). Conventional approaches cannot simultaneously achieve low response time and flexible binning strategy in the three cases.Abstract-Analysts commonly investigate the data distributions derived from statistical aggregations of data that are represented by charts, such as histograms and binned scatterplots, to visualize and analyze a large-scale dataset. Aggregate queries are implicitly executed through such a process. Datasets are constantly extremely large; thus, the response time should be accelerated by calculating predefined data cubes. However, the queries are limited to the predefined binning schema of preprocessed data cubes. Such limitation hinders analysts flexible adjustment of visual specifications to investigate the implicit patterns in the data effectively. Particularly, RSATree enables arbitrary queries and flexible binning strategies by leveraging three schemes, namely, an R-tree-based space partitioning scheme to catch the data distribution, a locality-sensitive hashing technique to achieve locality-preserving random access to data items, and a summed area table scheme to support interactive query of aggregated values with a linear computational complexity. This study presents and implements a web-based visual query system that supports visual specification, query, and exploration of large-scale tabular data with user-adjustable granularities. We demonstrate the efficiency and utility of our approach by performing various experiments on real-world datasets and analyzing time and space complexity.

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ECharts: A declarative framework for rapid construction of web-based visualization

Cited by 209 publications

References 17 publications

SOOCP: A Platform for Data and Analysis of Space Object Optical Characteristic

SOOCP: A Platform for Data and Analysis of Space Object Optical Characteristic

CuAS: a database of annotated transcripts generated by alternative splicing in cucumbers

RSATree: Distribution-Aware Data Representation of Large-Scale Tabular Datasets for Flexible Visual Query

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