Linking Text and Visualizations via Contextual Knowledge Graph.

The integration of visualizations and text is commonly found in data news, analytical reports, and interactive documents. For example, financial articles are presented along with interactive charts to show the changes in stock prices on Yahoo Finance. Visualizations enhance the perception of facts in the text while the text reveals insights of visual representation. However, effectively combining text and visualizations is challenging and tedious, which usually involves advanced programming skills. This paper proposes a semi-automatic pipeline that builds links between text and visualization. To resolve the relationship between text and visualizations, we present a method which structures a visualization and the underlying data as a contextual knowledge graph, based on which key phrases in the text are extracted, grouped, and mapped with visual elements. To support flexible customization of text-visualization links, our pipeline incorporates user knowledge to revise the links in a mixed-initiative manner. To demonstrate the usefulness and the versatility of our method, we replicate prior studies or cases in crafting interactive word-sized visualizations, annotating visualizations, and creating text-chart interactions based on a prototype system. We carry out two preliminary model tests and a user study and the results and user feedbacks suggest our method is effective.

JsonCurer: Data Quality Management for JSON Based on an Aggregated Schema.

High-quality data is critical to deriving useful and reliable information. However, real-world data often contains quality issues undermining the value of the derived information. Most existing research on data quality management focuses on tabular data, leaving semi-structured data under-exploited. Due to the schema-less and hierarchical features of semi-structured data, discovering and fixing quality issues is challenging and time-consuming. To address the challenge, this paper presents JsonCurer, an interactive visualization system to assist with data quality management in the context of JSON data. To have an overview of quality issues, we first construct a taxonomy based on interviews with data practitioners and a review of 119 real-world JSON files. Then we highlight a schema visualization that presents structural information, statistical features, and quality issues of JSON data. Based on a similarity-based aggregation technique, the visualization depicts the entire JSON data with a concise tree, where summary visualizations are given above each node, and quality issues are illustrated using Bubble Sets across nodes. We evaluate the effectiveness and usability of JsonCurer with two case studies. One is in the domain of data analysis while the other concerns quality assurance in MongoDB documents. The source code of JsonCurer is available under the Apache License 2.0 at https://github.com/changevis/JsonCurer.

Higher expression of PLEK and LY86 as the potential biomarker of carotid atherosclerosis.

Carotid atherosclerosis (AS) occurs in atherosclerotic lesions of the carotid artery, which can lead to transient ischemic attack and stroke in severe cases. However, the relationship between pleckstrin (PLEK) and lymphocyte antigen 86 (LY86) and carotid AS remains unclear. The carotid AS datasets GSE43292 and GSE125771 were downloaded from the gene expression omnibus database. Differentially expressed genes (DEGs) were screened and weighted gene co-expression network analysis was performed. Construction and analysis of protein-protein interaction network. Functional enrichment analysis, gene set enrichment analysis and comparative toxicogenomics database analysis were performed. TargetScan screened miRNAs that regulated central DEGs. A total of 305 DEGs were identified. According to gene ontology analysis, they were mainly enriched in immune system processes, extracellular regions and cytokine binding. Kyoto encyclopedia of genes and genomes analysis showed that the target cells were mainly enriched in Rap1 signal pathway, B cell receptor signal pathway and PPAR signal pathway. In the enrichment project of metascape, the reaction to bacteria, cell activation and chemotaxis can be seen in the enrichment project of gene ontology. Total 10 core genes (TYROBP, FCER1G, PLEK, LY86, IL10RA, ITGB2, LCP2, FCGR2B, CD86, CCR1) were obtained by protein-protein interaction network construction and analysis. Core genes (PLEK, LY86, IL10RA, ITGB2, and LCP2) were highly expressed in carotid AS samples and lowly expressed in normal samples. Comparative toxicogenomics database analysis showed that 5 genes were associated with pneumonia, inflammation, necrosis, and drug allergy. PLEK and LY86 genes are highly expressed in carotid AS. The higher the expression of PLEK and LY86, the worse the prognosis is.

VisImages: A Fine-Grained Expert-Annotated Visualization Dataset.

Images in visualization publications contain rich information, e.g., novel visualization designs and implicit design patterns of visualizations. A systematic collection of these images can contribute to the community in many aspects, such as literature analysis and automated tasks for visualization. In this paper, we build and make public a dataset, VisImages, which collects 12,267 images with captions from 1,397 papers in IEEE InfoVis and VAST. Built upon a comprehensive visualization taxonomy, the dataset includes 35,096 visualizations and their bounding boxes in the images. We demonstrate the usefulness of VisImages through three use cases: 1) investigating the use of visualizations in the publications with VisImages Explorer, 2) training and benchmarking models for visualization classification, and 3) localizing visualizations in the visual analytics systems automatically.

Visualizing the Scripts of Data Wrangling With Somnus.

Data workers use various scripting languages for data transformation, such as SAS, R, and Python. However, understanding intricate code pieces requires advanced programming skills, which hinders data workers from grasping the idea of data transformation at ease. Program visualization is beneficial for debugging and education and has the potential to illustrate transformations intuitively and interactively. In this article, we explore visualization design for demonstrating the semantics of code pieces in the context of data transformation. First, to depict individual data transformations, we structure a design space by two primary dimensions, i.e., key parameters to encode and possible visual channels to be mapped. Then, we derive a collection of 23 glyphs that visualize the semantics of transformations. Next, we design a pipeline, named Somnus, that provides an overview of the creation and evolution of data tables using a provenance graph. At the same time, it allows detailed investigation of individual transformations. User feedback on Somnus is positive. Our study participants achieved better accuracy with less time using Somnus, and preferred it over carefully-crafted textual description. Further, we provide two example applications to demonstrate the utility and versatility of Somnus.

[Effects of Continuous Straw Returning with Chemical Fertilizer on the Carbon Pool and Crop Yield of Rice-Rape Rotation Soils].

According to the positioning experiment of straw returning in the continuous field 7a, the effects of straw returning combined with chemical fertilizer on soil total organic carbon (TOC), dissolved organic carbon (DOC), particulate organic carbon (POC), labile organic carbon (LOC), carbon pool management index (CPMI), and crop yield in farmland soil profiles (0-20, 20-50, and 50-80 cm) in the Chaohu Lake area were studied. There were four treatments:no straw returning+no fertilization (CK), conventional fertilization (F), straw returning+conventional fertilization (SF1), and straw returning+80% conventional fertilization (SF2). The changes in soil total organic carbon and component content, CPMI, and rape rice yield in different soil layers were analyzed. Taking CK as a reference, conventional fertilization and straw returning combined with chemical fertilizer increased the content of total organic carbon and components in the soil vertical profile, and the content of total organic carbon and components in different soil layers decreased gradually with the increase in soil depth. In the 0-20 cm soil layer, compared with that in the F treatment, the SF1 and SF2 treatments significantly increased the contents of TOC, DOC, POC, and LOC by 14.23%-28.97%, 7.86%-27.01%, 16.46%-24.24%, and 5.89%-6.64%, respectively (P<0.05). In the 20-50 cm soil layer, the contents of TOC and LOC in SF1 were significantly increased by 9.43% and 8.34%, respectively, compared with those in the F treatment (P<0.05), and the contents of DOC and POC in SF2 were significantly increased by 17.51% and 65.83% compared with those in the F treatment (P<0.05). In the 50-80 cm soil layer, there was no significant difference in the contents of total organic carbon and components among the treatments. The effect of straw returning and chemical fertilizer on the soil carbon pool management index was significant. SF1 significantly improved the CPMI of the 0-50 cm soil layer compared with that in the F treatment, whereas the CPMI of the F treatment was the largest in the 50-80 cm soil layer; however, there was no significant difference among all treatments. Straw returning combined with chemical fertilizer had a significant effect on crop yield, and the yield of the SF1 treatment was the highest; compared with that of the F treatment, the rice, rape, and annual yields were significantly increased by 6.19%, 7.67%, and 6.54%, respectively (P<0.05). In general, straw returning combined with chemical fertilizer was of great significance to improve the soil carbon pool, soil fertility, and crop yield in the Chaohu Lake area.

Revealing the Semantics of Data Wrangling Scripts With COMANTICS.

Data workers usually seek to understand the semantics of data wrangling scripts in various scenarios, such as code debugging, reusing, and maintaining. However, the understanding is challenging for novice data workers due to the variety of programming languages, functions, and parameters. Based on the observation that differences between input and output tables highly relate to the type of data transformation, we outline a design space including 103 characteristics to describe table differences. Then, we develop COMANTICS, a three-step pipeline that automatically detects the semantics of data transformation scripts. The first step focuses on the detection of table differences for each line of wrangling code. Second, we incorporate a characteristic-based component and a Siamese convolutional neural network-based component for the detection of transformation types. Third, we derive the parameters of each data transformation by employing a "slot filling" strategy. We design experiments to evaluate the performance of COMANTICS. Further, we assess its flexibility using three example applications in different domains.

Controllable Design and Preparation of Hydroxyl-Terminated Solution-Polymerized Styrene Butadiene for Polyurethane Elastomers with High-Damping Properties.

Vibration and noise are ubiquitous in social life, which severely damage machinery and adversely affect human health. Thus, the development of materials with high-damping performance is of great importance. Rubbers are typically used as damping materials because of their unique viscoelasticity. However, they do not satisfy the requirements of different applications with various working conditions. In this study, the advantages of the high loss factor of styrene butadiene rubber (SBR) are combined with the strong designability of polyurethane. Hydroxyl-terminated solution-polymerized styrene butadiene rubbers (HTSSBRs) with different structures are prepared using anionic polymerization. HTSSBRs are then used as the soft segment during the synthesis of temperature-tunable high-damping performance polyurethanes (HTSSBR-polyurethanes (PUs)). The prepared HTSSBR-PUs with different structures exhibit excellent loss performance, a maximum loss factor (tan δmax ) of above 1.60, and an effective damping performance over a wide temperature range compared to traditional SBR and polyurethane. Therefore, this work offers an effective method for the design of damping materials with adjustable properties.

Deep Colormap Extraction From Visualizations.

This article presents a new approach based on deep learning to automatically extract colormaps from visualizations. After summarizing colors in an input visualization image as a Lab color histogram, we pass the histogram to a pre-trained deep neural network, which learns to predict the colormap that produces the visualization. To train the network, we create a new dataset of  âˆ¼ 64K visualizations that cover a wide variety of data distributions, chart types, and colormaps. The network adopts an atrous spatial pyramid pooling module to capture color features at multiple scales in the input color histograms. We then classify the predicted colormap as discrete or continuous, and refine the predicted colormap based on its color histogram. Quantitative comparisons to existing methods show the superior performance of our approach on both synthetic and real-world visualizations. We further demonstrate the utility of our method with two use cases, i.e., color transfer and color remapping.

Nebula: A Coordinating Grammar of Graphics.

In multiple coordinated views (MCVs), visualizations across views update their content in response to users' interactions in other views. Interactive systems provide direct manipulation to create coordination between views, but are restricted to limited types of predefined templates. By contrast, textual specification languages enable flexible coordination but expose technical burden. To bridge the gap, we contribute Nebula, a grammar based on natural language for coordinating visualizations in MCVs. The grammar design is informed by a novel framework based on a systematic review of 176 coordinations from existing theories and applications, which describes coordination by demonstration, i.e., how coordination is performed by users. With the framework, Nebula specification formalizes coordination as a composition of user- and coordination-triggered interactions in origin and destination views, respectively, along with potential data transformation between the interactions. We evaluate Nebula by demonstrating its expressiveness with a gallery of diverse examples and analyzing its usability on cognitive dimensions.

[Effects of Straw Returning with Chemical Fertilizer on Soil Enzyme Activities and Microbial Community Structure in Rice-Rape Rotation].

Straw returning is an effective technique for improving soil fertility and maintaining crop productivity in agro-ecosystems. The effects of straw returning, when combined with chemical fertilizer, on soil nutrients, enzyme activity, and microbial community were explored in rice-rape rotation farmland in the Chaohu Area. We carried out a 4-year field experiment (2016-2020) and set up four treatments (no straw+no fertilization, CK; conventional fertilization, F; straw returning+conventional fertilization, SF; and straw returning+conventional fertilization minus 20%, SDF) to explore the key environmental factors affecting soil enzyme activity and microbial and fungal communities. The results showed that straw returning combined with chemical fertilizer could improve soil nutrient content, with the SF treatment resulting in the highest soil nutrient content. Compared with F, the SF treatment significantly increased the organic matter (OM) and total phosphorus (TP) content of the soil, by 7.94% and 24.07%, respectively, in rice seasons (P<0.05), while the alkaline nitrogen (AN) content was significantly increased by 13.62% in rape seasons (P<0.05). Compared with F, the SF treatment also significantly increased soil phosphatase and urease, by 28.54% and 24.13% in rice seasons and 38.97% and 30.70% in rape seasons, respectively (P<0.05). Compared with F, SDF treatments significantly increased urease activity by 20.31% in rice seasons and 24.33% in rape seasons (P<0.05). The results indicated that straw returning increased both the Chao1 and Shannon indices of soil bacteria in rice seasons, whereas decreased these indices in rape seasons. However, the Chao1 and Shannon index of the fungal community increased after straw returning. In terms of microbial community structure, the relative abundance of Proteobacteria in SF and SDF treatments increased by 8.22% and 7.88% in rice seasons and 18.53% and 5.68% in rape seasons, respectively, compared with the F treatment. Compared with F, the relative abundance of Chloroflexi in SF and SDF treatments increased by 12.00% and 11.25% in rice seasons and 15.02% and 8.43% in rape seasons, respectively. Compared with F, the relative abundance of Basidiomycota in SF and SDF treatments in rice seasons increased by 70% and 43.42% (P<0.05), respectively, while ascomycetes in rape seasons increased by 69.79% and 43.72% (P<0.05), respectively. In conclusion, straw returning combined with chemical fertilizer can improve soil nutrient content. Soil urease and phosphatase were more sensitive to straw returning. The compositional changes in the bacterial community of the soil were mainly affected by soil TP and available phosphorus (AP), whereas OM, AN, and pH were the main environmental factors causing changes in the fungal community composition. Consequently, straw returning can improve soil fertility and maintain ecosystem health.

ShuttleSpace: Exploring and Analyzing Movement Trajectory in Immersive Visualization.

We present ShuttleSpace, an immersive analytics system to assist experts in analyzing trajectory data in badminton. Trajectories in sports, such as the movement of players and balls, contain rich information on player behavior and thus have been widely analyzed by coaches and analysts to improve the players' performance. However, existing visual analytics systems often present the trajectories in court diagrams that are abstractions of reality, thereby causing difficulty for the experts to imagine the situation on the court and understand why the player acted in a certain way. With recent developments in immersive technologies, such as virtual reality (VR), experts gradually have the opportunity to see, feel, explore, and understand these 3D trajectories from the player's perspective. Yet, few research has studied how to support immersive analysis of sports data from such a perspective. Specific challenges are rooted in data presentation (e.g., how to seamlessly combine 2D and 3D visualizations) and interaction (e.g., how to naturally interact with data without keyboard and mouse) in VR. To address these challenges, we have worked closely with domain experts who have worked for a top national badminton team to design ShuttleSpace. Our system leverages 1) the peripheral vision to combine the 2D and 3D visualizations and 2) the VR controller to support natural interactions via a stroke metaphor. We demonstrate the effectiveness of ShuttleSpace through three case studies conducted by the experts with useful insights. We further conduct interviews with the experts whose feedback confirms that our first-person immersive analytics system is suitable and useful for analyzing badminton data.

Exemplar-based Layout Fine-tuning for Node-link Diagrams.

We design and evaluate a novel layout fine-tuning technique for node-link diagrams that facilitates exemplar-based adjustment of a group of substructures in batching mode. The key idea is to transfer user modifications on a local substructure to other substructures in the entire graph that are topologically similar to the exemplar. We first precompute a canonical representation for each substructure with node embedding techniques and then use it for on-the-fly substructure retrieval. We design and develop a light-weight interactive system to enable intuitive adjustment, modification transfer, and visual graph exploration. We also report some results of quantitative comparisons, three case studies, and a within-participant user study.

Narvis: Authoring Narrative Slideshows for Introducing Data Visualization Designs.

Visual designs can be complex in modern data visualization systems, which poses special challenges for explaining them to the non-experts. However, few if any presentation tools are tailored for this purpose. In this study, we present Narvis, a slideshow authoring tool designed for introducing data visualizations to non-experts. Narvis targets two types of end users: teachers, experts in data visualization who produce tutorials for explaining a data visualization, and students, non-experts who try to understand visualization designs through tutorials. We present an analysis of requirements through close discussions with the two types of end users. The resulting considerations guide the design and implementation of Narvis. Additionally, to help teachers better organize their introduction slideshows, we specify a data visualization as a hierarchical combination of components, which are automatically detected and extracted by Narvis. The teachers craft an introduction slideshow through first organizing these components, and then explaining them sequentially. A series of templates are provided for adding annotations and animations to improve efficiency during the authoring process. We evaluate Narvis through a qualitative analysis of the authoring experience, and a preliminary evaluation of the generated slideshows.

How Do Ancestral Traits Shape Family Trees Over Generations?

Whether and how does the structure of family trees differ by ancestral traits over generations? This is a fundamental question regarding the structural heterogeneity of family trees for the multi-generational transmission research. However, previous work mostly focuses on parent-child scenarios due to the lack of proper tools to handle the complexity of extending the research to multi-generational processes. Through an iterative design study with social scientists and historians, we develop TreeEvo that assists users to generate and test empirical hypotheses for multi-generational research. TreeEvo summarizes and organizes family trees by structural features in a dynamic manner based on a traditional Sankey diagram. A pixel-based technique is further proposed to compactly encode trees with complex structures in each Sankey Node. Detailed information of trees is accessible through a space-efficient visualization with semantic zooming. Moreover, TreeEvo embeds Multinomial Logit Model (MLM) to examine statistical associations between tree structure and ancestral traits. We demonstrate the effectiveness and usefulness of TreeEvo through an in-depth case-study with domain experts using a real-world dataset (containing 54,128 family trees of 126,196 individuals).

Visual Analysis of MOOC Forums with iForum.

Discussion forums of Massive Open Online Courses (MOOC) provide great opportunities for students to interact with instructional staff as well as other students. Exploration of MOOC forum data can offer valuable insights for these staff to enhance the course and prepare the next release. However, it is challenging due to the large, complicated, and heterogeneous nature of relevant datasets, which contain multiple dynamically interacting objects such as users, posts, and threads, each one including multiple attributes. In this paper, we present a design study for developing an interactive visual analytics system, called iForum, that allows for effectively discovering and understanding temporal patterns in MOOC forums. The design study was conducted with three domain experts in an iterative manner over one year, including a MOOC instructor and two official teaching assistants. iForum offers a set of novel visualization designs for presenting the three interleaving aspects of MOOC forums (i.e., posts, users, and threads) at three different scales. To demonstrate the effectiveness and usefulness of iForum, we describe a case study involving field experts, in which they use iForum to investigate real MOOC forum data for a course on JAVA programming.