Notebooks for Data Analysis and Visualization: Moving Beyond the Data.

Notebooks are a relatively new way of analyzing data and creating visualizations. They differ from the common graphical user interfaces used for visualization tools in many ways, and have their own strengths and weaknesses. In particular, they allow easy sharing, experimentation, and collaboration, and provide context about the data for different kinds of users. They also integrate modeling, forecasting, and complex analyses directly with the visualization. We believe that notebooks provide a unique and fundamentally new way of working with and understanding data. By laying out their unique properties, we hope to inspire both researchers and practitioners to investigate their many uses, explore their pros and cons, and share their findings.

More Than Meets the Eye: A Closer Look at Encodings in Visualization.

Encoding data visually is at the heart of visualization. We usually assume that encodings are read as specified (i.e., if a bar chart is drawn by the length of the bars based on the data, that is also how we read them). In this paper, we question this assumption and demonstrate that observed encodings often differ from the ones used to specify the visualization. The value of a chart also often comes from higher level derived encodings, and which encodings end up getting used also depends on the user's task.

From Jam Session to Recital: Synchronous Communication and Collaboration Around Data in Organizations.

Prior research on communicating with visualization has focused on public presentation and asynchronous individual consumption, such as in the domain of journalism. The visualization research community knows comparatively little about synchronous and multimodal communication around data within organizations, from team meetings to executive briefings. We conducted two qualitative interview studies with individuals who prepare and deliver presentations about data to audiences in organizations. In contrast to prior work, we did not limit our interviews to those who self-identify as data analysts or data scientists. Both studies examined aspects of speaking about data with visual aids such as charts, dashboards, and tables. One study was a retrospective examination of current practices and difficulties, from which we identified three scenarios involving presentations of data. We describe these scenarios using an analogy to musical performance: small collaborative team meetings are akin to jam session, while more structured presentations can range from semi-improvisational performances among peers to formal recitals given to executives or customers. In our second study, we grounded the discussion around three design probes, each examining a different aspect of presenting data: the progressive reveal of visualization to direct attention and advance a narrative, visualization presentation controls that are hidden from the audience's view, and the coordination of a presenter's video with interactive visualization. Our distillation of interviewees' responses surfaced twelve themes, from ways of authoring presentations to creating accessible and engaging audience experiences.

Generative Design Inspiration for Glyphs with Diatoms.

We introduce Diatoms, a technique that generates design inspiration for glyphs by sampling from palettes of mark shapes, encoding channels, and glyph scaffold shapes. Diatoms allows for a degree of randomness while respecting constraints imposed by columns in a data table: their data types and domains as well as semantic associations between columns as specified by the designer. We pair this generative design process with two forms of interactive design externalization that enable comparison and critique of the design alternatives. First, we incorporate a familiar small multiples configuration in which every data point is drawn according to a single glyph design, coupled with the ability to page between alternative glyph designs. Second, we propose a small permutables design gallery, in which a single data point is drawn according to each alternative glyph design, coupled with the ability to page between data points. We demonstrate an implementation of our technique as an extension to Tableau featuring three example palettes, and to better understand how Diatoms could fit into existing design workflows, we conducted interviews and chauffeured demos with 12 designers. Finally, we reflect on our process and the designers' reactions, discussing the potential of our technique in the context of visualization authoring systems. Ultimately, our approach to glyph design and comparison can kickstart and inspire visualization design, allowing for the serendipitous discovery of shape and channel combinations that would have otherwise been overlooked.

Presentation-Oriented Visualization Techniques.

Data visualization research focuses on data exploration and analysis, yet the vast majority of visualizations people see were created for a different purpose: presentation. Whether we are talking about charts showing data to help make a presenter's point, data visuals created to accompany a news story, or the ubiquitous infographics, many more people consume charts than make them. Traditional visualization techniques treat presentation as an afterthought, but are there techniques uniquely suited to data presentation but not necessarily ideal for exploration and analysis? This article focuses on presentation-oriented techniques, considering their usefulness for presentation first and any other purposes as secondary.

The Connected Scatterplot for Presenting Paired Time Series.

The connected scatterplot visualizes two related time series in a scatterplot and connects the points with a line in temporal sequence. News media are increasingly using this technique to present data under the intuition that it is understandable and engaging. To explore these intuitions, we (1) describe how paired time series relationships appear in a connected scatterplot, (2) qualitatively evaluate how well people understand trends depicted in this format, (3) quantitatively measure the types and frequency of misinter pretations, and (4) empirically evaluate whether viewers will preferentially view graphs in this format over the more traditional format. The results suggest that low-complexity connected scatterplots can be understood with little explanation, and that viewers are biased towards inspecting connected scatterplots over the more traditional format. We also describe misinterpretations of connected scatterplots and propose further research into mitigating these mistakes for viewers unfamiliar with the technique.

GenoSets: visual analytic methods for comparative genomics.

Many important questions in biology are, fundamentally, comparative, and this extends to our analysis of a growing number of sequenced genomes. Existing genomic analysis tools are often organized around literal views of genomes as linear strings. Even when information is highly condensed, these views grow cumbersome as larger numbers of genomes are added. Data aggregation and summarization methods from the field of visual analytics can provide abstracted comparative views, suitable for sifting large multi-genome datasets to identify critical similarities and differences. We introduce a software system for visual analysis of comparative genomics data. The system automates the process of data integration, and provides the analysis platform to identify and explore features of interest within these large datasets. GenoSets borrows techniques from business intelligence and visual analytics to provide a rich interface of interactive visualizations supported by a multi-dimensional data warehouse. In GenoSets, visual analytic approaches are used to enable querying based on orthology, functional assignment, and taxonomic or user-defined groupings of genomes. GenoSets links this information together with coordinated, interactive visualizations for both detailed and high-level categorical analysis of summarized data. GenoSets has been designed to simplify the exploration of multiple genome datasets and to facilitate reasoning about genomic comparisons. Case examples are included showing the use of this system in the analysis of 12 Brucella genomes. GenoSets software and the case study dataset are freely available at http://genosets.uncc.edu. We demonstrate that the integration of genomic data using a coordinated multiple view approach can simplify the exploration of large comparative genomic data sets, and facilitate reasoning about comparisons and features of interest.

Adaptive privacy-preserving visualization using parallel coordinates.

Current information visualization techniques assume unrestricted access to data. However, privacy protection is a key issue for a lot of real-world data analyses. Corporate data, medical records, etc. are rich in analytical value but cannot be shared without first going through a transformation step where explicit identifiers are removed and the data is sanitized. Researchers in the field of data mining have proposed different techniques over the years for privacy-preserving data publishing and subsequent mining techniques on such sanitized data. A well-known drawback in these methods is that for even a small guarantee of privacy, the utility of the datasets is greatly reduced. In this paper, we propose an adaptive technique for privacy preservation in parallel coordinates. Based on knowledge about the sensitivity of the data, we compute a clustered representation on the fly, which allows the user to explore the data without breaching privacy. Through the use of screen-space privacy metrics, the technique adapts to the user's screen parameters and interaction. We demonstrate our method in a case study and discuss potential attack scenarios.

Laws of attraction: from perceptual forces to conceptual similarity.

Many of the pressing questions in information visualization deal with how exactly a user reads a collection of visual marks as information about relationships between entities. Previous research has suggested that people see parts of a visualization as objects, and may metaphorically interpret apparent physical relationships between these objects as suggestive of data relationships. We explored this hypothesis in detail in a series of user experiments. Inspired by the concept of implied dynamics in psychology, we first studied whether perceived gravity acting on a mark in a scatterplot can lead to errors in a participant's recall of the mark's position. The results of this study suggested that such position errors exist, but may be more strongly influenced by attraction between marks. We hypothesized that such apparent attraction may be influenced by elements used to suggest relationship between objects, such as connecting lines, grouping elements, and visual similarity. We further studied what visual elements are most likely to cause this attraction effect, and whether the elements that best predicted attraction errors were also those which suggested conceptual relationships most strongly. Our findings show a correlation between attraction errors and intuitions about relatedness, pointing towards a possible mechanism by which the perception of visual marks becomes an interpretation of data relationships.

Pargnostics: screen-space metrics for parallel coordinates.

Interactive visualization requires the translation of data into a screen space of limited resolution. While currently ignored by most visualization models, this translation entails a loss of information and the introduction of a number of artifacts that can be useful, (e.g., aggregation, structures) or distracting (e.g., over-plotting, clutter) for the analysis. This phenomenon is observed in parallel coordinates, where overlapping lines between adjacent axes form distinct patterns, representing the relation between variables they connect. However, even for a small number of dimensions, the challenge is to effectively convey the relationships for all combinations of dimensions. The size of the dataset and a large number of dimensions only add to the complexity of this problem. To address these issues, we propose Pargnostics, parallel coordinates diagnostics, a model based on screen-space metrics that quantify the different visual structures. Pargnostics metrics are calculated for pairs of axes and take into account the resolution of the display as well as potential axis inversions. Metrics include the number of line crossings, crossing angles, convergence, overplotting, etc. To construct a visualization view, the user can pick from a ranked display showing pairs of coordinate axes and the structures between them, or examine all possible combinations of axes at once in a matrix display. Picking the best axes layout is an NP-complete problem in general, but we provide a way of automatically optimizing the display according to the user’s preferences based on our metrics and model.

The shaping of information by visual metaphors.

The nature of an information visualization can be considered to lie in the visual metaphors it uses to structure information. The process of understanding a visualization therefore involves an interaction between these external visual metaphors and the user's internal knowledge representations. To investigate this claim, we conducted an experiment to test the effects of visual metaphor and verbal metaphor on the understanding of tree visualizations. Participants answered simple data comprehension questions while viewing either a treemap or a node-link diagram. Questions were worded to reflect a verbal metaphor that was either compatible or incompatible with the visualization a participant was using. The results (based on correctness and response time) suggest that the visual metaphor indeed affects how a user derives information from a visualization. Additionally, we found that the degree to which a user is affected by the metaphor is strongly correlated with the user's ability to answer task questions correctly. These findings are a first step towards illuminating how visual metaphors shape user understanding, and have significant implications for the evaluation, application, and theory of visualization.

Legible cities: focus-dependent multi-resolution visualization of urban relationships.

Numerous systems have been developed to display large collections of data for urban contexts; however, most have focused on layering of single dimensions of data and manual calculations to understand relationships within the urban environment. Furthermore, these systems often limit the userâs perspectives on the data, thereby diminishing the userâs spatial understanding of the viewing region. In this paper, we introduce a highly interactive urban visualization tool that provides intuitive understanding of the urban data. Our system utilizes an aggregation method that combines buildings and city blocks into legible clusters, thus providing continuous levels of abstraction while preserving the userâs mental model of the city. In conjunction with a 3D view of the urban model, a separate but integrated information visualization view displays multiple disparate dimensions of the urban data, allowing the user to understand the urban environment both spatially and cognitively in one glance. For our evaluation, expert users from various backgrounds viewed a real city model with census data and confirmed that our system allowed them to gain more intuitive and deeper understanding of the urban model from different perspectives and levels of abstraction than existing commercial urban visualization systems.

Parallel sets: interactive exploration and visual analysis of categorical data.

Categorical data dimensions appear in many real-world data sets, but few visualization methods exist that properly deal with them. Parallel Sets are a new method for the visualization and interactive exploration of categorical data that shows data frequencies instead of the individual data points. The method is based on the axis layout of parallel coordinates, with boxes representing the categories and parallelograms between the axes showing the relations between categories. In addition to the visual representation, we designed a rich set of interactions. Parallel Sets allow the user to interactively remap the data to new categorizations and, thus, to consider more data dimensions during exploration and analysis than usually possible. At the same time, a metalevel, semantic representation of the data is built. Common procedures, like building the cross product of two or more dimensions, can be performed automatically, thus complementing the interactive visualization. We demonstrate Parallel Sets by analyzing a large CRM data set, as well as investigating housing data from two US states.

Tracing the formalization steps of textual guidelines.

This paper presents a new guideline authoring tool, called Guideline Markup Tool (GMT). It proposes two useful features, which are missing in existing tools. First, it facilitates the translation of a free-text guideline into a formal representation, providing special XML macros. Second, it can be used to create links between the original guideline and its formal representation. Therefore, the GMT eases the implementation of clinical guidelines in a formal representation, which can be used in monitoring and therapy planning systems.

Facilitating knowledge maintenance of clinical guidelines and protocols.

Clinical protocols and guidelines are widely used in the medi-cal domain to improve disease management techniques. Different software systems are in development to support the de-sign and the execution of such guidelines. The bottleneck in the guideline software developing process is the transformation of the text-based clinical guidelines into a formal representation, which can be used by the execution software. This paper introduces a method and a tool that was designed to provide a solution for that bottleneck. The so-called Guideline Markup Tool (GMT) facilitates the translation of guidelines into a formal representation written in XML. This tool enables the protocol designer to create links between the original guideline and its formal representation and ease the editing of guidelines applying design patterns in the form of macros. The usefulness of our approach is illustrated using GMT to edit Asbru protocols. We performed a usability study with eight participants to examine the usefulness of the GMT and of the Asbru macros, which showed that the proposed approach is very appropriate to author and maintain clinical guidelines.

Visualization methods for data analysis and planning in medical applications.

Time plays an important role in medicine, both the past and the future. The medical history of a patient represents the past, which needs to be understood by the physician to make the right decisions. The past contains two different kinds of information: measured data (such as blood pressure) and incidents (such as seizures). Planning therapies, on the other hand, requires looking into the future to a certain extent. Visual representations exist for both the past and the future, and they are very useful for getting a better understanding of data or a plan. This paper surveys visualization techniques for both data analysis and planning, and compares them based on a number of criteria.