We present GEM-NI -- a graph-based generative-design tool that supports parallel exploration of alternative designs. Producing alternatives is a key feature of creative work, yet it is not strongly supported in most extant tools. GEM-NI enables various forms of exploration with alternatives such as parallel editing, recalling history, branching, merging, comparing, and Cartesian products of and for alternatives. Further, GEM-NI provides a modal graphical user interface and a design gallery, which both allow designers to control and manage their design exploration. We conducted an exploratory user study followed by in-depth one-on-one interviews with moderately and highly skills participants and obtained positive feedback for the system features, showing that GEM-NI supports creative design work well.

Data surrounds each and every one of us in our daily lives, ranging from exercise logs, to archives of our interactions with others on social media, to online resources pertaining to our hobbies. There is enormous potential for us to use these data to understand ourselves better and make positive changes in our lives. Visualization (Vis) and visual analytics (VA) offer substantial opportunities to help individuals gain insights about themselves, their communities and their interests; however, designing tools to support data analysis in non-professional life brings a unique set of research and design challenges. We investigate the requirements and research directions required to take full advantage of Vis and VA in a personal context. We develop a taxonomy of design dimensions to provide a coherent vocabulary for discussing personal visualization and personal visual analytics. By identifying and exploring clusters in the design space, we discuss challenges and share perspectives on future research. This work brings together research that was previously scattered across disciplines. Our goal is to call research attention to this space and engage researchers to explore the enabling techniques and technology that will support people to better understand data relevant to their personal lives, interests, and needs.

Scripting has become an integral part of design work in Computer-Aided Design (CAD), especially with parametric systems. Designers who script face a very steep learning and use curve due to the new (to them) script notation and the loss of direct manipulation of the model. Programming In the Model (PIM) is a prototype parametric CAD system with a live interface with side-by-side model and script windows; real-time updating of the script and the model; on-demand dependency, object and script representations in the model; and operation preview (lookahead). These features aim to break the steep learning and use curve of scripting into small steps and to bring programming and modeling tasks `closer together.' A qualitative user study with domain experts shows the importance of multi-directional live scripting and script localization within the model. Other PIM features show promise but require additional design work to create a better user experience.

We introduce a propagation-based parametric symbolic model approach to supporting analytic provenance. This approach combines a script language to capture and encode the analytic process and a parametrically controlled symbolic model to represent and reuse the logic of the analysis process. Our approach first appeared in a visual analytics system called CZSaw. Using a script to capture the analyst’s interactions at a meaningful system action level allows the creation of a parametrically controlled symbolic model in the form of a Directed Acyclic Graph (DAG). Using the DAG allows propagating changes. Graph nodes correspond to variables in CZSaw scripts, which are results (data and data visualizations) generated from user interactions. The user interacts with variables representing entities or relations to create the next step’s results. Graph edges represent dependency relationships among nodes. Any change to a variable triggers the propagation mechanism to update downstream dependent variables and in turn updates data views to reflect the change. The analyst can reuse parts of the analysis process by assigning new values to a node in the graph. We evaluated this symbolic model approach by solving three IEEE VAST Challenge contest problems (from IEEE VAST 2008, 2009, and 2010). In each of these challenges, the analyst first created a symbolic model to explore, understand, analyze, and solve a particular subproblem and then reused the model via its dependency graph propagation mechanism to solve similar subproblems. With the script and model, CZSaw supports the analytic provenance by capturing, encoding, and reusing the analysis process. The analyst can recall the chronological states of the analysis process with the CZSaw script and may interpret the underlying rationale of the analysis with the symbolic model.

In this paper, the effects of design-task specificity level on design space exploration are studied. An experiment was conducted to study the effects of goals and methods on design process and design solutions by 16 individual designers, who performed two design tasks under different combination of design goal and method specifications. Protocol analysis and outcome-based analysis were carried out. The results of the outcome-based analysis reveal that the quality of the design solutions can greatly be affected by goal specificity level of a design task, whereas in case of quantity, novelty and designer's self satisfaction level, the effects are insignificant. None of these metrics showed significant influence of method specificity levels of a design task. The process-based analysis on the other hand, reveals some interesting search behaviors in parametric systems, which are then used to explain the possible reasons for insignificance in quantitative data.

The NEAR (navigating exhibitions, annotations and resources) panel is a method of managing digital collections and user preferences through collaborative filtering and graphically revealing implicit data relations such as sharing, reference and similarity. It is implemented on AldrVIldrRE, an online multimedia repository. AldrVIldrRE supports semi-structured collections (exhibitions) which containing various resources and annotations. Its users are encouraged to contribute, share, annotate and interpret resources. Similar to the act of adding items into shopping carts in the e-commence applications, a user's activities of searching, organizing and interpreting data in AldrVIldrRE are considered as evidence of user's preferences. The design process of NEAR was guided by several principles from the visualization literature. It implements new navigation and communication approaches that support discovery of relations. Having tested NEAR with several users, we further analyze the design, report the evaluation and consider its use in other applications.