Zoomable Graphical Sketchpad
Imagine a computer screen made of a sheet of a miraculous new material that is stretchable like rubber, but continues to display a crisp computer image, no matter what the sheet's size. Imagine that this sheet is very elastic and can stretch orders of magnitude more than rubber. Further, imagine that vast quantities of information are represented on the sheet, organized at different places and sizes. Everything you do on the computer is on this sheet. To access a piece of information you just stretch to the right part, and there it is.
Imagine further that special lenses come with this sheet that let you look onto one part of the sheet while you have stretched another part. With these lenses, you can see and interact with many different pieces of data at the same time that would ordinarily be quite far apart. In addition, these lenses can filter the data in any way you would like, showing different representations of the same underlying data. The lenses can even filter out some of the data so that only relevant portions of the data appear.
Imagine also new stretching mechanisms that provide alternatives to scaling objects purely geometrically. For example, instead of representing a page of text so small that it is unreadable, it might make more sense to present an abstraction of the text, perhaps just a title that is readable. Similarly, when stretching out a spreadsheet, instead of showing huge numbers, it might make more sense to show the computations from which the numbers were derived or a history of interaction with them.
The beginnings of an interface like this sheet exists today in a program we call Pad++. We don't really stretch a huge rubber-like sheet, but we simulate it by zooming into the data. We use what we call portals to simulate lenses, and a notion we call semantic zooming to scale data in non-geometric ways. The user controls where they look on this vast data surface by panning and zooming. Portals are objects on the Pad++ data surface that can see anywhere on the surface, as well as filter data to represent it differently than it normally appears.
Panning and zooming allow navigation through a large information space via direct manipulation. By tapping into people's natural spatial abilities, we hope to increase users' intuitive access to information. Conventional computer search techniques are also provided in Pad++, bridging traditional and new interface metaphors. Figure 1 depicts a sequence of views as we pan and zoom into some data.
Figure1: A sequence of views as we zoom into some data.
If interface designers are to move beyond windows, icons, menus, and pointers to explore a larger space of interface possibilities, additional ways of thinking about interfaces that go beyond the desktop metaphor are required. The exploration of virtual 3D worlds is one alternative. It follows quite naturally from traditional direct manipulation approaches to interface design and involves similar underlying metaphors, although they are enriched by the greater representational possibilities afforded by moving to richer 3D worlds.
There are myriad benefits associated with metaphor-based approaches, but they also orient designers to employ computation primarily to mimic mechanisms of older media. While there are important cognitive, cultural, and engineering reasons to exploit earlier successful representations, this approach has the potential of underutilizing the mechanisms of new media.
For the last few years we have been exploring a different strategy [22] for interface design to help focus on novel mechanisms enabled by computation rather than on mimicking mechanisms of older media. Informally, the strategy consists of viewing interface design as the development of a physics of appearance and behavior for collections of informational objects.
For example, an effective informational physics might arrange for an object's representation to be a natural by-product of normal activity. This is similar to the physics of certain materials that evidence the wear associated with use. Such wear records a history of use and at times this can influence future use in positive ways. Used books crack open at often referenced places. Frequently consulted papers are at the tops of piles on our desks. Usage dog-ears the corners and stains the surface of index cards and catalogs. All these wear marks provide representational cues as a natural product of doing, but the physics of materials limit what can be recorded and the ways it can influence future use.
Following an informational physics strategy has led us to explore history-enriched digital objects [19][20]. Recording on objects (e.g. reports, forms, source-code, manual pages, email, spreadsheets) the interaction events that comprise their use makes it possible on future occasions, when the objects are used again, to display graphical abstractions of the accrued histories as parts of the objects themselves. For example, we depict the copy history on source code. This allows a developer to see that a particular section of code has been copied and perhaps be led to correct a bug not only in the piece of code being viewed but also in the code from which it was derived.
This informational physics strategy has also lead us to explore new physics for interacting with graphical data. As part of that exploration we have formed a research consortium to design a successor to Pad [26]. This new system, Pad++, serves as a substrate for exploration of novel interfaces for information visualization and browsing in complex information-intensive domains. The system is being designed to operate on platforms ranging from high-end graphics workstations to PDAs (Personal Digital Assistants) and interactive set-top cable boxes. Here we describe the motivation behind the Pad++ development, report the status of the current implementation, and present initial prototype applications.
Today there is much more information available than we can readily and effectively access. The situation is further complicated by the fact that we are on the threshold of a vast increase in the availability of information because of new network and computational technologies. Paradoxically, while we continuously process massive amounts of perceptual data as we experience the world, we have perceptual access to very little of the information that resides within our computing systems or that is reachable via network connections. In addition, this information, unlike the world around is, is rarely presented in ways that reflect either its rich structure or dynamic character.
We envision a much richer world of dynamic persistent informational entities that operate according to multiple physics specifically designed to provide cognitively facile access. These physics need to be designed to exploit semantic relationships explicit and implicit in information-intensive tasks and in our interaction with these new kinds of computationally-based work materials.
One physics central to Pad++ supports viewing information at multiple scales and attempts to tap into our natural spatial ways of thinking. We address the information presentation problem of how to provide effective access to a large structure of information on a much smaller display. Furnas [16] explored degree of interest functions to determine the information visible at various distances from a central focal area. There is much to recommend the general approach of providing a central focus area of detail surrounded by a periphery that places the detail in a larger context.
With Pad++ we have moved beyond the simple binary choice of presenting or eliding particular information. We can also determine the scale of the information and, perhaps most importantly, the details of how it is rendered can be based on various semantic and task considerations that we describe below. This provides semantic task-based filtering of information that is similar to the early work at MCC on lens-based filtering of a knowledge base using HITS [21] and the recent work of moveable filters at Xerox [4][31].
The ability to make it easier and more intuitive to find specific information in large dataspaces is one of the central motivations behind Pad++. The traditional approach is to filter or recommend a subset of the data, hopefully producing a small enough dataset for the user to effectively navigate. Pad++ is complementary to these filtering approaches in that it promises to provide a useful substrate to structure information.
Copyright Computer Science Department, The University of New Mexico