This study deals with the problems users encounter in their daily work with computers and the typical practices that they employ. Sixteen daily computer users were interviewed about their habits and problems that they encountered during document classification and retrieval. For both these areas, we provide an overview of identified user practices and a citation-based analysis of the problems users encountered, including those related to the use of the screen real estate (the actual desktop). Two types of problems were identified: (1) Problems that concern the actual use of the system installed on the computer. (2) Problems that arise when people realise that they are using a system that does not allow for the desired work or organizational functions sought. We were able to show that skill continues to be an important factor with respect to the ease of using today’s systems. We suggest the following necessary improvements for the evolution of personal information systems: A storage facility that represents the user’s view of information; replacing pure technical file metadata with more user-friendly attributes; and introduction of annotations as a new information type.

Abstract. The use of multiple monitors for personal desktop computing is becoming more prevalent as the price of display technology decreases. The use of two monitors for a single desktop has been shown to have performance improvement in several studies. However, few studies have been performed with more than three monitors. As a result, we report an observational analysis of the use of a large tiled display containing nine monitors (in a 3x3 matrix). The total resolution of the large display is 3840x3072, for a total of 11,796,480 pixels. Over the course of six months we observed the behavior and actions of five users who used the display extensively as a desktop, and of 65 people who used the display during three other controlled experiments. We relate our observations, provide feedback concerning common usage of how people do and do not use the display, provide common scenarios and results of interviews, and give a series of design recommendations and guidelines for future designers of applications for high-resolution, tiled displays.

We report on a study of how people look for information within email, files, and the Web. When locating a document or searching for a specific answer, people relied on their contextual knowledge of their information target to help them find it, often associating the target with a specific document. They appeared to prefer to use this contextual information as a guide in navigating locally in small steps to the desired document rather than directly jumping to their target. We found this behavior was especially true for people with unstructured information organization. We discuss the implications of our findings for the design of personal information management tools.

Sometimes people cannot remember the names or locations of things on their computer, but they can remember what other things are associated with them. We created Feldspar, the first system that fully supports this associative retrieval of personal information on the computer. Feldspar’s contributions include (1) an intuitive user interface that allows users to find information by interactively and incrementally specifying multiple levels of associations as retrieval queries, such as: “find the file from the person who I met at an event in May”; and (2) algorithms for collecting the association information and for providing answers to associative queries in real-time. A user study showed that Feldspar is easy to use, and suggested that it might be faster than conventional browsing and searching for these kinds of retrieval tasks. Feldspar could be an important addition to search and browsing tools. Author Keywords Associative information retrieval, personal information

Re-finding information is commonly cited as a problem on the Web. One reason re-finding on the Web is difficult is that while people rely on a considerable amount of context to return to information (e.g., the original path taken to it), the Web makes no guarantee that the context will remain static. The Re:Search Engine is designed to help people return to information in the dynamic environment of the Web by maintaining consistency in the search results it returns across time. For example, if Connie, while looking to purchase a Global Positioning System, found several systems she liked via a search for “GPS”, she would expect to be able to use the same query to locate the exact same systems again. However, simply returning the original result list when she re-issues the query might omit newly available GPS systems that she would like to see. The ideal result list would contain both the systems Connie remembers having seen and high quality new systems. Because people tend to remember little of what is presented in a result list, when a person repeats a query, the Re:Search Engine can preserve what is remembered about the original result set while still presenting new information.

We present a novel system for performing information management in a unified manner. Users currently must manage large amounts of data which may be fragmented across file formats and applications. Our system, called Iolite, attempts to consolidate this information by automatically discovering associations within the data. Iolite uses these associations to provide a unified interface to navigate and operate on this information space.

The way people use computers has changed in recent years, from desktop single-machine settings to many computers and personal assistants in widely different contexts. Personal Document Spaces (PDSs) now tend to span several machines or locii. Moreover, the types and numbers of documents users manipulate have also grown. The advent of pervasive computing will reinforce this trend. In order to develop new approaches to help users manage their PDSs, we must have an idea of what documents they contain are and how these are organized across several locii. We performed an empirical study where the PDSs of eleven users were analyzed in depth, allowing us to extract a thorough characterization of those PDSs, both in terms of structure and contents.

We present Feldspar, the first system that allows people to find personal information on the computer by specifying chains of other information that it is associated with, emulating the information retrieval process of human associative memory. Feldspar’s contributions include (1) a user interface for constructing retrieval queries that consist of multiple levels of associations, such as “find the folder containing the email attachment from the person I met at an event”; and (2) algorithms for collecting the association information and for providing answers to associative queries in real-time. A user study showed that Feldspar is easy to use, and is superior to conventional browsing and searching for these kinds of retrieval tasks. We have reported Feldspar’s implementation and evaluation in our long paper at CHI 2008. Here, our discussion focuses on the design and implementation ideas that we have tried, or are currently investigating. We hope this will stimulate further discussions and help inspire more design ideas. Author Keywords Associative information retrieval, personal information

Within the TENCompetence project we aim to develop and integrate models and tools into an open source infrastructure for the creation, storage and exchange of learning objects, suitable knowledge resources as well as learning experiences. This contribution analyzes the potential of social software tools for providing part of the required functionality, as well as some challenges involved. 1.

In contextual computing, where cues beyond direct user input are used to trigger computation, one of the most daunting challenges is inferring what the user is doing. For the domain of task management, we have developed a new approach to reducing the problem of ambiguity of user action for intelligent systems. We introduce a construct we call an Activity, designed to reduce this ambiguity by providing a meaningful structure for task information that assists users with their work. We present ethnographic research and prototype evaluations to assess the value of the Activity construct from an end-user’s perspective. Our findings suggest that the Activity structure is useful to people and therefore could be exploited for inference. 1