3. The Information Access Process

A person engaged in an information seeking process has one or more goals in mind and uses a search system as a tool to help achieve those goals. Goals requiring information access can range quite widely, from finding a plumber to keeping informed about a business competitor, from writing a publishable scholarly article to investigating an allegation of fraud.

Information access tasks are used to achieve these goals. These tasks span the spectrum from asking specific questions to exhaustively researching a topic. Other tasks fall between these two extremes. A study of business analysts [oday93] found three main kinds of information seeking tasks: monitoring a well known topic over time (such as researching competitors' activities each quarter), following a plan or stereotyped series of searches to achieve a particular goal (such as keeping up to date on good business practices), and exploring a topic in an undirected fashion (as when getting to know an unfamiliar industry). Although the goals differ, there is a common core revolving around the information seeking component, which is our focus here.

1. Models of Interaction

Most accounts of the information access process assume an interaction cycle consisting of query specification, receipt and examination of retrieval results, and then either stopping or reformulating the query and repeating the process until a perfect result set is found [salton89][shneiderman98]. In more detail, the standard process can be described according to the following sequence of steps (see Figure ):

1.: Start with an information need.
2.: Select a system and collections to search on.
3.: Formulate a query.
4.: Send the query to the system.
5.: Receive the results in the form of information items.
6.: Scan, evaluate, and interpret the results.
7.: Either stop, or,
8.: Reformulate the query and go to step 4.

This simple interaction model (used by Web search engines) is the only model that most information seekers see today. This model does not take into account the fact that many users dislike being confronted with a long disorganized list of retrieval results that do not directly address their information needs. It also contains an underlying assumption that the user's information need is static and the information seeking process is one of successively refining a query until it retrieves all and only those documents relevant to the original information need.

**Figure:** A simplified diagram of the standard model of the information access processes.

In actuality, users learn during the search process. They scan information, read the titles in result sets, read the retrieved documents themselves, viewing lists of topics related to their query terms, and navigating within hyperlinked Web sites. The recent advent of hyperlinks as a pivotal part of the information seeking process makes it no longer feasible to ignore the role of scanning and navigation within the search process itself. In particular, today a near-miss is much more acceptable than it was with bibliographic search, since an information seeker using the Web can navigate hyperlinks from a near-miss in the hopes that a useful page will be a few links away.

The standard model also downplays the interaction that takes place when the user scans terms suggested as a result of relevance feedback, scans thesaurus structures, or views thematic overviews of document collections. It de-emphasizes the role of source selection, which is increasingly important now that, for the first time, tens of thousands of information collections are immediately reachable for millions of people.

Thus, while useful for describing the basics of information access systems, this simple interaction model is being challenged on many fronts [bates89][oday93][borg2][hendry97][cousins97b]. Bates [bates89] proposes the `berry-picking' model of information seeking, which has two main points. The first is that, as a result of reading and learning from the information encountered throughout the search process, the users' information needs, and consequently their queries, continually shift. Information encountered at one point in a search may lead in a new, unanticipated direction. The original goal may become partly fulfilled, thus lowering the priority of one goal in favor of another. This is posed in contrast to the assumption of `standard' information retrieval that the user's information need remains the same throughout the search process. The second point is that users' information needs are not satisfied by a single, final retrieved set of documents, but rather by a series of selections and bits of information found along the way. This is in contrast to the assumption that the main goal of the search process is to hone down the set of retrieved documents into a perfect match of the original information need.

The berry-picking model is supported by a number of observational studies [ellis89][borg2], including that of O'Day and Jeffries [oday93]. They found that the information seeking process consisted of a series of interconnected but diverse searches on one problem-based theme. They also found that search results for a goal tended to trigger new goals, and hence search in new directions, but that the context of the problem and the previous searches was carried from one stage of search to the next. They also found that the main value of the search resided in the accumulated learning and acquisition of information that occurred during the search process, rather than in the final results set.

Thus, a user interface for information access should allow users to reassess their goals and adjust their search strategy accordingly. A related situation occurs when users encounter a `trigger' that causes them to pursue a different strategy temporarily, perhaps to return to the current unfinished activity at a later time. An implication of these observations is that the user interface should support search strategies by making it easy to follow trails with unanticipated results. This can be accomplished in part by supplying ways to record the progress of the current strategy and to store, find, and reload intermediate results, and by supporting pursuit of multiple strategies simultaneously.

The user interface should also support methods for monitoring the status of the current strategy in relation to the user's current task and high-level goals. One way to cast the activity of monitoring the progress of a search strategy relative to a goal or subgoal is in terms of a cost/benefit analysis, or an analysis of diminishing returns [russell93]. This kind of analysis assumes that at any point in the search process, the user is pursuing the strategy that has the highest expected utility. If, as a consequence of some local tactical choices, another strategy presents itself as being of higher utility than the current one, the current one is (temporarily or permanently) abandoned in favor of the new strategy.

There are a number of theories and frameworks that contrast browsing, querying, navigating, and scanning along several dimensions [belkin93][chang93][march][waterworth91]. Here we assume that users scan information structure, be it titles, thesaurus terms, hyperlinks, category labels, or the results of clustering, and then either select a displayed item for some purpose (to read in detail, to use as input to a query, to navigate to a new page of information) or formulate a query (either by recalling potential words or by selecting categories or suggested terms that have been scanned). In both cases, a new set of information is then made viewable for scanning. Queries tend to produce new, ad hoc collections of information that have not been gathered together before, whereas selection retrieves information that has already been composed or organized. Navigation refers to following a chain of links, switching from one view to another, toward some goal, in a sequence of scan and select operations. Browsing refers to the casual, mainly undirected exploration of information structures, and is usually done in tandem with selection, although queries can also be used to create subcollections to browse through. An important aspect of the interaction process is that the output of one action should be easily used as the input to the next.

2. Non-Search Parts of the Information Access Process

The O'Day and Jeffries study [oday93] found that information seeking is only one part of the full work process their subjects were engaged in. In between searching sessions many different kinds of work was done with the retrieved information, including reading and annotating [ohara97] and analysis. O'Day and Jeffries examined the analysis steps in more detail, finding that 80% of this work fell into six main types: finding trends, making comparisons, aggregating information, identifying a critical subset, assessing, and interpreting. The remaining 20% consisted of cross-referencing, summarizing, finding evocative visualizations for reports, and miscellaneous activities. The Sensemaking work of Russell et al. [russell93] also discusses information work as a process in which information retrieval plays only a small part. They observe that most of the effort made in Sensemaking is in the synthesis of a good representation, or ways of thinking about, the problem at hand. They describe the process of formulating and crystallizing the important concepts for a given task.

From these observations it is convenient to divide the entire information access process into two main components: search/retrieval, and analysis/synthesis of results. User interfaces should allow both kinds of activity to be tightly interwoven. However, analysis/synthesis are activities that can be done independently of information seeking, and for our purposes it is useful to make a distinction between the two types of activities.

3. Earlier Interface Studies

The bulk of the literature on studies of human-computer information seeking behavior concerns information intermediaries using online systems consisting of bibliographic records (e.g., [markey82][saracevic88][borg1]), sometimes with costs assessed per time unit. Unfortunately, many of the assumptions behind those studies do not reflect the conditions of modern information access [hancock-beaulieu92b][drabenstott96]. The differences include the following:

The text being searched now is often full text rather than bibliographic citations. Because users have access to full text, rather than document surrogates, it is more likely that simple queries will find relevant answers directly as part of the search process.
Modern systems use statistical ranking (which is more effective when abstracts and full text are available than when only titles and citations are available) whereas most studies were performed on Boolean systems.
Much of modern searching is done by end users, many new to online searching, rather than professional intermediaries, which were the focus of many of the earlier studies.
Tens of thousands of sources are now available online on networked information systems, and many are tightly coupled via hyperlinks, as opposed to being stored in separate collections owned by separate services. Earlier studies generally used systems in which moving from one collection to another required prior knowledge of the collections and considerable time and effort to switch. A near miss is much more useful in this hyperlinked environment than in earlier systems, since hyperlinks allow users to navigate from the near miss directly to the source containing information of interest. In a card catalog environment, where documents are represented as isolated units, a near miss consists of finding a book in the general area of interest and then going to the bookshelf in the library to look for related books, or obtaining copies of many issues of a journal and scanning for related articles.
Finally, most users have access to bit-mapped displays allowing for direct manipulation, or at least form fillin. Most earlier studies and bibliographic systems were implemented on TTY displays, which require command-line based syntax and do a poor job of retaining context.

Despite these significant differences, some general information seeking
strategies have been identified that seem to transfer across systems. Additionally, although modern systems have remedied many of the problems of earlier online public access catalogs, they also introduce new problems of their own.

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