Visualizing Writing Activity as Knowledge Work: Challenges & Opportunities William Hart-Davidson
Clay Spinuzzi
Mark Zachry
Michigan State University Suite 7 Olds Hall East Lansing, MI 48824 517-432-2560
University of Texas at Austin 1 University Station B5500 Austin, TX 78712-1122 512-471-8707
University of Washington Box 352195 Seattle, WA 98195 USA 206-616-7936
[email protected]
[email protected]
[email protected]
depiction of a project plan, to a data-display that illuminates a multi-document process can be commonplace when a writer’s goal is to strategize about the best way to approach their work.
ABSTRACT Digital environments enable distributed work. Though they pose challenges for research, they also provide affordances for addressing these difficulties including opportunities to capture and visualize writing activity in significant detail. This paper surveys sources of visualizations of writing processes and practices, focusing on attempts to deal with writing as a distributed activity. We then ask: what qualities of visualizations seem desirable and help to render writing visible as knowledge work for the purpose of providing mediational support to writers?
But even in the best of situations, writers can experience the distributed nature of writing activity as fragmentation. A tremendous challenge faces those for whom writing is a key aspect of work that must be learned, improved, monitored for quality, or simply better understood: how can we “see” and understand writing practices and patterns that take place across temporal, spatial, personal and system boundaries? While the widespread use of networked information technologies makes this question more urgent, the problem of writing as distributed activity is not a new one. Researchers in composition studies have dealt with the issue of temporally distributed practices in writing for quite some time [1], [2], and some have recently attended to issues of space and place as well. Researchers in technical and professional writing have concentrated on the distributed nature of writing in organizations, focusing on the collaborative and social aspects of writing as it underpins crucial organizational functions and goals. Along the way, these researchers have given us representations of writing practices and processes meant to reveal structure and, generally, to deal with the problem of “seeing” the complexities of writing by visualizing writing activity.
Categories and Subject Descriptors K.4.3 [Computers and Society]: Organizational Impacts – Computer-supported collaborative work.
General Terms Documentation, Design, Theory.
Keywords Qualitative research, visualization, communicative event models, writing.
genre
ecologies,
1. WRITING AS DISTRIBUTED ACTIVITY The distributed nature of writing activity that takes place within and across information systems is a powerful, yet difficult feature to harness. Content management practices and the systems that support these provide some of the most coherent attempts to make distributed writing activity understandable and useful. Views of texts that include version histories, for example, can allow members of a team to see who contributed to a text during a particular period of time. Workflow functions can show how a particular type of document should move from its inception through revision and review cycles and beyond. Shifting perspectives from an individual document, to a
2. THREE TYPES OF WRITING VISUALIZATIONS: ARTIFACT-BASED, RESEARCH-BASED, MANAGEMENTBASED Researchers are not the only ones who provide visualizations of writing activity in an attempt to render it more readily understandable. Our work environments also provide views of writing activity. And writers, themselves, construct pictures and diagrams of their work as self-mediational resources. In this section, we discuss three types of visualizations of writing activity that attempt to deal with the problems of seeing writing that is distributed across time, space, people, artifacts and systems: research, artifact, and management-based views. Selfgenerated views of writing activity can be of any of these types and likely combine them, in fact, to produce useful resources for writers to reason about their work or explain it to others.
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We do not mean to suggest, that research-based views have no value, to do so would be to put ourselves out of a job! But we do want to note that the value these views hold for writers engaged in the day-to-day work of writing is limited at best.
2.1 Research-Based Views of Writing The most familiar views of writing processes for academic audiences are those generated by researchers. These can take a variety of forms, but they generally aim to consolidate and represent data collected from observing or otherwise studying individual instances of writing activity. As such, they are either detailed portraits of a single activity, or more often, representations of the regularities of writing activity across multiple instances.
2. 2 Artifact-Based Views of Writing On the other end of the spectrum from research-based views in terms of value for users are what we will call “artifact-based” views of writing activity. By “artifact-based” we mean the views of writing that are made by the tools we use to create, manipulate, access, and distribute texts and to manage writing activity. These are likely to be the most common views that writers access on a daily basis, and they may not even be recognized as views of work or work practices as such.
Perhaps the best well known representation of the writing process is the cognitive process model of writing by Flower & Hayes [1] (fig. 1), though many others are also notable for the ways they try to depict stabilities in otherwise complex and distributed processes.
For example, the screen shot in Fig. 2 shows a web-based e-mail application displaying the contents of a folder called “holding tank.” This is a location that one of the authors [Bill] uses to temporarily store messages that represent action items. Because he only uses this particular e-mail tool when he is away from his own computer, the “holding tank” represents a running list of items to incorporate into his other task-management tools when he returns to his own machine. Items with an “R” indicate that he has replied to the sender of the original message to acknowledge receipt, but the presence of the message itself in the “holding tank” folder means that some additional follow up is needed when he is able to work on his own computer again.
Task Environment Text produced so far
Assignment Topic, Audience, Motivating Cues
Long Term Memory
Knowledge of Topic Writing plans
Writing Process Planning generating
Knowledge of Audience
Translating
reading
Reviewing evaluating
goal setting
editing Monitor
Fig. 1 Flower & Hayes’ Cognitive Process Model of Writing Spilka [3], for example, modifies the Flower & Hayes model to include multiple actors as well as oral communication. Cross [4] maps writing activities in an organizational department according to where key events happen in the building, using a floor plan to depict the spatial area and relationships among workers’ roles and actions. These are just a few examples. The valuable researchbased visualizations of writing activity are too numerous to mention here, of course. What we would like to point out, however is that in nearly all cases, research-based views best serve the researcher who is trying to make an argument about what their data shows or what the implications of their findings are. Other researchers might also find these visualizations powerful for the way they represent or challenge a theory of writing, or the paths they may open up for further research. But research-based views are not typically very useful for writers themselves. Those views that act as consolidations of practice are typically too abstract to be of much use in specific writing situations. We can think of no situation, for example, where a writer would consult the Flower & Hayes process diagram before or during a writing project. Likewise, specific and detailed portraits of single writing activities are typically not very useful for reasoning about future action, particularly if the writer has had no involvement in the previous activity rendered in the portrait.
Fig. 2 Web mail screen showing contents of “holding tank” folder The “holding tank” view is a view of writing activity that has been completed as well as activity that awaits Bill. That is, a view of his work. The existence of this view saves him from remembering everything he must do upon returning to his computer, and he is grateful for it! But the view, as a view of work, has some limitations as well. For one, it is not comprehensive. This particular application only allows a limited number of items to be displayed on the screen at once, so there is no way to see all of the messages that await further action on a
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single screen if the total number exceeds this maximum allowed by the application. And while the “R” indicates that some reply has been made to a message, there is no further indication of the status of each message as a work item or a “to do” – that information has to be remembered, accessed in another view if it was written as part of the response, or stored in some other system.
3. Challenges in Representing Writing Activity in Ways That Support Writers’ Reasoning About Work We understand the limitations of management, artifact, and research-based views of writing to be related to writers’ needs for information when reasoning about their own work. Management and research-based views enable reasoning about writing practices and processes, but they do so for groups (researchers and managers) whose interests in doing so may not neatly coincide with those of writers. Artifact based views of writing practice may in fact enable reasoning about work by writers, but they are not often designed to do this and so affordances that are broadly available to knowledge workers in other domain-specific IT-enabled work settings may not be available to writers. We nonetheless have much to learn from all three types of views as we consider how to support writers’ reasoning about their work. As a preliminary step in providing views of writing practice that are specifically designed to support this type of reasoning we turn our attention in this section to three specific challenges that our currently available visualization methods help us to identify and begin to address.
To be fair, these limitations are all due to the fact that the e-mail application was not designed to provide views of writing activity. But it does just the same, and because it does Bill can use the application in ways that take advantage of the visualizations that are helpful in managing his work.
2.3 Management-based Views of Writing Management-based views of writing visualize projects for the explicit purpose of managing the distribution of tasks and subtasks over time, across team members, and in accordance with particular goals. GANTT and PERT charts are typical examples of these, as are flow charts and swimlane diagrams. None of these formats are limited to depicting writing activity, of course, and so they can be especially useful for showing how the tasks associated with writing and the written deliverables of a project fit together with other types of outcomes.
3.1 Practice vs. Process: How to help writers identify and leverage patterns in their work High-level, abstracted views of writing processes such as the diagram in Fig.1 do not provide much mediational support for writers working on a specific project. These diagrams lack specific information about documents, media types, genres, writers, readers, locations, deadlines – all the things that represent decisions that writers must make or, in the case of previous projects, have made. This level of detail is better represented by depictions of writing practices – recollections or aggregations of events, objects, people, transactions, etc. – than by depictions of processes that tend to look across specific instances to find patterns in practice. One reason why depictions of practice are more valuable for writers has as much or more to do with when they might consult them than with what it is being shown. Writers look at depictions of their work when they are actually working: on an ongoing project, or when planning a new project that requires them to recollect some work they may have done in the past. The questions they bring to views of practice reflect reasoning about project goals: what should I be doing next? What kinds of resources might I draw upon to complete the document I am currently working on? Who can I talk to in my organization for help with this type of writing task?
Fig. 3 A relentlessly linear GANTT chart [6] But as Fig. 3 demonstrates ad absurdum, the goals of management-oriented views is as much to plan projects for maximum efficiency as it is to represent what has happened or is happening “on the ground” [5] Management-based views can be fed with real-time data to function as status-monitoring tools, but they often are not. Even when they are, the resulting views may not be very valuable for individual writers because, in the end, they are meant to answer questions for project managers. They often lack representations of project artifacts that are not deliverables, making views of “tasks” reflections or projections of work rather than the resources to actually do work.
Detailed views of writing practice can provide very rich representations of work, as the drawings elicited in a study by Prior & Shipka [7] demonstrate. In the research-based depictions of practice that resulted from prompting participants to draw their writing process, Prior & Shipka’s participants depict not only texts and their development, but also the physical and emotional conditions that give rise to those texts. The pictures show images of people, technologies, food, pets, exterior and interior locations, and they depict the actions and flow of writing practices in both realistic and metaphorical terms. For Prior & Shipka, the rich representations of writing practice stimulated recall and acted as
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answer a different question. Each event has multiple metadata categories, and the value of any of these could conceivably be used to create different sorts that aid reasoning about work. Sorting by project type, for example, might produce a diagram that helped users to see how much of their total writing activity for a given two week period was devoted to grant writing as opposed to other types of projects.
beginning points to think carefully and in complex ways about literate activity with their study participants. As tools for writers, these kinds of accounts might be of slightly less value. Each depiction is detailed in interesting but arbitrary ways, making individual accounts difficult to compare with one another to answer questions that writers might have like: “what kinds of things have I done that lead to a successful outcome?” Or even, “just how much report writing have I done in the last year?” The ambiguities in the drawings are even more problematic if they are meant to be shared with others as resources for reasoning about work. Are the figures that represent people in the diagram representations of the author? Are they even representative of the same person or people each time they appear? Is the drawing as a whole a first person account, an omniscient third person account? Etc.
The CEM is not perfect. But it is a step toward building a visualization method where multiple, interactive portraits of work practices could be generated from user-supplied information. The CEM is at best a partial picture of writing activity and an even more partial picture of knowledge work. It does not yet contain all of the affective and extra-textual information that appear in Prior & Shipka’s participant’s diagrams, for example. But we can imagine asking for affective ratings to show – perhaps by using color-coding – how an individual or team member felt about a particular moment in a project. We can even imagine asking users to substitute arbitrary images for our standard icons where it helps them to do so.
None of these issues is a problem for Prior & Shipka, of course, because the drawings are acting as resources for an interview process. But it is clear to us that while the depictions of practice, the richer the better, are good tools for reasoning about individual instances of writing, some shared visual language conventions are required if the reasoning about work extends beyond a single writer and across accounts of projects. This would ensure that as writers build visual accounts of practice, enough similarity in the means of constructing these accounts exists to allow patterns or trends to be visible.
3.2 Looking back to look ahead: Helping writers construct tractable accounts of work in order to answer key questions Providing visualizations that aid writers in reasoning about their work requires a means to elicit, structure, aggregate and represent historical information – individual reflections, machine-generated logs, - in order to facilitate reflection and guide decision-making. How should we do these things? The richer the accounts we begin with, the more data we have to construct visualizations from. But the most comprehensive methods for capturing accounts of work – screen capture and/or event-logging software on a writer’s machine, for example, or videotaped work sessions showing writers working – produce huge data sets that must be filtered and reduced if they are to be used effectively by writers in reasoning about their own work. Nobody wants to watch a full-motion recording of themselves writing back in real time. And it is not clear what could be gained from doing this in any case.
The image in Fig. 4 depicts a visualization format developed by the authors called a Communication Event Model [8,9]. Here, specific communication events (written and oral) leading up to the creation of a particular target document are depicted iconically, produced from an event log kept by a grant writer.
proposal e-mail
2/21
IM
active genres
2/22
2/23
f2f
One solution to this problem is to narrow the range of activity that historical data is collected about. A commonly available artifactbased view of writing activity in many word-processing packages, for example, allows users to see changes made by multiple writers to a specific document. By using a feature like “track changes” in Microsoft Word, writers who are co-authoring a document can leave a visual trail of changes they have made for others coming after them to see.
key writing document
2/24
f2f
E-mail, web forms, web editing note-taking, planning
2/28
f2f 3/2
conversation
ph
This narrow view of writing activity, limited to a single document or document type produced in a specific software environment, does not provide the sort of comprehensive views of practice discussed earlier. Quite a lot of information is missing, in fact, from these views regarding what other texts, conversations, etc. might have influenced changes to a specific document.
Fig. 4 Communication Event Model: One Week of Grant Seeking The two dimensional display of communication events is meant to help users answer common questions about their work with simple visual logics. The model depicted in Fig. 4 sorts events related to grant writing for a chosen two-week period by day, with each new day that an event occurred beginning a new horizontal line on the diagram. This diagram answers a question like “what grant writing work have I done in the last two weeks?” A new sort of the events could produce a different kind of diagram meant to
Another solution to the problem of large data sets, then, involves methods that ask users to pre-filter data in order to get smaller and higher-quality information sets for visualizing practice. These methods have their drawbacks as well. They tend to be timeconsuming and may in some cases be too disruptive of the other work users have to do for them to be reasonable. Similar accounts
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of vertical lines representing changes in attention level to multiple documents, the writer explains that his work was more fragmented and less goal-oriented. The promising development here is that both characterizations of the writer’s work by the writer are visible and make sense to someone who has only seen the diagram.
created from third party observations have a similar set of drawbacks. They tend to be time consuming to gather and to analyze as well, and the results must often be vetted by participants afterwards to clear up ambiguities and to accurately ascribe motives, goals, etc. Still, the results of such work can produce quite impressive visualizations of practice that not only illuminate individual choices, but also place these against a backdrop of group activity drawn from aggregated accounts of similar work. Mirel [10] includes some very interesting example of this type of visualizations that take the form of topographical maps. The territories of the maps represent shared problem spaces, while trails and waypoints on the trails highlight individual paths through the problem spaces. Paths frequently traveled, roads not taken, shortcuts, switchbacks, and dead ends all appear on these maps as representations of decision-making within (or across) groups.
3.3 My work is your work: Aggregating views of individual work to produce views of collaborative work The most interesting features of knowledge work to visualize for purpose of reasoning about work may not be sequences of events, sets of tasks, or individual decisions or outcomes. Consider that when we have questions about our own work, what we often seek information about how that work relates to others’ work: how are we supposed to do this? Or, what have others done that I could do? Visualizing relationships among workers, goals, practices, texts and genres are the best ways to answer these sorts of questions. We see practical examples of this sort of visualization in recommender systems such as the one deployed by Amazon.com, and in social bookmarking applications like del.icio.us. In both of those applications, lists of resources related to an item that the user has selected or is viewing in detail provide cues as to what might also be interesting or valuable for that user.
The challenge in producing diagrams like Mirel’s that use abstract constructs such as “decision points” to show where deviations from a known path are likely is that these views depict something closer to process than practice. That is, they depict patterns of practice at the expense of showing the detailed steps of traversing a given path. The trouble with these depictions comes when a writer tries to follow the path and finds that the problem space of the map does not quite coincide with the terrain of their own project. There is no easy way to use the picture to guide future work in this case, though there may be quite a lot of value in the way the diagram allows users to conceptualize goals and anticipate obstacles.
Producing views that highlight the relationships among work practices, workers, or artifacts requires aggregation of individual accounts of work and the application of some kind of sorting algorithm that can recognize affinities that are of interest in these multiple accounts. The algorithms and the resulting visuals do not have to be terribly complex to be very useful, as the Amazon.com recommender system demonstrates. The logic applied is plainly explained in the header for the visualization, which is itself a simple list: readers who bought X also bought A,B,C…
The best options for gathering historical accounts of writing activity seem to be methods that involve user-initiated process tracing that is at least semi-automated, followed by some kind of coding or vetting process that further filters work-session data and allows users to apply comments, ratings, etc. This approach ensures that a detailed and accurate depiction of practice forms the basis of visualization, while leaving open the possibilities to add layers of data that contextualize, reduce, and focus the data.
Spinuzzi [13] produces a kind of network diagram called a Genre Ecology Model [10,14] that depicts the relationships among online and offline textual genres and at three different work sites, gauging the strength of these relationships by noting how often resources are co-present and actively used in work activities engaged in by his study participants. The resulting diagram aggregates the work of many individual writers, showing the networks of supporting genres that help them to do their work.
Slattery [11,12] offers an example of this sort of visualization work in his study of contract technical communicators. Focusing on a specific practice he calls “textual coordination,” Slattery traced the textual resources that writers used during writing sessions that involved drafting or editing a document on a computer. In two-second intervals, he noted which textual resources were available and to what extent each was “active” using a multi-state coding scheme that ranged from a document being absent to a document being actively created. Using a simple line diagram, Slattery shows how specific textual resources – each represented by a single line on the diagram – move in and out of the writer’s conscious work patterns.
Gunnarson [15] offers several visualizations of writing practices that emphasize a wide range of relationships in her study of a government office. Her diagrams depict relationships among workers in the office with respect to power, among the communications from the office to various levels of local, provincial, and national government, and among the various types of oral and written communication engaged in for typical projects, just to name a few. Working from a sociolinguistic framework, Gunnarson’s diagrams are excellent examples of how aggregating individual accounts – in this case, by hand – can produce valuable resources for reasoning for both the group and the individual writer. Perhaps the most significant value lies in the way that patterns emerge that would otherwise be invisible to individuals due to the distributed nature of writing activity.
The resulting diagrams can be “read” by noting where there are sustained patterns of attention on the “target document” – the document that the writer is attempting to create or revise – and/or patterns of attention on various other resources available to the writer. For one writer, an emergent pattern of incorporating information from a previous draft into a new draft, for example, when updating a user manual from a previous version is characterized by the writer as working “on task.” Where this pattern is interrupted, visible on the diagram as a much tighter set
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encouraged by the types of artifact-based views of writing activity we see in applications like del.icio.us and in the many, many examples of sites that use tagging to generate a bottom-up “folksonomy” capable of giving users immediate visual feedback that can further their work goals. In this final section, we will talk about a these trends in greater detail in an attempt to demonstrate how visualizing writing activity on the web is helping not only writers, but users who are engaged in a wide variety of knowledge work tasks that are carried out in writing, that is, they are mediated by and produce texts. In this way, visualizing writing activity becomes not only a way for writers to reason about writing, but for knowledge workers of all types to reason about the work they are engaged in, using the patterns and rhythms of writing activity depicted as relationships to assist them in doing so.
4. Features for Useful Visualizations of Technical Communication (for Technical Communicators) Our own aims in conducting research on writing practice and devising visualization methods that can serve writers’ own needs include developing new tools that help to record, aggregate, filter, and visualize data about writing practices in order to produce useful visualizations on demand and in the work environment(s) of writers. Following from the foregoing analysis and our previous research [16] we have identified a few basic functional requirements for the visualizations that such a system would produce. We expect this list to grow and change as our research continues and as we learn from the work of others who share our interest in visualizing data to support complex work across a wide variety of knowledge domains.
5.1 Seeing Documents & Genres: Tagging and Folksonomies
To best serve the mediational needs of writers who need to reason about their own work, visualizations of writing practice should be: •
Data driven – depicting practice in a detailed and accurate way with enough regularity to permit the emergence of visible patterns that are meaningful for understanding and, in some cases, acting strategically to change these patterns for the better
•
Represented by explicit, but flexible categories – to ensure that individual accounts are both meaningful to the individuals whose work they represent but also to others who may have an interest in learning from or comparing their work to others’
•
Interactive – allowing users to update, sort, extend, reconfigure, and refresh depictions of work in the course of reasoning about that work; interactive diagrams could also permit the images of work practices to serve as a kind of GUI for contentmanagement, social-networking, and social bookmarking, tagging, and folksonomy structures.
•
Portable – that is, not confined to a single software tool, a single computer, or a single network location, but available and updateable from wherever work might take place (and so accessible by mobile devices).
•
Timely – ready to respond to writers’ needs on demand, with the updated information required to do so.
•
Able to answer key questions – able to be extended and configured to become contextual beyond the point of being simply domain-aware, up to and including being personalized for an individual’s unique reasoning needs.
Because writing is an activity that is frequently mediated by many textual artifacts (a phenomenon Spinuzzi [12] calls “compound mediation”), a simple type of visualization technique that nonetheless provides significant value to writers is to provide lists of texts that are potentially useful because they are related in some way to the target text being used or produced. As long as the lists are not too long and can be sorted by relevance, they can be extremely useful, particularly for writers working in specialized knowledge communities. A good example of this visualization technique at work exists in Connotea, a website published by the Nature Publishing Group that allows users to share bookmarks to scientific articles. Built to mirror the basic functions of Del.icio.us, Connotea adds some additional functions meant to enhance the way readers and writers within the scientific community might want to discover and use resources.
5. Looking Ahead: Web 2.0 Aggregation and Visualization Trends Worth Watching
Fig. 5 “Recent Activity” page from www.connotea.org
In section 4, we mentioned recommender systems and the social bookmarking site del.icio.us as examples of applications that aggregate individual work practices in order to depict relationships among the work of group members. We are
We can see how the basic lists provided to the left and right of the main list of references by Connotea -- in Fig. 5 a list of
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items tagged by users with the term “leaf”-- provide visualizations that are useful in the ways outlined in Section 4, above: •
Data driven – the list displays aggregate user’s collective decision making, allowing trends to emerge in the form of relevance-sorted lists
•
Represented by explicit, but flexible categories – the resources that appear in the center column are all tagged by a common term, but the weight of any given tag as an index term is a function of its use by the community, meaning that these terms’ relevance can change over time and from search-to-search. The designers of Connotea note in a technical paper [17] that as the resource is being used, a folksonomy is emerging, but only as a second-order effect of individuals tagging individual articles with terms that serve their own immediate interests. That is, no user is indexing the collection for the good of the community only, but is indexing first for their own immediate needs.
•
Interactive, Portable, Timely – As a web-based resource, Connotea is available wherever and whenever users have internet access. Logging in gives users access to their bookmarks and clicking on any of the tag list or user list items allows for interactive exploration to promote resource discovery.
•
Able to Answer Key Questions – The boxes in the left and right side can be read to responses to common questions researchers in the scientific community, among others, might ask. In the upper left, the box labeled “Users Who Used Leaf” answers a question like: who else is using this same tag to describe articles? In the lower right, the “Related Tags” box contains a list that answers the question: “What other terms besides Leaf might be helpful for me to use?”
5.2 Seeing Actors and Artifacts: Social Networks For writers, as important as discovering genres and documents is the ability to explore the social resources they might draw upon to complete a writing task, or the ability to understand the network of recipients that may be constitute their “audience” for a given text they are preparing. Social networking programs – or functions built into other software systems such as blogs that highlight who is connected and or connecting to who – are another important source of visualizations of writing activity that we can learn quite a lot from. In the Connotea screen shot in Fig. 5, we see some social networking functions working to generate lists of other users who are using tags similar to the one entered in a given search, and also a list of “Related Users” who may be actively assembling lists of resources related to a particular resource or tag. Social networks are frequently mapped using network (node and edge) diagrams, and many, many examples of these exist to map everything from the networks present in a user’s personal e-mail inbox log to the networks implied in Shakespeare plays. We would point out that social network analyses useful to writers are likely to involve both human and non-human actors, or to put it another way, to allow the various texts that humans have created to stand in and represent them as needed. We hear this kind of simple substitution all the time – “have you seen the Johnson report?” – but the status of users in information system does not often allow user identities to intermingle with other types of information objects such as documents.
6. Conclusion: Can Seeing Knowledge Work as Writing Activity Help Users in A Variety of Work Contexts? The implications of the foregoing survey of visualization methods not only matter for technical writers, they are significant for many classes of knowledge workers. If we take a careful empirical look, much of the “work” in knowledge work involves writing and results in texts. To be sure, we cannot reduce all knowledge work to writing. And we would hasten to add that in most cases, writing serves as the means to accomplish knowledge work goals rather than the explicit ends of knowledge work. But to the degree that we may want to depict knowledge work activity in ways that allow us to understand, reason about, and perhaps even change the ways we do it, visualizing writing practices is a promising means to do so. What we have begun to lay out in this paper can constitute some guidelines for visualizing writing practices in an effort to create intelligible accounts of knowledge work. We look forward to producing and testing some of these visual accounts in our own work in the future, as well as to seeing those that others may produce.
One result of having the Connotea lists available as a user browses a specific list of articles is that more of the network of related genres and documents available to the writer is visible. When a particular resource is “in focus,” the relationships among genres and specific documents can become quite specific. When a broader category such as a research topic is the focus of the user’s attention, relationships are rendered in more general terms. This allows users to calibrate the level of detail they want to see simply by specifying (e.g. with a tag on an existing document) what connections they will likely have with other resources. Plant biologists may specify additional tags, for example, that open up more specific paths to studies of vascular structures in leaves than the tag “leaf,” alone, may do. The ability to move easily up and down levels of abstraction when browsing a large collection of resources is likely to be critical for supporting writing activity of all types. For example, when writing a memo, writers may simply need structural guidance or even just a version of the organization’s letterhead – so any item tagged “memo” might well be useful to grab. But when the task is to write a “quarterly technical services memo,” the tag “memo” by itself may not be sufficient to help the writer locate all the best resources that could be available.
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