# Fuse: In-Situ Sensemaking Support in the Browser

Andrew Kuznetsov  Carnegie Mellon UniversityPittsburghPAUnited States
<EMAIL_ADDRESS>,  Joseph Chee Chang  Allen Institute for
AISeattleWAUnited States<EMAIL_ADDRESS>,  Nathan Hahn  US Army Research
LabsAdelphiMDUnited States<EMAIL_ADDRESS>,  Napol Rachatasumrit  Carnegie
Mellon UniversityPittsburghPAUnited States<EMAIL_ADDRESS>,  Bradley
Breneisen  Carnegie Mellon UniversityPittsburghPAUnited States
<EMAIL_ADDRESS>,  Julina Coupland  Carnegie Mellon
UniversityPittsburghPAUnited States<EMAIL_ADDRESS>and  Aniket Kittur
Carnegie Mellon UniversityPittsburghPAUnited States<EMAIL_ADDRESS>
(2022)

###### Abstract.

People spend a significant amount of time trying to make sense of the
internet, collecting content from a variety of sources and organizing it to
make decisions and achieve their goals. While humans are able to fluidly
iterate on collecting and organizing information in their minds, existing
tools and approaches introduce significant friction into the process. We
introduce Fuse, a browser extension that externalizes users’ working memory by
combining low-cost collection with lightweight organization of content in a
compact card-based sidebar that is always available. Fuse helps users
simultaneously extract key web content and structure it in a lightweight and
visual way. We discuss how these affordances help users externalize more of
their mental model into the system (e.g., saving, annotating, and structuring
items) and support fast reviewing and resumption of task contexts. Our
22-month public deployment and follow-up interviews provide longitudinal
insights into the structuring behaviors of real-world users conducting
information foraging tasks.

Sensemaking Support Systems, Mental Models, In-Situ Systems

††journalyear: 2022††copyright: rightsretained††conference: The 35th Annual
ACM Symposium on User Interface Software and Technology; October 29-November
2, 2022; Bend, OR, USA††booktitle: The 35th Annual ACM Symposium on User
Interface Software and Technology (UIST ’22), October 29-November 2, 2022,
Bend, OR, USA††doi: 10.1145/3526113.3545693††isbn:
978-1-4503-9320-1/22/10††journal: JACM††journalvolume: 37††journalnumber:
4††article: 6††publicationmonth: 10††ccs: Human-centered computing Interactive
systems and tools††ccs: Information systems Multimedia information
systems††ccs: Human-centered computing Empirical studies in HCI

##  1\. Introduction

People spend a significant amount of time trying to make sense of the
internet, collecting content from a variety of sources and organizing it to
make decisions and achieve their goals. For example, consumers purchasing a
home appliance spend an average of 15.8 hours researching across 12 different
sources. 111(Google and Ipsos MediaCT, January 2014) and (Google and Inmar,
2013) respectively, as referenced by The Google Marketing Blogpost ”Thinking
with Google: Five Holiday Shopping Trends Marketers Should Watch”. Similar
sensemaking takes place for a variety of information seeking and decision
tasks, ranging from shopping to health to travel to troubleshooting (Kittur et
al., 2013).

Figure 1. The Fuse Prototype, expanded to demonstrate how the reader view
enables users to drill-down on specific items while maintaining a compact
representation during foraging.

caption

While humans are able to fluidly iterate on collecting and organizing
information in their minds (Russell et al., 1993), the amount of information,
options, and evidence involved in online sensemaking quickly exceeds the
limits of working memory (Miller, 1960). However, externalizing these
processes using existing tools and approaches introduces significant friction.
For example, a common way to collect information today is to use browser tabs
to externalize and keep track of information. However, tabs’ flat structure
and lack of support for more complex organization leads to a multitude of
issues, from tab overload (Chang et al., 2021) and tab hoarding (Vitale et
al., 2018)(Sweeten et al., 2018)(Dubroy and Balakrishnan, 2010) to losing
users’ mental context which isn’t externalized anywhere (Hwang et al., 2017).
These issues are not easily fixed by introducing tab groups or hierarchies
which can correspondingly lead to tab group overload (CHANG et al., 2021).

Exacerbating the problem, many online sensemaking tasks require extracting
information scattered across pages and reassembling them into the concepts or
items a user is considering (Hoch and Ha, 1986) (Racherla and Friske, 2012)
(Chang et al., 2020) (Hahn et al., 2016) (Chang et al., 2016b) (Chen et al.,
2015). For example, in the home appliance example above, a user may need to
collect unique features or important limitations which may be discussed in
different sources or reviews. Collecting and organizing this information by
copy-pasting and switching between web pages and docs or spreadsheets can be
onerous and time consuming (Chang et al., 2021). As a result, tools that
assist the user in clipping pieces or entire web pages have gained in
popularity as an effort at combating these costs (e.g., as found in Evernote,
hypothes.is, Pinterest, etc.).

However, while the above approaches have focused on reducing the friction of
collecting web content, users typically still need to switch to another
application in order to access and organize that content. This separation
between collection and organization is in contrast to the fluid and iterative
sensemaking process users engage in when information can be contained entirely
in their head. In this work we investigate the idea of providing users with an
in-situ workspace that more fluidly bridges the gap between browsing,
collecting, and organizing web content. Our goal is to take a step towards an
interaction paradigm in which the browser acts as a seamless, zero-friction
extension of a user’s mental workspace.

There are many benefits that a browser acting as a seamless mental workspace
could provide: quick access, resumption of tasks, recall of information origin
and purpose, and scaffolding users in building larger and more complex
information collections. In exploring this vision we grapple with several core
design challenges. First, how do we reduce the friction of collecting
information while keeping users in the flow of their sensemaking process? This
goal is challenging because users may wish to collect a variety of types of
information ranging from text to image to mixed-information clips and have
access to both the final visual rendering of that information as well as the
underlying text, links, and structures, all while maintaining the provenance
of where those clips came from. Furthermore, as the user is reading and
deciding to collect the information they are making judgments in their mind
that need to be externalized as well, such as through notes and annotations
such as the priority or expected utility of the item.

Second, how can we help users not only collect information in situ but also
view and organize the information collected in situ as well? Requiring the
user to switch between their information collection and another tab or app can
reduce the likelihood of their actually using and structuring their
information. Although previous systems have explored the value of capturing
users’ thoughts in an in-situ sidebar (e.g., (Van Kleek et al., 2009)), less
work has examined the ability to support informal and flexible organization in
an always-available sidebar. Exploring the affordances of structure and
organization needed by users was a key goal for this work that drove our
approach of a long term deployment with completely voluntary usage.

Third, how do we help users visually represent and make sense of all the
clips, pages, and notes collected and organized in the system? Given the
limited real estate afforded by a sidebar, exploring compact representations
that could compress and display a variety of diverse information collected was
essential to the success of the approach. In doing so we explore flexible
compression approaches such as ’container’ cards that support compressing
multiple pieces of evidence into a single card; visual previews for such
containers; and an expanded ’reader’ view which flattens clips, containers,
and nested structures so that users can quickly scroll through them to get an
overview of what they’ve collected, all without leaving the webpage they’re
on.

In this paper we present Fuse, an exploration of the idea of an externalized,
unified workspace in the browser, and a prototype instantiating that idea that
reduces the friction of collecting and organizing web content in the browser.
We discuss the design and development of Fuse as conducted over the course of
a year of iterative development by the research team and a small group of
users using it for their own tasks, as well as a 22 month public deployment
with over 100 volunteer users. Our findings validate the importance of
supporting in-situ organization in the browser and identify several challenges
for future systems aiming to support online sensemaking and task management.

Our contributions include:

  * •

Fuse, a prototype browser extension that provides a unified workspace for
conducting online research combining affordances for low-cost collection with
lightweight organization of content in a compact card-based sidebar that is
always available.

  * •

A analysis of how these affordances help users externalize their mental
structures into the workspace created by the system (e.g., saving, annotating,
and structuring items) and support fast reviewing and resumption of task
contexts.

  * •

A 22-month public deployment and follow-up interviews that provide
longitudinal insights into the structuring behaviors of real-world users
conducting information foraging tasks.

##  2\. Related Work

###  2.1. Clipping Content on the Web

The larger topic of capturing and clipping web content is well studied in both
industry and academia. By necessity, organization tools such as Notion
222https://www.notion.so/, Evernote 333https://evernote.com/, and Pocket
444https://getpocket.com/ implement clipping tools at the DOM level to import
web content to be organized within their respective applications. Clipping
systems in academic research have previously focused on extracting specific
media types such as images (Pham et al., 2012), or text (Tashman and Edwards,
2011) (Kittur et al., 2014) (Liu et al., 2022a) (Liu et al., 2022b) (Chang et
al., 2016a), although clipping tools that leverage HTML structure also appear
in several tools (Dontcheva et al., 2006) (Schraefel et al., 2002). Another
approach to extracting web content utilizes structured extraction, inducing a
schema from an initial collection and using this to extract similar content
(Hogue and Karger, 2005) (Dontcheva et al., 2006), or repeatedly extracting
updated content (Sugiura and Koseki, 1998). Fuse improves on existing clipping
tools by forgoing extraction templates and instead making it easy to collect
text, images, or screenshots of information by providing users with a variety
of approaches to import content at multiple granularities, including drag and
drop, screenshot clipping (which saves both image- and html-based
representations), and bookmarking entire pages. Additionally, Fuse provides
affordances for users to explicitly encode the context of information after
importing it, for example assigning tags, colors, adding notes, or changing
the order of items. Simultaneously, Fuse also automatically collects high-
level provenance information to help users recover the original context of the
content, such as origin url and a viewport screenshot.

###  2.2. In-Situ Sensemaking Support Systems

Researchers have explored a number of systems for supporting the sensemaking
activities of collecting and organizing in different contexts such as
literature review (Zhang et al., 2008), web search interfaces (Hearst and
Degler, 2013) (Hahn et al., 2018), as well as desktop applications that
mediate or review dedicated workspaces (Jeuris et al., 2014) or review screen
context (Hu and Lee, 2020). Such in-situ systems are frequently implemented as
standalone desktop programs that replace the user’s typical browser
experience, often consistent of a main reading panel and a working space for
viewing or organizing collected content. A few notable examples include
CiteSense (Zhang et al., 2008), which demonstrates this in the domain of
literature review, allowing users to take notes on search results while
querying a database in a standalone Java application. Hearst et al. (Hearst
and Degler, 2013) similarly explore the design of an interface for tagging and
organizing search results, with the main work space consisting of a card-based
clustering interface for highlighted documents. Reimer et al. (Reimer et al.,
2011) introduced a desktop application that imports elements via copy and
paste and splits organization into a two panels; a hierarchical file structure
on the left-hand side enables users to expand an item to view on the right-
hand side. However, the unstructured nature of web content mandates that
respective sensemaking support systems must implemented interfaces that
smoothly enable users to browse web content, extract it, and later review
extracted web DOM content, whatever it may be.

To better adapt such systems to the web content encountered while browsing the
web, researchers have also explored in-situ ‘sidebar’ systems implemented as
browser extensions. For example, systems like List-it (Van Kleek et al., 2009)
allow users to type free form notes and todos into a sidebar while browsing
the web, while systems with built-in clippers such as Clipper (Kittur et al.,
2013), ForSense (Rachatasumrit et al., 2021), or Threddy (Kang et al., 2022)
allow users to collect and organize text snippets manually extracted from the
web pages (Kittur et al., 2013)(Rachatasumrit et al., 2021) or scholarly
articles (Kang et al., 2022). These systems make it easy for users to preserve
context across pages and quickly reaccess information while browsing, but have
limited support for organization (typically at most one level of grouping) and
require switching to another tab or application for viewing and interacting
with collected content. As a result, many such systems end up visually
representing clips in relatively unordered structures such as collages
(Swearngin et al., 2021), with no structure or nesting possible. Systems that
do arrange clippings with structure, such as Dontcheva et al’s ”Summary
Tables” (Dontcheva et al., 2006) require the creation of custom templates and
views by users.

In Fuse we attempt to fuse the benefits of in-situ browser sidebars regarding
situational awareness and rapid reaccess of information with the benefits of
the organizations and visual structures found in dedicated workspaces. In
order to support the user in doing so without context switching we explore
approaches integrating user encoding of mental context, flexible organization,
and visual compression.

##  3\. System Design

###  3.1. Design Goals and Process

We developed the Fuse protoype to probe the gap between collecting and
organizing information online, which to date have been addressed by
researchers as largely separate activities. As such our high level research
goals were to provide a flexible set of affordances that could be used across
a variety of online research tasks to reduce the friction of not only
collecting web content but also organizing it in-situ and quickly reaccessing
and using that organization. Conceptually, our design goal could be framed as
trying to reduce the gap between the internal, evolving representations in the
mind of the users as they collect online information, and the externalized,
existing structure of their collection, eventually resulting in the browser
functioning as a seamless extension of the user’s mental workspace. This work
represents a first step towards that goal.

With the above in mind, we developed Fuse to assist users in conducting online
research by enabling them to collect and organize web document clips and links
in-situ in a persistent browser sidebar. Typically, a user synthesizing online
content would need to switch between the content they are exploring and a
reference document with their collected items as they synthesize information
across multiple online sources - a process often done with high context-
switching costs using copy-and-paste and an external spreadsheet application
(Chang et al., 2020). Existing systems use a combination of techniques for
avoiding this issue, from ‘importing’ entire tabs in Tabs.do (Chang, 2021) to
automatically extracting pre-defined content (such as price and average
reviews) from tabs in Mesh (Chang et al., 2020). Instead, our system enables
users to reference and organize their collection of snippets as they
simultaneously forage for more information. An inherent challenge to creating
such a general purpose system includes supporting a variety of foraging and
sensemaking activities that users undertake throughout a spectrum of domains
and tasks. To enable such flexibility, Fuse combines paradigms such as web
clipping, bundling, file management, and card interfaces to create a compact
interface for information foraging. For example, ‘snipping’ a piece of content
in the browser window creates a Fuse ‘card’ in the sidebar, which can then be
organized alongside, in a hierarchical folder structure, or bundled as part of
an existing card. As a complete system, Fuse is designed to afford users the
flexibility to synthesize a wide variety of web content into whichever
structure is most convenient for a given user’s task and domain.

To thoroughly explore the design space and produce a research prototype robust
enough for a large-scale field deployment, three of the authors spent a year
developing the extension while all team members used the extensions for a
variety of online sensemaking tasks including learning, shopping, trip
planning, literature review, UI design survey, market research, coursework
management, and more. As we deployed Fuse to more users we conducted informal
user studies throughout the development process to iterate on its design. For
example, the early versions of Fuse only provided a flat list of cards within
each project. We later introduced the ability to create folders to build
hierarchical structures so that users who were planning trips with Fuse can
separate their clips for restaurants, hotels, and places to visit but at the
same time see all collected information within the same project view. In later
iterations we further introduced the ability to put cards within cards because
users were collecting multiple snippets for the same items which lead to long
hierarchy structures that can be difficult to overview in the sidebar.
Instead, the ability to create cards-in-cards allows them to curate a single
card that contains all clippings for the same items (e.g., all the information
about the same restaurant), making it easier for users to see all their
choices in the same view for decision-making while enabling them to drill down
and inspect each of their options in the reader view.

In the below sections we describe an example user experience, then discuss in
more depth the various design challenges and decisions made during the
iterative design and deployment of Fuse, broken roughly into three functions:

  * •

(D1) Collecting content while encoding provenance and context

  * •

(D2) In-situ organizing

  * •

(D3) Visually compressing items

Figure 2. The main interface of Fuse that is accessible to users alongside
their web browser. (A) The web content, which can be freely interacted with as
normal. (B) The main sidebar view for organizing collected items and selecting
clipping interactions. In the screenshot, it has been expanded via clicking on
one of the cards, revealing (C) the expanded reader view which enables users
to dive deep into a specific card and view nested items in a compact manner.

###  3.2. Example User Experience

Consider an example in which a user needs to conduct online research to find
the best pair of wireless earbuds for her needs. She starts by searching on
Google for popular headphone models to consider, but quickly realizes that
there are dozens of “best wireless headphones” listicles recommending hundreds
of headphone models to track in her exploration. These listicles often contain
overlapping recommendations, but might say different things about the same
models. Even collecting exclusively from a recommended list of headphones, she
must cross-reference information about dozens of models from a variety of
sources, such as Amazon reviews and other listicles. To understand which
headphones might be best for her, she’d like to research the current
headphones offerings and collect their respective cost, important features,
and things-to-avoid, Normally, this process would typically take her a lot of
effort, involving several hours of constantly switching between web pages,
searches, and a separate external document such as a word document or a
spreadsheet to use as external workspace keep track of her progress. Instead,
she uses Fuse to create a new project called “Wireless headphone shopping” and
imports the different headphone models she found interesting through a variety
of interactions: bookmarking entire product pages, extracting one-off
recommendations from social media comments, or clipping a part of a listicle.
The system then creates cards for each item and automatically recovers
contextual information about the source, such as url, favicon, and screenshot
of the viewport (except for cards created from direct clippings). Skimming
over her list of cards, she reorders them by personal preference by dragging
the cards relative to one another.

As she dives deeper into researching specific options, she finds parts of
pages that she’d want to clip and organize on product pages, such as
impressive features and critical reviews. Using the Fuse sidebar, she quickly
clips a review about one of her options and drags the newly created card into
the option’s card, nesting it. Fuse creates a condensed representation of the
nested cards while hiding them, letting her know the rough size of her bundle
for each item. Although Fuse hides these nested cards for easier skimming, she
can expand to the toolbar at any time to see all the clips collected under any
card. As she accumulates more evidence and notes, she also creates folders to
organize different types of wireless headphones (such as over-the-ear or
earbuds), allowing her to externalize her task mental model and fluidly
compress or expand the subtopic folders she is currently focusing her research
on while maintaining a sense of situational awareness of the overall project.
Finally, she feels confident and informed and makes a purchase with the
information she has explored and saved in her Fuse project.

####  3.2.1. [D1] Collecting content while encoding provenance and context

As illustrated in the example above, our first design goal was to allow those
conducting online research to collect information while having direct access
to their prior sensemaking collection. Prior work has demonstrated the utility
of synthesizing information from multiple sources during sensemaking
activities (Dontcheva et al., 2006). A system built to collect web content
must enable users to quickly and effortlessly collect a diversity of web
content (images, text, part of pages, videos, pdfs, etc.) as well as
automatically capture the relevant surrounding context. The Fuse clipper
collects content and context in a variety of representations. Firstly, a
screenshot of the selected region is automatically saved as an image,
preserving the visual appearance and styling and used as the default
representation showing on cards to help users recall what they saved.
Secondly, Fuse resolves the selected bounding region to the best-match Web DOM
element and saves its HTML content. This allows users to access hyperlinks or
select and copy text in the selected region. For PDFs opened in the browser,
since PDFs do not contain DOM elements that contain blocks of text, we ran the
Tesseract.js 555https://tesseract.projectnaptha.com/ Optical character
recognition library locally in the browser to convert the saved image into
selectable text. Once saved, users can toggle between different automatically-
collected representations in the sidebar based on their needs. When more
context needs to be manually added, Fuse also implements text annotations that
the user may add for any item.

A critical design goal was for the collection interactions themselves to feel
sufficiently lightweight for the user to allow users to seamlessly transition
between browsing information and using Fuse to import content into their
collection without breaking their flow. To achieve this, the Fuse clipper
provides five interaction types that can be utilized by users to address
different clipping needs (Figure 3):

Figure 3. The many different ways Fuse enables users to capture web content:
(A) Text Highlighting (B) Image Drag and Drop (C) Bookmarking (D) Bounding Box
Clipping (E) Tab Importing.

  * •

Text Highlighting
Fuse implements a traditional text highlight to enable users to make high-
precision selections. After selection, users can use the context menu to
navigate to ’Collect with Fuse’ and then select which project to collect into.

  * •

Image Drag and Drop
Preliminary user tests revealed that although selecting images was common,
doing so with the mouse was much more tedious than dragging. Images that are
dragged into a Fuse project will automatically be imported as a card to
facilitate easy import of images.

  * •

Bookmarking
Fuse implements the familiar bookmarking feature, accessible via the sidebar.
Doing so saves the entirety of the page, the title and url, and captures the
current viewport to be used as the header image of the respective card.

  * •

Bounding Box Clipping
To facilitate capturing portions of webpages that are neither text nor images,
Fuse implements a bounding box clipping tool. Clicking on the respective item
in the sidebar triggers a bounding box selection, upon the completion of which
will become the header image of the new card. Url and page title data are
extracted automatically and associated with the new card.

  * •

Tab Importing
To assist users that would like to capture multiple pages consecutively (as is
often the case when closing a browser window), Fuse implements the ability to
import all currently open tables into the current Fuse project. Doing so
mimics activating the bookmarking capture interaction on every open tab.

####  3.2.2. [D2] In-situ organizing

A key design goal we aimed to explore was to enable users to view and organize
information as they forage for information, reducing switching costs which
produces considerable overhead for users conducting online research (Chang et
al., 2020). With this in mind we set out to design an always available sidebar
panel that would enable users to create, manage and switch between multiple
projects. To do this within the Fuse sidebar, we initially created a menu bar
with individual tabs to switch between projects, similar to file folder tabs.
Early user-testing of prototypes demonstrated the need to swiftly create and
pin new projects, inspiring the creation of two dedicated buttons on the panel
for doing so. To better keep users in flow, a user can minimize the Fuse
sidebar entirely and reopen it with a keyboard shortcut when they’d like to
refer back to it.

Figure 4. The ’peek’ interaction within Fuse, which enables users to see cards
within a container card without using the ’expanded reader’ view. Preview
versions of the content appear together in a pop-up left of the sidebar when
hovering the mouse over the card preview icons (positioned in the top-right of
container cards).

Additionally, we aimed for Fuse to support a variety of organizational
paradigms in-situ so that users could iteratively organize their collection to
best suit the task at hand, as well as account for personal organizational
preferences and strategies (Fisher et al., 2012). Fuse achieves this in
several ways. First, Fuse enables users to use existing cards as ’container
cards’, which we elaborate on in the next section. Users can also create more
traditional folder cards, which are intended to act primarily as labels for
explicit hierarchical structures, much like folders in a file system.
Internally, these are implemented as standard content cards without the
ability to bundle content within them. Lastly, users can utilize the Fuse
interface to manually create cards from scratch and assign them text titles
and annotations. Users often used these ’manually created cards’ as a third
type of organization as they could both be used as a simple label and contain
bundled content. There are several ways to import content into an
organization, regardless of whether it is going into a folder structure or
bundled into a container card. Users can drag content such as images from the
browsing pane into an existing folder or container card in the Fuse sidebar,
automatically creating a new card that will be placed within. Alternatively,
users can also drag existing cards from folder to folder or container card to
container card in the current collection.

####  3.2.3. [D3] Visually compressing items

Working within the constraints of an always-present sidebar presents
significant challenges to representing content and interactions in a compact
way that functions across a variety of types of web content, meaning an in-
situ system will need to offer a standardized but compact representations of
each collected item within the sidebar regardless of the granularity or media
type of the content collected. In order to design for this, we decided to
represent each piece of collected content using the Card UI paradigm, as it
would give users a highly visual representation that could be dragged around
to be reordered, and nested. By default, each card would show a header preview
image, with a title, source url, and blank annotation. In choosing to do so,
we also decided on several transformations so that each type of media imported
into Fuse would have a uniform presentation. Bookmarked websites would receive
their header images by way of an automatic viewport screenshot during
collection, and collected snippets appear directly in the header images. To
better support skimming, this header image can be collapsed by clicking.
Lastly, Fuse implements a generic ’expanded reader view’ (shown in Figure 2),
when fully seeing the content and context of an item is desired. In their
compressed forms, Fuse cards enable the enable the sidebar to fit many cards
and afford the opportunity for us to implement in-situ organization, which we
discuss next.

Early user-testing with Fuse revealed that users desired the ability to create
structures with multiple nested folders as they used the tool in-situ,
necessitating the creation of a compact representation for nested cards within
the sidebar. Later iterations of Fuse implement the ability to drag cards into
cards, particularly useful when users were collecting many snippets about a
singular item such as a product. From this iteration forward, the ’container
card’ was created as a concept independent of folder cards.

As opposed to creating hierarchical structures with folders, ’container cards’
are primarily meant to simplify structures by compressing many independent
pieces of evidence into one card. For example, early user-testing participants
often found themselves collecting individual images (such as food images for a
restaurant) and nesting them under individual folders named after each option
(in this case a restaurant). Instead, Fuse users can nest the many different
images within the original, rich card representing the restaurant, creating a
bundle of images. Fuse implements several additional affordances to make
viewing and previewing the bundled items easier. To view the items, we created
a reader view that would pop open on click, showing all of the snippets nested
in the card. When not in this view, we implemented a small preview panel that
uses a grid of squares to represent the number of snippets (and ’container
cards’) nested within a specific item to provide a quick overview for the
user. Lastly, hovering over this grid of squares activates a small pop-up
visual ’peek’, with miniaturized versions of each snippet appearing together
in a black bubble left of the card being peeked. This interaction can be seen
in Figure 4.

Figure 5. Fuse Architecture Diagram. The Fuse sidebar is implemented by
injecting javascript code into an iframe attached to the current tab’s DOM -
enabling the sidebar to capture page content, render the clipper interface
overlay, and communicate with both the Chrome user’s local storage and the
remote Firebase server.

###  3.3. Implementation Details

Fuse was implemented in approximately 37,000 lines of TypeScript. The UI
components were built with the React library and database and authentication
implemented with Google Firebase. This enabled users to access their projects
across consecutive sessions. The system was implemented as a Chrome extension,
which was crucial to keeping several interface interactions as native to the
browsing experience. In doing so, we were able to allow users to seamlessly
toggle and maintain the Fuse application alongside their normal web foraging
behavior with a click or keypress. Second, having read access to website
content was critical for implementing the ability for users to clip content on
their screen after activating the snipper in the sidebar. Lastly, implementing
Fuse as a chrome extension gave the system access to tab information such as
url titles and favicons. The sidebar is implemented by attaching an iframe to
the current tab’s DOM and embedded onto the page when the extension icon is
clicked by the user. Javascript code was injected into the iframe to render
Fuse’s interface and logic. This allows us to implement the sidebar in-situ
while encapsulating our CSS stylings and program logic. Each iframe in modern
browsers also has its own Javascript thread, this design also allows Fuse to
run independently of the current tab so the impact on its rendering and
performance is minimized. A system architecture diagram can be found in the
below figure.

##  4\. Field Deployment Study

To better understand how our system can support sensemaking behaviors in
online research and evaluate our prototype, we conducted a field deployment
with participants in the wild performing their everyday tasks. 134 distinct
users organically participated over a twenty two month period, recruited
through a combination of recruiting from authors’ social media feeds, a public
email list available on an informational landing page (https://getfuse.io/),
and a publicly searchable listing on the Google Chrome app store. The social
media posts were short and asked for participants that would “like a flexible
tool to help organize online researching” and contained a link to the
application’s listing on the Chrome App Store. Upon installing the
application, participants were informed that the application was part of a
research study and consent was obtained for the collection of project and card
information. Users were not given any specific directions during installation
or tasks to perform - the recruitment page consisted of informative content
regarding Fuse’s collection and organization features, and invited readers to
freely download and use the application for their personal online research
needs.

Of these users, 89 (66%) created projects with non-zero amounts of content.
Follow-up interviews were solicited by emailing the top ten most active users
in our deployment study (by event count), with eight users responding and
participating in a video call follow-up interview, compensated at $15/hour. As
we recruited interview participants, we found significant overlap between
themes as we interviewed users such that we were not finding new themes and
were reaching saturation with eight participants. In looking at the data
across all participants these themes were well reflected in the projects that
we inspected or analyzed. Questions spanned several topics detailing
participant usage of the application, user utility, the comparative strengths
and weaknesses of Fuse (as compared to other applications the user has tried),
and areas of potential improvement. The full text of these questions may be
found in the supplemental material at the following link.

##  5\. Results

Overall, participants found Fuse to be helpful in visually organizing their
online research and used it for both personal tasks such as shopping as well
as professional tasks such as academic literature review. One user reported
switching over from their browser’s bookmarking interface entirely, using Fuse
for organizing their online research throughout the entire 22 month deployment
period. As participants were not compensated or recruited for their usage of
the application beyond their own utility, we see this as an encouraging sign
that Fuse provided sustained value in users’ daily lives and replacing
existing tools for these long-term users. Below we discuss themes from two
passes of interview coding (one open and one closed) in order to provide an
in-depth understanding of how Fuse users derived value from Fuse’s designed
affordances as they conducted online research during the deployment study. We
finish this section with an analysis of the different types of Fuse projects
we observed, broken down by user intentions with another pass of coding
looking at project and card content.

###  5.1. [D1] Collecting content while encoding provenance and context

Fuse’s first design goal was to lower the friction of collecting information
and externalizing their thoughts about that information while conducting
online research. In our user interviews, we found evidence that the designed
features helped users to import content, augment it with both automatically
and manually collected provenence-related information, and organize it into a
coherent structure.

Fuse users described how the extension enabled them to quickly collect key
content from the web with lower friction, enabling them to clip a variety of
information while avoiding context switching to other tabs or applications. In
follow-up interviews, participants were excited by the speed with which Fuse
allowed them to import content from their screen into the sidebar:

> ”[I] can effortlessly throw something in, can easily come back to it later
> …. Esp if I’m doing shopping online, easy to [throw] stuff in” - P5

> ”[I] did like import tabs - would like to drag into a folder within a
> project” - P6

In addition to lightweight collection, Fuse users seemed to value the ability
to immediately annotate content using the sidebar, best illustrated by this
user’s remarks:

> ”[I enjoyed] capturing a web page and immediately going in and taking notes
> about what’s of interest” -P6

Beyond collecting content, Fuse users also seemed to greatly value the ability
to embed context within Fuse cards. Previously, provenance has been thought of
mostly as the context of where something comes from, but in this latter case,
we saw that Fuse enabled users to expand the concept of provenance to content
that they needed in order to recollect their own mental context, e.g., why it
was chosen, what they were doing, what they still need to do, etc. Within
Fuse, this information was collected in a number of ways, both automatically
by the Fuse system and explicitly by the users. Users seemed to value Fuse’s
automatic collection of basic provenance information, as it allowed them to
continue collecting without slowing down to record descriptions, source
details, and general impressions:

> ”[I] used to track everything in a google doc, [and] had to write a
> description - taking time …. [I] started using Fuse to have an immediate
> capture [with the same information]” - P3

> “[Fuse is nice because] sometimes I screenshot recipes and save it but I
> forget about it or forget what I named it, also with a screenshot I can
> never find the source” -P2

> ”I like that I can see a little image of the page [when I looked at it
> later] - helps remind me of what it is” -P5

Many Fuse users also manually created annotations for their items; annotations
were ubiquitously present across users that created projects with a non-zero
amount of content (49%) and their projects (41%). Looking more deeply at these
annotations, we found that annotations were a key affordance for storing
provenance-related information for users looking to store context while
conducting a task. To investigate how users did so, we conducted a qualitative
code (two passes, one open and one closed) of our annotations of user projects
in an attempt to understand what types of information users were collecting.
Reviewing all annotations, several things stood out. First, although many
note-taking applications build annotation features for attaching free-form
text comments to items, we noticed that user annotations in our system
primarily contained text extracted from the document, (e.g. the abstract of a
research article, highlighting key phrase in a recipe) and user-written
summaries of content, with one participant in our interviews (P3) explicitly
requesting features around automatic summarization and crowdsourced ’content
of importance’. It’s likely that key phrases, abstracts, and summaries stood
out to Fuse users as valuable annotations because they represent a summary of
the collected content that assisted users in overviewing their online research
collection. In comparison, few annotations recorded user opinions and comments
(e.g. ”I do not like this jacket”) or the state of the card within some sort
of task context (e.g. ”looked into this”).

Second, we looked at the length and size of user annotations, wondering if
there was any connection between the media type of content users collected and
the amount of user-embedded context they attached to it. We found that user
annotations are consistently logarithmic in size and shorter than two
sentences across the different types of card content (consistent with prior
work regarding user comments (e.g. (Horvath et al., 2021), (Marshall and
Brush, 2004))) with the exception of manually created cards and text snippets.
We hypothesize that cards containing text snippets may result from precise
extractions that create smaller, ’self-explanatory’ content that the user does
not feel the need to attach additional provenance content to. Manually created
cards seemed to have the largest diversity of (and largest average) lengths,
likely because they were less focused on summarizing extracted content and
more focused on externalizing user thinking, as indicated by P3: ”When I’m
[manually] adding a new card, I write my own title and text so I can keep
notes in my head”. This would be consistent with prior work highlighting the
diversity of different strategies users prefer for encoding provenance
information and indicates that similar tools may benefit from additional input
affordances (Fisher et al., 2012).

Figure 6. Bars graph representing the average lengths of annotations by word
in different types of Fuse content. The ’x’ marks refer to category means and
the lines refer to standard error bars (both colored respective to category).

Lastly, we investigated if the presence of annotations may be connected with
the organizational role of the card in the high-level structure of the
collection. Based on our findings regarding users’s preference for using
annotations for summaries, we hypothesized that the presence of annotation may
be linked to a higher position of the card in the structure, for example by
summarizing the content of a high-level folder. On the other hand, it’s
possible that the opposite were true - we knew from earlier that users valued
the ability to extract and highlight specific bits of content with
annotations, which implied that annotations would be most frequent in leaf
node cards that represent low-level evidence, such as an image of a restaurant
menu. Instead we found that cards in all positions of hierarchies seemed to be
equally likely to have annotations (approximately 16% of the time), regardless
of the whether the card was positioned as a root node within a hierarchy, had
content nested inside of it, or was a piece of content nested within another
piece of content (a leaf node, functionally).

###  5.2. [D2] In-situ organizing

Fuse’s second design goal focused on the need to enable users to organize
information without switching between browsing and a reference document,
inspiring the implementation of compact organizational features within Fuse
and ultimately the creation of the ’container card’ paradigm. Fuse users
seemed to value a variety of Fuse’s organizational features to help them
swiftly organize their content into a coherent structure where things fit
together. Nearly all users reordered their collection using the Fuse sidebar
(83%) to ensure a specific order to the cards. The ability to color-code cards
was in contrast much less used in practice - although color was highlighted by
a interview participant (P1) as a beloved feature, less than 1% of Fuse
projects used the feature. However, Fuse users seemed able and interested in
creating hierarchical structures to compress their collections, with 42% of
users creating hierarchy in their collections. These hierarchies were
consistently shallow, with only 4% of projects containing a structure deeper
than 2 levels. Users creating hierarchies did so with a variety of methods,
relying about equally on folder cards (46%) and Fuse’s unique ”container-
cards” (50%). Users seemed to understand and enjoy the card-in-card paradigm
and it’s related ’drop’ interaction for it’s intuitive usage:

> ”I like the fact that you can organize [the cards and] … drop all cards on
> top of each other (container cards)”-P1

Overall, this new feature was accepted by users, with 50% using it at least
once. In fact, users seemed to prefer this nesting affordance for different
types of content, card-in-cards largely held snippet content whereas folders
most often were used for holding more traditional bookmarks such as entire
webpages or PDFs. We see this as evidence that the card-in-card paradigm was
preferable to Fuse users compared to more traditional folders for aggregating
web snippets.

A detailed analysis of the types of organization and projects created by users
can be found in the ’Understanding Usage’ section below.

###  5.3. [D3] Visually compressing items

Fuse’s third design goal focused on the need to enable users to visually
compress items, resulting in the creation of a compact card UI design and
visually compressed representations of nested cards. We found that users
valued these features greatly, particularly in their combined ability to
provide a visual representation of user’s information foraging collections.
Users mentioned the impact of this affordance in many ways, whether it was
helping their collections feel readily-available for review, be quickly
skimmable, and provide the necessary depth to resume tasks. We discuss these
themes below.

The potency of having immediate visual access to their entire collection
regardless of media type or organizational structure was a common theme in
interviews, where users often compared it to current desktop and web paradigms
they use:

> ”Fuse seems to me to fit in between [Keep and Evernote] - much lighter
> weight and right there where you need it” -P7

> “Before with illustrator I have to save the file somewhere but with Fuse …
> and I can access it there without having to dig through the files” -P2

> “[I like Fuse] because of the pop out panel and being able to organize
> things right there and see what you already have … evernote does have a
> clipper but if you want to look or organize you have to go somewhere else.”
> -P7

> ”[It is] useful to have a quick way of seeing the things I’ve saved, instead
> of having to go onto Ikea site to check on my shopping cart” -P5

One user also appreciated the ability to toggle the entire sidebar for a more
dedicated reading experience, as demonstrated by their user quote:

> ”I’m not completely comfortable with something cluttering up the right side
> of my browser - I would open it if I wanted to look at what’s there, but if
> I’m browsing I don’t really need it” - P5

Beyond the ability to quickly access their collection, the responses of
several users indicated that the Fuse sidebar was valuable for overviewing
collections. This activity seemed to have two components. First, Fuse users
seemed to enjoy that the collapsed Fuse cards enabled them to see their entire
collection at once:

> With Fuse I can see the thumbnail and see what furniture it is, and can see
> every folder at once … Fuse is more accessible [than other tools] because
> [I] can open it on the browser, can see all the information at once - P2

> I like to read my notes and also scroll all of the materials. - P1

Second, Fuse users found this visual overview to be useful to think about
their foraging collections in spatial terms, as illustrated in this user
quote:

> “I like how it works visually, [especially] once I have the tabs
> established, I can really see where things are … [I will] soon have 115
> articles and poems coming at me - Fuse could be a good way to organize all
> that - could visualize how to neaten things up” -P4

Lastly, Fuse users indicated that the tool had assisted them in task
resumption. For some, the simple presence of the content within the sidebar
was helpful as a ”constant reminder” (P6). For others, the ability to recover
provenance allowed them to quickly jump back into their task and resume it
given limited time:

> ”[I] really like having all the information organized for me, [it] helps me
> when i’m scrolling through what I’ve saved, having the title, having the
> image there too helps me a lot. Sometimes if I just have 5 minutes I’ll
> click on things I didn’t have time to read yet” -P3

> ”[Fuse is] visually uncluttered and easy to organize information, easier to
> access and navigate and jog memory compared to bookmarks” - P8

Furthermore, by allowing users to quickly recollect their mental models, Fuse
enabled users to think about their tasks in terms of cycles of saving and
reviewing, a point made clear in several user responses regarding why they
enjoyed Fuse:

> can effortlessly throw something in, can easily come back to it later - P5
> (I enjoyed Fuse because I)

> able to very quickly make a bunch of bookmarks - haven’t gone back and
> organized them too much, because it’s only been a couple of days -P7  (I
> enjoyed Fuse because I was)

> ”organize pages I need to save and revisit/reread” - P8  (I enjoyed Fuse to)

In summary, Fuse users had found the visual nature of the sidebar system to be
useful for a number of activities related to managing their foraging
collections, from quickly reviewing their collections to spatially processing
their collections when overviewing them all together. These benefits seemed to
culminate in the ability to help start and stop foraging tasks, giving users
confidence to collect large amounts of content to review later. We discuss the
nature of these in-the-wild foraging tasks more in depth in the next section.

###  5.4. Understanding Usage

To further understand the foraging tasks that users were using Fuse for, the
primary author went through all 455 projects with their respective cards and
annotations in two passes (one open, one closed) to generate project and
domain categories from the collections until clear themes emerged (Charmaz and
Belgrave, 2019). In total, 134 users had created Fuse projects over the course
of the deployment. Projects with less than three non-folder cards were
excluded from the analysis as we found it difficult to infer user intention
for projects with very small collections of items, leaving 248 projects.

At a high level, follow-up interviews had made it clear that users were
utilizing Fuse for a diversity of tasks, from organizing instructional
materials to comparison shopping and trip planning:

> “[I’ll] soon have 115 articles and poems coming at me - Fuse could be a good
> way to organize all that - could visualize how to neaten things up” -P4

> “For quick comparison shopping … having [all of my cards] all saved
> somewhere together is useful …. [also I’m] planning road trip with family
> next summer - [I am] quickly bookmarking and tracking things we’re thinking
> about and getting that organized” - P7

T.M.* (14%) | U.S. (59%) | C. (23%) | S.F. (40%) | Q.A. (35%)
---|---|---|---|---
TD | ST | Q | OQ | CO | CL | SY | CO | FE | C/J | EV | DE | - | -
54% | 23% | 54% | 14% | 100% | 55% | 4% | 100% | 34% | 14% | 17% | 14% | 100% | 100%
Table 1. Project Categories based on inferred user intention found in FUSE
projects during the field study. Project categories are nonexclusive and as
follows: Task Management (TM), Understanding a Subject (US), Comparison (C),
Self-Reference (SF), Quick Access (QA). Sublabels are computed within each
Project Category and are as follows (from left to right): Todo (TD), State
(ST), Queue (Q), Open Question (OQ); Collection (CO), Clipping (CL), Synthesis
(SY); Collection (CO), Feature Extraction (FE), Criteria/Judgement (C/J),
Evidence (EV), Dependencies (DE). *Not a Project Category, records presence of
task management within the collection.

Furthermore, it was clear that users were getting different utility from Fuse
for different tasks, for example, some users were only interested in a
specific media type:

> “[Fuse is] good for things that you think look cool - not about bookmarking
> sites or pages, but more of a repository of nice images” - P5

Our qualitative analysis surfaced five main user intentions within projects.
This analysis also generated fifteen distinct domain categories, which we
discuss in relation to the user intentions in the section below:

####  5.4.1. Understanding a subject

A common user intention among analyzed projects was to collect resources to
research a subject, such as understanding the space of payment processing or
conducting a literature review of academic research. These projects were
primarily characterized by users who collected multiple documents of
information about the one subject or overlapping subjects, extracted clips
from the articles, and then (rarely but occasionally; 4% of the time)
synthesized the clips in some sort of external resource such as Google Docs.
It is highly likely that the reason we did not encounter many examples of
external synthesis stems from the fact that Fuse filled that role for users,
diminishing the need to store such links in Fuse projects. The percentage of
projects that showed evidence of external synthesis was low, with only about
2.4% of all projects doing so. However, annotations were frequent additions.
We found this user intention in a total of 58.9% percentage of all projects.

####  5.4.2. Comparing items

Several prior systems such as Mesh (Chang et al., 2020) and Unakite (Liu et
al., 2019) focus on supporting users sensemaking as part of a making a
decision. It was therefore of little surprise that we frequently (23.4% of all
Fuse projects) found users creating projects to compare sets of items or
services for purchase, such as selecting a piece of furniture or choosing
lodging for a trip. Unlike the previous category, projects in this category
were characterized by user collection consisting of many individual options.
Additionally, users often used the snippet, image extraction, and annotation
features of Fuse to surface features extracted features from content and
document judgements (e.g. ’this is too expensive’), with several clever users
representing dependencies between objects with the use of nesting. In one such
example, a user collected 12 different bed frames, nesting alternative frame
colors and sidetables under the item that they wanted to associate the two
under. Occasionally, Fuse projects contained elements of both comparing items
and understanding a subject. This often involved a collection of educational
resources for consumers such as articles on ’how to select a bicycle’ or
’types of coffee machines’.

####  5.4.3. Building a Self-Reference

In our review, we identified a more distinct and more advanced version of
understanding a subject. In this category, users created lengthy summaries of
documents and frequently extracted of key content into the card annotations as
part of curating a self-reference within Fuse. This is perhaps unsurprising,
as extracting or summarizing content into the annotations was mentioned
several times in our interviews with power-users, with one person suggesting
Fuse implement the ability to import an automatic summary of the webpage, and
another suggesting the use of crowdsourced summaries for popular webpages.
This more robust version of collection was popular in the domains of
literature review and instructional content, perhaps owing to the fact that
such material is often dense and requires summarization or extraction when
embedded in a compact collection such as Fuse. Such projects made up 40.3% of
all Fuse projects analysed.

####  5.4.4. Accessing resources quickly (bookmarking)

Prior literature has repeatedly shown that users collect content in bookmarks
in order to have rapid access to specific resources (Abrams and Baecker,
1997). Such projects were easily identify-able and frequently contained links
to coordination materials/hubs or instructional content, such as informational
portals. This category most frequently fit into two usage paradigms: users
maintained links to internet resources that they needed access as part of
conducting another task, or more rarely, the collection had no evident purpose
beyond serving as a collection of links that are pleasant for the user to
return to. Such collections rarely had items that were related and most likely
were collected for their aesthetic or emotional appeal to the user.
Altogether, 34.7% of all Fuse projects were created by users to have swift
access to internet resources.

####  5.4.5. Task Management

Although we did not design the system for task management, we noticed that
some users were using the organizational features of Fuse to document their
progress within a task, for example logging which items had already been
ordered and which under consideration within a Fuse project regarding
Christmas shopping. 14.1% of all projects contained aspects of task management
in this way. Within these projects, we noticed several distinct behaviors. 54%
of such projects contained annotations with explicit todos written down,
unsurprising as past social computing researchers have found todos to be a
frequent occurrence in notetaking. A similar number of the projects (54%) had
an explicit queue developed for future processing of items, often implemented
as a folder with nested items or a bookmarked listicle. Explicit notes
regarding the state of a task (e.g. reaching out to a company for a quote when
conducting comparison shopping) were present in 22.8% of such projects.
Lastly, a handful of projects (5; 14.2% of projects with task management),
contained externalized ’open questions’ that the user was likely holding to
guide future exploration.

##  6\. Discussion and Future Work

In this work, we explored the idea of an in-situ online research support tool
that affords both collection and organization. Our design was motivated by the
need to bridge the gap between collecting and organizing web content and
explores an interaction paradigm in which the browser can act as a seamless
extension of a user’s mental workspace. To implement this vision, we created
the Fuse prototype, a collapsible, card-based sidebar that is always available
to the user. Fuse allowed users to quickly collect pages or clips of web
content, organize and reference their structures in-situ, and create a variety
of complex structures to support the synthesis of information snippets for a
wide range of tasks. Throughout a 22-month deployment study and follow-up
interviews with power-users, we found that Fuse enabled users to utilize their
browser as an extension of their mental workspace throughout online research
tasks in a variety of domains.

Our results suggest that creating applications that interweave content
collection and organization can benefit users looking to synthesize web
content as part of online tasks. However, fully supporting users performing
online research within the browser will require revisiting several areas of
study regarding information management in the context of the browser. As
demonstrated by our work, a future system designer will need to consider the
personal provenance needs of users as they perform online research, as well as
the affordances of the environment where this task-related content will be
reviewed and accessed after it is initially foraged and curated. The nature of
the ensuing task may not be well aligned with the provenance desires of the
user when the data was collected and represented in the previous stage, as
prior work shows that task schemas of information differ highly between tasks,
as well between users. One potential approach to this would be the study and
creation of applications that mediate provenance needs for information
representations as they are imported from foraging applications such as Fuse
to a more complex organizational tools such as personal knowledge management
(PKM) software or applications tuned for presentation and sharing such as
slideshow software. An early thread in this direction can be found in the work
of Liu et al. regarding the information needs of programmers reusing
framework-related information (Liu et al., 2021). In the more immediate
context of supporting in-situ sensemaking, this research direction can also
foster new ideas regarding the support of multiple representations of
collected artifacts in information foraging software. As we’ve seen in Fuse,
some familiar concepts such as bookmarking are an enduring phenomena while
others representations may be best suited for specific user intentions such as
comparison.

Conversations with Fuse users in our follow-up interviews results implied that
Fuse assisted users in expanding their working memory during online research
by helping users visualize their information collections. As noted earlier,
one possible explanation for this positive response could be that visual cards
and spatial organizations are easier for browser users to process, therefore
increasing the amount of potential items that can be stored before becoming
burdensome. This is supported by prior work in psychology (Gyselinck and
Meneghetti, 2011) as well as web browser design (Robertson et al., 1998).
Understanding the empirical effects of either could be important for the
design of future card-based in-situ sensemaking support tools. In our
deployment, Fuse users occasionally collected very large projects that could
not be viewable without large amounts of scrolling, limiting the amount of
spatial information available to the user at any one time. One fruitful
direction of research could potentially explore methods of visualizing such
large collections that preserve the benefits of spatial and visual memory even
when the majority of items are collapsed beyond the view of the user, such as
degree of interest graphs (Van Ham and Perer, 2009), automatic tab clustering
(Dipin et al., 2019), or lightweight interactions for previewing and
overviewing (Greene et al., 2000).

Another explanation for this positive effect may originate from the design of
our cards, which are compact and can be collapsed in order to enable overviews
of large collections. Since a user would need to process fewer pieces of
information per item as they are performing their organizational tasks, this
would hypothetically enable them to build representations that contain more
items. When a user does need more information about a specific item, they can
use the embedded cues within the card to recall additional details, much like
Fuse users used viewport screenshots and urls to help recall details about why
a specific page was captured. The high utility from these simple cues implies
that it’s likely that even with our compact design, Fuse cards may hold more
information than is necessary for a user before they decide to perform an
additional ’recall’ step. It remains an open question to determine how much
information needs to exist for users performing common online research tasks
to be able to perform the deeper recall of features such as provenance,
intentions, or quality. Removing this redundant or extraneous information
could pave the way to even more compact representations, and thus supporting
an even larger working memory for users. Lastly, the ability to structure
cards within cards could have also played a role in enabling users to reduce
the amount of information they need to interact with by removing the need for
users to generate organizational labels that semantically group all nested
elements, a burdensome task (Abrams and Baecker, 1997). Instead, users
frequently nested items within other items without inputting a label to the
higher-level card (aside from the metadata that Fuse provides from the
original site).

Fuse also enabled users to maintain page and snippet collections over long
durations of use, traditionally a burdensome task for users of explicit
bookmarking lists (Kaasten and Greenberg, 2001). Perhaps attributing to Fuse’s
ability to support users’ ability to recall information about collected items
(including in some cases the item’s state within the process of an external
task), Fuse users were able to resume their foraging and organizing over many
sessions - in one case entirely replacing the native bookmarking features of
their browser for daily use. Understanding which features of Fuse beyond
annotation were most useful to users for the resumption of their processes of
collection and organization is still an open question, although such work
would be valuable for any future extensions into the mobile context, where
interruption is common and session times are generally shorter. The topic of
suspension and resumption of tasks in the browser has been approached by
researchers from several angles, such as re-using searches and re-finding
(Morris et al., 2008) as well as task-focused approaches to grouping browser
tabs (Rajamanickam et al., 2010) (Wang and Chang, 2010). This direction of
research also has strong parallels with the study of personal task management
(PTM) tools and tools that explore the intersection of task management and
browser tab organization (CHANG et al., 2021). Leveraging the insights from
such work can be key to optimising systems such as Fuse for long-term use,
whether it be understanding how to best hide old, irrelevant items or
maintaining quick access to useful resources as collections grow.

###  6.1. Beyond Collecting and Curating

Our interviews with power-users made it clear that their foraging within Fuse
was situated alongside a task context that would involve other activities and
applications that are specialized such as for accounting or documentation:

> ”A spreadsheet is pretty good for keeping track of the budget [of Christmas
> shopping], which I don’t think fuse would be good at” - P7

> ”[If possible, I’d like Fuse to help me] create citations/references - would
> be a lot of value to me” - P6

As previously mentioned, these user quotes suggest that tools aiming to
support sensemaking in the browser will likely need to be designed with tasks-
specific information representations in mind. This need would be further
amplified if Fuse collections were extended to be shareable between users, as
it’s likely that re-users of Fuse collections will have different goals and
need to re-represent the data. The grander vision of Fuse could perhaps take a
similar form to that of Vannevar Bush’s vision of the Memex, wherein
information collections would not just be stored for individual users, but
also shared with others for use in exploration (Nyce and Kahn, 1991). In the
context of Fuse and online research, enabling the sharing of information
collections in a way that is productive to other users would require an
understanding of how and why sensemaking reuse occurs. Additionally, it would
be important to understand how users select which parts of other’s sensemaking
collection to co-opt, and what factors influences this act of trust. Work in
this vein is far and few in between, although researchers have studied this in
the context of comparison charts for software documentation (Liu et al.,
2021).

In this work, we explored the idea of an in-situ online research support tool
that aims to support seamless collection, externalization, and organization
across a wide range of domains. In doing so, we created the Fuse prototype, a
collapsible, card-based sidebar that is always available to the user.
Throughout a 22-month deployment study and follow-up interviews with power-
users, we found that Fuse supported their working memory in online research
tasks in a variety of domains. Although Fuse was a prototype system, we hope
it spurs the development and exploration of sensemaking support tools that
seamlessly combine the experience of browsing and curating to support online
research directly into the browser.

###### Acknowledgements.

This work was supported by NSF grants FW-HTF-RL-1928631, SHF-1814826, and the
Office of Naval Research. We’d also like to thank the reviewers for their
generous review and feedback. Finally, we’d also like to acknowledge our study
participants, without whom this work would not have been possible.

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