How do we find personal files?

Bergman, Ofer; Whittaker, Steve; Sanderson, Mark; Nachmias, Rafi; Ramamoorthy, Anand

doi:10.1145/2207676.2208707

Cited by 20 publications

(5 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This might be because navigation-based retrieval requires less cognitive effort. Bergman [5] also found a difference in retrieval time between Windows and MacOS users (17.3 seconds on Windows vs. 12.6 on MacOS on average). Furthermore, as with command usage [22] and email messages [9], Fitchett [15] also found that the frequencies of file retrievals can be approximated by Zipf's Law [40], suggesting that people's patterns of file retrieval are strongly repetitive, with a small number of frequently revisited files, and a large number of infrequently visited ones.…”

Section: Personal File Systemsmentioning

confidence: 91%

“…Users have thousands of files and folders in their file systems (Goncalves & Jorge [21] found 8000 on average and Henderson & Srinivasan [26] 5850). They create hierarchical structures that reflect their activities, as reported by Bergman [2,3,4,5], Henderson [24,25,26] and Jones [28]. Although users tend to have different habits for building these structures (e.g.…”

Section: Personal File Systemsmentioning

confidence: 99%

“…Wanyu In addition to using search to potentially improve file access, e.g. [8], researchers have tried to tackle this problem by looking at different aspects of file retrieval: how users organize personal information [5] and how visualization [27] and prediction algorithms [10,14,31] can improve efficiency. Fitchett & Cockburn introduced AccessRank [14], an algorithm to predict what users are going to look for next, and demonstrated using three real datasets that it outperforms other prediction algorithms such as MRU (Most Recently Used) and Markov chain models [34].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

BIGFile

Liu

Rioul

McGrenere

et al. 2018

Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems

View full text Add to dashboard Cite

We introduce BIGFile, a new fast file retrieval technique based on the Bayesian Information Gain framework. BIGFile provides interface shortcuts to assist the user in navigating to a desired target (file or folder). BIGFile's split interface combines a traditional list view with an adaptive area that displays shortcuts to the set of file paths estimated by our computationally efficient algorithm. Users can navigate the list as usual, or select any part of the paths in the adaptive area. A pilot study of 15 users informed the design of BIGFile, revealing the size and structure of their file systems and their file retrieval practices. Our simulations show that BIGFile outperforms Fitchett et al.'s AccessRank, a best-of-breed prediction algorithm. We conducted an experiment to compare BIGFile with ARFile (AccessRank instantiated in a split interface) and with a Finder-like list view as baseline. BIGFile was by far the most efficient technique (up to 44% faster than ARFile and 64% faster than Finder), and participants unanimously preferred the split interfaces to the Finder.

show abstract

Section: Personal File Systemsmentioning

confidence: 91%

Section: Personal File Systemsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

BIGFile

Liu

Rioul

McGrenere

et al. 2018

Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems

View full text Add to dashboard Cite

show abstract

“…This works well for identifying broad PIM practices and challenges that users remember, like transferring files between computers (Capra, 2009). It is limited, however, as it cannot capture data about activities or aspects of behavior of which users may not be cognizant, like the number of empty folders they keep, and participants" perceptions of their own PIM behavior can be inaccurate (Bergman, Gradovitch, Bar-Ilan, & Beyth-Marom, 2013) The second approach, observing participant behavior, entails recording participant behavior, for example using video to capture the behavior exhibited during typical work tasks (Bruce, Jones, & Dumais, 2004), guided tours of the participants" desktops (Barreau, 1995), or structured experiment tasks (Bergman, Whittaker, Sanderson, Nachmias, & Ramamoorthy, 2012;Benn et al, 2015). This allows for exploring particular aspects of user behavior in depth, like organizing downloaded files (Jones, Bruce, & Dumais, 2001) and retrieving shared files (Bergman et al, 2014).…”

Section: Problem Areamentioning

confidence: 99%

“…The second approach, observing participant behavior, entails recording participant behavior, for example using video to capture the behavior exhibited during typical work tasks (Bruce, Jones, & Dumais, ), guided tours of the participants' desktops (Barreau, ), or structured experiment tasks (Bergman, Whittaker, Sanderson, Nachmias, & Ramamoorthy, ; Benn et al ., ). This allows for exploring particular aspects of user behavior in depth, like organizing downloaded files (Jones, Bruce, & Dumais, ) and retrieving shared files (Bergman et al ., ).…”

Section: Problem Areamentioning

confidence: 99%

Cardinal: Novel software for studying file management behavior

Dinneen

Odoni

Frissen

et al. 2016

Proc. Assoc. Info. Sci. Tech.

View full text Add to dashboard Cite

In this paper we describe the design and trial use of Cardinal, novel software that overcomes the limitations of existing research tools used in personal information management (PIM) studies focusing on file management (FM) behavior. Cardinal facilitates large-scale collection of FM behavior data along an extensive list of file system properties and additional relevant dimensions (e.g., demographic, software and hardware, etc). It enables anonymous, remote, and asynchronous participation across the 3 major operating systems, uses a simple interface, and provides value to participants by presenting a summary of their file and folder collections. In a 15-day trial implementation, Cardinal examined over 2.3 million files across 46 unsupervised participants. To test its adaptability we extended it to also collect psychological questionnaire responses and technological data from each participant. Participation sessions took an average of just over 10 minutes to complete, and participants reported positive impressions of their interactions. Following the pilot, we revised Cardinal to further decrease participation time and improve the user interface. Our tests suggest that Cardinal is a viable tool for FM research, and so we have made its source freely available to the PIM community.

show abstract

The ubiquitous digital file: A review of file management research

Dinneen

Julien

2019

Asso for Info Science & Tech

View full text Add to dashboard Cite

Computer users spend time every day interacting with digital files and folders, including downloading, moving, naming, navigating to, searching for, sharing, and deleting them. Such file management has been the focus of many studies across various fields, but has not been explicitly acknowledged nor made the focus of dedicated review. In this article we present the first dedicated review of this topic and its research, synthesizing more than 230 publications from various research domains to establish what is known and what remains to be investigated, particularly by examining the common motivations, methods, and findings evinced by the previously furcate body of work. We find three typical research motivations in the literature reviewed: understanding how and why users store, organize, retrieve, and share files and folders, understanding factors that determine their behavior, and attempting to improve the user experience through novel interfaces and information services. Relevant conceptual frameworks and approaches to designing and testing systems are described, and open research challenges and the significance for other research areas are discussed. We conclude that file management is a ubiquitous, challenging, and relatively unsupported activity that invites and has received attention from several disciplines and has broad importance for topics across information science.

show abstract

How do we find personal files?

Cited by 20 publications

References 11 publications

BIGFile

BIGFile

Cardinal: Novel software for studying file management behavior

The ubiquitous digital file: A review of file management research

Contact Info

Product

Resources

About