Synopsis Presentation

Design and evaluation of a new file browser interface

in Linux environment

Debmalya Sinha

Synopsis SeminarJanuary 2013

Objective

Provide file browsing convenience to new users

● Filesystem Visualization● File Arrangement● Finding Files

Objective



File copyDownloads

DesktopHome

Pictures

Objective



Development

SahajBrowser

A novel file Browser

Gardener

A file browser assistant

Helps in Visualization and file arrangement

Helps saving files into its correct contextual place

Development

SahajBrowser

A novel file Browser

Gardener

A file browser assistant

Sahaj Linux

Work Done

1. Design and evaluation of SahajBrowser Visualization

2. Design and evaluation of SahajBrowser File Arrangement

3. Living with Trees: a cognitive study to find the nature and extent of categorization and organization practices of target users

4. Design and evaluation of Gardener

5. Design and evaluation of Sahaj Linux

1. Filesystem Visualization

● Helps users understand Folder Hierarchy – the parent-child relationship between folders

● Reduces time for browsing through the filesystem

Good Visualization

Faster File Browsing

Clearly distinguishable folder relationship

1. Filesystem Visualization

● Placement of the folders

● Length of the representation

Good Visualization

Faster File Browsing

Clearly distinguishable folder relationship

Existing file browsers

● Narrow tree-view

● Congested

● No file list in tree-view

● Length of tree depends on number of child folders

SahajBrowser Visualization


● Constant distance

● Length does not depend on number of child folders

● Better placement

● Intuitive parent-child relationship

● File list in tree view

● Comparing content easier








between a parent and its child folder






















Issues addressed

Helps new users understandthe Filesystem Hierarchy

intuitively

Constant distance reducesFile browsing time

User Interaction Survey

Modelling by Fitts' Law

The browsing task

Task: To go from one folder in the filesystem to another folder in an expanded treeview

1) source and destination are L levels away

2) all the folders in between source and destination hasN number of child folders in an average.

/home/ecntrk/Documents/research-writing/Thesis/Chapters

The browsing task

Task: To go from one folder in the filesystem to another folder in an expanded treeview

1) source and destination are L levels away

2) all the folders in between source and destination hasN number of child folders in an average.

/home/ecntrk/Documents/research-writing/Thesis/Chapters

In this example, the level difference L = 5

source destination

The task

● Browse a hierarchy of (N, L):

– N number of average child folders for each folder

– L numbers of level of the hierarchy

● We vary N from 3 to 20 and L from 4 to 8

Level 1

Level 2

Level 3

Level 4

Level 5

} L

N

Fitts' Law modeling

Calculates the Index of difficulty(ID)

Destination

source

B

HD

ID = log2(1+D/W) Where W = min(B,H)

Windows Explorer

● For Explorer, the distance from one source folder to a destination folder depends on both the number of average child folders (N) and the level difference (L)

D = (N * L * 17) px

W = 17 px

ID = log2( 1 + N * L )

SahajBrowser

● For SahajBrowser, the distance between parent and child does not depend on number of child folders.

● Thus, distance from one source folder to one destination folder depends only on the level L

D = (L * 238.64) pxW = 170 px

ID = log2( 1 + (1.40 L) )∗

Result

Windows Explorer

SahajBrowser

Average number of child folders (N)

Ind

ex o

f Diff

icul

ty

Level 864

User Interaction Survey

● Finds out how easily new users understand filesystem hierarchy (with two different visualizations)

● Comparison of Explorer and SahajBrowser

● Users: 21 new users

– Computer inexperienced

– Digital experience: mobile phone

– Age: 32-40● Were given a brief introductory concept on folder hierarchy

Method

● Set up and expanded a hierarchy of level 3 with 12 child folders at each level

● The folders has same names (alphabets A – L ) in each level

● 3 Questions asked :

– Find parent

– Find Grandparent

– Find 2 siblings of parent named “B” and “J”

A

B

C

D

E

F

G

H

I

J

K

L

A

B

C

D

E

F

G

H

I

J

K

L

A

B

C

D

E

F

G

H

I

J

K

L

Result

Q1 Q2 Q30

5

10

15

20

25

SahajBrowserExplorer

Questions

Res

pon s

e T

ime

in s

econ

ds

2. File Arrangement

One Source Folder One Destination Folder

File copy

Existing file browsers only provide

Multi Folder File Arrangement

Pictures

File copyDownloads

Desktop

Home

Multi Folder File Arrangement

Pictures

File copyDownloads

Desktop

Home

Conventional method: one-to-one copy for each source folders

Accross the room

Jars of candy !

Empty jar to put some candies

Empty Bowl

Empty jar to put some candies

File arrangement task

/home

user1 user2 user3

music songs Downloads

mediafiles

files

Level 1

Level 2

Level 3

Level 4copy

SahajBrowser File Arrangement

Select item A1, A2 from folder A

Select item B1, B2, B3 from folder B

Start

End

Selection Queue

Existing Browsers SahajBrowser

A1, A2

B1, B2, B3 A1, A2, B1, B2, B3

A1, A2

A1, A2, B1, B2, B3B1, B2, B3

Nil Nil

Job:

SahajBrowser Multi-folder selection

KLM-GOMS model analysis

Algorithm for Nautilus

Algorithm for Windows Explorer

Algorithm for SahajBrowser with Multiple Selection

KLM-GOMS

Kieras(2003) has analytically and experimentally defined average completion times for the primitive operators in Keystroke Level Modeling(KLM)

Predicted time in seconds

Assuming Level = L for every folder to operate on. We also assume the average time to select files from one source folder is C seconds.

tnaut

= (n (5 L + C + 0.1)) sec∗ ∗

texpl

= (2.5 L + n (2.5 L + C + 1.3)) sec∗ ∗ ∗

tsahaj

= (n (2.5 L + C) + 2.5 L + 0.1) sec∗ ∗ ∗

n = total number of source foldersL = average level of every source and destination foldersC = time to select the files in a single source folder

2 3 4 5 6 7 8 9 10

0

50

100

150

200

250

Nautilus

Explorer

SahajBrowser

Number of source folders

Tim

e in

se

con

dsResult

Comparison of SahajBrowser with two existing file browsers; Nautilus and Windows Explorer

Here we vary the number of source folders “n” and have the graph for 3 different browsers.

Assuming: Level L = 4

3. Finding files in a filesystem

Maa,Have you seen My thesis draft?

3. Finding files in a filesystem

● It is pretty hard to find from an unorganized pile

● Users hardly use “find” utilities (Sasse 2003, Nardi 2001)

● People “Browse” contextually to find files in filesystem

Our approach

● Browsing by context needs a semantic hierarchy

● Such hierarchy needs to be maintained by users.

● We provide necessary assistance to help users maintaining semantic folder hierarchy by putting the files into their correct contextual place while saving

Maa,Have you seen My thesis draft?

PUT IT WHERE IT BELONGS

IN THE FIRST PLACE

Semantic Folder Hierarchy

● It is very easy to find items while browsing in a Semantic Folder Hierarchy

● Everytime a new file is added, it has to be put in its correct contextual place.

● But users are reluctant to maintain it this way

● We help them maintaining the semantic hierarchy

Our work

● Living with Trees: a cognitive experiment that finds out the nature of categorization and organization practices of the target users

● Gardener: A filebrowser assistant that helps users maintaining semantic filesystem hierarchy.

Our work

● Living with Trees: a cognitive experiment that finds out the nature of categorization and organization practices of the target users

● Gardener: A filebrowser assistant that helps users maintaining semantic filesystem hierarchy.

Living with Trees

● Categorization: Everyone can .. but people are reluctant to actually do so

● Do people organize the categories hierarchically?

● upto how many levels target users do organize hierarchically?

● What is the effect of external stimulation on their performance?

● The findings are crucial for implementing semantic folder hierarchy.

The method

● An unorganized pile of 82 cards (bearing pictures of common objects and personalities) is given to the participants

● They were asked to categorize the cards on the floor

● Unlimited space given for placing

● We noted the if they are making smaller concepts from more general concepts

● After they finishes, we asked them if they can do better

● The final performance after our stimulation, is noted

Sample placement

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 230

2

4

6

8

10

12

14

Participants

Hig

hest

Le

vel o

f H

iera

rch

y

Results - (top-down)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 230

5

10

15

20

25

30

Participants

Nu

mb

er

of C

ate

go

rie

s

After Stimulation

Before Stimulation

After Stimulation

Before Stimulation

Results - (bottom-up)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 230

1

2

3

4

5

6

7

Participants

Leve

l of

Bo

tto

m- u

p H

iera

rch

ies

After

Before

TopDown and BottomUp comparison

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 230

1

2

3

4

5

6

Top DownBottom Up

Participants

Hig

he

st L

eve

l of

Hie

rarc

hy

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 230

1

2

3

4

5

6

7

8

9

Participants

Hig

he

st L

eve

l of

Ca

teg

ori

es

Top DownBottom Up

BeforeStimulation

AfterStimulation

Result

In top down approach:1. Average Level of hierarchy during categorization is 3. 2. Average Number of Categories are 6.43 3. Both the numbers shoot up to 7 and 16.29 after some help from the experimenter

In bottom up approach:1. Participants are much less able to categorize like this2. Help from experimenter only increases the number to very tiny portion.

Conclusion

● The initial hierarchical organization is, in average, moderate (3 levels)

● External assistance has a huge impact on the performance (135%)

● People can organize much better if an assistant is guiding them.

Challenges

● The main challenge for users is:Maintaining the Semantic Hierarchy each time a file is saved

● Maintenance is a major problem for two main reasons:

1. Users have to “remember” all concepts in filesystem in order to find a suitable place for the new item

2. Filesystem is non associative. Users can't directly access files. Have to browse by the hierarchy

The GardenerA filebrowser assistant to help users

create and maintain semantic folder hierarchy tree

How Gardener works

● Whenever a user tries to create a file, Gardener takes the input filename/foldername and suggests a location

● It generates a set of similar keywords from the filename and then searches the filesystem for a contextual match.

● User can store the file/folder in a single click from the Gardener interface.

Let's see a little demo

Contextual SuggestionsDoes not suggest only by filenames, but its context

Richard_Feynman_smiling_awkwardly.png

Save this picture.. but where?

Contextual Suggestions

Richard_Feynman_smiling_awkwardly.png

Gotcha..

this fellow is a

Nuclear Physicist

Does not suggest only by filenames, but its context

~/Pictures/people/physicists

So let's save it in:

ArchitectureGardener is a filebrowser plugin. It has two main parts in its execution. The back-end part has 3 blocks. The output suggestions of the backend are shown by a front end.

1. Input sanitizer: The input keyword is generated from the raw input. 2. Keyword generator: Takes sanitized input keyword and generates Hypernym and Synonym keywords. 3. Filesystem Search: Takes this list of the keywords list searches them in the filesystem to give parent and the peer suggestions fro the front end.

Input Filename

InputSanitizer

Gardener Interface

Keyword Generator

FilesystemSearch

OutputSuggestions

Input

keyword

Synonyms

Hypernyms

RegExp

matches

Architecture

Input Filename

InputSanitizer

Gardener Interface

Keyword Generator

FilesystemSearch

OutputSuggestions

Input

keyword

Synonyms

Hypernyms

RegExp

matches

falling leaves in autumn123.jpg

['leaf', 'autumn', 'fall'] ['plant organ',

'leaf', 'season', 'leafage', 'autumn', 'foliage', 'fall', 'time of year']

1) ~/Pictures/walpaper/seasons

2) ~/Pictures/leafy sky

Input Sanitizer

1. Stop Word Removal: Removes words such as “and”, “of”, etc2. Stemming: Removes unwanted suffixes like numbers and special symbols etc 3. Lemmatization: helps finding the base word from the stemmed word.4. POS Tagging: chooses only the nouns and verbs from a compound filename

Input FilenameStopword Removal

Stemming

LemmatizationKeyword

compound

input

Significant

Words

Unwanted Prefix and Suffix removal

POSTagger

Clean

Words

Extracted

Nouns

Input Sanitizer Module

To be used by Keyword Generator

Keyword Generator

Synonym Generation

Hypernym Generation

Input keyword

Synonymkeywords

Hypernymkeywords

WordNetDatabase

NLTK DB(RDF schema)

Instance of Supersetkeywords

Filesystem Search

● Categorizes the files into 4 parts: Documents, Music & Video, Pictures and Misc.

● Search the keywords in the appropriate folder according to file type.

● will search .jpg, .png etc in /home/Pictures (changable)

● If any match has not been found, it'll ask the user to create a new folder with the right context

● User can cancel suggestions and browse to save in any other folder

How good is Gardener

● Usability survey with 12 computer experienced users

● Task is to save 32 files with Gardener

● Categorized Gardener output into 4 parts:

– Actual words, Hypernym, Synonyms and new folder suggesiton

● Average acceptance rate = Total number of suggestion clicked

Total number of suggestions generated

Average usage of Gardener suggestions

24.47

9.11

20.83

49.73

4.17

ActualSynonymHypernymNew folderCancel

4.17

Average acceptance rateA

vera

g e a

cce

pta

nce

(in

pe r

cent

a ge)

Total number of suggestion clicked We define the “Average Acceptance rate” =

Total number of suggestions generated

System Usability Scale

● Measured usability with 10 questions of SUS

● Each question is a 5 point “Likert scale” type (Strongly agree (5 points) to Strongly disagree (1 point) )

1. I think that I would like to use this system frequently.

2. I found the system unnecessarily complex.

3. I thought the system was easy to use.

4. I think that I would need the support of a technical person to be able to use this system.

5. I found the various functions in this system were well integrated.

6. I thought there was too much inconsistency in this system.

7. I would imagine that most people would learn to use this system very quickly.

8. I found the system very cumbersome to use.

9. I felt very confident using the system.

10. I needed to learn a lot of things before I could get going with this system.

SUS scoreThe average SUS score of Gardener is very high at 89.42 out of a possible 100.

Questions

Stronglydisagree

Future Work

Clarity.mp3

Black Pearl.jpg

User saves

Which is a song by

John Mayer

Pirates of Caribbean

If the user doesn't provide this, Gardener can't decide the right folder, Unless there's an entry about it in the RDF schema, which is very impractical

We will try to include more sparse informations like these in future from Internet.

Which is a ship in

Sahaj Linux

UI survey

● Two tasks were given to 21 target users:– Open a text file

– Play a music file

● How to open something by clicking was explained.● The response time was noted.

Results

Task 1 Task 20

5

10

15

20

25

30

35

40

Sahaj LinuxWindows XP

Res

pon s

e T

ime

in s

econ

ds

Overview

1. Design and evaluation of SahajBrowser Visualization

2. Design and evaluation of SahajBrowser File Arrangement

3. Living with Trees: a cognitive study to find the nature and extent of categorization and organization practices of target users

4. Design and evaluation of Gardener

5. Design and evaluation of Sahaj Linux

Technology

Synopsis Presentation