netlens: iterative exploration of content-actor network data
DESCRIPTION
NetLens: Iterative Exploration of Content-Actor Network Data. Hyunmo Kang, Catherine Plaisant, Ben Bederson. Challenges of Network Data Visualization. by Frank van Ham. TouchGraph. Challenges of Network Data Visualization. Complex Analytic Tasks Incremental data exploration - PowerPoint PPT PresentationTRANSCRIPT
NetLens:Iterative Exploration of Content-Actor Network Data
Hyunmo Kang, Catherine Plaisant, Ben Bederson
Challenges of Network Data Visualization
by Frank van HamTouchGraph
Challenges of Network Data Visualization
Complex Analytic Tasks Incremental data exploration Iterative query refinement
Scalability Common simple UI components
e.g. histogram and lists
Generality Apply to any dataset matching Content-Actor model
e.g. digital library, photo collections, email collections, case law, etc.
Data Analysis (Content-Actor Model)
Entity E1(Content)
Entity E2(Actor)
Intra-relationship Intra-relationship
Inter-relationship
Data Analysis (Content-Actor Model)
Content(Paper)
Actor(Author)
Intra-relationship Intra-relationship
Inter-relationship
Paper
Year
Reference People
Title
Category Keywords Address
Name
Author
Data Analysis (Content-Actor Model)
Content(Email)
Actor(People)
Intra-relationship Intra-relationship
Inter-relationship
Date
Reply, Forward
People
Subject
Size Attachment Address
NameTo, CC
From
Data Analysis (Content-Actor Model)
Actor(Photo)
Content(People or Category)
Intra-relationship Intra-relationship
Inter-relationship
Photo
DatePeople
Comments
Path Favorite
X, Y location
X, Y location
HAS
HAS Category
DEMOScreenshots at www.cs.umd.edu/hcil/netlens Video at www.cs.umd.edu/hcil/netlens/VASTvideo
Task Analysis
Search By
SearchResult
Entity1 (Paper) Entity2 (People)
Entity1’s Attributes Entity1(Paper) Entity2’s Attributes Entity2 (People)
Entity1(Paper)
Search for papers by paper attributes such as year, keywords, title, conference, topics, etc.
Search for papers that “cite” or “are cited by” the selected papers along with frequency
Search for papers by people attributes such as author’s affiliation, institution, nationality, etc.
Search for papers written by the selected authors (either conjunctive or disjunctive)
Entity2(People)
Search for authors by paper attributes such as year, keywords, title, conference, topics, etc.
Search for authors of the selected papers with frequency (the number of papers per each author)
Search for authors by people attributes such as author’s affiliation, institution, nationality, etc.
Search for academic advisors of the selected authors (either conjunctive or disjunctive)
Task Analysis
Single step tasks How many papers on “User Study” were published in 1998? Who are the authors of the papers on “Virtual Reality”, which
were published at the CHI 99 conference? Which paper is the most frequently cited by the papers
published at the CHI 04 conference? Which author is most frequently cited in the “InfoVis” topic? How many papers were published by UMD HCIL people? Who are the authors whose nationality is Korea?
Task Analysis
Multiple step tasks Evaluate individuals:
- how many papers were self-referenced? - how frequently was each paper referenced by other papers?
Identify communities:- what are the major paper topics published by UMD HCIL? and who in this group has the most papers in that topic?- how do UMD HCIL’s research interests change over time? and who in this group made that change?
Find experts (to review papers or come to workshop):- who wrote the most papers in the InfoVis topic? and how many papers cited his papers?- whose paper in the InfoVis area is most frequently referenced by other papers?
Learning about a new topic (to find a good PhD topic):- which topic has growing publications? and who contributed most to this topic last 3 years?- what are the other topics the authors in InfoVis area also get interested in?
Where should I go on a sabbatical?- which country (or research group)’s authors most frequently reference my papers?
Design Challenges
History and Integrated HelpSequence of interactions to
accomplish a task (lost in exploration)
“How did I get here?”“What does the current filtered
dataset mean?”
Design Challenges
Multi-layered InterfaceUsers do not need all the windows
• Complexity of data and tasks
• Computation efficiency
• Users’ usage levels and their preferences
• Etc.
Design Challenges
Data ExportIntegration of graph visualizing tool
TreePlusExporting methods
• Windows clipboard
• Internal graph class object
• Xml documents
NetLens Extension
Emails on the leftPeople on the right
Overviews provided for all attributes (here for emotional tone on emails side)
Filtered to show only emails related to CAenergy crisis; and the people who sentthem are shown on the right side.
(Joint Institute for Knowledge Discovery) - http://jikd.umiacs.umd.edu
NetLens Extension(Joint Institute for Knowledge Discovery)
• Generality and Scalability
JIKD data schema
NetLens Data Schema
NetLens System Architecture
NetLens Written in C#, Piccolo toolkit
Database Server MySQL
ADO.NET driver for MySQL MySQL connector/NET 1.0.7
Web Server Mac OS X Server
Web API CGI, JSP (e.g. email search, people’s bio, etc.)
Evaluation
Heuristic Evaluation by NIST Possible directions:
Usability• Measure usability• Speed, performance, • Learnability• Error rates
Power• Comparing range and complexity of possible
queries• SQL queries?
Generality• How easy it is to apply new datasets to NetLens
PhotoMesaBrowse, Annotate, and Search Digital Images
Hyunmo Kang and Ben Bederson
PhotoMesa Image Browsing
Zoomable User Interface
Zooming into a group of photos
Zooming into a single photo• PhotoMesa shows all photos in a single view• Bigger preview by moving over a thumbnail• Browse photos by zooming in or out• Dynamic sorting and grouping
PhotoMesa Image Browsing
Zoomable User Interface
• PhotoMesa lets you control visible photos
• All photos• Unhidden photos• Representative photos• Favorite photos only
Show only the representative photos for each group
PhotoMesa Image Browsing
Zoomable User Interface
• Browse photos in “Scroll” mode with detail photo view
Photo Information with EXIF
Scrollable Thumbnails Panel
Detail Photo Panel
PhotoMesa Annotating
Add a caption and mark photo as favorite or hidden
Label who is in the photo
Label objects in the photo (e.g. animals, locations, etc.)
• People Annotation Mechanisms: Checkbox Annotation, Drag-and-drop Annotation, Hotkey Annotation
• Category Annotation: Create user-defined hierarchical structure of object types to annotate your photos with
PhotoMesa Annotating
• Bulk Annotation: Annotate multiple photos simultaneously with the same annotation mechanisms
PhotoMesa Searching
By keyword
By folders
By people
By category
By year
By month
PhotoMesa Photo Sharing
Upload Photos Metadata e.g.) people, category, photo info, etc.
Remove Update Search Web Services
Browse with web browser Add comments
PhotoMesa Data Schema
PhotoMesa SQL Query
Free Text Search (Find photos containing word “kang”)
SELECT Photos.*FROM (Photos INNER JOIN (Categories INNER JOIN
PhotosCategories ON Categories.categoryname = PhotosCategories.categoryname) ON Photos.url = PhotosCategories.url) INNER JOIN (People INNER JOIN PhotosPeople ON People.personname = PhotosPeople.personname) ON Photos.url = PhotosPeople.url
WHERE (((PhotosPeople.personname) Like "*kang*") OR ((Photos.url) Like "*kang*") OR ((Photos.created) Like "*kang*") OR ((Photos.uploaded) Like "*kang*") OR ((Photos.description) Like "*kang*")) OR (((PhotosCategories.categoryname) Like "*kang*"));
PhotoMesa SQL Query
Add Photo
INSERT INTO Photos (url, created, uploaded, description, photomark, thumbnail, width, height) Values(“url”, “2006-04-20", “2006-04-20", “hyunmo’s trip to Seoul”, 1280, 1024);
Add People
INSERT INTO PhotosPeople (url, personname, x, y, time) Values(“url”, “hyunmo kang“, “0.1234”, “0.789” “2006-04-20");
INSERT INTO People (personname, lastname, firstname) Values(“hyunmo kang”, “kang”, “hyunmo”);
PhotoMesa System Architecture
PhotoMesa Client Written in C#, Piccolo toolkit
Database Server MySQL
ADO.NET driver for MySQL MySQL connector/NET 1.0.7
Web Server Apache
Web API PHP (photo upload, web services)
Questions?
More visualization projects are available athttp://www.cs.umd.edu/hcil
PhotoMesahttp://windsorinterfaces.com
NetLenshttp://www.cs.umd.edu/hcil/netlens
Email: [email protected]