Transcript What is Zotero?

SEASR Analytics and Zotero
Data-Intensive Technologies and Applications,
National Center for Supercomputing Applications,
University of Illinois at Urbana-Champaig
Outline
• Brief Zotero Introduction
• SEASR Analytics for Zotero Plugin
• Interaction between SEASR and VUE
The Zotero Picture
The
WEB
Zotero
Store
What is Zotero? (from Zotero Quick Start Guide)
•
A citation manager. It is
designed to store, manage,
and cite bibliographic
references, such as books and
articles. In Zotero, each of
these references constitutes
an item.
•
An extension for the Firefox
web-browser by the Center for
History and New Media at
George Mason University.
•
Installed by visiting zotero.org
and clicking the download
button on the page.
Zotero Features (from zotero.org)
• Automatically capture citations
• Remotely back up and sync your
library
• Store PDFs, images, and web
pages
• Cite from within Word and
OpenOffice
• Take rich-text notes in any
language
• Wide variety of import/export
options
• Free, open source, and extensible
• Collaborate with group libraries
• Organize with collections and tags
• Access your library from anywhere
• Automatically grab metadata for
PDFs
• Use thousands of bibliographic
styles
• Instantly search your PDFs and
notes
• Advanced search and data mining
tools
• Interface available in over 30
languages
The Zotero + SEASR Picture
The
WEB
The
WEB
Zotero
Store
SEASR Analytics for Zotero
• An extension for the Firefox web-browser by the SEASR
Team
• Uses your Zotero Collections
• Performs analysis using SEASR Services
SEASR Analytics for Zotero Interface
How to Setup Your Machine
• Install/Open Firefox
• Install Zotero
– https://addons.mozilla.org/en-US/firefox/addon/3504
– http://zotero.org
• Install the SEASR Zotero plugin
– https://addons.mozilla.org/en-US/firefox/addon/10020
• The plugin points to the default services provided by
SEASR (running on our server)
Zotero and SEASR
Tag Cloud Analysis
Readability Analysis
Date Entity to Simile Timeline
Automatic Summarization
Tag Cloud Examples
• Tag Cloud Viewer
– Creates tag cloud for all items submitted (with a url), stop words
filtered including common tokens (punctuation), stemmed, top
100 words displayed in tag cloud viewer
• NGram Tag Cloud Viewer
– Creates tag cloud for all items submitted (with a url), stop words
filtered including common tokens (punctuation), 2-grams, top
100 2-grams displayed in tag cloud viewer
Entity Extraction Examples
• Date Entities to Simile Timeline
– Extracts date entities from all items submitted (with a url), and
plots these dates on the Simile Timeline
• Location Entities to Google Map
– Extracts location entities from all items submitted (with a url), and
plots these on a Google Map
• Entities to Protovis Network
– Extracts entities, creates relationships of entities existing in the
same sentence and display in a Protovis force directed link node
graph
Text Summarization
HITS Summarizer
– Finds top sentences and tokens from all items submitted (with a
url) and displays them in a report
Flesch-Kincaid Readability Test
• Given: Zotero item(s)
• Results show scores for
each item selected
– Designed to indicate
comprehension difficulty
when reading a passage of
contemporary academic
English
– Flesch Reading Ease:
higher scores indicate
material that is easier to
read; lower numbers mark
passages that are more
difficult to read
– Flesch–Kincaid Grade
Level: result is a number
that corresponds with a
Authorship Analysis
• Given: Zotero Collection (or
multiple items selection) with
Author/Co-Author Information
• Determine importance of given
authors in this collection?
– Each author is a vertex in the graph
– Authors are connected with an edge
if they are co-authors of an item
– List of Authors ranked by the
Betweenness Centrality Measure
– Betweenness is a centrality measure
of a vertex within a graph. Vertices
that occur on many shortest paths
between other vertices have higher
betweenness than those that do not.
Zotero to SEASR : Fedora
Interactive Web
Application
Web Service
The Value Added
• Analytical Results are saved as Zotero items (View Snapshot)
– Includes metadata
– Item naming strategy identifies the item or collection processed
– Creator indicates the Menu Label of the SEASR Analysis
• Related Tab links to the items processed in the Analysis
• No need to install the analysis, it runs as web service
The Zotero Plugin
• Open Firefox
• Install Zotero
– https://addons.mozilla.org/en-US/firefox/addon/3504
• Install the SEASR Zotero plugin
– https://addons.mozilla.org/en-US/firefox/addon/10020
• The plugin will point to the default services provided by
SEASR
• You can develop and deploy your own (samples
available)
• SEASR plugin preferences allow to point to other service
providers
Zotero and VUE
The VUE team has integrated their tool, so that items can
be exported into VUE
SEASR Support in VUE
• Goal: Provide functionality in
VUE to use SEASR flows
• Implementations:
– Add content to map for top
10 words from the given url
– Get metadata for content
– Get information about
content
SEASR and VUE
• Top words from 2 different web pages with nodes moved
around to see overlap
SEASR and VUE
Demonstration
• We will be demonstrating how to install and use the
SEASR Analytics extension for Zotero
• We will also showcase Tufts' Visual Understanding
Environment (VUE) for Zotero and its integration with
SEASR
Learning Exercises: Zotero Collection
Have participants run some of the Zotero-enabled flows
– Setup a Zotero collection you want to use, skip to the next step
• Create a collection by right-clicking on "My Library" and selecting "New
Collection"
– Give the collection a name (such as "DocSouth")
• Select this collection
• Use Firefox to navigate to http://docsouth.unc.edu/neh/aaron/aaron.html
• Open Zotero by clicking the Zotero icon in Firefox (bottom-right corner)
• Capture the current webpage as a Zotero item by clicking the "Create
new item from current page" button (fifth from the left on the Zotero
toolbar)
• Navigate to http://docsouth.unc.edu/neh/adams/adams.html and repeat
the previous step
Learning Exercise: Access SEASR
• Select one or more items in Zotero and then right-click
on one of the selected items and choose SEASR
Analytics -> SEASR -> Tag Cloud Viewer to create a tag
cloud from text extracted from your Zotero item(s)
• Do the same thing but select SEASR Analytics ->
SEASR -> Hits Summarizer instead, to view a list of top
tokens and sentences extracted from your item(s)
• Repeat the same procedure one more time, but this time
select SEASR Analytics -> SEASR -> Date Entities to
Simile Timeline to view a timeline containing dates
extracted from your item(s)
Learning Exercise: Zotero and VUE
• Run an analysis on a Zotero collection through VUE.
These steps will create nodes in VUE and extract the
words from these documents and connect them with a
link. By doing this for multiple documents, you will see
what words (concepts) are mentioned in multiple
documents. Note that we could change from words to an
extracted entity, like Person and automatically build a
social network around the documents that are selected.
– Note: This exercise requires the existence of a Zotero collection;
you can create one by following step 1 in the previous exercise,
if necessary
Learning Exercise: SEASR and VUE
– Open Zotero by clicking on the Zotero icon in Firefox (bottomright corner)
– Click the Settings button on the Zotero toolbar (third from left)
and select "Start VUE"
• Confirm the security prompt, if one is presented
– Right-click the collection (ex: "DocSouth") and select "Send to
VUE and Add to Map"
– Select one of the boxes (documents) in the VUE workspace and
then choose Analysis -> SEASR from the VUE menu
– In the new window that is displayed, select "Create new nodes"
in step 2, and the "Resource Word Count" analysis in step 3 and
press Analyze
– Repeat this for additional nodes in your graph to build a more
complex network of words. You can now use the functionality of
VUE to rearrange your graph to tell a story.
Discussion Questions
• What kinds of data assets would you be creating in
Zotero?
• What other analysis would you like to use against
this data?