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An Introduction to Structured Data Presentation New Perspectives on Old Data Shawn Day Digital Humanities Observatory 14 November 2012 http://www.slideshare.net/shawnday/structured-data-presentation

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Page 1: Structured Data Presentation

An Introduction to Structured Data PresentationNew Perspectives on Old Data

Shawn DayDigital Humanities Observatory

14 November 2012

http://www.slideshare.net/shawnday/structured-data-presentation

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Objective

To appreciate the variety of structured data presentation tools available to digital humanities scholars and to be able to judge between them.

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AgendaData Presentation versus Data Analysis?

The ReadingsExhibit Thesis

The Data Vis Challenge to the Humanities

Products to be have an awareness of

Hands On Install and ConfigExhibit

OMEKA?

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The Two Faces of Data Visualisation

One of the keys to good visualization is understanding what your immediate (and longer term) goals are.

Are you visualizing data to understand what’s in it, or are you trying to communicate meaning to others?

You - Visualisation for Data Analysis

Others - Visualisation for Presentation

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Information Visualisation:Challenge for the Humanities

To use the vast stores of digitised data we are collecting we need to develop a digital fluency

Access

Exploration

Visualisation

Analysis

Collabouration

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The ChallengesDeveloping new genres for complex info presentation

creating a literacy that has same rigour and richness as current scholarship

expanding text-based pedagogy to include simulation, animation and spatial and geographic representation

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The OpportunityBalance complexity with conciseness

Balance accuracy with essence

Speak authoritatively, yet inspire exploration and personal insight

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A Short HistoryOriginated in Computer Science

Disseminated into broader scientific realm

A late comer to the humanities

Tufte: concise - clear - accurate

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William Playfair (1758 - 1823)bar chart

pie chart

time series

This is a file from the Wikimedia Commons.

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John Snow (1813 - 1858)Dot Plot

Spatial Analysis

This is a file from the Wikimedia Commons

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Charles Minard (1781 - 1870)Flow Diagram

Multi-Vector Information Visualisation

This is a file from the Wikimedia Commons

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Tools for collection are far more successful to date than those for exploration

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New InfluencesSimulation - 3D What if?

Monitor - Real time data

Collabouration - Many Eyes

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The Challenges to the Use of Visualisation

Too Easy to confuse, miscommunicate or downright lie

Break or lack basic visual design principles

Fail to understand the data, the audience or the problem being solved

Fail to appreciate the visceral or emotional power of graphics

Lack of technical skills in this domain

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Structured Data Presentation Tools(a tiny subset)

WebservicesTimeFlow

Google Fusion Tables

Many Eyes

HostedOmeka (Omeka)

FrameworksGephi

Exhibit (Exercise)

GraphViz

Prefuse

D3

Processing

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TimeFlow

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Google FusionTables

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Many Eyes

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Hands-On Exercise: Simile Exhibit

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Looking at Exhibit

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Setup and PreparationDo Not Use Safari - Firefox or Chrome should be fine

You can find instructions at: http://myeye.ie/ftp1/exhibit/recipe.txt

Need to copy datafiles:http://myeye.ie/ftp1/exhibit/nobelists.js?action=raw

http://myeye.ie/ftp1/exhibit/index1.html

X

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Background on Exhibit

Exhibit was developed at MIT to provide a lightweight framework for the presentation, searching and faceted browsing of digital collections. Exhibit lets you easily create web pages with advanced text search and filtering functionalities, with interactive maps, timelines, and other visualizations

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Little programming (JavaScript Template);

No database (JSON text);

a series of useful ‘instantly interactive’ visualisations.

So What?...

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Exhibit in a Nutshell

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The Simplest Exhibit<html>

! <head>

! ! <title>MIT Nobel Prize Winners</title>

! ! <link href="nobelists.js" type="application/json" rel="exhibit/data" />

! ! <script src=http://static.simile.mit.edu/exhibit/api-2.0/exhibit-api.js type="text/javascript"></script>

! <style></style>

! </head>

! <body>

! ! <h1>MIT Nobel Prize Winners</h1>

! ! <table width="100%”>

! ! <tr valign="top”>

! ! <td ex:role="viewPanel”><div ex:role="view"></div></td><td width="25%”>browsing controls here… </td></tr>

</table>

</body>

</html>

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The Data {

"items" : [

{ type : "Nobelist",

label : "Burton Richter",

! ! ! latlng: "42.359089,-71.093412",

discipline : "Physics",

shared : "yes",

"last-name" : "Richter",

"nobel-year" : "1976",

relationship : "alumni",

"co-winner" : "Samuel C.C. Ting",

"relationship-detail" : "MIT S.B. 1952, Ph.D. 1956",

imageURL : "http://nobelprize.org/nobel_prizes/physics/laureates/1976/richter_thumb.jpg"

},

………

]

}

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The Simplest View

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Add Faceted BrowsingExplore data in context

Filter data by attributes

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Faceted Browsing Code <div ex:role="facet" ex:expression=".discipline" ex:facetLabel="Discipline"></div>

<div ex:role="facet" ex:expression=".relationship" ex:facetLabel="Relationship"></div>

<div ex:role="facet" ex:expression=".shared" ex:facetLabel="Shared?"></div>

<div ex:role="facet" ex:expression=".deceased" ex:facetLabel="Deceased?"></div>

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Add Search and Sort

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Search Code

<div ex:role="facet" ex:facetClass="TextSearch"></div>

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Add a Table View

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Table Code<div

ex:role="exhibit-view”

ex:viewClass="Exhibit.TabularView” ex:columns=".label, .imageURL, .discipline, .nobel-year, .relationship-detail”

ex:columnLabels="name, photo, discipline, year, relationship with MIT”

ex:columnFormats="list, image, list, list, list”

ex:sortColumn="3”

ex:sortAscending="false">

</div>

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Add a Timeline

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Timeline Code<script src="http://static.simile.mit.edu/exhibit/extensions-2.0/time/time-extension.js"

type="text/javascript"></script>

+

<div ex:role="view" ex:viewClass="Timeline" ex:start=".nobel-year" ex:colorKey=".discipline"></div>

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Add a Map View

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Wrapup: ExhibitPros

Simple

Lightweight

No server required

A host of visualisations

Embeddable in other systems - ExhibitPress

ConsLimited Scalability

Some cross-browser issues

Restrictions on Look and Feel

Extensive customisation means getting into code

Here comes Exhibit 3

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Moving Beyond with ExhibitEnsemble Project Advanced Tutorial:

http://ensemble.ljmu.ac.uk/q/calbooklet

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OMEKA for Curated Collectionshttp://omeka.net

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Omeka Basics

ItemRepresentations

Metadata TypeTag(s)Item

Representations

Metadata TypeTag(s)Item

Representations

Metadata TypeTag(s)

Collection(s)

ExhibitMetadata

OAI/PMH

CSV

etc...

SectionPage

Page

SectionPage

Page

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1. Show the Data

2. Provoke Thought about the Subject at Hand

3. Avoid Distorting the Data

4. Present Many Numbers in a Small Space

5. Make Large Datasets Coherent

6. Encourage Eyes to Compare Data

7. Reveal Data at Several Levels of Detail

8. Serve a Reasonably Clear Purpose

9. Be Closely Integrated with Statistical and Verbal Descriptions of the Dataset

Data Visualisation Lessons from Tufte

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Connecting your data with the right visualisation

What is your message?

How do we know what we might use?

Start with your Exploratory/Research/Analytical Environment (last seminar)

How do visuals fit into your narrative?

What Visual Techniques Exist?

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Thanks for your attention