The document provides an overview of structured data presentation tools for digital humanities scholars. It discusses the difference between data presentation and analysis, and highlights some early pioneers of data visualization like William Playfair and Charles Minard. The document then examines challenges in using visualization for the humanities. It also profiles several structured data presentation tools, including TimeFlow, Google Fusion Tables, Many Eyes, and Omeka. Hands-on examples are provided using the Exhibit framework to create interactive visualizations like faceted browsing, searching, tables, timelines, and maps.
9 Amazingly Simple Data Presentation TipsSketchBubble
Presenting data can be a tricky proposition, because different rules apply in different contexts. Learn the given Data Presentation tips to make the right choices for your Presentation?
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9 Amazingly Simple Data Presentation TipsSketchBubble
Presenting data can be a tricky proposition, because different rules apply in different contexts. Learn the given Data Presentation tips to make the right choices for your Presentation?
Talk at 3th Keystone Training School - Keyword Search in Big Linked Data - Institute for Software Technology and Interactive Systems, TU Wien, Austria, 2017
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This presentation describes an investigation of user-centred design methodologies intended to apply to metadata or information architecture evaluation and deployment. The primary focus of this work is investigation of user conceptual models and comparison with formally architected models.
Extensible Application Markup Language, better known as XAML (pronounced “zammel”), is a language developed by Microsoft that is based on XML. It provides a declarative way to instantiate rich object graphs – in other words, through XAML you are able to create instances of classes, set properties, and define behaviors. Most commonly used to describe the user interface for technologies like Silverlight, WPF, and Windows 8.1, XAML provides a separation of concerns between the presentation and business logic for an app and gives the designer the flexibility to create experiences that interact with code through data-binding. This enables design-time data and true parallel workflows between designers and developers. Jeremy Likness will walk you through XAML, including how it is used by various technologies and the advantages it provides when building applications.
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Nowadays, Data Science is buzzing all over the place.
But what is a, so-called, Data Scientist?
Some will argue that a Data Scientist is a person able to report and present insights in a data set. Others will say that a Data Scientist can handle a high throughput of values and expose them in services. Yet another definition includes the capacity to create meaningful visualizations on the data.
However, we enter an age where velocity is a key. Not only the velocity of your data is high, but the time to market is shortened. Hence, the time separating the moment you receive a set of data and the time you’ll be able to deliver added value is crucial.
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Three Tier is no more a model for Cloud and in general Scalable Web Applications. Scaffolding from SQL Database is, sure, the worst way to do. A road to do this is changing modeling activity, from scaffolded DB model to Command/DTO model, through ViewModel pattern. Command and DTOs are pillars of CQRS model.
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Video recording at https://www.youtube.com/watch?v=3Li_xIQ1K84
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CAMA 2007 Visions of the Future for Contextualized Attention MetadataWayne Hodgins
Invited keynote presentation by Wayne Hodgins at the CAMA 2007 http://ariadne.cs.kuleuven.ac.be/cama2007/ Contextualized Attention Metadata workshop at the Joint Conference on Digital Libraries JCDL 2007 http://www.jcdl2007.org/ in Vancouver British Columbia Canada on June 23, 2007
This presentation describes an investigation of user-centred design methodologies intended to apply to metadata or information architecture evaluation and deployment. The primary focus of this work is investigation of user conceptual models and comparison with formally architected models.
Extensible Application Markup Language, better known as XAML (pronounced “zammel”), is a language developed by Microsoft that is based on XML. It provides a declarative way to instantiate rich object graphs – in other words, through XAML you are able to create instances of classes, set properties, and define behaviors. Most commonly used to describe the user interface for technologies like Silverlight, WPF, and Windows 8.1, XAML provides a separation of concerns between the presentation and business logic for an app and gives the designer the flexibility to create experiences that interact with code through data-binding. This enables design-time data and true parallel workflows between designers and developers. Jeremy Likness will walk you through XAML, including how it is used by various technologies and the advantages it provides when building applications.
Towards a rebirth of data science (by Data Fellas)Andy Petrella
Nowadays, Data Science is buzzing all over the place.
But what is a, so-called, Data Scientist?
Some will argue that a Data Scientist is a person able to report and present insights in a data set. Others will say that a Data Scientist can handle a high throughput of values and expose them in services. Yet another definition includes the capacity to create meaningful visualizations on the data.
However, we enter an age where velocity is a key. Not only the velocity of your data is high, but the time to market is shortened. Hence, the time separating the moment you receive a set of data and the time you’ll be able to deliver added value is crucial.
In this talk, we’ll review the legacy Data Science methodologies, what it meant in terms of delivered work and results.
Afterwards, we’ll slightly move towards different concepts, techniques and tools that Data Scientists will have to learn and appropriate in order to accomplish their tasks in the age of Big Data.
The dissertation is closed by exposing the Data Fellas view on a solution to the challenges, specially thanks to the Spark Notebook and the Shar3 product we develop.
No more Three Tier - A path to a better code for Cloud and AzureMarco Parenzan
Three Tier is no more a model for Cloud and in general Scalable Web Applications. Scaffolding from SQL Database is, sure, the worst way to do. A road to do this is changing modeling activity, from scaffolded DB model to Command/DTO model, through ViewModel pattern. Command and DTOs are pillars of CQRS model.
Explore Data: Data Science + VisualizationRoelof Pieters
Talk on Data Visualization for Data Scientist at Stockholm NLP Meetup June 2015: http://www.meetup.com/Stockholm-Natural-Language-Processing-Meetup/events/222609869/
Video recording at https://www.youtube.com/watch?v=3Li_xIQ1K84
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Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
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Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
1. 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
2. Objective
To appreciate the variety of structured data
presentation tools available to digital humanities
scholars and to be able to judge between them.
3. Agenda
Data Presentation versus Data Analysis?
The Readings
Exhibit Thesis
The Data Vis Challenge to the Humanities
Products to be have an awareness of
Hands On Install and Config
Exhibit
OMEKA?
4. 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
5. 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
6. The Challenges
Developing 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
7. The Opportunity
Balance complexity with conciseness
Balance accuracy with essence
Speak authoritatively, yet inspire exploration and
personal insight
8. A Short History
Originated in Computer Science
Disseminated into broader scientific realm
A late comer to the humanities
Tufte: concise - clear - accurate
9. William Playfair (1758 - 1823)
bar chart
pie chart
time series
This is a file from the Wikimedia Commons.
10. John Snow (1813 - 1858)
Dot Plot
Spatial Analysis
This is a file from the Wikimedia Commons
11. Charles Minard (1781 - 1870)
Flow Diagram
Multi-Vector Information Visualisation
This is a file from the Wikimedia Commons
13. New Influences
Simulation - 3D What if?
Monitor - Real time data
Collabouration - Many Eyes
14. 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
15. Structured Data Presentation Tools
(a tiny subset)
Webservices Frameworks
TimeFlow Gephi
Google Fusion Tables Exhibit (Exercise)
Many Eyes GraphViz
Prefuse
Hosted D3
Omeka (Omeka) Processing
21. Setup and Preparation
Do Not Use Safari - Firefox or Chrome should be
X
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
22. 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
23. So What?...
Little programming (JavaScript Template);
No database (JSON text);
a series of useful ‘instantly interactive’
visualisations.
38. Wrapup: Exhibit
Pros Cons
Simple Limited Scalability
Lightweight Some cross-browser
No server required issues
A host of Restrictions on Look
visualisations and Feel
Embeddable in other Extensive
systems - customisation means
ExhibitPress getting into code
Here comes Exhibit 3
39. Moving Beyond with Exhibit
Ensemble Project Advanced Tutorial:
http://ensemble.ljmu.ac.uk/q/calbooklet
43. Where to go next
http://datajournalism.stanford.edu/
Bamboo - DIRT (Digital Research Toolkit)
Timeline Tools
Visualisation in Education
Visual Complexity
44. Academic Visualisation?
There’s lots of published papers out there
...what can you do with them?
http://www.autodeskresearch.com/projects/citeology
47. Data Visualisation Lessons from Tufte
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
48. What Visual Techniques Exist?
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?