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Tools and Methods So What? 18 March 2014

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Page 1: Sharing  - Collecting our DAH Thoughts

Tools and MethodsSo What?

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18 March 2014

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Objectives‣ Take a look at where we’ve been; ‣ Talk about going forward; ‣ Discuss larger research trajectories.

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A Few Foundation Frameworks‣ GraphViz ‣ R Programming Language ‣ JIT (JavaScript Infovis

Toolkit) ‣ Protovis ‣ D3 ‣ Processing ‣ Tableau ‣ Prefuse

‣ Gephi ‣ WEAVE (http://

www.oicweave.org/) !

‣ Exhibit

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GraphViz

‣ An Open Source Framework

‣ Mature (1988) ‣ AT&T Labs ‣ Used as a basis for subsequent ‣ A great prototyping and starting point

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‣ http://www.graphviz.org/

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R Programming Language‣ Geared towards statistical analysis ‣ In recent times has had developed into an engine

supporting some powerful graphics frameworks ‣ Open Source ‣ Typically Command Line but a variety of GUI editors

available ‣ > Jeff Rydberg-Cox: R for the Digital Humanities

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JavaScript InfoVis Toolkit (JIT)‣ JIT Demos (http://thejit.org/demos/) ‣ The JavaScript InfoVis Toolkit is a complete set of tools to

create Interactive Data Visualizations for the Web. It includes JSON loading, animation, 2D point and graph classes and some predefined tree visualization methods.

‣ Smaller datasets in a clean form ‣ Related and Aggregated/Categorised Data

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JavaScript InfoVis Toolkit (JIT)

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JavaScript InfoVis Toolkit (JIT)

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ProtoVis‣ Protovis is a visualization toolkit for JavaScript using SVG.

It takes a graphical approach to data visualization, composing custom views of data with simple graphical primitives like bars and dots. These primitives are called marks, and each mark encodes data visually through dynamic properties such as color and position.

‣ Jerome Cukier: ProtoVis Tutorial ‣ Development shifted to D3 ‣ ProtoVis still very accessible and usable

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ProtoVis

http://mbostock.github.com/protovis/ex/crimea-rose.html

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ProtoVis

http://mbostock.github.com/protovis/ex/napoleon.html

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D3‣ D3 allows you to bind arbitrary data to a Document

Object Model (DOM), and then apply data-driven transformations to the document. As a trivial example, you can use D3 to generate a basic HTML table from an array of numbers. Or, use the same data to create an interactive SVG bar chart with smooth transitions and interaction.

‣ Open Source

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Processing‣ Now we are getting serious... ‣ Ben Fry ‣ Like R has a serious statistical bent ‣ Has a client and development environment, but deploys easily to the

web using processing.js ‣ Large and VL datasets ‣ Good with related data ‣ Serious support for aesthetics ‣ Modelling Environment ‣ http://processing.org/ ‣ http://www.openprocessing.org/

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Processing.js

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Processing.js

http://nytlabs.com/projects/cascade.html

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Tableau‣ Commercial ‣ Offers a Free Public Application ‣ Encourages sharing and focusses on building a narrative around

visualisation of your research data ‣ Education and Non-Commercial Licenses available ‣ Mature and evolving rapidly to demonstrate the newest and most

exciting visualisation types ‣ And our friends Wattenberg and Viegas seem to be onboard

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Tableau

http://www.tableausoftware.com/public

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Prefuse‣ flare.prefuse ‣ Flash-based ‣ Great transitions and very approachable ‣ Beware of Datalocking ‣ http://flare.prefuse.org/demo

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Gephi‣ We Looked at it two weeks ago ‣ Open Source ‣ Mapping and Visualising Relationships and Networks ‣ An outstanding Visual Development Environment ‣ Multiplatform ‣ Extensible!! ‣ https://gephi.org/

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"If you are not making anything, you are not…a digital humanist."

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- Stephen Ramsay

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Considering the state of things: !

"Sample on Building versus Sharing"

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Sample ‣ Production versus Reproduction of Knowledge ‣ The promise of the digital is not in the way it allows us to ask new

questions because of digital tools or because of new methodologies made possible by those tools. The promise is in the way the digital reshapes the representation, sharing, and discussion of knowledge. We are no longer bound by the physical demands of printed books and paper journals, no longer constrained by production costs and distribution friction, no longer hampered by a top-down and unsustainable business model. And we should no longer be content to make our work public achingly slowly along ingrained routes, authors and readers alike delayed by innumerable gateways limiting knowledge production and sharing.

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Digital Arts and Humanities Communities of Practise?Type 1: Humanities computing subfield, work with computers dating back to the 1990s (and

earlier) Type 1.5: Appearance of the "alt-ac/digital humanities tendency," emerging around 2008/2009

positioning the digital solving the jobs crisis among humanities PhDs with scholars pursuing broader range of intellectual jobs beyond professorships. Visions of the "big tent," of an opening up of scholarly activity.

Type 2: Recent emergence of critique and backlash (coming from a media studies/cultural studies orientation) against digital arts+humanities as a kind of inside-job sabotage of academia by neoliberal forces and ideologies dressed up to seem like liberation from hierarchy, but in fact smuggling in invidious forces: the deskilling of academic laborers; the assessment-crazed "show me the data" loss of control over the classroom; the loss of control over the publication process; MOOC-ville; and, worst of all, the mirroring at the micro-level of academe what are macro-level operations of neoliberalism, surveillance, corporatization, and inequality in contemporary society.

- Michael Kramer in response to Stephen Ramsay

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mix, match, mash, manifest

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1st wave of digital work was quantitative, mobilizing the search and retrieval powers

of the database, automating corpus linguistics, stacking hypercards into

critical arrays.

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The second wave is qualitative, interpretive, experiential, emotive,

generative in character.

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Interdisciplinarity/transdisciplinarity/multidisciplinarity are empty words ( ) unless they imply changes in language,

practice, method, and output.

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The digital is the realm of the : open source, open resources - 4M

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Digital Humanities implies the multi‐purposing and multiple channeling of humanistic knowledge

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Digital Humanities = Big Humanities = Generative Humanities

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by emphasizing design, multimediality, and the experiential, it seeks to expand the compass of the affective range to

which scholarship can aspire

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Process is the new god; not product. Anything that stands in the way of the perpetual mash‐up and remix stands in the

way of the digital revolution

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Wiki‐scholarship is iterative, cumulative, and collaborative

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Digital Humanists recognize curation as a central feature of the future of the Humanities disciplines

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It recasts the scholar as curator and the curator as scholar !

Curation means making arguments through objects as well as words, images, and sounds

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Moving Forward

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Selling A DAH Project1. Have a Concrete Idea.

1. Find a few successful project models of what you want to do in order to demonstrate feasibility.

2. You should look for examples both inside and outside of your discipline. Matthew Kirschenbaum has an article “What is Digital Humanities and What’s it Doing in English Departments?” for English folks.  If you only have a vague sense of an idea that excites you, let it simmer until you can learn more and become prepared to answer tough questions.

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Selling A DAH Project2. Get the Facts. If some of your ideas come under attack, you should be prepared to defend them if you are committed to, say, sharing your work online with open-access. Steve Hitchcock maintains a webliography on the open-access question that addresses both sides of the debate (though many trend towards showing greater citation under open-access).

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Selling A DAH Project3. Do It. Moving from planning to learning and doing can be the greatest challenge, but if you get something rolling and make a commitment you must follow through. Everything might not make it into your final project, but your efforts will provide valuable experience. There is also something to be said about asking for forgiveness rather than permission.

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- Alex Galazara

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Thank You and Be In [email protected] @iridium