‣ Take a look at where we’ve been;
‣ Talk about going forward;
‣ Discuss larger research trajectories.
A Few Foundation Frameworks
‣ R Programming Language
‣ WEAVE (http://
‣ An Open Source
‣ Mature (1988)
‣ AT&T Labs
‣ Used as a basis for subsequent
‣ A great prototyping and starting point
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
‣ > Jeff Rydberg-Cox: R for the Digital Humanities
‣ JIT Demos (http://thejit.org/demos/)
create Interactive DataVisualizations for theWeb. 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
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
‣ 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
‣ Open Source
‣ 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 andVL datasets
‣ Good with related data
‣ Serious support for aesthetics
‣ Modelling Environment
‣ 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 friendsWattenberg andViegas seem to be onboard
‣ Great transitions and very approachable
‣ Beware of Datalocking
‣ We Looked at it two weeks ago
‣ Open Source
‣ Mapping andVisualising Relationships and Networks
‣ An outstandingVisual Development Environment
Points of Departure
‣ DIRT (Digital Research Tools)
‣ Visualisation in Education
‣ Getting Started with R
‣ Using R in DH
‣ Data Journalism @ Stanford
"If you are not making anything,
you are not…a digital humanist."
- Stephen Ramsay
Considering the state of things:
"Sample on Building versus Sharing"
‣ 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.
Digital Arts and Humanities Communities of Practise?
Type 1: Humanities computing subfield, work with computers dating back to the 1990s (and
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
1st wave of digital work was quantitative,
mobilizing the search and retrieval powers
of the database, automating corpus
linguistics, stacking hypercards into
The second wave is qualitative,
interpretive, experiential, emotive,
generative in character.
empty words ( ) unless they imply changes in language,
practice, method, and output.
The digital is the realm of the :
open source, open resources - 4M
Digital Humanities implies the multi‐purposing and multiple
channeling of humanistic knowledge
Digital Humanities = Big Humanities = Generative
by emphasizing design, multimediality, and the experiential,
it seeks to expand the compass of the affective range to
which scholarship can aspire
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
iterative, cumulative, and collaborative
Digital Humanists recognize curation as a central feature of
the future of the Humanities disciplines
It recasts the scholar as curator and the curator as scholar
Curation means making arguments through objects as well
as words, images, and sounds
Selling A DAH Project
1. 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 andWhat’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
Selling A DAH Project
2. 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
Selling A DAH Project
3. 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.
- Alex Galazara
ThankYou and Be In Touch